text:
الرئيسية Clinical Functional MRI: Presurgical Functional Neuroimaging
Clinical Functional MRI: Presurgical Functional Neuroimaging
Christoph Stippich (eds.)
The second, revised edition of this successful textbook provides an up-to-date description of the use of preoperative fMRI in patients with brain tumors and epilepsies. State of the art fMRI procedures are presented, with detailed consideration of practical aspects, imaging and data processing, normal and pathological findings, and diagnostic possibilities and limitations. Relevant information on brain physiology, functional neuroanatomy, imaging technique, and methodology is provided by recognized experts in these fields. Compared with the first edition, chapters have been updated to reflect the latest developments and in particular the current use of diffusion tensor imaging (DTI) and resting-state fMRI. Entirely new chapters are included on resting-state presurgical fMRI and the role of DTI and tractography in brain tumor surgery. Further chapters address multimodality functional neuroimaging, brain plasticity, and pitfalls, tips, and tricks.
الناشر: Springer-Verlag Berlin Heidelberg
ISBN 13: 978-3-662-45123-6
Series: Medical Radiology
تحميل (pdf, 27.70 MB)
اقرأ الكتاب مباشرة
fmri1539
presurgical473
dti386
gyrus328
tractography309
connectivity287
magnetic resonance imaging278
sulcus274
localization269
neuroimage228
intraoperative227
functional magnetic224
brain tumors201
functional mri198
neurosurg197
functional magnetic resonance195
hemisphere187
anatomical185
sma177
inferior176
tracts174
voxel171
gliomas166
preoperative164
neuroimaging163
Basiswissen Urologie
Prof. Dr. med. Thomas Gasser (auth.)
Die Sinne der Vögel oder Wie es ist, ein Vogel zu sein: Mit Zeichnungen von Katrina van Grouw
Springer Spektrum
Tim Birkhead (auth.)
Medical Radiology · Diagnostic Imaging
Series Editors: M.F. Reiser · H.-U. Kauczor · H. Hricak · M. Knauth
Christoph Stippich Editor
Functional MRI
Presurgical Functional Neuroimaging
Medical Radiology
Maximilian F. Reiser
Hans-Ulrich Kauczor
Hedvig Hricak
Michael Knauth
Andy Adam, London
Fred Avni, Brussels
Richard L. Baron, Chicago
Carlo Bartolozzi, Pisa
George S. Bisset, Durham
A. Mark Davies, Birmingham
William P. Dillon, San Francisco
D. David Dershaw, New York
Sam Sanjiv Gambhir, Stanford
Nicolas Grenier, Bordeaux
Gertraud Heinz-Peer, Vienna
Robert Hermans, Leuven
Hans-Ulrich Kauczor, Heidelberg
Theresa McLoud, Boston
Konstantin Nikolaou, Munich
Caroline Reinhold, Montreal
Donald Resnick, San Diego
Rüdiger Schulz-Wendtland, Erlangen
Stephen Solomon, New York
Richard D. White, Columbus
For further volumes:
http://www.springer.com/series/4354
Christoph Stippich
Clinical Functional MRI
Christoph Stippich, MD
Professor and Division Head
Division of Diagnostic and Interventional Neuroradiology
University Hospitals Basel
ISSN 2197-4187 (electronic)
ISBN 978-3-662-45123-6 (eBook)
DOI 10.1007/978-3-662-45123-6
Library of Congress Control Number: 2015933163
Springer Berlin Heidelberg New York Dordrecht London
© Springer-Verlag Berlin Heidelberg 2015
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Printed on acid-free paper
Springer-Verlag GmbH Berlin Heidelberg is part of Springer Science+Business Media (www.springer.com)
To my beloved family Alexandra, Tim, Jan and Nils
In the economic world, a inscription suggests that the book was considered by its publishers,
after a close look at sales, to appeal to a large enough, possibly growing readership. In the
scientific world, a inscription of a monograph suggests that the authors succeeded in finding
readers for their special topic and keeping them. In the case of "Clinical Functional MRI", I'm
sure, it is more than just keeping readers: it is making the entire clinical neuro-community
aware of the increasing importance of this field. At the same time the new edition provides a
state-of-the-art summary, as it were, helpful to all those colleagues who are unable to closely
follow the pertinent literature. As 7 years have passed since its first publication, "Clinical
Functional MRI" was completely revised, and new chapters on emerging subtopics – e.g., on
resting-state presurgical fMRI, presurgical fMRI in epilepsy, DTI-tractography, and brain plasticity as seen in fMRI and DTI – were added. Christoph Stippich, now heading neuroradiology
at University of Basel/Switzerland, proved his excellence as editor by refining the book's concept, unifying the text, and strengthening his team of experts. My prediction? A third edition
in less than 7 years.
Klaus Sartor, MD
Emeritus Professor of Neuroradiology
University of Heidelberg Medical Center
Preface to the Second Edition
Since the publication of this textbook's first edition, presurgical functional magnetic resonance
imaging (fMRI) has undergone relevant development and is increasingly used in many
neurocenters worldwide. fMRI has progressed towards a more standardized and user friendly
neuroimaging modality, but is still not a simple clinical routine application and requires special
expertise. Meanwhile, first official recommendations on stimulation paradigms have been
published online by the American Society for Functional Neuroradiology, and larger multicenter trials have been rolled out using consensus imaging protocols. Despite considerable
technical and methodological variabilities, a very substantial body of evidence has been generated that further supports presurgical fMRI's role as a feasible, robust and valid clinical imaging tool. In addition, diffusion-tensor-imaging (DTI) and diffusion-tensor-tractography (DTT)
have proven their value to visualize functionally important white matter structures as well as
pathological alterations, which can be meaningfully combined with presurgical fMRI also for
functional neuronavigation. More recently, resting-state fMRI (RS-fMRI) has entered this
clinical arena providing noninvasive measures of functional brain networks and connectivity
studies even without active cooperation of the patients. EEG-correlated fMRI in imaging
epilepsies has seen further development, as well as multimodality functional neuroimaging
with MEG, PET or SPECT. A rapidly increasing number of functional imaging studies have
contributed to a better understanding of neuroplastic changes that can occur in various brain
pathologies. Such phenomena should be considered with caution, when presurgical fMRI data
need to be interpreted.
With the second edition of this textbook, we account for these developments and have
implemented new chapters on DTI, RS-fMRI, EEG-fMRI and brain plasticity – all written by
renowned experts in their respective fields. All other chapters have been updated and fully
revised. This increase in information is unavoidably reflected by a slightly larger volume of
this textbook, which is still very comprehensive and practically oriented. Again, it has been a
great pleasure writing this book together, and we hope that it will be of value for all working,
or intending to work, in the field of clinical functional neuroimaging, and in particular with
presurgical fMRI and DTI.
Last, but not least, I would like to thank Drs. Maria Blatow and Meritxell Garcia for their
support and assistance.
Preface to the First Edition
Over the past decade, functional magnetic resonance imaging (fMRI) has undergone a
continuing process of technical and methodological maturation and refinement, facilitating its
application in a clinical environment. One of the earliest and best validated clinical applications of fMRI was, and remains, presurgical assessment of brain function in patients with brain
tumors and epilepsies. There is a substantial body of evidence that fMRI is suited to localizing
different body representations in the primary motor and somatosensory cortex, as well as to
localizing and lateralizing language function prior to surgery. This diagnostic information
permits function-preserving and safe treatment. However, fMRI cannot be considered an
established diagnostic neuroimaging modality as yet. To this end, a consensus on standardization of imaging procedures, data processing, data evaluation, and medical interpretation of
imaging findings is mandatory. Various dedicated hard- and software components require
medical certification and, last but not least, recommendations or guidelines need to be issued
by the relevant medical associations. Until then, it is each investigator's responsibility to establish his/her own routines and standards. This requires a profound knowledge of all topics
relevant to the presurgical application of fMRI.
There are several textbooks available relating to (clinical) fMRI covering neurophysiology, neuroanatomy, neurosurgery, neurology, neuropsychology, (neuro)radiology, etc., as
well as various aspects of functional neuroimaging, most of the latter being dedicated to
neuroscientific research. In addition, the abundant original literature published on presurgical
fMRI is somewhat heterogeneous, yielding partly conflicting results, which in turn makes it
difficult and time-consuming for the reader to extract the clinically relevant information.
Furthermore, fMRI is not the sole method in the field of functional neuroimaging. There are
other powerful tools such as EEG/MEG, PET, or SPECT that complement each other when
combined in a meaningful way. The same holds true for MR spectroscopy and diffusion
tensor imaging (DTI). Consequently, dealing with fMRI is intrinsically complex, multimodal,
and multidisciplinary.
The motivation for writing this book was the idea of creating a comprehensive text covering
the whole field of presurgical fMRI from physiological, anatomical, and methodological basics
up to neuroplasticity. Besides compiling the current knowledge on presurgical fMRI, the core
of this book has a clear focus on practical issues, providing guidance for those less familiar
with the field. Experienced investigators may profit from the various strategies, tips, and tricks
given, as well as from a deeper insight into different areas directly linked to presurgical fMRI.
For easier reading, this book has been designed as an assembly of successive chapters, each
dealing with a specific topic and providing a particular point of view on presurgical fMRI.
Therefore, it is not necessary to go through the whole book – areas of specific interest can be
selected easily from the "keypoints" sections and from extensive illustrations.
Each chapter has been written by experienced clinicians and researchers, some world
renowned in their respective fields. It has been a great pleasure writing this book together, and
we hope that it will be of value for all working, or intending to work, in the field of clinical
functional neuroimaging, and in particular with presurgical fMRI.
Last, but not least, I would like to thank Professor Klaus Sartor for encouraging me to edit
this book and Dr. Maria Blatow for her support and assistance.
Presurgical Functional MRI and Diffusion Tensor Imaging . . . . . . . . . . . . . . . . . . .
Revealing Brain Activity and White Matter Structure Using Functional
and Diffusion-Weighted Magnetic Resonance Imaging . . . . . . . . . . . . . . . . . . . . . . .
Rainer Goebel
Functional Neuroanatomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Thomas P. Naidich and Tarek A. Yousry
Task-Based Presurgical Functional MRI in Patients with Brain Tumors . . . . . . . . .
Christoph Stippich, Maria Blatow, and Meritxell Garcia
Presurgical Resting-State fMRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Monica G. Allen, Abraham Z. Snyder, Carl D. Hacker, Timothy J. Mitchell, Eric C.
Leuthardt, and Joshua S. Shimony
Simultaneous EEG-fMRI in Epilepsy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
R. Wiest, E. Abela, and C. Rummel
Diffusion Imaging with MR Tractography for Brain Tumor Surgery . . . . . . . . . . . .
Alberto Bizzi
Functional Neuronavigation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Volker M. Tronnier
Presurgical Functional Localization Possibilities, Limitations, and Validity . . . . . .
Stéphane Lehéricy, Delphine Leclercq, Hugues Duffau,
Pierre-François Van de Moortele, and Christine Delmaire
Multimodality in Functional Neuroimaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Jan Kassubek, Hans-Peter Müller, and Freimut D. Juengling
Brain Plasticity in fMRI and DTI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
R. Beisteiner and E. Matt
Clinical BOLD fMRI and DTI: Artifacts, Tips, and Tricks . . . . . . . . . . . . . . . . . . . .
Ronald Peeters and Stefan Sunaert
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
E. Abela, MD, Support Center for Advanced Neuroimaging (SCAN), Institute for
Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
Department of Neurology, University Hospital Bern, Bern, Switzerland
Monica G. Allen, Mallinckrodt Institute of Radiology, Washington University School of
Medicine, Saint Louis, MO, USA
R. Beisteiner, Department of Neurology, Highfield MR Center, Medical University of
Vienna, Vienna, Austria
Alberto Bizzi, MD, Department of Neuroradiology, Humanitas Clinical and Research
Hospital IRCCS, Rozzano (Milano), Italy
Maria Blatow, MD, Division of Diagnostic and Interventional Neuroradiology, Clinic for
Radiology and Nuclear Medicine, University Hospitals Basel, Basel, Switzerland
Christine Delmaire, MD, Department of Neuroradiology, CHRU Lille, Hopital Roger
Salengro, boulevard du Pr Leclerc, Lille cedex, France
Hugues Duffau, MD, PhD, Department of Neurosurgery, Hôpital Gui de Chauliac and
INSERM U1051, Montpellier University Medical Center, Montpellier, France
Meritxell Garcia, MD, Division of Diagnostic and Interventional Neuroradiology, Clinic
for Radiology and Nuclear Medicine, University Hospitals Basel, Basel, Switzerland
Rainer Goebel, Department of Cognitive Neuroscience, Maastricht University, Maastricht,
Carl D. Hacker, Department of Biomedical Engineering, Washington University School of
Freimut D. Juengling, MD, PET/CT Center NW-Switzerland, Claraspital Basel, Basel,
Jan Kassubek, MD, Department of Neurology, University of Ulm, Ulm, Germany
Delphine Leclercq, MD, Department of Neuroradiology, Groupe Hospitalier PitiéSalpêtrière, Université Pierre et Marie Curie – Paris 6, Paris, France
Stéphane Lehéricy, MD, PhD, Centre de NeuroImagerie de Recherche – CENIR,
Institut du Cerveau et de la Moelle – ICM, Sorbonne Universités, UPMC Univ Paris 06,
UMR S 1127, CNRS UMR 7225, Paris, France
Department of Neuroradiology, Groupe Hospitalier Pitié-Salpêtrière, Université Pierre et
Marie Curie – Paris 6, Paris, France
Eric C. Leuthardt, Department of Neurosurgery, Washington University School of
E. Matt, Department of Neurology, Highfield MR Center, Medical University of Vienna,
Timothy J. Mitchell, Washington University School of Medicine, Saint Louis, MO, USA
Hans-Peter Müller, PhD, Department of Neurology, University of Ulm, Ulm, Germany
Thomas P. Naidich, Mount Sinai School of Medicine, One Gustave Levy Place,
Department of Neuroradiology and Neurosurgery, Irving and Dorothy Regenstreif Research,
Ronald Peeters, PhD, Department of Radiology, University Hospitals of the Catholic
University of Leuven, Leuven, Belgium
C. Rummel, PhD, Support Center for Advanced Neuroimaging (SCAN), Institute for
Joshua S. Shimony, Washington University School of Medicine, Saint Louis, MO, USA
Abraham Z. Snyder, Washington University School of Medicine, Saint Louis, MO, USA
Stefan Sunaert, MD, PhD, Department of Radiology, University Hospitals of the Catholic
Christoph Stippich, MD, Professor and Division Head, Division of Diagnostic and
Interventional Neuroradiology, University Hospitals Basel, Basel, Switzerland
Volker M. Tronnier, MD, PhD, Department of Neurosurgery, Universitätsklinikum
Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
Pierre-François Van de Moortele, MD, PhD, Center for Magnetic Resonance Research,
University of Minnesota, Minneapolis, MN, USA
R. Wiest, MD, Support Center for Advanced Neuroimaging (SCAN), Institute for
Tarek A. Yousry, Lysholm Department of Neuroradiology, The National Hospital for
Neurology and Neurosurgery, Institute of Neurology, London, UK
Presurgical Functional MRI
and Diffusion Tensor Imaging
Introduction ...........................................................................
Blood-Oxygenation-Level-Dependent Functional
MRI (BOLD fMRI)...............................................................
Diffusion Tensor Imaging (DTI) and DTI
Tractography (DTT) .............................................................
Presurgical fMRI and DTI ...................................................
Content Overview .................................................................
References ....................................................................................
C. Stippich, MD
Professor and Division Head, Division of Diagnostic and
Interventional Neuroradiology, University Hospitals Basel,
Petersgraben 4, Basel CH 4031, Switzerland
e-mail: christoph.stippich@usb.ch
Functional magnetic resonance imaging (fMRI) provides
noninvasive localisation and lateralisation of specific brain
functions by measuring local hemodynamic changes coupled to neuronal activation. Different magnetic properties
of oxygenated (diamagnetic) and deoxygenated (paramagnetic) hemoglobin are exploited to generate the blood oxygen level dependent (BOLD) contrast. Diffusion tensor
magnetic resonance imaging (DTI) measures anisotropic
(directional) diffusion of protons along myelinated fibers
and thereby provides detailed information on the white
matter architecture. Specific white matter tracts can be
reconstructed using diffusion tensor tractography (DTT).
During the last two decades both novel MR-modalities
have revolutionised the imaging research on human brain
function and structural connectivity under physiological
and pathological conditions.
Task-based presurgical fMRI in patients with brain
tumors or epilepsies represents the best established and
validated clinical application. Essential cortical motor and
language areas can be localised and the language dominant
hemisphere can be determined prior to treatment. DTI and
DTT provide complimentary data on important white matter connections, e.g., the pyramidal tract and arcuate fascicle. This imaging information is indispensible to establish
the best possible treatment for each individual patient, and
to achieve the ultimate goal of surgery: function preserving
complete or most radical removal of the pathology. To this
end fMRI and DTI are integrated meaningfully into functional neuronavigation. While promising, resting-state
fMRI is currently still under initial clinical investigation.
The responsible clinical application requires standardised imaging and data processing as well as a profound knowledge of the imaging techniques employed,
the underlying functional neuroanatomy, physiology and
pathology, neuroplastic alterations, influencing factors,
artifacts, pitfalls, validity and limitations. Finally, information on other functional neuroimaging modalities and
multimodal integration is essential.
C. Stippich (ed.), Clinical Functional MRI: Presurgical Functional Neuroimaging, Medical Radiology,
DOI 10.1007/978-3-662-45123-6_1, © Springer-Verlag Berlin Heidelberg 2015
C. Stippich
Functional magnetic resonance imaging (fMRI) is a modern,
noninvasive imaging technique to measure and localize specific functions of the human brain without the application of
radiation (Bandettini et al. 1992; Kwong et al. 1992). Brain
function is indirectly assessed with high spatial resolution
via detection of local hemodynamic changes in capillaries
(Menon et al. 1995) and draining veins (Frahm et al. 1994) of
the so-called functional areas, e.g., regions of the human
brain that govern motor, sensory, language, or memory functions. In task-based fMRI (fMRI), specific stimulation of the
respective neurofunctional system is required (Belliveau
et al. 1991). The stimuli are presented in a predefined manner
during the fMRI measurement, which is called a stimulation
paradigm. The measurement of spontaneous brain activation
is also possible, by using resting-state fMRI (RS-fMRI) techniques (Purdon and Weisskoff 1998). Here, low-frequency
fluctuations in the hemodynamics of the brain are analyzed
for synchrony to detect interconnected areas that constitute
different functional systems. RS-fMRI is typically employed
to study functional brain connectivity in neuroimaging
research. Clinical applications are currently under initial
investigation (Lee et al. 2013).
The blood-oxygen-level-dependent (BOLD) fMRI technique makes use of blood as an intrinsic contrast (Ogawa
et al. 1990, 1992, 1993), superseding the intravenous application of paramagnetic contrast agents (Belliveau et al. 1991) or
radioactive substances (Mazziotta et al. 1982; Raichle 1983;
Fox et al. 1986; Holman and Devous 1992). The different
magnetic properties of oxygenated and deoxygenated hemoglobin are exploited to generate the BOLD contrast. Although
the underlying physiological mechanisms of neurovascular
coupling are not ultimately understood, there seems to be a
very good correspondence of BOLD signals with actual neuronal activity (Logothetis et al. 2001; Logothetis 2002, 2003;
Logothetis and Pfeuffer 2004; Logothetis and Wandell 2004).
New powerful gradient systems and the development of
ultrafast MR sequences enable examination of the entire brain
in clinically feasible time frames. Furthermore, fMRI profits
from high main magnetic field strength and multichannel head
coils in terms of improved signal-to-noise ratio (SNR), higher
spatial resolution, and/or shorter examination times. Better
functionality of data processing and immediate data analysis,
as obtained with real-time fMRI, facilitate the usability of
fMRI in the clinical context (Fernandez et al. 2001; Weiskopf
et al. 2003; Steger and Jackson 2004; Moller et al. 2005).
Today, most vendors offer some functionality with their MR
imagers to analyze fMRI data at the scanners' console directly.
Thus, functional MRI not only offers a variety of novel
options for clinical diagnostics and research but also opens
up a new diagnostic field of radiology and neuroradiology,
by shifting paradigms from strictly morphological imaging
to measurement and visualization of brain function (Stippich
et al. 2002a; Thulborn 2006).
The combination of fMRI with diffusion tensor imaging
(DTI) has proven scientific and clinical relevance (Bick et al.
2012). By measuring the directed diffusion of protons along
myelinated fibers, DTI provides complementary information
on white matter architecture, i.e., on the course and integrity
of functionally important white matter tracts. In neuroimaging research, DTI is mainly applied to study the human
brain's structural connectivity, whereas diffusion tensor
tractography (DDT) is often also employed for clinical
applications (Leclercq et al. 2011). DTI measurements can
be obtained together with fMRI in the same scanning session, which gives an even more complete picture of each
patient's individual brain pathology.
With this textbook, we aim to provide the reader with thorough and comprehensive information on the abovementioned
advanced MRI techniques, namely, task-based fMRI, restingstate fMRI, diffusion tensor imaging, and tractography in the
presurgical context, which constitute their best established
and validated clinical applications. A meaningful combination
of these advanced MRI techniques with standard MR
sequences (T2-FLAIR, T1-weighted sequences pre- and postcontrast administration) as well as with diffusion- and perfusion-weighted MRI is recommended to complete the
state-of-the-art preoperative structural and functional neuroimaging in patients with brain tumors and drug-resistant epilepsy (Svolos et al. 2013) (Fig. 1). On current MR imagers
with main magnetic field strength of 1.0 T or above, equipped
with powerful gradients and multichannel head coils, such
protocols should not require more than 45 min of scanning
time. Regarding functional studies, 20 min should be approximated for a multiparadigm language mapping and 5–10 min
for a somatotopic motor or somatosensory mapping. It is recommended to acquire the T1-weighted 3D post-contrast data
set – which will be used for the overlay of functional on
structural images and for neuronavigation – within the same
scanning session in order to minimize coregistration inaccuracies. Typically, another meaningfully selected MR sequence
is added to the protocol within that time frame, e.g., susceptibility-weighted imaging (SWI). MR spectroscopy (MRS) and
chemical shift imaging (CSI) are other MR modalities for
advanced neuroimaging in oncology which may be added
selectively and provide important complementary information on brain and tumor metabolism (Tsougos et al. 2012).
Blood-Oxygenation-Level-Dependent
Functional MRI (BOLD fMRI)
Enhanced synaptic activity resulting from stimulation of neurons leads to a local increase in energy and oxygen consumption in functional areas. The following local hemodynamic
Presurgical Functional MRI and Diffusion Tensor Imaging
Fig. 1 The state-of-the-art preoperative multimodality MR imaging in a right glioblastoma affecting the basal ganglia, insula, and
inferior frontal lobe as visualized on standard MR sequences (a,
upper row). Advanced MR imaging (b , lower row) revealed disintegration of white matter architecture/alterations in fractional
anisotropy on color-coded DTI maps (left ), increased relative
blood volume on dynamic susceptibility contrast- enhanced
(DSCE) perfusion imaging (middle), and right language dominance on BOLD fMRI (right ) in this left-handed male patient
(Color figure online)
changes transmitted via neurovascular coupling are measured by fMRI with high spatial accuracy:
• Increase of regional cerebral blood volume (rCBV)
• Increase of regional cerebral blood flow (rCBF)
• Relative increase of oxyhemoglobin in capillaries and
venous blood
In principle, fMRI measurements can be accomplished
with different techniques; BOLD fMRI being the most frequently used in human brain is therefore often referred to as
the standard technique (Thulborn et al. 1996; Thulborn 1998,
2006). Bolus tracking measures rCBV making use of external
contrast agents (Belliveau et al. 1991), and spin tagging
assesses rCBF using arterial blood for intrinsic contrast (Detre
et al. 1992). In contrast, BOLD technique (Ogawa et al. 1990,
1992, 1993) takes advantage of the different magnetic properties of oxygenated (oxy-Hb) and deoxygenated (deoxy-Hb)
hemoglobin to generate an image contrast. Paramagnetic
deoxy-Hb produces local field inhomogeneities in a measurable range for MRI resulting in a signal decrease in susceptibility-weighted MR sequences (T2*), whereas diamagnetic
oxy-Hb does not interfere with the external magnetic field.
Specific neuronal stimulation augments local cerebral oxygen
consumption, which initially results in a decrease of oxy-Hb
and an increase in deoxy-Hb in the functional area. To provide the active neurons with oxygenated blood, perfusion
(rCBF, rCBV) in capillaries and draining veins is increased
within several seconds. This mechanism not only equalizes
the initial decrease of local oxy-Hb concentration but even
overcompensates it (Fox and Raichle 1986). Deoxy-Hb is
progressively washed out which is reflected by a reduction of
local field inhomogeneity and a raise of BOLD signal in T2*weighted MR images (Turner et al. 1991).
BOLD measurements are currently exerted with ultrafast
single-shot echo-planar-imaging (EPI) sequences as gradient
echo (GRE) or spin echo (SE) (Stippich et al. 2002a, b). GRE
sequences usually obtain higher BOLD signal predominantly
from venous origin, whereas SE sequences also measure lower
BOLD signals arising from the capillary bed in brain parenchyma (Hulvershorn et al. 2005a, b). Temporal resolution in
paradigms with a blocked or parametric design corresponds to
the chosen block duration but could be substantially improved
(<100 ms) by the introduction of event-related measurements
(Buckner et al. 1996). FMRI, however, cannot attain the temporal resolution of electroencephalography (EEG) (Berger
1929; Gevins 1995; Gevins et al. 1995) or magnetoencephalography (MEG) (Hari and Ilmoniemi 1986; Hämäläinen et al.
1993) but lacks the need for a complicated model-based calculation for source localization and offers higher spatial precision
due to a direct correlation with the surface anatomy. Signal
intensity and realizable spatial resolution vary with the magnetic field strength. MR scanners with magnetic field strengths
below 1.0 Tesla (T) are not suitable for clinical functional
BOLD imaging. The broadly available 1.5 T scanners allow
reliable measurements of cortical activation provided that powerful gradient systems (possibly >30 mT/m) are on hand, while
high-magnetic-field scanners with 3 T or above even permit
functional imaging of subcortical structures and the brain stem
(Thulborn 1999; Zambreanu et al. 2005). Despite excellent
SNR and spatial resolution, the application of fMRI at field
strengths 7.0 T or above has to be considered experimental
(Goa et al. 2014; Hua et al. 2013; Huber et al. 2014). This is
mainly due to technical and logistical difficulties as well as to
the very limited availability of ultrahigh-field MR imagers in a
clinical setting. Advantages of fMRI over positron emission
tomography (PET) (Mazziotta et al. 1982; Raichle 1983; Fox
et al. 1986) or single photon emission computer tomography
(SPECT) (Holman and Devous 1992) – other methods
measuring brain activity indirectly with lower spatial/temporal
resolution (glucose or oxygen metabolism, blood flow/perfusion changes) – are its noninvasiveness, lack of radiation,
reproducibility, and broad availability of clinical scanners.
Task-based presurgical BOLD fMRI represents the best
established and validated clinical application of fMRI,
whereas resting-state fMRI should still be considered under
initial clinical investigation. Due to the intrinsically low SNR,
it is mandatory to perform multiple repeated stimulations during each task-based fMRI measurement in order to obtain
robust BOLD signals. Statistical correlation of BOLD signal
time courses with the chosen stimulation protocol (paradigm)
enables the identification of those brain areas that show hemodynamic changes in synchrony with the task. A prerequisite
for this is a further processing of fMRI data, which is normally done after the measurements with freely available or
commercial software (Cox 1996; Friston 1996; Gold et al.
1998; Roberts 2003). However, not all of these programs have
been certified for medical use. Nowadays, most manufacturers of clinical high-magnetic-field scanners offer options for
an online processing of fMRI data (real-time fMRI) (Fernandez
et al. 2001; Moller et al. 2005; Posse et al. 2013). Since the
functionality and the statistical calculations used vary considerably between the different softwares, the appropriate choice
largely depends on individual criteria and preferences.
Basically, any data processing software for fMRI should at
least offer image alignment, motion correction, temporal and
spatial data smoothing, multiple statistical tests to assess functional activation, and options for spatial normalization
(Stippich et al. 2002a, b). Furthermore, each fMRI software
used for neurosurgery or radiation treatment should provide
precise and reliable tools for superimposing functional on
morphological images, for the integration of fMRI with DTI
data, and for data export (e.g., into neuronavigation systems).
This textbook has its traditional focus on presurgical
functional neuroimaging. Today, presurgical task-based
fMRI is the most widely used modality and is commonly
combined with DTI and DTT to visualize both functionally
important cortical areas and white matter tracts. Hence, we
have now added essential information on this complementary MR modality but keep the focus strictly on pre- and
intraoperative applications in patients with brain tumors and
epilepsy. A detailed description of diffusion MRI is beyond
the scope of this book – for this purpose, we refer the reader
to the extensive literature available.
Diffusion Tensor Imaging (DTI)
and DTI Tractography (DTT)
Diffusion MR signal mainly originates from protons that
move in the extracellular space of biological tissues (Brownian
motion) (LeBihan 2006, 2013; LeBihan and Johansen-Berg
2012). Within a given voxel, the diffusion may be fully free
and undirected (isotropic) or directed (anisotropic) due to
barriers preventing proton movement (e.g., myelinated
axons). DTI is capable to detect such anisotropic diffusion
(Basser et al. 1994; LeBihan et al. 2001), but for this end diffusion must at least be measured in six different directions.
Anisotropic diffusion can then be modeled mathematically
using a 3D Gaussian probability function from which a 3 × 3
matrix is calculated, named diffusion tensor. The diffusion
tensor is characterized by eigenvalues and eigenvectors and
indicates the main orientation of diffusion within a voxel. The
fractional anisotropy (FA) quantifies such directed diffusion.
Isotropic (undirected) diffusion corresponds to an FA value of
0 which translates graphically to a sphere. In contrast, an FA
value of 1 reflects the opposite extreme, i.e., a totally directed
(anisotropic) diffusion which would graphically translate to a
line but does not occur in biological tissues – thus, the typical
shape of the FA is an ellipsoid.
Myelinated axons are lipophilic and represent diffusion barriers for hydrophilic protons that travel perpendicularly. In turn,
this results in a preferred orientation and higher velocity of
diffusion along such barriers. Thus, DTI reflects the white matter architecture and the course of functionally important fiber
bundles rather indirectly by measuring the anisotropic diffusion of protons between and along axons. Basically, DTI fiber
tracts are reconstructed by following and connecting the predominant directed diffusion across adjacent voxels. Standard
DTI measurements and most mathematical algorithms
employed for analyzing DTI data have limitations when different orientations of diffusion need to be differentiated within a
voxel, when crossing fibers need to be reconstructed, or when
diffusion anisotropy is affected by the brain's pathology, e.g.,
by tumor invasion or edema (Cortez-Conradis et al. 2013;
Kallenberg et al. 2013; Kleiser et al. 2010; Stadlbauer et al.
2010). At the expense of scanning/processing time, more
advanced MR techniques enable the assessment of the contribution of the differential intravoxel anisotropy (diffusion spectrum imaging, q-ball imaging, HARDI, etc.) or the employment
of a more sophisticated (e.g., probabilistic or advanced deterministic) modeling for tractography (Bauer et al. 2013; Kuhnt
et al. 2013a, b; O'Donell et al. 2012). In general, the quality of
DTI images depends on the number of directions measured, the
number of averages used, and the spatial resolution chosen,
which are all inversely related to scanning time.
Presurgical fMRI and DTI
Presurgical fMRI and DTI measurements are carried out to
facilitate function-preserving and safe treatment in patients with
brain tumors and epilepsy by localizing and lateralizing specific
brain functions, functionally important axonal connections, or
epileptic activity, noninvasively (Bick et al. 2012; Dimou et al.
2013; Centeno and Carmichael 2014). This diagnostic information cannot be obtained from morphological brain imaging
alone or from invasive measures prior to treatment.
Consequently, presurgical fMRI and DTI are always performed in individual patients to achieve a functional diagnosis. This differs fundamentally from applications in basic
neuroscience research where normal or altered brain function
is usually investigated in group studies to better understand
physiological or pathological conditions in general. A direct
contribution to the patient management is not required. In contrast, for clinical diagnostic applications, the experimental
setup as well as the processing and evaluation of the data need
to be adapted to the clinical environment so that patients – who
may present with neurological or cognitive deficits – can be
examined successfully in a standardized way. Still, in clinical
fMRI and DTI, this is typically achieved via local experts,
individual routines, and own validation (Pillai 2010). The
novel applications of resting-state fMRI (RS-MRI) may have
practical advantages, as an active cooperation of the patient is
not required (Lang et al. 2014). Uncooperative, sedated, or
anesthesized patients or children who are not able to perform
task-based fMRI properly may profit from RS-MRI. Potentially,
RS-fMRI could also be applied intraoperatively (Nimsky
2011). The available data on presurgical RS-fMRI are very
limited, however, and therefore do not justify to draw any firm
conclusion on its clinical feasibility and validity, yet.
During the last years, more and more devices and software
solutions have become commercially available that facilitate
the clinical application of fMRI. These products are mainly
dedicated to stimulation and data processing. Moreover, first
attempts have been made to define robust clinical applications
for task-based fMRI. To this end, paradigms have been proposed and published online by the American Society of
Functional Neuroradiology (for details, please visit www.
asfnr.org/paradigms.html). At least in the USA, CPT codes
have been established for reimbursement of clinical fMRI
examinations. It is important to note, however, that fMRI and
DTI cannot be considered as fully standardized methods routinely used in clinical diagnostic neuroimaging. Hence,
depending on the local situations, it may still be required to
perform presurgical fMRI and DTI examinations in the
framework of scientific studies until all hard- and software
components used for medical application have been certified
and official recommendations or guidelines have been issued
by the relevant national medical association. Until then, individual routines and standards still need to be established for
data acquisition, processing, and evaluation, as well as for the
medical interpretation and documentation of clinical fMRI
and DTI findings. For a meaningful clinical application, a
profound knowledge of the specifications of the different
software packages used, of possible sources of errors and
imaging artifacts, and of relevant limitations of the techniques
employed is indispensible. As a basic principle, presurgical
fMRI and DTI examinations should be performed, evaluated,
and interpreted by trained and experienced physicians with
particular expertise in this area, since careless use of this very
promising technique could endanger patients.
There are numerous studies available suggesting a high
reliability of fMRI to localize the different cortical representations of the human body within the primary motor and
somatosensory cortices (Fig. 2) as well as the motor and sensory language areas (Fig. 3) prior to brain surgery, if indications and limits of the method are considered. The same
holds true for the noninvasive determination of the dominant
brain hemisphere for language function.
Additional attention needs to be paid to technique-related
inaccuracies due to the superposition of functional and morphological images, the referencing of fMRI data in neuronavigation systems, or the surgery-induced localization
errors following removal of brain tissue or loss of cerebrospinal fluid (brain shift) (Reinges et al. 2004; Wittek et al.
Fig. 2 Preoperative fMRI somatotopic mapping of the motor (a) and
somatosensory (b) homunculus and DTI tractography of the corticospinal (pyramidal) tract in a symptomatic patient with a left parietal
astrocytoma. Voluntary movements of the toes and fingers on the right
side were used for motor mapping, and fully automated pneumatically
driven tactile stimulation of digits 1 and 2 to the right foot and hand,
respectively, was employed for somatosensory stimulation. Of note is
the enhanced co-activation of the premotor and primary hand
representations in the right hemisphere during voluntary right hand
movements as an fMRI indicator for tumor-associated neuroplastic
reorganization. Integration of the abovementioned different functional
body representations (foot motor (dark blue), foot somatosensory
(light blue), hand motor (yellow), hand somatosensory (orange),
tongue motor (purple)) and of the pyramidal tract (green) into a 3D
data set for functional neuronavigation (c, left), 3D surface view
(c, right) (Color figure online)
2005). Safety of surgical procedures in functional areas or
their proximity can be improved by concomitant visualization of functional landmarks and important fiber tracts (e.g.,
pyramidal tract, arcuate fascicle) using diffusion tensor
imaging (DTI) (Coenen et al. 2001; Holodny et al. 2001;
Krings et al. 2001; Stippich et al. 2003a; Ulmer et al. 2004b;
Holodny et al. 2005; Shinoura et al. 2005). The same holds
true for the combined use of fMRI and EEG (Towle et al.
2003), MEG (Kober et al. 2001; Grummich et al. 2006) or
PET (Baumann et al. 1995; Bittar et al. 1999). Tumorinduced hemodynamic changes can lead to erroneous fMRI
localization and missing or artificial BOLD signals (Holodny
et al. 1999, 2000; Schreiber et al. 2000; Krings et al. 2002;
Ulmer et al. 2004a, b). Electrophysiological techniques are
unsusceptible to these problems, since they directly measure
electromagnetic fields resulting from synaptic activity
(Berger 1929; Hari and Ilmoniemi 1986; Hämäläinen et al.
1993). However, localization of electromagnetic sources
requires complicated modeling and calculations and is therefore limited in precision and accuracy. Furthermore, it
should be borne in mind that fMRI and DTI results are gen-
erated by using mathematical correlations and therefore vary
with the chosen statistical parameters or thresholds.
Consequently, the size and extent of fMRI cortical activations or of reconstructed DTI fiber tracts do not reflect the
truth and may confront the operator with and unfounded
safety margin. Thus, resection borders cannot be determined
reliably on the basis of fMRI or DTI data without standardisation and validation.
When applied in a standardized way, fMRI has the diagnostic potential to substantially contribute to the planning and
implementation of function-preserving therapies in patients
with brain tumors and epilepsy (Lee et al. 1999; Gaillard
et al. 2000; Grabowski 2000; Hirsch et al. 2000; Sunaert and
Yousry 2001; Baxendale 2002; Binder et al. 2002; Rutten
et al. 2002; Stippich et al. 2003a, b; Van Westen et al. 2005;
Stippich et al. 2007; Thulborn 2006). Prior to and during
neurosurgical interventions, fMRI can help to reduce the need
for invasive diagnostic procedures, as intra-arterial WADA
test (Wada and Rasmussen 1960; Rausch et al. 1993; Benbadis
et al. 1998; Abou-khalil and Schlaggar 2002) or intraoperative electrocorticography (Penfield 1937; Cedzich et al. 1996;
Fig. 3 Preoperative fMRI language mapping of the motor (Broca) and
sensory (Wernicke) language areas and DTI tractographies of the arcuate fascicle (green) and pyramidal tract (purple) integrated into the
T1-weighted post-contrast 3D MRI used for functional neuronavigation
in a female patient with a symptomatic left astrocytoma involving the
inferior frontal and superior temporal lobes and the insula; transverse,
coronal, and sagittal views, 3D surface view. fMRI revealed a left language dominance and a good spatial agreement between the functional
localizations obtained with four different language paradigms for both
essential language areas (Color figure online)
Duffau et al. 2002, 2003). Whether the embedding of fMRI
and DTI in presurgical diagnostics can indeed reduce surgery-related morbidity and mortality should be investigated
in prospective clinical trials (Zacharaki et al. 2012).
Prerequisites are a consensus on measuring techniques, analysis procedures, and medical evaluation of clinical fMRI as
well as the establishment of official recommendations and
guidelines by the assigned medical association. As stated earlier, first attempts in that direction are underway.
Content Overview
Chapter 2 provides an easy, but in-depth, access to the
techniques and underlying physiology of the abovementioned
different fMRI and DTI techniques (Bandettini et al. 1992;
Kwong et al. 1992; Ogawa et al. 1993; Basser et al. 1994;
Purdon and Weisskoff 1998). The principles and basics of
MRI, fMRI, and DTI, as well as the different established
experimental designs for task-based fMRI, are presented
along with the options for specific data analysis. The restingstate fMRI technique is explained in detail and what methods
can be implemented to study functional connectivity in different resting-state networks. Finally, diffusion tensor imaging
and tractography are addressed (LeBihan and Johansen-Berg
2012). On a solid methodological basis, the capabilities to
study structural connectivity and to employ presurgical
tractography are demonstrated.
Chapter 3 extensively deals with the relevant morphological and functional neuroanatomy to facilitate the reader's
access to presurgical fMRI and DTI. In addition to a detailed
systematic description of the surface anatomy and cytoarchitecture of the human brain, important morphological criteria
for a straightforward identification of different anatomical
structures are discussed. Comprehensive information on the
functional neuroanatomy of the motor and language systems
is provided. Here, it cannot be sufficiently stressed that a
profound knowledge of the relevant neuroanatomy is indispensable for a correct medical interpretation of clinical fMRI
and DTI data. In any case, the precentral knob is the only
reliable anatomical landmark for a functional area, namely,
the motor hand representation (Yousry et al. 1997; Fesl et al.
2003). There are no morphological landmarks for areas
related to cognitive brain functions such as language or
memory (Ojemann et al. 1989; Ojemann 1991). Due to the
vast physiological interindividual anatomical variability
(Amunts et al. 1999, 2000) and the dependence on various
individual factors, functional areas are traditionally mapped
intraoperatively by means of electrophysiological methods
(Penfield 1937, 1950; Woolsey et al. 1979; Ojemann et al.
1989; Ojemann 1991; Uematsu et al. 1992; Cedzich et al.
1996; Duffau et al. 1999). However, this information is preoperatively inaccessible, and the time needed for surgery is
therefore significantly prolonged. FMRI and DTI, on the
other hand, yield relevant diagnostic information on anatomy,
pathology, and function prior to surgery in one single
examination. Thus, the indication for presurgical fMRI and
DTI results from:
• Clinical signs and symptoms
• The limitations of morphological imaging
• The necessity to measure and visualize normal, modified
neuroplastic, and pathological (e.g., epileptic) brain activity
Chapter 4 covers presurgical task-based BOLD fMRI,
which represents fMRI's best established, validated, and
most widely used clinical application. Particular notice is
given to practical and methodological-technical aspects
(Sect. 3) as well as to specific requirements of fMRI diagnostics in patients with rolandic brain tumors (Sect. 4) or lesions
with critical spatial relationship to language areas (Sect. 5).
Diagnostic aims and selection criteria for patients are discussed, clinically tested examination protocols are proposed
(Stippich et al. 1999, 2000, 2002b, 2003b, 2004, 2005, 2007;
Stippich 2010), and their applications are illustrated with
example cases. Further, potentials and limits of presurgical
task-based fMRI are depicted (Sect. 6).
Chapter 5 highlights the initial experience with restingstate fMRI (RS-fMRI) as a novel functional neuroimaging
modality in the presurgical work-up of patients with brain
tumors (Mitchell et al. 2013). Here, no stimulation or active
cooperation of the patients is required to assess important
functional systems, which is potentially of great value to further facilitate the clinical application of fMRI (Posse et al
2013). RS-fMRI provides additional information on the connectivity between different functionally important brain
areas, which may be exploited in the future to study the
effects of lesions, treatment, and medication on brain function (Niu et al 2014; Smucny et al. 2014; Otten et al. 2012;
Martino et al. 2011). Such neuroplastic alterations in brain
function may be compensatory or pathological in nature.
Chapter 6 refers to the highly specific application of presurgical fMRI in patients with epilepsy which requires fundamentally different data acquisition and processing
techniques as compared to both task-based and resting-state
fMRI, such as EEG-correlated fMRI for the localization of
epileptogenic foci (Centeno and Carmichael 2014: Chiang
et al. 2014). To this end, major technical and methodological
problems had to be solved, which now enables us to use electrical devices (EEG) inside MR scanners to correct for interferences and related artifacts and thereby precisely detect
and localize the sources of epileptic activity in the human
brain. EEG-correlated fMRI is by no means a standard application (Pittau et al. 2014). It should be considered as a valuable additional investigation tool in the field of epilepsy
imaging which is available in some leading medical centers
Chapter 7 accounts for DTI and DTT with their proven
value for functional brain tumor surgery with respect to both
preoperative neuroimaging and intraoperative navigation
(Potgieser et al. 2014; Shahar et al. 2014; Sternberg et al.
2014; Kuhnt et al. 2013a, b). In this setting, DTI is fully
complementary to fMRI, by providing additional relevant
information on the course and integrity of important white
matter tracts in relation to a surgical target. Hence, these
techniques should be applied in combination whenever possible. Specific attention is given to the corticospinal tract and
sensorimotor system; the arcuate, uncinate, inferior frontooccipital fascicles and language systems; as well as the superior longitudinal fascicle, optic radiation, and the visuospatial
attention network.
Chapter 8 addresses the specific aspects of functional
neuronavigation (Orringer et al. 2012; Risholm et al. 2011).
With the help of the functional landmarks provided by fMRI
and DTI, the spatial relationship between the brain tumor or
epileptogenic zone, functional brain areas, and essential
white matter tracts can be evaluated preoperatively, which
facilitates the selection of the most cautious therapy.
Functional neuronavigation permits planning and implementation of radical and, at the same time, function-preserving operations. This goal is rarely achieved with
morphological information alone, especially in the presence
of brain malformations, anatomical variants, or a disturbed
or destroyed anatomy due to tumor growth or pathologyrelated neuroplastic changes of brain function. Technical
inaccuracies and corrections for brain shift due to intraoperative loss of cerebrospinal fluid and tissue removal have to be
taken into account (Kuhnt et al. 2012a).
Chapter 9 is dedicated to the validation of presurgical
fMRI and DTI with established reference procedures such as
intraoperative electrocorticography (ECoG) or intra-arterial
administration of barbiturates (Wada test) (Leclercq et al.
2011). For a thorough understanding of the topic, these reference procedures are presented in detail together with a repetition of the relevant methodological aspects and limitations of
fMRI. Today, it can be assumed that presurgical task-based
fMRI is a robust and valid tool to localize different representations of the human body in the primary motor and somatosensory cortices, to localize essential language centers – namely,
Broca's and Wernicke's areas – and to lateralize the brain's
dominant hemisphere for language function. There is also
substantial evidence that DTT is reliable to visualize the
pyramidal tract, the arcuate fascicle, the optic radiation, and
other large white matter bundles both pre- and intraoperatively (Shahar et al. 2014). FMRI and DTI have the potential
to help to reduce the number of invasive measures needed, to
better select those patients who require such interventions,
and to facilitate the planning and targeted intraoperative positioning of electrodes. If and to what extent a substitution of
invasive measures may be appropriate is not fully clear, yet.
This topic is inherently related to Chap. 10 which provides
the reader with an overview on multimodal investigations
comparing fMRI to other methods of functional neuroimaging (Wehner 2013). These methods include multiparametric
functional and structural MRI and MR spectroscopy (MRS),
positron emission tomography (PET), and single positron
emission computed tomography (SPECT) – the latter two
techniques are from the domain of nuclear medicine that utilize radioactive substances/tracers and can be employed
together with CT or MR scanners for hybrid imaging (Nensa
et al. 2014) – just as the electrophysiological methods electroencephalography (EEG) and magnetoencephalography
(MEG) that noninvasively measure electromagnetic fields as
a direct correlate of neuronal (synaptic) activity with a very
high temporal resolution (Grummich et al. 2006). These
techniques are therefore not susceptible to hemodynamic or
metabolic influencing factors.
Chapter 11 covers neuroplasticity from its definition to its
implications for diagnosis, treatment, and prognosis in the clinical context from a neuroimaging's perspective (Niu et al. 2014;
Tozakidou et al. 2013; Partovi et al. 2012). The measurable
neuroplastic changes are also discussed on the basis of the
underlying pathophysiology down to the cellular and molecular
levels. The current understanding of neuroplasticity imaging is
condensed from an extensive literature research on patients with
stroke, epilepsy, brain tumors, multiple sclerosis, and peripheral
nervous system disorders used to interpret neuroplastic imaging
findings. Clinical examples are provided with a focus on neuroplasticity of the motor system, which in turn is helpful to better
understand phenomena that may be observed in preoperative
functional neuroimaging. Clear and valuable considerations are
provided for a practical imaging of neuroplasticity.
Chapter 12 accounts for pitfalls, drawbacks, and diagnostic
errors in clinical BOLD fMRI and DTI. Important imaging
artifacts, influencing factors of brain lesions and pharmaceutical effects on the measurable BOLD response and DTI data,
are presented and discussed in detail. Practical suggestions to
overcome these problems are provided for a successful application of presurgical diagnostic fMRI and DTI.
Abou-Khalil B, Schlaggar BL (2002) Is it time to replace the Wada test?
Neurology 59(2):160–161
Amunts K, Schleicher A et al (1999) Broca's region revisited: cytoarchitecture and intersubject variability. J Comp Neurol 412(2):319–341
Amunts K, Malikovic A et al (2000) Brodmann's areas 17 and 18
brought into stereotaxic space-where and how variable? Neuroimage
11(1):66–84
Bandettini PA, Wong EC et al (1992) Time course EPI of human brain
function during task activation. Magn Reson Med 25(2):390–397
Basser PJ, Mattiello J, LeBihan D (1994) Estimation of the effective
self-diffusion tensor from the NMR spin echo. J Magn Reson B
103(3):247–254
Bauer MH, Kuhnt D et al (2013) Reconstruction of white matter tracts via
repeated deterministic streamline tracking – initial experience. PLoS
One 8(5):e63082. doi:10.1371/journal.pone.0063082, Print 2013
Baumann SB, Noll DC et al (1995) Comparison of functional magnetic
resonance imaging with positron emission tomography and magnetoencephalography to identify the motor cortex in a patient with an
arteriovenous malformation. J Image Guid Surg 1(4):191–197
Baxendale S (2002) The role of functional MRI in the presurgical investigation of temporal lobe epilepsy patients: a clinical perspective
and review. J Clin Exp Neuropsychol 24(5):664–676
Belliveau JW, Kennedy DN Jr et al (1991) Functional mapping of the
human visual cortex by magnetic resonance imaging. Science
254(5032):716–719
Benbadis SR, Binder JR et al (1998) Is speech arrest during wada testing a valid method for determining hemispheric representation of
language? Brain Lang 65(3):441–446
Berger H (1929) Über das Elektroenzephalogramm des Menschen.
Arch Psychiatr Nervenk 87:527–570
Bick AS, Mayer A, Levin N (2012) From research to clinical practice:
implementation of functional magnetic imaging and white matter
tractography in the clinical environment. J Neurol Sci 312(1–
2):158–165. doi:10.1016/j.jns.2011.07.040, Epub 2011 Aug 23
Binder JR, Achten E et al (2002) Functional MRI in epilepsy. Epilepsia
43(Suppl 1):51–63
Bittar RG, Olivier A et al (1999) Presurgical motor and somatosensory
cortex mapping with functional magnetic resonance imaging and
positron emission tomography. J Neurosurg 91(6):915–921
Buckner RL, Bandettini PA et al (1996) Detection of cortical activation
during averaged single trials of a cognitive task using functional
magnetic resonance imaging. Proc Natl Acad Sci U S A 93(25):
Cedzich C, Taniguchi M et al (1996) Somatosensory evoked potential
phase reversal and direct motor cortex stimulation during surgery in
and around the central region. Neurosurgery 38(5):962–970
Centeno M, Carmichael DW (2014) Network connectivity in epilepsy:
resting state fMRI and EEG-fMRI contributions. Front Neurol 5:93.
doi:10.3389/fneur.2014.00093, eCollection 2014
Chiang S, Levin HS, Haneef Z (2014) Computer-automated focus lateralization of temporal lobe epilepsy using fMRI. J Magn Reson
Imaging. doi:10.1002/jmri.24696
Dimou S, Battisti RA et al (2013) A systematic review of functional
magnetic resonance imaging and diffusion tensor imaging modalities used in presurgical planning of brain tumour resection.
Neurosurg Rev 36(2):205–214; discussion 214. doi:10.1007/
s10143-012-0436-8, Epub 2012 Nov 29
Cortez-Conradis D, Favila R et al (2013) Diagnostic performance of
regional DTI-derived tensor metrics in glioblastoma multiforme:
simultaneous evaluation of p, q, L, Cl, Cp, Cs, RA, RD, AD, mean
diffusivity and fractional anisotropy. Eur Radiol 23(4):1112–1121.
doi:10.1007/s00330-012-2688-7, Epub 2012 Oct 21
Cox RW (1996) AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res
29(3):162–173
Detre JA, Leigh JS et al (1992) Perfusion imaging. Magn Reson Med
Dimou S, Battisti RA et al (2013b) A systematic review of functional
Neurosurg Rev 36(2):205–214. doi:10.1007/s10143-012-0436-8;
discussion 214, Epub 2012 Nov 29
Duffau H, Capelle L et al (1999) Intra-operative direct electrical stimulations of the central nervous system: the Salpetriere experience
with 60 patients. Acta Neurochir (Wien) 141(11):1157–1167
Duffau H, Capelle L et al (2002) Intraoperative mapping of the subcortical language pathways using direct stimulations. An anatomofunctional study. Brain 125(Pt 1):199–214
Duffau H, Capelle L et al (2003) Usefulness of intraoperative electrical
subcortical mapping during surgery for low-grade gliomas located
within eloquent brain regions: functional results in a consecutive
series of 103 patients. J Neurosurg 98(4):764–778
Fernandez G, de Greiff A et al (2001) Language mapping in less than
15 minutes: real-time functional MRI during routine clinical investigation. Neuroimage 14(3):585–594
Fesl G, Moriggl B et al (2003) Inferior central sulcus: variations of
anatomy and function on the example of the motor tongue area.
Neuroimage 20(1):601–610
Fox PT, Raichle ME (1986) Focal physiological uncoupling of cerebral
blood flow and oxidative metabolism during somatosensory stimulation in human subjects. Proc Natl Acad Sci U S A
83(4):1140–1444
Fox PT, Mintun MA et al (1986) Mapping human visual cortex with
positron emission tomography. Nature 323(6091):806–809
Frahm J, Merboldt KD et al (1994) Brain or vein – oxygenation or
flow? On signal physiology in functional MRI of human brain activation. NMR Biomed 7(1–2):45–53
Friston K (1996) Statistical parametric mapping and other analyses of
functional imaging data. In: John M, Toga AW (eds) Brain mapping:
the methods. Academic Press, New York, pp 363–386
Gaillard WD, Bookheimer SY, Cohen M (2000) The use of fMRI in
neocortical epilepsy. Adv Neurol 84:391–404
Gevins A (1995) High-resolution electroencephalographic studies of
cognition. Adv Neurol 66:181–195; discussion 195–198
Gevins A, Leong H et al (1995) Mapping cognitive brain function with
modern high-resolution electroencephalography. Trends Neurosci
18(10):429–436
Goa PE, Koopmans PJ et al (2014) BOLD fMRI signal characteristics
of S1 and S2-SSFP at 7 Tesla. Front Neurosci 8:49. doi:10.3389/
fnins.2014.00049
Gold S, Christian B et al (1998) Functional MRI statistical software
packages: a comparative analysis. Hum Brain Mapp 6(2):73–84
Grabowski TJ (2000) Investigating language with functional neuroimaging. In: John M, Toga AW (eds) Brain mapping: the systems.
Academic Press, San Diego, pp 425–461
Grummich P, Nimsky C et al (2006) Combining fMRI and MEG
increases the reliability of presurgical language localization: a clinical study on the difference between and congruence of both modalities. Neuroimage 32(4):1793–1803
Hämäläinen M, Ilmoniemi RJ et al (1993) Magnetoencephalography
-theory, instrumentation and applications to noninvasive studies of
the working human brain. Rev Mod Phys 65:413–487
Hari R, Ilmoniemi RJ (1986) Cerebral magnetic fields. Crit Rev Biomed
Eng 14(2):93–126
Hirsch J, Ruge MI et al (2000) An integrated functional magnetic resonance imaging procedure for preoperative mapping of cortical areas
associated with tactile, motor, language, and visual functions.
Neurosurgery 47(3):711–721; discussion 721–722
Holman BL, Devous MD Sr (1992) Functional brain SPECT: the emergence of a powerful clinical method. J Nucl Med 33(10):1888–1904
Holodny AI, Schulder M et al (1999) Decreased BOLD functional MR
activation of the motor and sensory cortices adjacent to a glioblastoma multiforme: implications for image-guided neurosurgery.
AJNR Am J Neuroradiol 20(4):609–612
Holodny AI, Schulder M et al (2000) The effect of brain tumors on
BOLD functional MR imaging activation in the adjacent motor cortex: implications for image-guided neurosurgery. AJNR Am J
Neuroradiol 21(8):1415–1422
Holodny AI, Schwartz TH et al (2001) Tumor involvement of the corticospinal tract: diffusion magnetic resonance tractography with
intraoperative correlation. J Neurosurg 95(6):1082
Holodny AI, Gor DM et al (2005) Diffusion-tensor MR tractography of
somatotopic organization of corticospinal tracts in the internal
capsule: initial anatomic results in contradistinction to prior reports.
Radiology 234(3):649–653
Hua J, Qin Q et al (2013) Whole-brain three-dimensional T2-weighted
BOLD functional magnetic resonance imaging at 7 Tesla. Magn
Reson Med. doi:10.1002/mrm.25055
Huber L, Goense J et al (2014) Investigation of the neurovascular coupling in positive and negative BOLD responses in human brain at
7T. Neuroimage 97:349–362
Hulvershorn J, Bloy L et al (2005a) Spatial sensitivity and temporal
response of spin echo and gradient echo bold contrast at 3 T using
peak hemodynamic activation time. Neuroimage 24(1):216–223
Hulvershorn J, Bloy L et al (2005b) Temporal resolving power of spin
echo and gradient echo fMRI at 3T with apparent diffusion coefficient compartmentalization. Hum Brain Mapp 25(2):247–258
Kallenberg K, Goldmann T et al (2013) Glioma infiltration of the corpus
callosum: early signs detected by DTI. J Neurooncol 112(2):217–
222. doi:10.1007/s11060-013-1049-y, Epub 2013 Jan 24
Kleiser R, Staempfli P et al (2010) Impact of fMRI-guided advanced
DTI fiber tracking techniques on their clinical applications in
patients with brain tumors. Neuroradiology 52(1):37–46.
doi:10.1007/s00234-009-0539-2, Epub 2009 May 29
Kober H, Nimsky C et al (2001) Correlation of sensorimotor activation
with functional magnetic resonance imaging and magnetoencephalography in presurgical functional imaging: a spatial analysis.
Neuroimage 14(5):1214–1228
Krings T, Reinges MH et al (2001) Functional and diffusion-weighted
magnetic resonance images of space-occupying lesions affecting
the motor system: imaging the motor cortex and pyramidal tracts.
J Neurosurg 95(5):816–824
Krings T, Reinges MH et al (2002) Factors related to the magnitude of
T2∗ MR signal changes during functional imaging. Neuroradiology
Kuhnt D, Bauer MH, Nimsky C (2012a) Brain shift compensation and
neurosurgical image fusion using intraoperative MRI: current status
and future challenges. Crit Rev Biomed Eng 40(3):175–185
Kuhnt D, Bauer MH et al (2012b) Intraoperative visualization of fiber
tracking based reconstruction of language pathways in glioma surgery.
Neurosurgery 70(4):911–919. doi:10.1227/NEU.0b013e318237a807;
discussion 919–920
Kuhnt D, Bauer MH et al (2013a) Optic radiation fiber tractography in
glioma patients based on high angular resolution diffusion imaging
with compressed sensing compared with diffusion tensor imaging –
initial experience. PLoS One 8(7):e70973. doi:10.1371/journal.
pone.0070973, Print 2013
Kuhnt D, Bauer MH et al (2013b) Functional imaging: where do we go
from here? J Neurosurg Sci 57(1):1–11
Kwong KK, Belliveau JW et al (1992) Dynamic magnetic resonance
imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A 89(12):675–679
Lang S, Duncan N, Northoff G (2014) Resting-state functional magnetic
resonance imaging: review of neurosurgical applications.
Neurosurgery 74(5):453–464. doi:10.1227/NEU.0000000000000307;
LeBihan D (2006) From Brownian motion to mind imaging: diffusion
MRI. Bull Acad Natl Med 190(8):1605–1627; discussion 1627
LeBihan D (2013) Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. Radiology
268(2):318–322. doi:10.1148/radiol.13130420
LeBihan D, Johansen-Berg H (2012) Diffusion MRI at 25: exploring
brain tissue structure and function. Neuroimage 61(2):324–341.
doi:10.1016/j.neuroimage.2011.11.006, Epub 2011 Nov 20
LeBihan D, Mangin JF et al (2001) Diffusion tensor imaging: concepts
and applications. J Magn Reson Imaging 13(4):534–546
Leclercq D, Delmaire C et al (2011) Diffusion tractography: methods, validation and applications in patients with neurosurgical lesions. Neurosurg
Clin N Am 22(2):253–268. doi:10.1016/j.nec.2010.11.004, ix
Lee CC, Ward HA et al (1999) Assessment of functional MR imaging
in neurosurgical planning. AJNR Am J Neuroradiol
Lee MH, Smyser CD, Shimony JS (2013) Resting-state fMRI: a review
of methods and clinical applications. AJNR Am J Neuroradiol
34(10):1866–1872. doi:10.3174/ajnr.A3263, Epub 2012 Aug 30
Logothetis NK (2002) The neural basis of the blood-oxygen-leveldependent functional magnetic resonance imaging signal. Philos
Trans R Soc Lond B Biol Sci 357(1424):1003–1037
Logothetis NK (2003) The underpinnings of the BOLD functional
magnetic resonance imaging signal. J Neurosci 23(10):3963–3971
Logothetis NK, Pfeuffer J (2004) On the nature of the BOLD fMRI
contrast mechanism. Magn Reson Imaging 22(10):1517–1531
Logothetis NK, Wandell BA (2004) Interpreting the BOLD signal.
Annu Rev Physiol 66:735–769
Logothetis NK, Pauls J et al (2001) Neurophysiological investigation of
the basis of the fMRI signal. Nature 412(6843):150–157
Martino J, Honma SM et al (2011) Resting functional connectivity in
patients with brain tumors in eloquent areas. Ann Neurol 69(3):521–
532. doi:10.1002/ana.22167, Epub 2011 Mar 11
Mazziotta JC, Phelps ME et al (1982) Tomographic mapping of
human cerebral metabolism: auditory stimulation. Neurology 32(9):
Menon RS, Ogawa S et al (1995) BOLD based functional MRI at 4
Tesla includes a capillary bed contribution: echoplanar imaging correlates with previous optical imaging using intrinsic signals. Magn
Reson Med 33(3):453–459
Mitchell TJ, Hacker CD et al (2013) A novel data-driven approach to
preoperative mapping of functional cortex using resting-state functional magnetic resonance imaging. Neurosurgery 73(6):969–982.
doi:10.1227/NEU.0000000000000141; discussion 982–983
Moller M, Freund M et al (2005) Real time fMRI: a tool for the routine
presurgical localisation of the motor cortex. Eur Radiol 15(2):
Nensa F, Beiderwellen K et al (2014) Clinical applications of PET/MR:
current status and future perspectives. Diagn Interv Radiol.
doi:10.5152/dir.14008 [Epub ahead of print]
Nimsky C (2011) Intraoperative acquisition of fMRI and DTI. Neurosurg
Niu C, Zhang M et al (2014) Motor network plasticity and lowfrequency oscillations abnormalities in patients with brain gliomas:
a functional MRI study. PLoS One 9(5):e96850. doi:10.1371/journal.pone.0096850, eCollection 2014
O'Donell LJ, Rigolo L et al (2012) fMRI-DTI modeling via landmark
distance atlases for prediction and detection of fiber tracts.
Neuroimage 60(1):456–470. doi:10.1016/j.neuroimage.2011.11.014,
Epub 2011 Dec 2
Ogawa S, Lee TM et al (1990) Brain magnetic resonance imaging with
contrast dependent on blood oxygenation. Proc Natl Acad Sci U S
A 87(24):9868–8972
Ogawa S, Tank DW et al (1992) Intrinsic signal changes accompanying
sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci U S A 89(13):5951–5955
Ogawa S, Menon RS et al (1993) Functional brain mapping by blood
oxygenation level-dependent contrast magnetic resonance imaging.
A comparison of signal characteristics with a biophysical model.
Biophys J 64(3):803–812
Ojemann GA (1991) Cortical organization of language. J Neurosci
Ojemann G, Ojemann J et al (1989) Cortical language localization in
left, dominant hemisphere. An electrical stimulation mapping investigation in 117 patients. J Neurosurg 71(3):316–326
Orringer DA, Golby A, Jolesz F (2012) Neuronavigation in the surgical
management of brain tumors: current and future trends. Expert Rev
Med Devices 9(5):491–500. doi:10.1586/erd.12.42
Otten ML, Mikell CB et al (2012) Motor deficits correlate with resting
state motor network connectivity in patients with brain tumours. Brain
135(Pt 4):1017–1026. doi:10.1093/brain/aws041, Epub 2012 Mar 8
Partovi S, Jacobi B et al (2012) Clinical standardized fMRI reveals
altered language lateralization in patients with brain tumor. AJNR
Am J Neuroradiol 33(11):2151–2157. doi:10.3174/ajnr.A3137,
Epub 2012 May 17
Penfield W (1937) Somatic motor and sensory representation in the
cerebral cortex of man as studied by electrical stimulation. Brain
Penfield W (1950) The cerebral cortex of man. MacMillan, New York:
57 ff
Pillai JJ (2010) The evolution of clinical functional imaging during the
past 2 decades and its current impact on neurosurgical planning.
AJNR Am J Neuroradiol 31(2):219–225. doi:10.3174/ajnr.A1845
Pittau F, Groullier F et al (2014) The role of functional neuroimaging in
pre-surgical epilepsy evaluation. Front Neurol 5:31. doi:10.3389/
fneur.2014.00031, eCollection 2014
Posse S, Ackley E et al (2013) High-speed real-time resting-state FMRI
using multi-slab echo-volumar imaging. Front Hum Neurosci
7:479. doi:10.3389/fnhum.2013.00479, eCollection 2013
Potgieser AR, Wagemakers M et al (2014) The role of diffusion tensor
imaging in brain tumor surgery: a review of the literature. Clin
Neurol Neurosurg 124C:51–58. doi:10.1016/j.clineuro.2014.06.009
[Epub ahead of print]
Purdon PL, Weisskoff RM (1998) Effect of temporal autocorrelation
due to physiological noise and stimulus paradigm on voxel-level
false-positive rates in fMRI. Hum Brain Mapp 6:239–249
Raichle ME (1983) Positron emission tomography. Annu Rev Neurosci
Rausch R, Silfvenious H et al (1993) Intra-arterial amobarbital procedures. In: Engel JJ (ed) Surgical treatment of the epilepsies. Raven
Press, New York, pp 341–357
Reinges MH, Nguyen HH et al (2004) Course of brain shift during
microsurgical resection of supratentorial cerebral lesions: limits of
conventional neuronavigation. Acta Neurochir (Wien) 146(4):
369–377; discussion 377
Risholm P, Golby AJ, Wells W 3rd (2011) Multimodal image registration for preoperative planning and image-guided neurosurgical procedures. Neurosurg Clin N Am 22(2):197–206, viii. doi:10.1016/j.
nec.2010.12.001
Roberts TP (2003). Functional magnetic resonance imaging (fMRI) processing and analysis. ASNR Electronic Learning Center Syllabus 1–23
Rutten GJ, Ramsey NF et al (2002) Development of a functional magnetic resonance imaging protocol for intraoperative localization of
critical temporoparietal language areas. Ann Neurol 51(3):350–360
Schreiber A, Hubbe U et al (2000) The influence of gliomas and nonglial space-occupying lesions on blood-oxygen-level-dependent
contrast enhancement. AJNR Am J Neuroradiol 21(6):1055–1063
Shahar T, Rozovski U et al (2014) Preoperative imaging to predict
intraoperative changes in tumor-to-corticospinal tract distance: an
analysis of 45 cases using high-field intraoperative magnetic resonance imaging. Neurosurgery 75(1):23–30
Shinoura N, Yamada R et al (2005) Preoperative fMRI, tractography
and continuous task during awake surgery for maintenance of
motor function following surgical resection of metastatic tumor
spread to the primary motor area. Minim Invasive Neurosurg
Smucny J, Wylie KP, Tregellas JR (2014) Functional magnetic resonance imaging of intrinsic brain networks for translational drug discovery. Trends Pharmacol Sci. doi:10.1016/j.tips.2014.05.001
Stadlbauer A, Buchfelder M et al (2010) Fiber density mapping of gliomas: histopathologic evaluation of a diffusion-tensor imaging data
processing method. Radiology 257(3):846–853. doi:10.1148/
radiol.10100343, Epub 2010 Sep 30
Steger TR, Jackson EF (2004) Real-time motion detection of functional
MRI data. J Appl Clin Med Phys 5(2):64–70
Sternberg EJ, Lipton ML, Burns J (2014) Utility of diffusion tensor
imaging in evaluation of the peritumoral region in patients with primary and metastatic brain tumors. AJNR Am J Neuroradiol
35(3):439–444. doi:10.3174/ajnr.A3702, Epub 2013 Sep 19
Stippich C (2010) Presurgical functional magnetic resonance imaging.
Radiologe 50(2):110–122
Stippich C, Hofmann R et al (1999) Somatotopic mapping of the human
primary somatosensory cortex by fully automated tactile stimulation using functional magnetic resonance imaging. Neurosci Lett
277(1):25–28
Stippich C, Kapfer D et al (2000) Robust localization of the contralateral precentral gyrus in hemiparetic patients using the unimpaired
ipsilateral hand: a clinical functional magnetic resonance imaging
protocol. Neurosci Lett 285(2):155–159
Stippich C, Heiland S et al (2002a) Functional magnetic resonance
imaging: physiological background, technical aspects and prerequisites for clinical use. Röfo 174(1):43–49
Stippich C, Ochmann H, Sartor K (2002b) Somatotopic mapping of the
human primary sensorimotor cortex during motor imagery and
motor execution by functional magnetic resonance imaging.
Neurosci Lett 331(1):50–54
Stippich C, Kress B et al (2003a) Preoperative functional magnetic
resonance tomography (FMRI) in patients with rolandic brain
tumors: indication, investigation strategy, possibilities and limitations of clinical application. Röfo 175(8):1042–1050
Stippich C, Mohammed J et al (2003b) Robust localization and lateralization of human language function: an optimized clinical functional
magnetic resonance imaging protocol. Neurosci Lett 346(1–2):
Stippich C, Romanowski A et al (2004) Fully automated localization
of the human primary somatosensory cortex in one minute by
functional magnetic resonance imaging. Neurosci Lett 364(2):
Stippich C, Romanowski A et al (2005) Time-efficient localization of
the human secondary somatosensory cortex by functional magnetic
resonance imaging. Neurosci Lett 381(3):264–268
Stippich C, Rapps N et al (2007) Localizing and lateralizing language
in patients with brain tumors: feasibility of routine preoperative
functional MR imaging in 81 consecutive patients. Radiology
243(3):828–36.
Sunaert S, Yousry TA (2001) Clinical applications of functional magnetic
resonance imaging. Neuroimaging Clin N Am 11(2):221–236, viii
Svolos P, Tsolaki E et al (2013) Investigating brain tumor differentiation with diffusion and perfusion metrics at 3T MRI using pattern
recognition techniques. Magn Reson Imaging 31(9):1567–1577
Thulborn KR (1998) A BOLD move for fMRI. Nat Med 4(2):155–156
Thulborn KR (1999) Clinical rationale for very-high-field (3.0 Tesla)
functional magnetic resonance imaging. Top Magn Reson Imaging
Thulborn K (2006) Clinical functional magnetic resonance imaging. In:
Haacke EM (ed) Current protocols in magnetic resonance imaging.
Wiley, New York
Thulborn KR, Davis D et al (1996) Clinical fMRI: implementation and
experience. Neuroimage 4(3 Pt 3):S101–S107
Towle VL, Khorasani L et al (2003) Noninvasive identification of
human central sulcus: a comparison of gyral morphology, functional MRI, dipole localization, and direct cortical mapping.
Tozakidou M, Wenz H et al (2013) Primary motor cortex activation and
lateralization in patients with tumors of the central region.
Neuroimage Clin 2:221–228. doi:10.1016/j.nicl.2013.01.002, eCollection 2013
Tsougos I, Svolos P et al (2012) Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance
spectroscopy, diffusion and perfusion metrics at 3 T. Cancer
Imaging 12:423–436. doi:10.1102/1470-7330.2012.0038
Turner R, Le Bihan D et al (1991) Echo-planar time course MRI of cat
brain oxygenation changes. Magn Reson Med 22(1):159–166
Uematsu S, Lesser R et al (1992) Motor and sensory cortex in humans:
topography studied with chronic subdural stimulation. Neurosurgery
31(1):59–71; discussion 71–72
Ulmer JL, Hacein-Bey L et al (2004a) Lesion-induced pseudodominance at
functional magnetic resonance imaging: implications for preoperative
assessments. Neurosurgery 55(3):569–579; discussion 580–581
Ulmer JL, Salvan CV et al (2004b) The role of diffusion tensor imaging
in establishing the proximity of tumor borders to functional brain
systems: implications for preoperative risk assessments and postoperative outcomes. Technol Cancer Res Treat 3(6):567–576
Van Westen D, Skagerberg G et al (2005) Functional magnetic
resonance imaging at 3T as a clinical tool in patients with intracranial tumors. Acta Radiol 46(6):599–609
Wada J, Rasmussen T (1960) Intracarotid injection of sodium amytal
for the lateralization of cerebral speech dominance. Experimental
and clinical observations. J Neurosurg 17:266–282
Wehner T (2013) The role of functional imaging in the tumor patient.
Epilepsia 54(Suppl 9):44–49. doi:10.1111/epi.12443
Weiskopf N, Veit R et al (2003) Physiological self-regulation of regional
brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. Neuroimage
Wittek A, Kikinis R et al (2005) Brain shift computation using a fully
nonlinear biomechanical model. Med Image Comput Comput
Assist Interv 8(Pt 2):583–590
Woolsey CN, Erickson TC, Gilson WE (1979) Localization in somatic
sensory and motor areas of human cerebral cortex as determined by
direct recording of evoked potentials and electrical stimulation.
Yousry TA, Schmid UD et al (1997) Localization of the motor hand
area to a knob on the precentral gyrus. A new landmark. Brain
120(Pt 1):141–157
Zacharaki EI, Morita N et al (2012) Survival analysis of patients with
high-grade gliomas based on data mining of imaging variables.
AJNR Am J Neuroradiol 33(6):1065–1071. doi:10.3174/ajnr.
A2939, Epub 2012 Feb 9
Zambreanu L, Wise RG et al (2005) A role for the brainstem in central
sensitisation in humans. Evidence from functional magnetic resonance imaging. Pain 114(3):397–407
Revealing Brain Activity and White
Matter Structure Using Functional
and Diffusion-Weighted Magnetic
Resonance Imaging
Physical Principles of MRI.................................................
1.1		Spin Excitation and Signal Reception...................................
1.2		Image Reconstruction...........................................................
Physiological Principles of fMRI.......................................
2.1		Neurovascular Coupling........................................................
2.2		The BOLD Effect..................................................................
2.3		The BOLD Hemodynamic Response....................................
2.4		Limits of Spatial and Temporal Resolution..........................
FMRI Data Analysis...........................................................
3.1		Block- and Event-Related Designs.......................................
3.2		Basic Analysis Steps.............................................................
3.3		Statistical Analysis of Functional Data.................................
3.4		 Integration of Anatomical and Functional Data....................
3.5		Group Analysis of Functional Data Sets...............................
3.6		 Selected Advanced Data Analysis Methods.........................
Functional Connectivity and Resting-State Networks.....
4.1		Functional and Effective Connectivity..................................
4.2		Resting-State Networks........................................................
Diffusion-Weighted MRI and Tractography....................
5.1		Diffusion Tensor Imaging.....................................................
5.2		Validation and Improvements...............................................
5.3		Applications..........................................................................
References.....................................................................................
R. Goebel
Department of Cognitive Neuroscience, Maastricht University,
Oxfordlaan 55, 6229 EV Maastricht, The Netherlands
e-mail: r.goebel@maastrichtuniversity.nl
Magnetic resonance imaging (MRI) is based on the
magnetic excitation of body tissue and the reception of
returned electromagnetic signals from the body. Excitation
induces phase-locked precession of protons with a
frequency proportional to the strength of the surrounding
magnetic field as described by the Larmor equation. This
fact can be exploited for spatial encoding by applying
magnetic field gradients along spatial dimensions on top
of the strong static magnetic field of the scanner. The
obtained frequency-encoded information for each slice is
accumulated in two-dimensional k space. The k space data
can be transformed into image space by Fourier analysis.
Functional MRI (fMRI) allows localizing brain function
since increased local neuronal activity leads to a surprisingly strong increase in local blood flow, which itself results
in measurable increases in local magnetic field homogeneity. Increased local blood flow delivers chemical energy
(glucose and oxygen) to the neurons. The temporary increase
and decrease of local blood flow, triggered by increased neuronal activity, is called the hemodynamic response starting
2–4 s after stimulus onset. Increased local blood flow results
in an oversupply of oxygenated hemoglobin in the vicinity
of increased neuronal activity. The oversupply flushes deoxygenated hemoglobin from the capillaries and the downstream venules. Deoxygenated hemoglobin is paramagnetic
reducing the homogeneity of the local magnetic field resulting in a weaker MRI signal than would be measurable without it. Oxygenated hemoglobin is diamagnetic and does not
strongly reduce field homogeneity. Since the increased local
blood flow replaces deoxygenated hemoglobin with oxygenated hemoglobin, local field homogeneity increases,
leading to a stronger MRI signal as compared to a nonactivated state. Measured functional brain images thus reflect
neuronal activity changes as blood oxygenation level-
dependent (BOLD) contrast.
Functional images are acquired using the fast echo-
planar imaging (EPI) pulse sequence allowing acquisition
of a 64 × 64 image matrix in less than 100 ms. To sample
signal changes over time, a set of slices typically covering
the whole brain is measured repeatedly. Activation of neurons results in a BOLD signal increase of only about 1–5 %
and lie buried within strong physical and physiological
noise fluctuations of similar size. Proper preprocessing
steps, including 3D motion correction and removal of
drifts, reduce the effect of artifacts increasing the signal-tonoise ratio (SNR). In order to reliably detect stimulusrelated effects, proper statistical data analysis is performed.
In order to estimate response profiles, condition-related
time course episodes may be averaged in various regions-ofinterest (ROIs). The core statistical tool in fMRI data analysis is the general linear model (GLM) that allows the
analysis of blocked and event-related experimental designs.
To run a GLM, a design matrix (model) has to be constructed containing reference functions (predictors, model
time courses) for all effects of interest (conditions) as well
as confounds. The GLM fits the created model to the data
independently for each voxel's data (time course) providing a set of beta values estimating the effects of each condition. These beta values are compared with each other using
contrasts resulting in a statistical value at each voxel. The
statistical values of all voxels form a three-dimensional statistical map. To protect against wrongly declaring voxels as
significant, statistical maps are thresholded properly by
taking into account the multiple comparison problem. This
problem is caused by the large number of independently
performed statistical tests (one for each voxel).
In recent years, parallel imaging techniques have been
developed, which allow acquiring MRI data simultaneously with two or more receiver coils. Parallel imaging
can be used to increase temporal or spatial resolution. It
also helps to reduce EPI imaging artifacts, such as geometrical distortions and signal dropouts in regions of different neighboring tissue types.
MRI has not only revolutionized functional brain
imaging targeting gray matter neuronal activity but also
enabled insights into the human white matter structure
using diffusion-weighted magnetic resonance imaging.
With proper measurement and modeling schemes including diffusion tensor imaging (DTI), major long-range
fiber tracts can be reconstructed using computational tractography providing important information to guide neurosurgical procedures potentially reducing the risk of
lesioning important fiber tracts.
Since its invention in the early 1990s, functional magnetic
resonance imaging (fMRI) has rapidly assumed a leading
role among the techniques used to localize brain activity. The
spatial and temporal resolution provided by state-of-the-art
MR technology and its non-invasive character, which allows
multiple studies of the same subject, are some of the main
advantages of fMRI over the other functional neuroimaging
techniques that are based on changes in blood flow and cortical metabolism (e.g., positron-emission tomography, PET).
FMRI is based on the discovery of Ogawa et al. (1990), that
magnetic resonance imaging (MRI, also called nuclear magnetic resonance imaging) can be used in a way that allows
obtaining signals depending on the level of blood oxygenation. The measured signal is therefore also called "BOLD"
signal (BOLD = blood oxygenation level-dependent). Since
locally increased neuronal activity leads to increased local
blood flow, which again changes local blood oxygenation,
fMRI allows indirect measurements of neuronal activity
changes. With appropriate data analysis and visualization
methods, these BOLD measurements allow drawing conclusions about the localization and dynamics of brain function.
This chapter describes the basic principles and methodology of functional and diffusion-weighted MRI. After a description of the physical principles of MRI at a conceptual level, the
physiology of the blood oxygenation level-dependent (BOLD)
contrast mechanism is described. The subsequent, major part
of the chapter provides an introduction to the current strategies
of statistical image analysis techniques with a focus on the
analysis of single-subject data because of its relevance for presurgical mapping of human brain function. This is followed by
a description of functional connectivity focusing on the analysis of resting state fMRI data. Finally, principles of diffusionweighted MRI measurements are described including diffusion
tensor imaging, which is the most common acquisition and
modeling approach in clinical MRI.
Physical Principles of MRI
Magnetic resonance imaging allows visualizing both anatomical and functional data of the human brain. This section
shortly describes the main concepts of the physical principles of MRI. More detailed descriptions of the physical basis
of MRI are available in several introductory texts, for example, Huettel et al. (2004), Bandettini et al. (2000), Brown and
Semelka (1999), NessAiver (1997), and Schild (1990).
A typical whole-body MR scanner has a hollow bore
(tube) about 1 m across. Inside of that bore a cylinder is
placed containing the primary magnet producing a very
strong static, homogeneous magnetic field (B0). Today, nearly
all scanners create the magnetic field with superconducting
electromagnets whose wires are cooled by cryogens (e.g.,
liquid helium). Most standard clinical scanners used to image
the human brain possess a magnetic field strength of 1.5 T,
which is 30,000 times the strength of the Earth's magnetic
field (1 T = 10,000 G). In recent years, installation of tomographs with 3.0 T has become common in major hospitals
and research centers. In a few research labs, the human brain
is imaged at ultrahigh fields such as 7 and 9.4 T. At higher
field strengths it gets increasingly difficult to create a homogenous magnetic field, which is necessary for accurate spatial
Revealing Brain Activity and White Matter Structure Using Functional and Diffusion-Weighted Magnetic Resonance Imaging
decoding of the raw measurement data. Since homogenous
fields are easier to create for scanners with small bores, scanners with higher magnetic fields (10–20 T) are currently only
available for animal use. Besides the main magnet, additional
coils are located inside the cylinder including shimming
coils, gradient coils, and a radio frequency (RF) coil. The
shimming coils are used to shape the magnetic field increasing its homogeneity. The gradient coils are used to temporarily change the magnetic field linearly along any direction
which is essential for spatial localization (see below). The RF
coil is used to send radio frequency pulses into the subject.
In a typical brain scanning session, a subject or patient in
supine position is slowly moved into the scanner bore using a
maneuverable table. Scanning of anatomical and functional
images is managed from a terminal in a control room by specifying slice positions and by running appropriate MRI pulse
sequences. The control room usually has a window behind the
computer terminal, which allows looking into the scanner
room. Before the subject is moved into the scanner, the head
is placed in a small replaceable coil, called the head coil. This
coil surrounds the head and is used to send radio frequency
pulses into the subject as well as to receive electromagnetic
echoes. When receive-only head coils are used, the radio frequency pulses are provided by the RF coil in the cylinder of
the scanner. The head coil is an example of a volume coil,
which is designed such that the sensitive volume (e.g., brain)
experiences a fairly uniform RF field. Surface coils are
receive-only RF coils that are placed directly upon the surface
of the anatomy to be imaged. They provide very high signalto-noise in their immediate vicinity, but recorded images suffer from extreme nonuniformity because the obtained signal
intensity drops rapidly with distance and approaches zero
about one coil diameter away from the coil. Phased array coils
are an attempt to combine the positive properties of volume
and surface coils by combining images from two or more surface coils to produce a single image (see Sect. 1.2.6).
The physical principles of MRI are the same for anatomical
and functional imaging. What makes functional imaging special
is described in Sect. 2. The operation of MRI can be described
in two major themes. The first theme refers to the excitation and
recording of electromagnetic signals reflecting the properties of
the measured object. The second theme refers to the construction of two- and three-dimensional images reflecting how the
measured object properties vary across space.
Spin Excitation and Signal Reception
Magnetic resonance imaging is based on the magnetic excitation of body tissue and the recording of returned electromagnetic signals from the body. All nuclei with an odd number of
protons are magnetically excitable. The atom of choice for
MRI is 1H, the most common isotope of hydrogen having a
nucleus with only one proton. Hydrogen protons are ideally
suited for MRI because they are abundant in human tissue and
possess particularly favorable magnetic properties. Water is
the largest source of protons in the body followed by fat.
Protons have magnetic properties because they possess a spin:
they rotate like a spin top around their own axes inducing a
small directed magnetic field. In a normal environment, the
magnetic fields of the spins in the human body are oriented
randomly and, thus, cancel each other out. If, however, the
body of a subject is placed in the strong static magnetic field
of a MRI tomography (called B0), the spins orient themselves
in line with that field, either parallel or antiparallel (Fig. 1).
Since a slightly larger proportion of spins aligns parallel to the
Precession
Fig. 1 Spinning protons are little magnets because of the spin property.
(a) Without an external magnetic field, the directions of the spins are
randomly distributed. (b) When placed within a large magnetic field,
the spins align either with the field (parallel) or against the field
(antiparallel). A slight excess of spins aligns with the external magnetic
field resulting in a net magnetic field parallel to the external magnetic
field. (c) A spin is actually not aligning its axis of rotation with the
external magnetic field as shown in (a) and (b) but rotates around the
direction of the field. This motion is called precession
Y'
(RF pulse)
X'
Rotating frame
Laboratory Frame
Fig. 2 Spins in the lower energy state can be excited by an
electromagnetic pulse at the resonance frequency ω0 forcing the spins
absorbing the transmitted energy to precess in phase. (a) As an effect of
excitation, the net magnetic field M0 (blue vector) smoothly tips down
toward the x-y plane. The longitudinal component Mz (green vector)
decreases over time while the transverse component Mxy (red vector)
increases. This view assumes that the observer is moving with the
precessing protons (rotating frame of reference). (b) Viewed from outside (laboratory frame of reference), the net magnetization vector
rotates with angular velocity ω0 given by the Larmor equation. The
rotating magnetic field in the x-y plane emits radiofrequency waves,
which can be measured by a receiver coil
scanner magnetic field, the body gets magnetized. The excess
number of spins aligned with the external magnetic field is
proportional to the strength of the external magnetic field and
is in the order of 1015 spins at 1.5 in a 2 × 2 × 2 mm volume of
water. The total magnetic field of the excess spins is called
M0. Just as a spinning top wobbles about its axis, the spinning
protons wobble, or precess, about the axis of the external B0
field (Fig. 1c). The precession frequency of the protons
depends on the strength of the surrounding magnetic field.
More precisely, the precession frequency ω is directly proportional to the strength of the external magnetic field and is
defined by the Larmor equation:
toward the x-y plane is a function of the strength and duration
of the RF pulse. If α = 90°, the magnetization vector is completely moved into the x-y plane with an equal amount of
spins aligned parallel and antiparallel (Fig. 2b). Since the
protons precess in phase, that is, they point in the same direction within the x-y plane, the magnetic fields of the spins add
up to form a net magnetic field MXY in the x-y plane. This
transversal component of the rotating electromagnetic field
can be measured (received) in the receiver coil (antenna)
because it induces a detectable current flow.
The established inphase precession is, however, not stable
after the RF transmitter is turned off. Because of interactions
between the magnetic fields of the protons, the transverse
magnetization decays within a few tenth of milliseconds.
These spin-spin interactions lead to slightly different local
magnetic field strengths and, thus, to slightly different precession frequencies leading to phase shifts between the precessing spins (dephasing). The dephasing process is also
called transversal relaxation. It progresses initially rapidly
but slows down over time following an exponential function
with time constant T2 with values in the range of 30–150 ms.
Due to magnetic field inhomogeneities in the static magnetic
field and in physiological tissue, the spins get out of phase
actually faster than T2, and therefore the measured raw signal
in the receiver coil, the free induction decay (FID), decays
with a shorter time constant T2* (Fig. 3):
w0 = g B 0
The symbol ω0 is known as the precessional, Larmor, or resonance frequency. The symbol γ refers to the gyromagnetic
ratio, which is a constant unique to every atom. For hydrogen protons, γ = 42.56 MHz per Tesla. At the magnetic field
strength of a 3 T scanner, the precession frequency of hydrogen protons is thus 128 MHz.
If an applied electromagnetic pulse has the same frequency as the proton's precession frequency, then the protons get "excited" by absorbing the transmitted energy. This
important principle is called resonance and gives the method
"magnetic resonance imaging" its name. Since the precession frequency is in the range of radio frequency waves, the
applied electromagnetic pulse is also called a radio frequency
(RF) pulse. As an effect of excitation, spins flip from the
parallel (lower-energy) state to the antiparallel (higher-
energy) state. The RF pulse furthermore lets the excited protons precess in phase. As a result, the magnetization vector
M0 moves down toward the x-y plane (Fig. 2). The x-y plane
is perpendicular to the static magnetic field and is also
referred to as the transverse plane. The angle, α, of rotation
M XY = M 0 e
−t / T *
The fact that local field inhomogeneities lead to different
precession frequencies increasing the speed of dephasing is
an important observation for functional MRI because local
field inhomogeneities also depend on the local physiological
state, especially the state of local blood oxygenation, which
Fig. 3 The signal amplitude
(red curve) of the measured raw
MR signal, the free induction
decay (FID), decays exponentially with time constant T2*. The
raw signal itself is oscillating at
the resonance frequency (blue
curve). The signal is lost due to
dephasing as indicated by the
phase coherency plots (circles)
with three representative,
superimposed spins (see inset).
The amplitude of the signal at
any moment in time is determined by the sum of the spin

redpajama_set_name: RedPajamaCommonCrawl