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R E S E A R CH A R T I C L E
Tracer-specific reference tissues selection improves detection
of 18F-FDG, 18F-florbetapir, and 18F-flortaucipir PET SUVR
changes in Alzheimer's disease
Yanxiao Li1,2 | Yee Ling Ng1 | Manish D. Paranjpe3 | Qi Ge1 | Fengyun Gu1,4 |
Panlong Li5 | Shaozhen Yan6 | Jie Lu6 | Xiuying Wang2 | Yun Zhou1 |
for the Alzheimer's Disease Neuroimaging Initiative
1Central Research Institute, United Imaging
Healthcare Group Co., Ltd, Shanghai, China
2School of Computer Science, The University
of Sydney, Sydney, New South Wales,
3Harvard-MIT Health Sciences and
Technology Program, Harvard Medical School,
4Department of Statistics, University College
Cork, Cork, Ireland
5School of Electrical and Information
Engineering, Zhengzhou University of Light
Industry, Zhengzhou, Henan, China
6Department of Radiology and Nuclear
Medicine, Xuanwu Hospital, Capital Medical
University, Beijing, China
Yun Zhou, United Imaging Healthcare Group
Co. Ltd, 2258 Chengbei Road, Jiading District,
Shanghai 201807, China.
Xiuying Wang, School of Computer Science,
The University of Sydney, City Road,
Camperdown/Darlington NSW 2006,
This study sought to identify a reference tissue-based quantification approach for
improving the statistical power in detecting changes in brain glucose metabolism,
amyloid, and tau deposition in Alzheimer's disease studies. A total of 794, 906, and
903 scans were included for 18F-FDG, 18F-florbetapir, and 18F-flortaucipir, respec-
tively. Positron emission tomography (PET) and T1-weighted images of participants
were collected from the Alzheimer's disease Neuroimaging Initiative database,
followed by partial volume correction. The standardized uptake value ratios (SUVRs)
calculated from the cerebellum gray matter, centrum semiovale, and pons were eval-
uated at both region of interest (ROI) and voxelwise levels. The statistical power of
reference tissues in detecting longitudinal SUVR changes was assessed via paired
t-test. In cross-sectional analysis, the impact of reference tissue-based SUVR differ-
ences between cognitively normal and cognitively impaired groups was evaluated by
effect sizes Cohen's d and two sample t-test adjusted by age, sex, and education
levels. The average ROI t values of pons were 86.62 and 38.40% higher than that of
centrum semiovale and cerebellum gray matter in detecting glucose metabolism
decreases, while the centrum semiovale reference tissue-based SUVR provided
higher t values for the detection of amyloid and tau deposition increases. The three
reference tissues generated comparable d images for 18F-FDG, 18F-florbetapir, and
18F-flortaucipir and comparable t maps for 18F-florbetapir and 18F-flortaucipir, but
pons-based t map showed superior performance in 18F-FDG. In conclusion, the
tracer-specific reference tissue improved the detection of 18F-FDG, 18F-florbetapir,
and 18F-flortaucipir PET SUVR changes, which helps the early diagnosis, monitoring
of disease progression, and therapeutic response in Alzheimer's disease.
Abbreviations: ACR, annual change rate; AD, Alzheimer's disease; ADNI, Alzheimer's Disease Neuroimaging Initiative; ATN, amyloid, tau, and neurodegeneration; Aβ, amyloid-β; CDR, clinical
dementia rating; CI, cognitively impaired; CN, cognitively normal; GM, gray matter; MCI, mild cognitively impaired; MMSE, Mini-Mental Status Examination; MNI, Montreal Neurologic Institute;
PVC, partial volume correction; ROI, region of interest; SUVR, standardized uptake value ratio.
Received: 15 September 2021 Revised: 17 December 2021 Accepted: 30 December 2021
DOI: 10.1002/hbm.25774
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any
medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
© 2022 United Imaging Healthcare. Human Brain Mapping published by Wiley Periodicals LLC.
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K E YWORD S
18F-FDG, 18F-florbetapir, 18F-flortaucipir, Alzheimer's disease, reference tissue
1 | INTRODUCTION
Alzheimer's disease (AD) is a progressive neurodegenerative disease
associated with memory deficits and cognitive impairments, brain
deposition of amyloid-β (Aβ) peptide plaques, neurofibrillary tangles
composed of hyperphosphorylated tau (ptau) protein, and glucose
hypometabolism (DeTure & Dickson, 2019; Serrano-Pozo, Frosch,
Masliah, & Hyman, 2011; Uddin et al., 2018). The standardized assess-
ment of pathological processes underlying AD can be accomplished
by biomarker-evidenced amyloid, tau, and neurodegeneration (ATN)
framework (Jack Jr et al., 2018). Positron emission tomography (PET)
using radiolabeled ligands including 18F-FDG, 18F-florbetapir, and
18F-flortaucipir has been widely used to assess neurodegeneration,
deposition of Aβ fibrils, and tau for diagnosis and monitoring progres-
sion of AD. Standardized uptake value ratio (SUVR) relative to a refer-
ence tissue is commonly used for ATN PET quantification.
Specifically, 18F-FDG SUVR can be used to estimate the metabolic
glucose uptake rate ratio (Y. Wu et al., 2012; Y. G. Wu, 2008), while
the 18F-florbetapir and 18F-flortaucipir SUVRs can be used to approxi-
mate the tracer distribution volume ratio (DVR) of binding to Aβ and
tau, respectively (Wong et al., 2010; Zhou et al., 2021; Zhou, Endres,
Braši�c, Huang, & Wong, 2003; Zhou, Sojkova, Resnick, &
Wong, 2012).
Various reference tissues-based SUVRs have been used in previ-
ous AD studies, leading to different statistical power in PET assess-
ments (Chen et al., 2015; Zhou et al., 2021). The pons reference
region previously demonstrated the best preservation of glucose
metabolism in AD and therefore was deemed as a reliable reference
tissue for brain 18F-FDG PET normalization (Minoshima, Frey, Fos-
ter, & Kuhl, 1995). Reference tissues including whole brain (Nugent
et al., 2020), cerebellum gray matter (GM; Förster et al., 2012;
Ossenkoppele et al., 2012), and pons (Alexander, Chen, Pietrini,
Rapoport, & Reiman, 2002; Ortner et al., 2019; Schmidt et al., 2008)
have been used to calculate 18F-FDG PET SUVR in longitudinal AD
studies. The effect of reference tissues including cerebellum GM,
pons, and whole brain on 18F-FDG PET SUVR have been also evalu-
ated in cross-sectional (Minoshima et al., 1995; Yakushev et al., 2008)
and longitudinal AD studies (Nugent et al., 2020; Verger, Doyen, Cam-
pion, & Guedj, 2021). Similarly, different reference tissues including
cerebellar GM, centrum semiovale, pons, and corpus callosum have
been used to quantify 18F-florbetapir and 11C-PIB amyloid PET
(Blautzik et al., 2017; Chen et al., 2015; Chiao et al., 2019; Heeman
et al., 2020; Shokouhi et al., 2016; Su et al., 2015; Wang et al., 2021;
Xie et al., 2020) and 18F-flortaucipir tau PET (Baker et al., 2017; Cho
et al., 2020; Devous Sr. et al., 2018; Southekal et al., 2018; Zhao, Liu,
Ha, Zhou, & Alzheimer's Disease Neuroimaging Initiative, 2019). The
amyloid PET SUVRs calculated from different reference tissues were
compared and evaluated by correlation analysis of SUVR versus cog-
nitive assessment (Chen et al., 2015), test–retest analysis (Blautzik
et al., 2017), and effect size for evaluation of the treatment response
(Chiao et al., 2019). Our previous research has demonstrated that spa-
tially constrained kinetic model with dual reference tissues comprising
of cerebellum GM and centrum semiovale significantly improves
quantification of relative perfusion and tau binding (Zhou et al., 2021).
In previous longitudinal 18F-FDG and 18F-florbetapir PET studies, dif-
ferent reference tissues based SUVRs were compared, but the com-
parisons were limited to the region of interest (ROI) levels. Also, these
previous studies focused 18F-FDG PET in normal aging (Nugent
et al., 2020; Verger et al., 2021) or amyloid treatment effects in mild
cognitive impairment (MCI) and AD participants (Chen et al., 2015;
Chiao et al., 2019). Moreover, for tau PET studies, to the best of our
knowledge, there has been no evaluation for multiple reference tis-
sues in longitudinal studies.
The selection of an appropriate reference tissue is reliant on mul-
tivariable factors and imperative aspects such as the studied popula-
tion, study sample size, PET acquisition protocol, and the type of
radiopharmaceutical used. The objective of this study is to improve
statistical power for detecting 18F-FDG, 18F-florbetapir, and
18F-flortaucipir PET SUVR changes in AD by selecting appropriate
reference tissues. Using the AD Neuroimaging Initiative (ADNI), we
performed longitudinal analysis on individuals with disease progres-
sion regardless of their disease stage, whether from cognitively nor-
mal (CN) to AD, MCI to AD, or CN to MCI. The impact of the
reference tissue selection on discriminating between CN and cogni-
tively impaired (CI) were also evaluated. This study is the most com-
prehensive comparative analysis of different reference tissues
measured with multiple radiotracers to monitor the progression of
AD. Our study may improve clinical staging diagnosis through quanti-
tative PET which has important implications for biomarker-guided
precision medicine.
2 | MATERIALS AND METHODS
2.1 | Participants
All 18F-FDG, 18F-florbetapir, and 18F-flortaucipir PET and structural
MRI data in this study were obtained from the AD Neuroimaging Ini-
tiative (ADNI) dataset (https://adni.loni.usc.edu). Informed written
consent was obtained from all participants at each site. In total, we
downloaded 794 18F-FDG-PET scans, 906 18F-florbetapir-PET scans,
and 903 18F-flortaucipir-PET scans, which encompass 420, 434, and
2122 LI ET AL.
https://adni.loni.usc.edu
666 participants, respectively. Demographics and clinical assessments
including the Mini-Mental Status Examination (MMSE), Clinical
Dementia Rating (CDR), and clinical diagnostic status of CN, MCI, and
AD participants were also obtained.
2.2 | PET data acquisition and image preprocessing
Raw T1-weighted structural MRI and preprocessed 18F-FDG, 18F-
florbetapir, and 18F-flortaucipir PET images of each subject were
downloaded from the ADNI database. The downloaded PET images
were aligned, averaged, reoriented, and interpolated into a standard
160 � 160 � 96 voxel image grid and smoothed with an 8 mm in full
width at half maximum (FWHM) 3D Gaussian filter by the ADNI con-
sortium with 1.5 mm cubic voxels. Further details of PET and
T1-weighted MR acquisition protocols can be found at http://adni.
loni.usc.edu/methods/pet-analysis-method/pet-analysis/ and http://
adni.loni.usc.edu/methods/documents/mri-protocols/, respectively.
The PET and MRI data were further processed by partial volume
correction (PVC) and spatial normalization, both using Statistical Para-
metric Mapping (SPM12, Wellcome Department of Imaging Neurosci-
ence, Institute of Neurology, London, UK) in the MATLAB R2020b (The
MathWorks Inc., Natick, MA) environment, as reported in our earlier
studies (Paranjpe et al., 2019; Yan et al., 2020, 2021). PVC was per-
formed to minimize the possibility of underestimation in PET images,
especially for small brain regions such as amygdala and striatum. The
reblurred Van Cittert iteration method was applied for PVC in individual
PET images, where a 3D Gaussian Kernel of 8 mm FWHM was used as
the spatial smoothing function with step length α of 1.5 (Tohka &
Reilhac, 2008). All PET images were then coregistered to the individ-
ual's own structural MRI images, which were normalized to the stan-
dard Montreal Neurologic Institute (MNI) space using an MRI template
(image volume: 121 � 145 � 121, voxel size: 1.5 � 1.5 � 1.5 mm in x,
y, z). The median (interquartile range) of time intervals between PET
and MRI are 28(49) days, 30(48) days, and 51(129.5) days for 18F-FDG,
18F-florbetapir, and 18F-flortaucipir, respectively. The transformation
parameters determined by MRI spatial normalization were then applied
to the coregistered PET images for PET spatial normalization. SUVR
images were calculated relative to the cerebellum GM (SUVRCereb_GM),
centrum semiovale (SUVRCS), and pons (SUVRPons) reference tissues.
The ROI SUVR values were calculated by applying ROIs on the SUVR
images in the standard MNI space for minimizing variance related to
the variability of ROI volume and shape in native space (Gottesman
et al., 2017; Liu et al., 2019; Paranjpe et al., 2019; Tudorascu
et al., 2018; Yan et al., 2021). A total of 18 ROIs including three refer-
ence tissues (cerebellum GM, centrum semiovale, and pons) and an
additional 15 ROIs including the orbital frontal, prefrontal, superior
frontal, medial temporal, inferior temporal, lateral temporal, parietal,
posterior precuneus, anterior cingulate, posterior cingulate, occipital,
entorhinal cortex, amygdala, hippocampus, and parahippocampal gyrus
regions were manually delineated on the MRI template using the
PMOD software program (PMOD 4.002, PMOD Technologies Ltd.,
Zürich, Switzerland) in standard MNI space. These ROI templates were
previously developed in the Johns Hopkins Department of Radiology
and have been validated in our former studies (Liu et al., 2019; Paranjpe
et al., 2019; Yan et al., 2020, 2021; Zhou et al., 2021).
2.3 | Longitudinal SUVR PET analysis for
cognitively declined participants
The effects of different reference tissues were evaluated on the sensi-
tivity of SUVR measurements for the detection of cognitively declined
populations. The baseline and last scans were defined as the subject's
first and last scan in the downloaded data. Participants at the last scan
who had an increased CDR score (Morris, 1993) or evidence of clinical
disease progression (CN to MCI, MCI to AD, or CN to AD) were
included in the longitudinal studies. This population inclusion criterion
was consistent across 18F-FDG, 18F-florbetapir, and 18F-flortaucipir
studies. Based on the baseline and last scan SUVR values of each sub-
ject, paired statistical t values were calculated at both ROI- and voxel-
levels for each reference tissue. The annual change rates for 18F-FDG,
18F-florbetapir, and 18F-flortaucipir uptake were further calculated as
Annual Change Rate ACRxð Þ
¼ SUVRlast scan�SUVRbaselineð Þ= SUVRbaseline �Tð Þ, ð1Þ
where x represents the reference tissue (cerebellum GM, centrum
semiovale, or pons), SUVRlast scan and SUVRbaseline are the SUVR values
of the ROI at the last scan and baseline, T is the time interval from
baseline to the last scan in years.
2.4 | Cross-sectional SUVR PET analysis for CN
and CI participants
To comprehensively assess the performance of the cerebellum GM,
centrum semiovale, and pons reference tissues in discriminating
between CN or CI individuals, ROI- and voxelwise-based cross-
sectional statistical analyses were performed. All baseline scans
were included for cross-sectional analysis and participants were
classified as either CN (CDR = 0) or CI (CDR ≥ 0.5; Zhou
et al., 2021). To investigate the sensitivity of the PET SUVR mea-
surement in discriminating CN from CI, effects sizes were approxi-
mated using Cohen's d (Chand et al., 2020; Cohen, 1988; Lopresti
et al., 2005; Sullivan & Feinn, 2012; Zhou et al., 2021) of CN and CI
groups as follows:
d¼ mean SUVRx at group1ð Þ�mean SUVRx at group2ð Þð Þ�SDpooled,
where SDpooled represents the standard deviation of SUVR in pooled
population, x represents either cerebellum GM, centrum semiovale, or
pons reference tissues. Since the 18F-FDG SUVR decreased while the
18F-florbetapir and 18F-flortaucipir SUVR increased with disease pro-
gression, we set group 1 to be CN and group 2 to be CI for 18F-FDG,
LI ET AL. 2123
http://adni.loni.usc.edu/methods/pet-analysis-method/pet-analysis/
http://adni.loni.usc.edu/methods/documents/mri-protocols/
and group1 to be CI and group2 to be CN for 18F-florbetapir and
18F-flortaucipir.
For correcting the influence of covariates, the two-sample inde-
pendent t test adjusted by age, sex, and education levels were per-
formed at voxelwise level using SPM12. For ROI-based analysis, the
generalized linear model was used to assess the group difference in
SUVR for each ROI by adjusting for covariates, the Bonferroni-
corrected p-value < .05 was defined as significant.
3 | RESULTS
3.1 | Study cohort characteristics
Study cohort characteristics for participants in the longitudinal ana-
lyses are summarized in Table 1. A total of 53, 55, and 20 participants
were included with a mean time interval between the baseline and last
scan of 63.42 ± 27.15 months, 57.05 ± 18.75 months, and 19.88
± 8.03 months for 18F-FDG, 18F-florbetapir, and 18F-flortaucipir,
respectively. For each tracer, there were substantial differences
between the baseline and last scan in age, education level, and CDR.
There was no significant difference in the baseline and last scan for
the MMSE of the participants in 18F-flortaucipir. Comparison across
tracers demonstrated that MMSE values at the baseline showed dif-
ferences between 18F-FDG and 18F-flortaucipir groups and between
18F-florbetapir and 18F-flortaucipir groups. Other groups showed no
significant difference in age and CDR in all three tracers.
Study cohort characteristics for participants in the cross-sectional
study are listed in Table 2. There were no significant differences
between CN and CI groups in terms of their age and education level,
but considerable differences were observed for the MMSE and CDR
scores for 18F-FDG and 18F-florbetapir PET studies. Significant differ-
ences were detected in age, education level, MMSE, and CDR scores
in 18F-flortaucipir PET study.
3.2 | Effect of reference tissue selection on
sensitivity to detect longitudinal PET SUVR changes
in AD
3.2.1 | 18F-FDG PET
The statistic t maps based on the 18F-FDG SUVR images for three ref-
erence tissues are illustrated in Figure 1. It was evident that the t-
values calculated from SUVR images were in the order of t(SUVRPons)
> t(SUVRCereb_GM) > t(SUVRCS) in the frontal, temporal and parietal
regions. ROI-based analysis showed consistent results as demon-
strated in Figure 2. The t(SUVRPons) showed the greatest sensitivity in
the orbital frontal, prefrontal, superior frontal, lateral temporal,
inferior temporal, posterior precuneus, anterior cingulate, posterior
cingulate, caudate, entorhinal cortex, amygdala, hippocampus, and
parahippocampal gyrus, 86.62 ± 47.63% higher than the t(SUVRCS)
and 38.40 ± 29.13% higher than the t(SUVRCereb_GM). In contrast, T
(C
I/
(M
(y
†.
,r
SUVRCS had the lowest sensitivity and failed to detect SUVR
decrease in the orbital frontal, prefrontal, and amygdala (t < 1.67).
Compared with the SUVRCS, the SUVRCereb_GM detected changes in
the orbital frontal and prefrontal. The ACRs of ROIs for each refer-
ence tissue are listed in Table 3. The pons demonstrated the largest
ACR across all listed brain regions, with an average of 73.8 ± 42.4%
and 92.2 ± 61.7% higher than the ACRCereb_GM and ACRCS, respec-
tively. Regardless of which reference tissue was used, the caudate,
anterior cingulate, lateral temporal, parahippocampal gyrus, poste-
rior cingulate, parietal, and entorhinal cortex showed the greatest
longitudinal annual change rates of 18F-FDG uptake with each hav-
ing at least a 1% reduction (Table 3).
3.2.2 | 18F-florbetapir PET
In contrast to the 18F-FDG PET analysis where the SUVRPons demon-
strated the greatest sensitivity, the SUVRCS in 18F-florbetapir was
superior in detecting longitudinal amyloid depositions (Figure 3). As
demonstrated in Figure 4, significant longitudinal differences in the
orbital frontal, prefrontal, superior frontal, lateral temporal, inferior
temporal, parietal, posterior precuneus, occipital, anterior cingulate,
and posterior cingulate were detected using the centrum semiovale
reference tissue. The t(SUVRCS) was 27.12 ± 12.31% and 52.12
± 23.78% higher than the t(SUVRCereb_GM) and t(SUVRPons), respec-
tively, which was consistent with the t map at the voxel-level. The
cerebellum GM and pons demonstrated similar sensitivities in moni-
toring all regions, however, the use of these reference tissues was
unable to detect changes in the anterior cingulate. The greatest amy-
loid ACR for disease-progressed participants was observed in the pos-
terior cingulate (2.2%) when centrum semiovale was used as
reference tissue (Table 3). The average of ACRs in all the studied brain
regions was 1.2% using a cerebellum GM reference tissue
(ACRCereb_GM), 1.7% using a centrum semiovale reference tissue
(ACRCS), and 1.6% using the pons reference (ACRPons) tissue (Table 3).
ACRCS was 10.2 ± 1.8% and 44.3 ± 10.1% greater than the
ACRCereb_GM and ACRPons, respectively, highlighting the superiority of
the centrum semiovale in detecting longitudinal amyloid changes.
3.2.3 | 18F-flortaucipir PET
The ROI and voxelwise results for 18F-flortaucipir are displayed in Fig-
ures 5 and 6, respectively. Centrum semiovale reference tissue could
only identify longitudinal changes in known AD-sensitive regions includ-
ing the superior frontal, lateral temporal, and inferior temporal. The t
(SUVRCS) ranged from 2.02 to 2.34, which was 8.46 and 15.42 times
higher than the t(SUVRCereb_GM) and t(SUVRPons), respectively (Figure 6).
The ACRs of these significant brain regions using three reference tissues
are also listed in Table 3. The ACRs of the superior frontal, lateral tempo-
ral, and inferior temporal demonstrated an average of 3.2% when using
the centrum semiovale as the reference tissue, exceeding ACRCereb_GM
(0.5%) and ACRPons (0.8%) by 5.5 and 3.2 times, respectively.T
(n
sensitivity to detect PET SUVR differences between
CN and CI groups in cross-sectional study cohort
The Cohen's d maps (Figure 7) generated from the cerebellum GM,
centrum semiovale, and pons reference tissue-based SUVR images
were visually comparable. The average d-values over 15 ROIs for the
cerebellum GM, centrum semiovale and pons in 18F-FDG were d
(SUVRCereb_GM) = 0.33 ± 0.89, d(SUVRCS) = 0.30 ± 0.15 and d
(SUVRPons) = 0.38 ± 0.35; in 18F-florbetapir were d
(SUVRCereb_GM) = 0.44 ± 0.16, d(SUVRCS) = 0.46 ± 0.14, and d
(SUVRPons) = 0.49 ± 0.13; in 18F-flortaucipir were d
(SUVRPons) = 0.59 ± 0.21. The covariates adjusted t maps (Figure 8)
generated from reference tissue-based SUVR images were compara-
ble in 18F-florbetapir and 18F-flortaucipir, but pons had increased per-
formance in 18F-FDG. The average t values from ROIs for the
cerebellum GM, centrum semiovale, and pons in 18F-FDG were t
(SUVRCereb_GM) = 3.52 ± 1.09, t(SUVRCS) = 3.37 ± 0.96, and t
(SUVRPons) = 4.76 ± 0.91; in 18F-florbetapir were t
(SUVRPons) = 5.51 ± 1.20; in 18F-flortaucipir were t
(SUVRPons) = 7.96 ± 2.67.
4 | DISCUSSION
In this study, we evaluated the effect of reference tissue selection on
the statistical power to detect longitudinal and cross-sectional SUVR
changes in 18F-FDG, 18F-florbetapir, and 18F-flortaucipir PET studies
of AD. Specifically, the results from 18F-FDG were consistent with
previous reference tissue selection studies in which the pons showed
superiority in both longitudinal and cross-sectional analyses, especially
in elucidating longitudinal SUVR changes (Minoshima et al., 1995;
Nugent et al., 2020; Verger et al., 2021). After the correction of
covariates (age, sex, and education level) effects in cross-sectional
analysis, the pons demonstrated better performance in distinguishing
F IGURE 2 Statistical t values of ROI-based longitudinal 18F-FDG SUVR changes in subjects with cognitive decline. Statistical p values
indicate *p < .05, **p < .001, ***p < .0001. ACC, anterior cingulate; Amy, amygdala; Caud, Caudate; EC, entorhinal cortex; Hip, hippocampus; InfT,
inferior temporal; LatT, lateral temporal; MT, medial temporal; OrbF, orbital frontal; Par, parietal; PCC, posterior cingulate; PHip, parahippocampal
gyrus; PPrC, posterior precuneus; PreF, prefrontal; SupF, superior frontal
F IGURE 1 Paired statistical t map of longitudinal (mean follow-up
period: 63.42 ± 27.15 months, n = 53) 18F-FDG SUVR changes in
participants with cognitive decline. The SUVR was calculated for
reference tissue cerebellum GM, centrum semiovale, and pons,
respectively
CN and CI groups, particularly in the orbital frontal, prefrontal, and
inferior temporal (Table S1). Minoshima et al. (1995) evaluated pons
and other reference tissues in AD by observing the preservation of
glucose metabolism. They concluded that pons was a reliable and
appropriate reference tissue for data normalization to distinguish
between CN and CI groups. In the investigation of the metabolic
changes of normal aging, pons was also identified as the most appro-
priate area for brain intensity normalization due to its minimal corre-
lation with age and greater significant longitudinal cluster volumes
compared to other normalizations (Verger et al., 2021). Similarly, in
the context of healthy aging, pons was verified as the optimal refer-
ence tissue by examining changes in brain glucose uptake when com-
paring with the whole brain based on the posterior cingulate and the
precuneus regions (Nugent et al., 2020). Although these previous
studies have identified pons as the most appropriate reference tis-
sue, these studies did not conduct voxelwise analysis and consid-
ered only a limited number of ROIs. More importantly, the
longitudinal population these studies included were either normal
aging or patients with only follow-up scans, regardless of the sub-
jects' disease progression and clinical severity. In our study, we
confirmed the use of pons in 18F-FDG for the population with dis-
ease progression according to their clinical diagnosis. The annual
reduction rates in 18F-FDG uptake under normal aging in the ante-
rior cingulate cortex and posterior cingulate cortex/precuneus
were previously reported as 0.6 and 0.6% (Ishibashi et al., 2018).
By using pons, our result illustrated that the ACRs of the subjects
with clinical declines in the anterior cingulate and posterior cingu-
late were 1.7 and 1.6%, as more than twice as that of the normal
participants reported (Ishibashi et al., 2018).
For 18F-florbetapir amyloid PET, our results suggest that the cen-
trum semiovale is the ideal reference tissue to detect 18F-florbetapir
longitudinal changes in AD for monitoring brain amyloid accumulation.
The centrum semiovale showed the greatest statistical power to
detect brain regions with highly significant t-values, as well as the
highest ACR (ACRCS = 1.7%) compared to the cerebellum GM and
pons. The cerebral white matter has been previously validated as the
reference tissue with less variability and great statistical power to
detect longitudinal increases in Aβ depositions (Chen et al., 2015).
Interestingly, the application of subcortical white matter and cerebellar
white matter alone or in combination produced an enhanced result
when assessed by effect size (Cohen's d; Chiao et al., 2019). More-
over, in a test–retest 18F-florbetapir longitudinal SUVR study, the
brainstem had the highest stability and correlation between PET and
concurrent cerebrospinal fluid Aβ1–42 levels (Shokouhi et al., 2016). It
is well-recognized that partial volume effects exist in brainstem- or
pons-based SUVR measurements (Chen et al., 2015; Su et al., 2019).
In our cross-sectional analysis including effect size estimates and two-
independent sample t-test, cerebellum GM, centrum semiovale, and
pons all demonstrated comparable statistical power in distinguishing
SUVR differences between CN and CI groups. Cerebellum GM was
ultimately recommended as the ideal reference tissue in 18F-
florbetapir PET studies especially in studies involving relative cerebel-
lar perfusion measurement (Bilgel et al., 2020; Hsiao et al., 2013).T
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Our study also revealed the centrum semiovale as the optimal ref-
erence tissue for 18F-flortaucipir tau PET studies. Superior frontal, lat-
eral temporal, and inferior temporal were the only brain regions that
were detected as significant using the centrum semiovale reference in
tau PET. Considering the shorter time intervals between tau scans, all
three reference tissues were indicated as the sensitive regions in tau
PET imaging which strongly correlated with neurodegeneration (Zhou
et al., 2021). To the best of our knowledge, this is the first study that
evaluated reference tissue effects longitudinally for tau PET. For
cross-sectional analysis, the presented d maps and covariates adjusted
t maps showed that the cerebellum GM, centrum semiovale, and pons
revealed similar performance in 18F-flortaucipir, but the cerebellum
GM was still the recommended reference tissue due to previous cere-
bral blood flow studies (Rubinski et al., 2021; Zhou et al., 2021). Our
previous research has demonstrated that the centrum semiovale ref-
erence tissue-based DVR and SUVR at the late phase, as well as the
cerebellum GM reference tissue-based R1 and SUVR at the early
phase, demonstrated higher Cohen's d effect size to detect tau depo-
sition with improved quantification power for dynamic 18F-flortaucipir
PET quantifications (Zhou et al., 2021). Notice that the cerebellum
GM was frequently used as reference tissue in full dynamic 18F-
flortaucipir PET studies (Baker et al., 2017; Barret et al., 2017; Devous
Sr. et al., 2018; Golla et al., 2017). The average ACR of tau obtained in
this study when centrum semiovale as reference tissue was
ACRCS = 3.22%, which was close to the previous annual 18F-
flortaucipir change of 4% collected from the inferior temporal region
when cerebral white matter was used as the reference tissue
(Hanseeuw et al., 2019).
To date, the cerebellum GM reference tissue, a region without
relevant specific binding, has been suggested for the quantitation of
amyloid and tau burden (Baker et al., 2017; Barret et al., 2017;
Joachim, Morris, & Selkoe, 1989; Price et al., 2005; Yamaguchi, Hirai,
Morimatsu, Shoji, & Nakazato, 1989), as well as for the quantification
of the tracer perfusion (Bilgel et al., 2020; Weiner et al., 2013; Zhou
et al., 2007, 2021). For example, cerebellum GM was the suggested
reference tissue to estimate relative transport rate R1 for dynamic
18F-flortaucipir PET studies (Zhou et al., 2021). Based on the cerebel-
lum GM reference, the R1 images derived from 11C-PIB dynamic PET
have been used to assess the cerebral blood flow decreases in AD
studies (Bilgel et al., 2020). Previous studies have also proposed and
period: 57.05 ± 18.75 months, n = 55) 18F-florbetapir SUVR changes
in participants with cognitive decline. The SUVR was calculated for
F IGURE 4 Statistical t values of ROI-based longitudinal 18F-florbetapir SUVR changes in subjects with cognitive decline. Statistical p values
indicate *p < .05, **p < .001, ***p < .0001. ACC, anterior cingulate; InfT, inferior temporal; LatT, lateral temporal; Occ, occipital; OrbF, orbital
frontal; Par, parietal; PCC, posterior cingulate; PPrC, posterior precuneus; PreF, prefrontal; SupF, superior frontal
validated the benefits of using a white matter reference in longitudinal
amyloid PET studies (Brendel et al., 2015; Chen et al., 2015). The
cerebral white voxels were usually collected in the corpus callosum
and centrum semiovale, rather than the cerebellum white matter
which is close to gray matter or ventricles due to the likelihood of
being confounded by the partial volume effect. Although the whole
cerebellum is also used for cross-sectional analyses of florbetapir PET
(Doraiswamy et al., 2012; Fleisher et al., 2013; Landau et al., 2013), a
reference region including subcortical white matter is suggested for
the measurement of the SUVR changes in longitudinal florbetapir PET
study (Landau et al., 2015), which is consistent with our longitudinal
study. We have also implemented the longitudinal analysis and
covariates corrected cross-sectional analysis using the whole cerebel-
lum (a combination of gray matter and white matter) reference tissue
and compared the results. In the longitudinal analysis, the sensitivity of
the whole cerebellum reference tissue to detect 18F-FDG PET SUVR
changes is lower than that of cerebellum GM and is close to that of
white matter (centrum semiovale; Figure S1). In 18F-florbetapir and 18F-
flortaucipir PET studies, the whole cerebellum still has comparable sen-
sitivity to detect SUVR changes with centrum semiovale but has
remarkable higher detection power as compared with cerebellum GM
reference tissue (Figures S2 and S3). The covariates adjusted t-test
showed that the whole cerebellum reference tissue based SUVR has
the least sensitivity to discriminate CN and CI groups in both 18F-FDG
(Figure S4) and 18F-florbetapir (Figure S4) when compared to the cere-
bellum GM, centrum semiovale and pons based SUVRs, specifically for
the frontal and hippocampus (Table S1) in 18F-FDG and occipital and
parahippocampal gyrus in 18F-florbetapir (Table S2). Whereas in 18F-
flortaucipir, the cerebellum GM, centrum semiovale, pons, and whole
cerebellum demonstrate similar sensitivities in distinguishing CN and CI
groups (Table S3 and Figure S4).
In conclusion, the reference tissue pons-based 18F-FDG SUVR
and centrum semiovale-based 18F-florbetapir and 18F-flortaucipir
SUVR significantly improved the detection power of longitudinal PET
changes in subjects with cognitive decline. For our cross-sectional
analyses, the pons demonstrated a better performance in dis-
tinguishing CN and CI groups in 18F-FDG. For amyloid and tau PET,
the cerebellum GM, centrum semiovale and pons revealed a compara-
ble statistical power to distinguish between CN and CI, but the cere-
bellum GM was suggested as the ideal reference tissue for
quantification of relative cerebral blood flow, as well as amyloid and
tau depositions using 18F-florbetapir and 18F-flortaucipir. The
suggested tracer-specific reference tissues for SUVR calculation pro-
vide a basis for clinical quantitative ATN PET normalization and stan-
dardization. Our study supports an improved quantitative PET
approach for early diagnosis, monitoring of disease progression, and
therapeutic response in AD studies.
F IGURE 5 Paired statistical tmap of longitudinal (mean follow-up
period: 19.88 ± 8.03 months, n = 20) 18F-flortaucipir SUVR changes in
participants with cognitive decline. The SUVR was calculated for reference
tissue cerebellum GM, centrum semiovale, and pons, respectively
F IGURE 6 Statistical t values of ROI-based longitudinal 18F-flortaucipir SUVR changes in subjects with cognitive decline. Statistical p values
indicate *p < .05, **p < .001, ***p < .0001
Data collection and sharing for this project was funded by the
Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Insti-
tutes of Health Grant U01 AG024904) and DOD ADNI (Department
of Defense award number W81XWH-12-2-0012). ADNI is funded by
the National Institute on Aging, the National Institute of Biomedical
Imaging and Bioengineering, and through generous contributions from
the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discov-
ery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers
Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuti-
cals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd
and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare;
IXICO Ltd.;Janssen Alzheimer Immunotherapy Research & Development,
LLC.; Johnson & Johnson Pharmaceutical Research & Development
LLC.; Lumosity; Lundbeck; Merck & Co., Inc.;Meso Scale Diagnostics,
LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharma-
ceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda
Pharmaceutical Company; and Transition Therapeutics. The Canadian
Institutes of Health Research is providing funds to support ADNI clinical
sites in Canada. Private sector contributions are facilitated by the Foun-
dation for the National Institutes of Health (www.fnih.org). The grantee
organization is the Northern California Institute for Research and Educa-
tion, and the study is coordinated by the Alzheimer's Therapeutic
Research Institute at the University of Southern California. ADNI data
are disseminated by the Laboratory for Neuro Imaging at the University
of Southern California.
The authors have declared no conflicts of interest for this article.
tiative (ADNI) dataset (https://adni.loni.usc.edu).
F IGURE 8 Statistical t images for SUVR differences between cognitively normal (CN) and impaired (CI) groups in 18F-FDG (a), 18F-florbetapir
(b), and 18F-flortaucipir (c) PET studies when using cerebellum GM, centrum semiovale, and pons as reference tissue. The SUVR was calculated
for reference tissue cerebellum GM, centrum semiovale, and pons, respectively
F IGURE 7 Statistical Cohen's d images for SUVR differences between cognitively normal (CN) and impaired (CI) groups in 18F-FDG (a),
18F-florbetapir (b), and 18F-flortaucipir (c) PET studies when using cerebellum GM, centrum semiovale, and pons as reference tissue. The SUVR
was calculated for reference tissue cerebellum GM, centrum semiovale, and pons, respectively
Jie Lu https://orcid.org/0000-0003-0425-3921
Xiuying Wang https://orcid.org/0000-0001-7160-5929
Yun Zhou https://orcid.org/0000-0001-9135-336X
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Tracer-specific reference tissues selection improves detection of 18F-FDG, 18F-florbetapir, and 18F-flortaucipir PET SUVR c…
2 MATERIALS AND METHODS
2.2 PET data acquisition and image preprocessing
2.3 Longitudinal SUVR PET analysis for cognitively declined participants
2.4 Cross-sectional SUVR PET analysis for CN and CI participants
3.1 Study cohort characteristics
3.2 Effect of reference tissue selection on sensitivity to detect longitudinal PET SUVR changes in AD
3.2.1 18F-FDG PET
3.2.2 18F-florbetapir PET
3.2.3 18F-flortaucipir PET
3.3 Effect of reference tissue selection on sensitivity to detect PET SUVR differences between CN and CI groups in cross-s…
due in 24 hours attached Funeral Service Law Week 8 Discussion Forum There will be a discussion f
Prior to the financial recession in the late 2000s, some companies built up significant cash balan


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Even though dams have ruined sections of this river this is still a big water Class IV run. After putting in below the dam you get some warm up class II to III water and then the Class IV creeking action starts. Since this run generally is runnable at flood levels scouting can be tricky because of the lack of eddies.
There is no road or trail access between the putin and takeout. Even though this is a fairly short run you should be a comfortable class IV to V boater used to wilderness boating. There are lots of holes and hydraulics in here that can give even the best kayakers a beat down.
Follow the road below the Dam on the south side of the river until you see a small cemetary. There is a small road/trail that cuts down to the river. This is mainly used by rock climbers to climb the Cachi Rock routes. After a short hike and haul to the river bank; put on the river here.
As the gorge opens up you will see a small bridge with several green buildings on river right. Take out at the small clearing above the bridge on (river right).
Access this by car from Highway 225. The turn off and road length to the river is about 1 KM.


Trim the stems from the figs. With the blossom end down, cut an X in the stem end of each fig, cutting ¾ of the way down but not cutting through the figs.
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text:
'The Great Wave': The struggle between humans and nature
Claudio Zonta SJ / Art / Published Date:22 January 2021/Last Updated Date:16 March 2021
The Great Wave of Kanagawa, by Katsushika Hokusai, is one of the most famous Japanese works of art. It served as inspiration for Van Gogh's Starry Night and Debussy's orchestral work La Mer. It is a woodcut from 1830, belonging to a larger series, as evidenced by the title in Japanese, Thirty-six views of Mount Fuji / off Kanagawa / under a wave. The work was printed in multiple copies, which are in the Library of Congress of the United States of America, the Museum of Oriental Art in Turin, and the British Museum in London. When the elderly artist created this image, he was living through economically difficult times, a situation symbolized precisely by the imposing wave in the foreground which is sweeping away some Japanese fishing boats.
The intensity and depth of the sea are achieved using "Prussian Blue," a shade that was accidentally discovered by the German Johann Jacob Diesbach. Picasso often used it in his works. This color communicates to the viewer the fascinating impetus of the stormy sea bearing down on the boats. Also reinforcing the feeling of dismay is the pyramidal shape of the wave, bordered by a white foam, which ends with curls that look like claws ready to strike the fishermen. In a not dissimilar way, through poetry, Homer had sung about the monster Scylla as she crashed down on Odysseus' ship: She has twelve feet, all misshapen, six necks, exceeding long, on each one an awful head, and therein three rows of teeth, thick and close, and full of black death (Odyssey, XII, 89-93).
The boats, with their elongated shape, make their way through the raging waves, carrying the fishermen who are returning home. As the writer Jorge Amado also recounts in Sea of Death, speaking of the fishermen of Bahia: "Each one [of them] has something at the bottom of the sea: a son, a brother, an arm, a saveiro that has been shipwrecked, a sail that the wind of the storm has taken away." In the background, Mount Fuji, awe-inspiring in its height and whiteness, seems to be an immobile spectator with respect to the alternating human events. But the wave has not yet closed, making "the stern rise up," as Dante said: the clash between nature and humans is sealed in that prior moment, where anything can yet occur.

redpajama_set_name: RedPajamaCommonCrawl


Katie: "I started working with Fudge Professional five years ago. The hair is so important for Katie Eary shows, because my designs are very print-tastic, and when it comes to my shows they're always drenched in colour and vibrancy. The week before a show I'll sit down with Fudge Professional, tell them about my inspiration for the collection, pulling together my references and what I love, to show the team. From here, we work together to create the hair look for the show.
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Fudge have worked on the hair for Katie Eary's shows for a number of seasons now. What has been your favourite look of all and why?
Tracy: Working with Katie is always an exciting collaboration as she loves colour to be a big part - including the hair. This enables us to push the creative boundaries of the Fudge Professional colour range. Although it is difficult to choose a favourite from the many shows we have worked on together, I would have to say SS18 really showcased our Paintbox range at its best. I coloured many wefts in lime greens, salmon pinks and burnt orange, which the hair team then weaved into the models' hair, resulting in such a powerful visual for the catwalk.
How different is the preparation for a fashion show when you're creating colourful looks in the models' hair, versus when the look is more natural?
Tracy: The hair tests for the shows can often be finalised at the last minute, or even change drastically a few days before. So you need to be prepared, ensure that you have plenty of colour stock in all colours, and plenty of wefts, and be prepared for long days! Always do test colours to show the designer, as a colour in the pot can sometimes look different on a weft.
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Notice is hereby given that public hearings will be held by the Oconto County Board of Adjustment under the Oconto County Zoning Ordinance on July 30, 2014.
APPLICATION NO. 1 at 8:45 AM at the Little Suamico Town Hall for JTH Properties, 509 County Road C, Pulaski, WI 54162, Agent: Anne Shallow, for a conditional use permit for a barbershop. Location of the property is in Section 15, T26N, R20E, Town of Little Suamico. (On-site inspection at 8:30 AM) 5731 Lade Beach Rd.
APPLICATION NO. 2 at 9:45 AM at the Abrams Town Hall for Kenneth Beekman, 2599 Lakeview Dr, Suamico, WI 54173, for a conditional use permit for storage units. Location of the property is in Section 35, T27N, R20E, Town of Abrams. (On-site inspection at 9:30 AM) 2772 E. Frontage Rd.
APPLICATION NO. 3 at 11:15 AM at the Little River Town Hall for KBM Construction, N4937 US Hwy 141, Crivitz, WI 54114, for a conditional use permit for a dwelling over 15 years old. Location of the property is in Section 20, T29N, R22E, Town of Little River. (On-site inspection at 10:30 AM) 8321 Swedetown Rd.
APPLICATION NO. 6 at 2:00 PM at the Brazeau Town Hall for Michael Laurent, 3137 Molly Brown Ln, Green Bay, WI 54313, for a variance to build closer to the road. Location of the property is in Section 32, T30N, R19E, Town of Brazeau. (On-site inspection at 1:30 PM) 9245 N. Kelly Lake Rd.
APPLICATION NO. 7 at 2:30 PM at the Brazeau Town Hall for Scott Thomson, 8706 Lee Lake Rd, Pound, WI 54161, for a conditional use permit to continue to operate a quarry. Location of the property is in Section 28, T30N, R19E, Town of Brazeau. (On-site inspection at 1:45 PM) Lee Lake Rd.
APPLICATION NO. 8 at 2:45 PM at the Brazeau Town Hall for Scott Thomson, 8706 Lee Lake Rd, Pound, WI 54161, for a conditional use permit to continue to operate a quarry. Location of the property is in Section 28, T30N, R19E, Town of Brazeau. (On-site inspection at 1:50 PM) Brazeau Town Hall Rd.


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As a new patient your needs and wishes are important to us. When you ring the practice a member of our friendly team will introduce themselves to you and offer to help by asking you some questions aimed at understanding your dental needs. If your first contact is a visit to the practice the same process will occur face to face in a confidential private area. We are confident that we can handle any of your treatment needs. If you need to talk to the dentist Joe will come if he is available and help. If he is busy he will call you back as soon as he does become available.
Your first visit to the dentist will start with us taking some medical details and then Joe Rawcliffe will sit with you for a little while to discuss your past and current dental treatment needs. Following this informal meeting there will be a thorough examination of your mouth, soft tissues, gums, teeth, jaws, joints and muscles. Following this an x-ray would complete this part of your visit so that we can effectively establish your exact needs. (If for any reason you cannot have an x-ray at that time then we would defer this to another time).
Once our team have collected all of the necessary information, we can begin planning your dental care with you ensuring that we help meet your expectations and give you all the advice you need for a healthier smile which you can be proud of.
Pain relief is important so if your first visit is due to pain this will be the first thing we will help with. If for any reason you are nervous, please inform us and we will always do our very best to allay your fears. We have an excellent reputation for helping anxious patients.
So, you've joined us, had a treatment - so what happens next?
Once you have completed your first course of treatment(s) and your home-care dental routine is in place then your need for corrective dental treatments should reduce. Year on year you will find fewer fillings (if any) are required and generally you would feel a lot more comfort in your mouth and gums and also generally feel better in yourself.
St Andrews Dental Care work really hard to make visiting us a pleasure not something to look forward to. Of course, if at any time there is something about your smile or oral care you are not happy with then Joe with his extensive training in Cosmetic Dentistry can always help advise you on ways to improve your smile.
Want to speak to a Hull Dentist?