Microscopy with ultraviolet surface excitation for rapid slide-free
histology
UV surface excitation The optical system comprises one or more UV LEDs and UV-compatible sample
stage, complemented by conventional microscope components . Oblique UV excitation light illuminates the
specimen, bypassing the glass microscope lens, which, as it is opaque in the
sub-300-nm spectral region, serves as an intrinsic excitation filter that blocks
backscattered UV light from the optical path. The oblique excitation angle, as
compared to full en-face illumination, can also generate
shading across the face of a specimen that usefully highlights tissue surface
topography . MUSE is distinct from
other UV microscope systems (for example , which detect
fluorescence emission from or absorbance by thinly sectioned samples, largely in
the UV spectral range; unlike MUSE, such instruments require the use of special
UV-transmitting or reflecting objective lenses. The advantage provided by sub-300-nm UV excitation compared to
visible-range excitation is demonstrated in . The cut surface of an unfixed lamb kidney specimen was
stained with eosin (a fluorescent as well as chromogenic dye) and excited using
either a visible-range, 405-nm LED (launched via traditional dichroic mirror
with accompanying in-line emission filter) or an off-axis 280-nm UV LED. Images
were captured with a monochrome CCD camera (see Methods for details) with the
objective focused on the surface of the specimen. In this example, the 405-nm
excitation generated an image with low overall contrast due to out-of-focus
signals originating from multiple tissue depths. In comparison, 280-nm
excitation of the same field provided a sharp, high-contrast image with clearly
demarcated kidney tubules arranged among bundles of collecting ducts because the
UV excitation was restricted to regions very close to the surface. To identify optimal excitation wavelengths for MUSE, a tunable laser was
used to illuminate stained cardiac tissue; images were acquired as the
excitation was stepped from 350 nm to 210 nm. The results suggested that
wavelengths from about 290 to 240 nm generate similar surface-limited excitation
. See also and for
further discussion. 280-nm UV excitation and standard fluorescent dyes A variety of exogenous dyes were sought that would be excitable at 280
nm, emit in the visible range, and stain diagnostically relevant tissue features
(nuclei, cytoplasm, and extracellular components) . Such behavior (UV-excitation with
visible emission) would appear to be inconsistent with the narrow
Stokes’ shifts usually associated with many fluorescent labels, but many
visible-range fluorophores are in fact excitable at a less familiar, sub-300-nm
spectral region, as illustrated with DAPI and rhodamine in (see for additional
discussion). Consequently, multiple stains can be combined, all excited at 280
nm while emitting across the visible range; the resulting colour signals are
then captured simultaneously using a colour camera—of course, more
sophisticated sensors can be used as well. As example, a kidney specimen stained
for 10 seconds with a rhodamine-Hoechst solution is shown in . In addition to nuclear and parenchymal
staining, the elastic laminae of the artery are visible in orange, while
collagen demonstrates an intrinsic blue autofluorescence. Moreover, the oblique
illumination and the extended depth of the unsectioned specimen provides a
glimpse down into the vessel, the nuclei of the endothelial lining cells
vanishing out of the field of view. MUSE workflow compared to conventional histology The steps in standard slide preparation involve fixation, orientation
and trimming, dehydration (via alcohol and xylene), paraffin-embedding,
block-facing and microtomy, transfer of sections to glass slides, rehydration,
staining with haematoxylin and eosin, a second dehydration step, cover slipping,
labeling, transport to a pathologist, or possibly to a whole-slide scanner, and
review. While much of this is automated, it still requires hours and crucial
input from highly skilled technicians. In contrast, MUSE processing minimally
involves tissue orientation and possible surface-preparation via manual cutting
using a sharp blade, staining tissue for as little as 10 seconds, rinsing for 20
seconds and placement directly onto a UV-transparent stage. Small, soft
specimens can benefit from use of a mechanical jig to help orient the cuts. If
the whole specimen does not have to be scanned, the resulting images can be
viewed in real-time. Both fresh and fixed tissue specimens are suitable, and the
resulting MUSE images are comparable suggesting that the fixation step and
timing does not appear to be a crucial variable, at least for the dyes in
current use. This is convenient since in many operating rooms tissues are
automatically placed in formalin. In addition, samples acquired by non-planar
cutting tools, such as the rounded blades of endoscopic biopsy forceps, can also
yield acceptable results. Colour conversion to virtual haematoxylin-and eosin-appearance While MUSE captures images in fluorescence, histologists and
pathologists are (currently) most comfortable looking at brightfield,
H&E-stained specimens. In order to convert full-colour MUSE images (acquired
in a single exposure using a colour camera) directly into virtual H&E
(vH&E), a Python-language-based utility was developed that uses a variant of
spectral unmixing and a Beer-Lambert blending model . A screenshot of this utility is shown
in , see also . Implemented on a GPU (graphics processing unit, code available on
GitHub), such conversions can be performed automatically in near-real-time. As
shown in , the conversion generates
images that can closely approximate authentic H&E appearance and thus
enhances image familiarity . Image quality and resolution, and suitability for replacing frozen
sections MUSE is capable of revealing important subcellular details, in
particular, chromatin texture and mitotic figures. With a high-NA 10X lens, the
current MUSE instrument generates imaging results that are close to that
achievable with a conventional whole slide scanning operating at a nominal 20X
setting, as shown in . Frozen sections, used for intraoperative guidance, can be challenging to
perform and often result in poor histology attributable to freezing artifacts . While MUSE promises
to be suitable for replacing frozen sections, a formal assessment is still in
progress; preliminary comparisons between MUSE, frozen sections and permanents
are shown in . As with frozen sections, MUSE does not always faithfully
reproduce some familiar and often useful artifacts attributable to FFPE
processing . For example,
the clear-cell carcinoma example in does not show the eponymous cleared cytoplasm visible in the H&E image. Extended field of view, or “whole-slide” imaging In regular histology practices, the size of the tissue to be imaged is
limited by the capability of sectioning instrumentation; large-format
microtomes, in use at a few sites, are expensive and technically challenging.
However, experience suggests that large fields of view can provide insights not
discernible with conventionally sized slides . A MUSE system equipped with a suitable
stage can scan arbitrarily large specimens, for example, entire adult brain
slices, with resolution uncoupled from sample dimensions. Examples of
multi-field stitched images are shown in . Imaging speed is acceptable for collecting these large fields of view.
Individual 10X images are currently captured at about 5 frames per second, which
permits imaging a 15 × 15-mm region within about 2–3 minutes.
Higher-power LEDs will shorten imaging time further. This scan time is
comparable to that of conventional bright-field whole-slide scanners, with the
proviso that the latter typically use effective lens magnifications of at least
~20X, providing somewhat higher spatial resolution than the 0.6 μm
provided by the 10X, 0.45 NA-objective used in the present studies. While the
current 10X objective can generate sub-nuclear resolution that may be adequate
for most applications, MUSE systems deploying higher magnification objectives
are technically feasible. Preliminary validation studies As with brightfield whole-slide imaging (WSI), recently cleared by the
FDA after a process examining more than 2,000 specimens , MUSE will require detailed,
multi-tissue, multi-pathology validation to support clinical use. A validation
study was performed that compared diagnoses determined from MUSE images with
those derived from viewing corresponding images from H&E-stained
conventional slides of same specimens. The images were accompanied by
tissue-of-origin information only. The study set consisted of 42 cases
comprising both benign and malignant processes; the diagnoses made from MUSE and
H&E images were essentially identical in 39 cases (a concordance rate of
93%). Of the 3 remaining cases, the paired diagnoses reflected alternate
candidates on the differential diagnosis list, and the third discrepant case
displayed diagnostic features in the MUSE images that were originally
overlooked. Some representative example images are shown in , and case-by-case written diagnoses plus
comments are provided in .. A separate study examining MUSE applicability
to neuropathology cases with positive results is also presented in . Suitability for downstream molecular analysis Increasingly, complex molecular diagnostic tests are being performed on
ever smaller tissue samples, and a needle biopsy may have to be called upon to
provide morphological diagnosis as well as molecular characterization. It would
be ideal if MUSE could be used to non-destructively image such specimens (for
diagnosis or sample adequacy determination) without interfering with downstream
procedures, such as analysis of protein or DNA/RNA expression; targeted, exome
or entire genome sequencing; metabolomics, and the like. It is also important
that prior MUSE imaging not interfere with subsequent standard FFPE histology,
IHC or FISH. Preliminary results presented in suggest
that prior MUSE imaging does indeed not interfere with these tasks (see ),
although considerable further work is required to fully explore possible
effects. 2.5-dimensional surface profiling and extended colour gamut MUSE images can resemble conventional histology, but they also differ in
several aspects. For example, 3-dimensional surface profile information can be
appreciated, as shown in that is not easily perceived with the corresponding
5-μm-thin slices. Panels a and b demonstrate
proteinaceous renal tubular casts; the MUSE image (acquired with a grayscale
camera and emission filters and recoloured for clarity) clearly visualizes their
cylindrical nature (unsurprising, but not easy to appreciate in the H&E).
Panels c and d compare an H&E-stained preparation
of a nerve sheath tumor with the MUSE image of the same specimen. The swirling
nature of the tumor can be inferred from the H&E, but is more evident in the
paired MUSE image. Finally, panels e and f examine the
epithelium and fibrovascular core of a seromucinous ovarian carcinoma. An
opening into a core can be seen in the upper right region of panel f. Additional
examples of quasi-3D (thus termed 2.5D) views can be seen in . It is also possible to acquire actual
quantitative depth information using Z-stack analysis (ms. in preparation).
Interesting surface profiles imply excursions along the z-axis, which poses a
challenge for high-magnification (high-NA) limited depth-of-field objectives.
With Z-axis control it is possible to extend depth of field to ensure that
entire specimens are in focus as shown in . The staining repertoire available to MUSE is also broader than that seen
with conventional H&E . For example, the stomach fundus contains two distinct
cell types, chief and parietal cells. While these cell types are somewhat
distinguishable in conventional histology, the two populations can be much more
distinct following rhodamine and Hoechst staining ( g vs. h ). Stromal components that are hard to appreciate with
conventional H&E can also be better distinguished with MUSE staining. In
panels i (H&E) and j (MUSE) from a region of renal
pelvis, features (labeled 1–5 ) are compared. The
artery’s elastic laminae ( 1 ) and the vein ( 2 ),
along with additional small vessels, are much easier to discern in the MUSE
image. The three stromal layers (labeled 3–5 ) located
beneath the urothelium in the upper right corner are tinctorially distinct with
MUSE, but are only distinguishable in the H&E image through minor variations
in texture. The stromal components reflected in these staining differences are
not yet understood. The possible diagnostic utility of 2.5-dimensional views and
extended colour ranges MUSE will require further investigation. Additional examples of different tissue types imaged by MUSE MUSE provides novel views of familiar tissues. Some examples of this,
spanning a variety of specimens, are shown in Fig. 8. See figure legend for
details, but some highlights include a remarkable cluster of histiocytes in lung
( a ), apparently surrounded by a thin purple sheath that also
connects to other clusters (and not visible in paired FFPE specimens);
multicolour view of skin with elastin, collagen and melanin clearly delineated
( c ); an unusual en-face view of endocardium with underlying
myocardium ( e ); ( f) ; nerve above and penetrating and
between adipocytes from a fresh mastectomy specimen ( f ); breast
ducts in stroma ( g ); skeletal muscle ( h ), and
sebaceous gland ( i ), with tinctorial differences between the stem
cells at the periphery and the maturing and apoptotic cells in the interior.
Finally, it is possible to use MUSE in brightfield, transillumination mode to
scan conventional whole slides, which could be a useful additional capability.
An example is shown in . 

The optical system comprises one or more UV LEDs and UV-compatible sample
stage, complemented by conventional microscope components . Oblique UV excitation light illuminates the
specimen, bypassing the glass microscope lens, which, as it is opaque in the
sub-300-nm spectral region, serves as an intrinsic excitation filter that blocks
backscattered UV light from the optical path. The oblique excitation angle, as
compared to full en-face illumination, can also generate
shading across the face of a specimen that usefully highlights tissue surface
topography . MUSE is distinct from
other UV microscope systems (for example , which detect
fluorescence emission from or absorbance by thinly sectioned samples, largely in
the UV spectral range; unlike MUSE, such instruments require the use of special
UV-transmitting or reflecting objective lenses. The advantage provided by sub-300-nm UV excitation compared to
visible-range excitation is demonstrated in . The cut surface of an unfixed lamb kidney specimen was
stained with eosin (a fluorescent as well as chromogenic dye) and excited using
either a visible-range, 405-nm LED (launched via traditional dichroic mirror
with accompanying in-line emission filter) or an off-axis 280-nm UV LED. Images
were captured with a monochrome CCD camera (see Methods for details) with the
objective focused on the surface of the specimen. In this example, the 405-nm
excitation generated an image with low overall contrast due to out-of-focus
signals originating from multiple tissue depths. In comparison, 280-nm
excitation of the same field provided a sharp, high-contrast image with clearly
demarcated kidney tubules arranged among bundles of collecting ducts because the
UV excitation was restricted to regions very close to the surface. To identify optimal excitation wavelengths for MUSE, a tunable laser was
used to illuminate stained cardiac tissue; images were acquired as the
excitation was stepped from 350 nm to 210 nm. The results suggested that
wavelengths from about 290 to 240 nm generate similar surface-limited excitation
. See also and for
further discussion. 

A variety of exogenous dyes were sought that would be excitable at 280
nm, emit in the visible range, and stain diagnostically relevant tissue features
(nuclei, cytoplasm, and extracellular components) . Such behavior (UV-excitation with
visible emission) would appear to be inconsistent with the narrow
Stokes’ shifts usually associated with many fluorescent labels, but many
visible-range fluorophores are in fact excitable at a less familiar, sub-300-nm
spectral region, as illustrated with DAPI and rhodamine in (see for additional
discussion). Consequently, multiple stains can be combined, all excited at 280
nm while emitting across the visible range; the resulting colour signals are
then captured simultaneously using a colour camera—of course, more
sophisticated sensors can be used as well. As example, a kidney specimen stained
for 10 seconds with a rhodamine-Hoechst solution is shown in . In addition to nuclear and parenchymal
staining, the elastic laminae of the artery are visible in orange, while
collagen demonstrates an intrinsic blue autofluorescence. Moreover, the oblique
illumination and the extended depth of the unsectioned specimen provides a
glimpse down into the vessel, the nuclei of the endothelial lining cells
vanishing out of the field of view. 

The steps in standard slide preparation involve fixation, orientation
and trimming, dehydration (via alcohol and xylene), paraffin-embedding,
block-facing and microtomy, transfer of sections to glass slides, rehydration,
staining with haematoxylin and eosin, a second dehydration step, cover slipping,
labeling, transport to a pathologist, or possibly to a whole-slide scanner, and
review. While much of this is automated, it still requires hours and crucial
input from highly skilled technicians. In contrast, MUSE processing minimally
involves tissue orientation and possible surface-preparation via manual cutting
using a sharp blade, staining tissue for as little as 10 seconds, rinsing for 20
seconds and placement directly onto a UV-transparent stage. Small, soft
specimens can benefit from use of a mechanical jig to help orient the cuts. If
the whole specimen does not have to be scanned, the resulting images can be
viewed in real-time. Both fresh and fixed tissue specimens are suitable, and the
resulting MUSE images are comparable suggesting that the fixation step and
timing does not appear to be a crucial variable, at least for the dyes in
current use. This is convenient since in many operating rooms tissues are
automatically placed in formalin. In addition, samples acquired by non-planar
cutting tools, such as the rounded blades of endoscopic biopsy forceps, can also
yield acceptable results. 

While MUSE captures images in fluorescence, histologists and
pathologists are (currently) most comfortable looking at brightfield,
H&E-stained specimens. In order to convert full-colour MUSE images (acquired
in a single exposure using a colour camera) directly into virtual H&E
(vH&E), a Python-language-based utility was developed that uses a variant of
spectral unmixing and a Beer-Lambert blending model . A screenshot of this utility is shown
in , see also . Implemented on a GPU (graphics processing unit, code available on
GitHub), such conversions can be performed automatically in near-real-time. As
shown in , the conversion generates
images that can closely approximate authentic H&E appearance and thus
enhances image familiarity . 

MUSE is capable of revealing important subcellular details, in
particular, chromatin texture and mitotic figures. With a high-NA 10X lens, the
current MUSE instrument generates imaging results that are close to that
achievable with a conventional whole slide scanning operating at a nominal 20X
setting, as shown in . Frozen sections, used for intraoperative guidance, can be challenging to
perform and often result in poor histology attributable to freezing artifacts . While MUSE promises
to be suitable for replacing frozen sections, a formal assessment is still in
progress; preliminary comparisons between MUSE, frozen sections and permanents
are shown in . As with frozen sections, MUSE does not always faithfully
reproduce some familiar and often useful artifacts attributable to FFPE
processing . For example,
the clear-cell carcinoma example in does not show the eponymous cleared cytoplasm visible in the H&E image. 

In regular histology practices, the size of the tissue to be imaged is
limited by the capability of sectioning instrumentation; large-format
microtomes, in use at a few sites, are expensive and technically challenging.
However, experience suggests that large fields of view can provide insights not
discernible with conventionally sized slides . A MUSE system equipped with a suitable
stage can scan arbitrarily large specimens, for example, entire adult brain
slices, with resolution uncoupled from sample dimensions. Examples of
multi-field stitched images are shown in . Imaging speed is acceptable for collecting these large fields of view.
Individual 10X images are currently captured at about 5 frames per second, which
permits imaging a 15 × 15-mm region within about 2–3 minutes.
Higher-power LEDs will shorten imaging time further. This scan time is
comparable to that of conventional bright-field whole-slide scanners, with the
proviso that the latter typically use effective lens magnifications of at least
~20X, providing somewhat higher spatial resolution than the 0.6 μm
provided by the 10X, 0.45 NA-objective used in the present studies. While the
current 10X objective can generate sub-nuclear resolution that may be adequate
for most applications, MUSE systems deploying higher magnification objectives
are technically feasible. 

As with brightfield whole-slide imaging (WSI), recently cleared by the
FDA after a process examining more than 2,000 specimens , MUSE will require detailed,
multi-tissue, multi-pathology validation to support clinical use. A validation
study was performed that compared diagnoses determined from MUSE images with
those derived from viewing corresponding images from H&E-stained
conventional slides of same specimens. The images were accompanied by
tissue-of-origin information only. The study set consisted of 42 cases
comprising both benign and malignant processes; the diagnoses made from MUSE and
H&E images were essentially identical in 39 cases (a concordance rate of
93%). Of the 3 remaining cases, the paired diagnoses reflected alternate
candidates on the differential diagnosis list, and the third discrepant case
displayed diagnostic features in the MUSE images that were originally
overlooked. Some representative example images are shown in , and case-by-case written diagnoses plus
comments are provided in .. A separate study examining MUSE applicability
to neuropathology cases with positive results is also presented in . 

Increasingly, complex molecular diagnostic tests are being performed on
ever smaller tissue samples, and a needle biopsy may have to be called upon to
provide morphological diagnosis as well as molecular characterization. It would
be ideal if MUSE could be used to non-destructively image such specimens (for
diagnosis or sample adequacy determination) without interfering with downstream
procedures, such as analysis of protein or DNA/RNA expression; targeted, exome
or entire genome sequencing; metabolomics, and the like. It is also important
that prior MUSE imaging not interfere with subsequent standard FFPE histology,
IHC or FISH. Preliminary results presented in suggest
that prior MUSE imaging does indeed not interfere with these tasks (see ),
although considerable further work is required to fully explore possible
effects. 

MUSE images can resemble conventional histology, but they also differ in
several aspects. For example, 3-dimensional surface profile information can be
appreciated, as shown in that is not easily perceived with the corresponding
5-μm-thin slices. Panels a and b demonstrate
proteinaceous renal tubular casts; the MUSE image (acquired with a grayscale
camera and emission filters and recoloured for clarity) clearly visualizes their
cylindrical nature (unsurprising, but not easy to appreciate in the H&E).
Panels c and d compare an H&E-stained preparation
of a nerve sheath tumor with the MUSE image of the same specimen. The swirling
nature of the tumor can be inferred from the H&E, but is more evident in the
paired MUSE image. Finally, panels e and f examine the
epithelium and fibrovascular core of a seromucinous ovarian carcinoma. An
opening into a core can be seen in the upper right region of panel f. Additional
examples of quasi-3D (thus termed 2.5D) views can be seen in . It is also possible to acquire actual
quantitative depth information using Z-stack analysis (ms. in preparation).
Interesting surface profiles imply excursions along the z-axis, which poses a
challenge for high-magnification (high-NA) limited depth-of-field objectives.
With Z-axis control it is possible to extend depth of field to ensure that
entire specimens are in focus as shown in . The staining repertoire available to MUSE is also broader than that seen
with conventional H&E . For example, the stomach fundus contains two distinct
cell types, chief and parietal cells. While these cell types are somewhat
distinguishable in conventional histology, the two populations can be much more
distinct following rhodamine and Hoechst staining ( g vs. h ). Stromal components that are hard to appreciate with
conventional H&E can also be better distinguished with MUSE staining. In
panels i (H&E) and j (MUSE) from a region of renal
pelvis, features (labeled 1–5 ) are compared. The
artery’s elastic laminae ( 1 ) and the vein ( 2 ),
along with additional small vessels, are much easier to discern in the MUSE
image. The three stromal layers (labeled 3–5 ) located
beneath the urothelium in the upper right corner are tinctorially distinct with
MUSE, but are only distinguishable in the H&E image through minor variations
in texture. The stromal components reflected in these staining differences are
not yet understood. The possible diagnostic utility of 2.5-dimensional views and
extended colour ranges MUSE will require further investigation. 

MUSE provides novel views of familiar tissues. Some examples of this,
spanning a variety of specimens, are shown in Fig. 8. See figure legend for
details, but some highlights include a remarkable cluster of histiocytes in lung
( a ), apparently surrounded by a thin purple sheath that also
connects to other clusters (and not visible in paired FFPE specimens);
multicolour view of skin with elastin, collagen and melanin clearly delineated
( c ); an unusual en-face view of endocardium with underlying
myocardium ( e ); ( f) ; nerve above and penetrating and
between adipocytes from a fresh mastectomy specimen ( f ); breast
ducts in stroma ( g ); skeletal muscle ( h ), and
sebaceous gland ( i ), with tinctorial differences between the stem
cells at the periphery and the maturing and apoptotic cells in the interior.
Finally, it is possible to use MUSE in brightfield, transillumination mode to
scan conventional whole slides, which could be a useful additional capability.
An example is shown in . 

Although current microscope-based diagnostics are familiar and in use
globally, they require sectioned and stained tissue slices mounted on glass slides,
which may take hours to days to prepare and review. The overall process postpones
diagnoses and contributes to overall health system inefficiencies and substantial,
avoidable, patient anxiety. Hundreds of million slides are prepared just in the US
each year, representing billions of dollars in technical costs alone. Conversely,
rural areas and other low-resource settings may have no access to histology (and
thus accurate diagnoses) whatsoever , . In addition, as
a microscopy technique alone, MUSE can contribute to fields as disparate as basic
biology, microanatomy, toxicology, agriculture and education at all levels. We demonstrate that 280-nm UV excitation, generated by now widely available
LED sources, penetrates tissue to about the thickness of a typical tissue section,
and generates images with excellent spatial resolution and contrast when tested on
an array of normal and neoplastic tissues. It is possible to appreciate not only
overall tissue architecture but also nuclear chromatin texture and mitotic figures.
The samples are stained with inexpensive fluorescent dyes within seconds; resulting
images can be colour-mapped in real-time to replicate standard H&E staining. The
hardware itself is simple and robust, and the images are generated directly by a
colour camera without requiring complex mathematical reconstruction. Preliminary
validation studies described here indicate that MUSE indeed has the potential to
generate images of diagnostic quality. Specimens ranging in size from needle
biopsies to prostatectomies, and potentially to whole adult human brain slices, for
example, can be accommodated simply by employing an XY stage with appropriate
travel. Individual images can be acquired at 3–10 frames/second; enabling
the capture of the equivalent of whole-slide scans in 2–3 minutes. Another
important use case for MUSE is the rapid interrogation of large specimens to find
critical areas to sample, either at higher magnification by MUSE and/or for
selection of regions for FFPE, biobanking, or molecular testing. US CLIA regulations
currently require the preservation of patient material even after diagnoses are
rendered; following MUSE, tissues can be readily transferred into paraffin as
necessary. Both fresh and fixed tissues can be prepared and imaged using similar
protocols. Fixed tissues are easy to orient and cut by hand, but their relative
stiffness can interfere with having the cut face lie completely flat against the
sapphire support. On the other hand, fresh tissue is more conformable, allowing
small biopsies to be imaged directly without further surface preparation. However,
it can be somewhat challenging to orient and section small soft specimens or ones
with components of differing resistance to being cut by a blade. Jigs or temporary
supports using fast-gelling agarose can help with cut-surface orientation. In recent years, new treatment options that offer a personalized approach in
treating cancer have been established. However, they require specific biomarker
tissue testing to help predict response to new targeted therapy, sometimes years
following primary diagnosis. Relatively non-invasive needle biopsies are useful for
interrogating tumor recurrences especially in patients in advanced stages of disease
who have failed several lines of conventional therapy. The non-destructive nature of
MUSE can be particularly helpful in this setting, especially for small tissue
biopsies that might otherwise be significantly consumed following frozen and/or
conventional sectioning. Prior MUSE imaging does not appear to interfere with
subsequent conventional histology, IHC, FISH or RNA-Seq studies. In fact, FFPE-based
methods (dispensable with MUSE) can themselves have deleterious effects on nucleic
acid integrity , antigen
preservation and retrieval – . MUSE was developed with an eye towards examining manually cut tissue
specimens, but there are tasks that call for examining closely spaced serial
sections, for example, searching for small metastases in tumor-draining lymph nodes.
Such fine spacing can be accomplished using vibrating blade microtomes able to slice
fresh tissue at spacings of 50 μm or less . Another possible limitation: some useful
artifacts associated with FFPE techniques, such as the chromatin clearing
characteristic of some tumors, may not be visible in MUSE images, which in this
regard resemble fine-needle aspirates or frozen sections . Additional differences between MUSE and conventional histology exist, some
advantageous, others perhaps may be distractions. (1) As UV penetration is slightly
deeper than the thickness of conventional sections, cellularity estimates trend
somewhat higher and nuclear crowding may interfere with some manual or automated
evaluations. (2) A broader colour palette is available than that afforded by simple
H&E. Even a simple two-dye cocktail (rhodamine and Hoechst), when combined with
tissue autofluorescence (e.g., from collagen and tryptophan) or under the influence
of other environmental effects ,
can generate multiple hues. On the one hand, such hues can serve as instant special
stains in histology, highlighting important features such as elastic laminae that
may be poorly delineated in H&E-staining. Converting these high-content colour
images into H&E-like bright-field versions without a) confusing the viewer used
to viewing a limited colour range, or b) collapsing the extra information into just
2 colour channels, remains an interesting challenge. (3) MUSE can generate
2.5-dimensional views of surface topography, revealing novel aspects of tissue
organization and connectivity. While this may be an advantage in some settings,
anything that diminishes the familiarity of the resulting images may be undesirable.
That said, the prominence of topographical features in MUSE images can be regulated
by how the surface of the specimen is prepared. 

Optical design and components As shown in section, the essential components of a
functional system, based on an inverted microscope geometry, consist of a
UV-transparent stage, one or more obliquely oriented 280-nm LEDs, and a
conventional microscope optical train and imaging sensor. The specimen, which
can be of any thickness, and stained as described below, is supported on
300-μm-thick, UV-transparent sapphire window (GT Advanced Technologies,
Salem, MA, USA). The sample is oriented with a nominally flat surface, created
in most cases using a knife or razor blade, towards the objective. The specimen
can be lightly compressed against the stage to help flatten the tissue. The
sapphire window is held in a custom mount attached to a motorized XYZ
translational stage (433-series, Newport, Irvine, CA, USA) to allow for fully
motorized translational scanning and focus. The current version of the MUSE microscope prototype employs 280-nm
UV-emitting LEDs for sample excitation (MTE280H32-UV, Marktech, Latham, NY,
USA). These UV LEDs had a maximum output of 0.9 mW per LED. The light from one
or more UV-LEDs was focused onto the surface of the sample using
short-focal-length ball lenses in an oblique off-axis orientation, illuminating
an approximately 1-mm 2 area. Note: recently released LEDs in the same
wavelength range (Nikkiso America, San Diego, CA, USA) can have maximum output
of 30 mW or more. The emitted fluorescent light was collected using a variety of
long-working-distance objectives (e.g., 10X NA 0.28, Mitutoyo, Kawasaki, Japan,
and 10X NA, 0.45 Nikon, Tokyo, Japan) and focused using an infinity-corrected
tube lens (Thorlabs-ITL200, F = 200 mm, Thorlabs, Newton, New Jersey,
USA) onto either a grayscale CCD camera (Retiga 2000 EXi, 1.5 megapixel, 6.4
μm/pixel, QImaging, Surrey, Canada), a Bayer-pattern colour CCD camera,
either a Micro Publisher 3.3, 3.1-Mpixel, 3.45 μm/pixel (QImaging,
Surrey, Canada), or a 9.2-Mpixel, 3.7 μm/pixel, colour CCD (Ximea,
Münster, Germany). The grayscale camera was used to collect the dataset
for exploring wavelength-dependent imaging depth, whereas the colour cameras
were used to collect the other images shown (except for ). Using the 9.2-Mpixel colour camera and a 10X
objective, the field of view comprised approximately 1 mm 2 . In addition to the core components described above, the MUSE system was
temporarily augmented with additional optics to allow for a comparison with
conventional epifluorescence excitation ; these included a 405-nm LED, a dichroic mirror
(Thorlabs 500 LP, Thorlabs, Newton, New Jersey, USA) and a long-pass emission
filter (Thorlabs FEL0500, Thorlabs, Newton, New Jersey, USA) To explore the
wavelength-dependent depth of imaging in tissue, a laser system equipped with a
tunable optical parametric oscillator (Vibrant 355I, Opotek, Carlsbad,
California, USA) was used to generate excitation light in the 210-to-350-nm
range. Mirrors were used to guide the laser light onto the sample with oblique
geometry like that used by the LED excitation path, and the emitted fluorescence
was collected as described above, except that a 500-nm long-pass filter was
inserted to ensure that the entire range of excitation wavelengths used would be
prevented from reaching the camera. A convenient feature: the inverted optics design of this configuration
allows the scanning of conventional whole stained slides in brightfield mode
simply by using room light (or appropriately configured built-in white light
sources) in transmission. See for an example image. Assessment of depth of UV light penetration in biological tissue To investigate the depth of penetration of the excitation light into
tissue as a function of wavelength, a specimen of fresh porcine heart was
stained for 16 hours (to allow deep penetration into the tissue) with Hoechst
33342 (Life Technologies, Carlsbad, CA, USA, 500 μg/ml in PBS) a dye
that selectively labels nuclei, and the specimen was then imaged using tunable
laser excitation, a blue long-pass filter, and a monochrome camera (shown in ). The excitation light was tuned from 350 to 210 nm in 10-nm
steps. At each of the 15 wavelengths used, single-field images at 10 focal
depths were collected by moving a 20X-objective lens using a micrometer stage in
4-μm steps. The stack images were projected onto a single image using the maximum
intensity Z-projection algorithm in ImageJ. Thereafter, a rolling-ball algorithm
(ImageJ) was used to highlight the nuclei and suppress background signals
resulted from excess binding of Hoechst to myocyte cytoplasm attributable to
extended exposure to the stain. The nuclei were counted manually, assisted by an
ImageJ cell-counter plugin. Image acquisition and processing Microscope control and image acquisition tasks were performed with
custom software written in Microsoft Visual Basic .NET (VB.NET, Microsoft Corp,
Redmond, WA, USA). Grayscale and colour images were captured with exposures that
typically ranged from 0.1 to 0.5 seconds per frame, and were saved in TIFF or
JPEG format. Image processing was performed using open-source ImageJ image
processing and analysis software ( http://imagej.nih.gov/ij/ )
along with open-source GIMP image processing software ( https://www.gimp.org ), and was in most cases confined to
flat-fielding, adjusting brightness and contrast, colour balance, and sharpening
with an unsharp mask tool (with the GIMP default settings, radius 5.0, amount
0.5, threshold 0.0). Using an XYZ translation stage (the Z axis is currently
used for manual focus); multiple fields of view were collected and assembled by
mosaicking single frames together. In many cases, the XYZ stage was sufficiently
precise that the images were simply abutted after flat-fielding to create
acceptable large montages. However, optimal montage results were obtained by
allowing 10% image-to-image spatial overlap and using the Microsoft
Image Composite Editor ( http://research.microsoft.com/en-us/um/redmond/projects/ice/ ) to
perform subpixel registration and image stitching. When extended depth of field imaging was required, multiple Z-stacks
were acquired at 10-micron spacing. See and Note 4
for more information. Sample preparation and staining In this study, both fresh and formalin-fixed tissues were used. Human
specimens were sourced through two mechanisms. Predominantly, de-identified
excess patient material was obtained directly from the frozen section or
grossing room at UC Davis Medical Center. These tissue samples were determined
to be exempt from oversight by the UC Davis Institutional Review Board (IRB ID
743439-1). Alternatively, formalin-fixed specimens from patients diagnosed with
primary brain tumors were collected under IRB approval from the Department of
Pathology and Laboratory Medicine at UC Davis Medical Center. Only excess
tissues were retained and reviewed by a board-certified neuropathologist
(co-author ML) for diagnostic purposes and for tissue quality control. Tissue
samples were then coded and de-identified per protocol. Efforts were made to
obtain tissue from both genders and from minorities. Animal tissues were
obtained from the UC Davis Meat Lab from slaughtered animals, or from discarded
experimental animals post-sacrifice; in the latter case, all procedures were
performed under IACUC supervision. Several dyes and dye-combinations were studied, including eosin,
rhodamine, DAPI, Hoechst, acridine orange, propidium iodine, and proflavine.
Eosin and rhodamine stain cytoplasm and the extracellular matrix, making the
bulk of the tissue visible. Hoechst and DAPI fluoresce brightly when bound to
DNA, allowing them to serve as excellent nuclear stains. A suitable combination
proved to be rhodamine B (Sigma Aldrich, St. Louis, MO, USA 500 μg/ml in
PBS) plus Hoechst 33342 (Life Technologies, Carlsbad, CA, USA, 500 μg/ml
in PBS), which were combined in a single solution. Tissues were submerged in
this combination for 10 seconds, and then briefly washed in water (fixed
tissues), or in PBS (fresh tissues). The resulting stained tissue specimens
generated bright enough signals for direct and interpretable visualization
through microscope eyepieces, as the reddish rhodamine contrasts well with blue
nuclear labels. Compared to captured digital images, live binocular viewing
provides better appreciation of surface shape information. Camera-acquired
images, however, benefit from additional digital enhancement, as described
above. For precise correlation between H&E and MUSE, we prepared
conventional FFPE and H&E-stained slides, and then released the remaining
tissue from the paraffin block by deparaffinization (essentially reversing the
solvent steps used in embedding). The cut face of the recovered tissue specimen
was then imaged via MUSE, creating essentially a serial-section rendition, as
illustrated in .
Alternatively, after primary MUSE imaging, samples were then processed for
standard histology; the resulting H&E-stained slides were scanned on an
Aperio AT2 slide scanner. Colour-mapping fluorescence to virtual haematoxylin and eosin
(vH&E) A two-staged approach was used to convert original MUSE fluorescence
images to an H&E-stained brightfield appearance. The first step consisted of
unmixing the RGB colour image based on the (3-channel) spectral properties of
the fluorescent dyes, using end-members selected from regions corresponding to
cytoplasm and nuclei, with spectral correction to estimate the colour
coordinates of the pure dye components. The second step converted the
corresponding dye-specific abundance images into simulated H&E
concentrations using a Beer-Lambert physical model of transillumination
microscopy, wherein the absorption RGB values of haematoxylin and eosin are used
to determine the colours in the computed output image. Additional details are
provided in and . Immunohistochemical and fluorescence in situ hybridization methods Standard histological and immunohistochemical (IHC) procedures,
including semiquantitative analyses were performed as previously published . Representative
sections were stained by immunohistochemical labeling using DAKO OMNIS automated
immunohistochemistry system (Dako, Agilent Technologies, Carpinteria, CA) using
the following antibodies: (1) an anti-ATRX (α thalassemia/mental
retardation syndrome X-linked)) rabbit polyclonal antibody (cat. No. HPA001906,
Sigma-Aldrich, a part of Millipore-Sigma, St. Louis, MO); (2) an
anti–Ki-67 mouse monoclonal antibody (GA626, prediluted, Dako, Agilent
Technologies, Carpinteria, CA). Fluorescence in-situ hybridization (FISH)
testing for 1p19q co-deletion on interphase cells was performed on
formalin-fixed paraffin embedded tissue (FFPE): A) FFPE only; B) FFPE after
MUSE. The tumor cells that were labeled with 19q13 Spectrum Orange/19p13
Spectrum Green using Vysis LSI 1p36/1q25 and LSI 19q13/19p13 dual-colour probes
using a previously published protocol . Results are shown in . RNA-Seq To investigate whether MUSE staining and imaging, steps that involve the
use of intercalating dyes and UV excitation, might affect labile RNA sample
integrity, two core needle “biopsies”—obtained ex-vivo
from a resected specimen—were processed in parallel. One was stained
with Hoechst and rhodamine for 10 seconds as described above, and imaged over
several fields for a total imaging time of about 2 minutes. The unstained and
unimaged paired specimen was kept moist in PBS at room temperature during this
time. After MUSE imaging, both cores were snap-frozen in liquid N 2 and processed for RNA sequencing. Total RNA was isolated using RNeasy Mini Kit
(Qiagen, Inc.). Subsequently, RNA quantity and quality were assessed on a
NanoDrop spectrophotometer and an Agilent 2100 Bioanalyzer. Whole transcriptome
profiling was performed using a directional, strand-specific mRNA-Seq approach
in the UC Davis Genomics Shared Resource (GSR), and indexed RNA-Seq libraries
were prepared. Double-stranded cDNA was generated as described , , and libraries were sequenced on an Illumina MiSeq
System (75-bp, paired-end; ~30 million reads/sample) as described . To compare the results from the MUSE-imaged and control RNA sequencing
runs, de-multiplexed raw sequence data (FASTQ) were aligned to the human genome
(GRCh37) using the DRAGEN™ bioinformatics processor. The aligned reads
(bam format) were analyzed using the RSeQC RNA-Seq Quality Control package , . None of the metrics examined showed
appreciable differences between the MUSE and non-MUSE samples outside of
expected RNA-seq library variation. and summarize a few key metrics. The results provide reassurance that the approach
of using MUSE-imaged small specimens will not seriously impair downstream
molecular diagnostic applications. Assessment of diagnostic suitability of MUSE images A. General surgical pathology specimens, MUSE vs. H&E 42 cases from the general surgical pathology service at UC Davis
were selected for a comparison between diagnoses obtained via MUSE and
H&E imaging. Excess material beyond that required for patient care was
obtained under an UC Davis IRB exemption allowing study of anonymized tissue
samples. The distribution was weighted towards ovary, kidney, colon, breast,
lung, and prostate, along with a few other sites of origin. Out of the 42
cases, 10 were benign, and the balance was either frankly malignant or
borderline. No effort was made to select text-book examples of common
pathologies, and some of the cases posed considerable degree of diagnostic
difficulty. 8 specimens were examined in the fresh state, and the remainder
had been formalin-fixed for variable periods of time ranging from a few days
to a few weeks. Each case was imaged via MUSE using 10-second staining with
rhodamine and Hoechst, and multiple fields of view were captured at 10X
magnification. Companion tissue was submitted for fixation (if required) and
standard histological processing followed by H&E staining and
whole-slide scanning at 20X. Representative fields reflecting both normal
(if present), adjacent and diagnostic regions were selected and matched by
one of the authors, and then presented to two experienced, board-certified
pathologists, with only tissue of origin information being provided (i.e.,
no age, gender, medical history or procedure). Each reviewer saw approximate
190 images over the 42 cases (mean 4.5 images per case, range 2–11).
One reviewer made diagnosis viewing only the MUSE images (in both
fluorescence and vH&E mode), and similarly, the other viewed only the
H&E images; no communication between the reviewers occurred. Their
diagnoses, along with comments, if any, more or less verbatim, are presented
in . B. Neuropathology specimens A panel of board-certified/eligible practicing anatomic pathologists
and neuropathologists conducted blinded analysis to assess diagnostic
accuracy achievable with MUSE images (primary MUSE and virtual H&E) when
compared with diagnosis obtained by review of the standard FFPE,
microtome-sectioned and H&E-stained glass slides of the same brain tumor
specimens. Given the histopathological heterogeneity of CNS tumors and the
fact that some specimens may contain a mixture of normal and lesional areas
of interest, 2–4 representative images were captured from each case
and selected by an independent board-certified neuropathologist in order to
best represent diagnostic features. 24 adult patients (14 male, 10 female),
mean age 54 years (range 19 – 83 years), who underwent surgical
resection for newly diagnosed brain and spinal cord tumors were included in
the study. 7 (29%) were diagnosed with diffuse astrocytic or
oligodendroglial tumors; 8 (33.5%) with meningiomas; 3
(12.5%) with ependymal and choroid plexus tumors; 3 (12.5%)
with tumors of the cranial or paraspinal nerves and 3 (12.5%) with
metastatic tumors by the conventional methodology. Each pair of test images (primary MUSE and vH&E) was accompanied
by a questionnaire that included a series of potential diagnoses that
included the above diagnoses. The pathologists had to pick the one answer
that represented the correct diagnostic category. Any differences in diagnosis between primary MUSE or vH&E as
compared to the ground-truth diagnoses made by conventional methodology were
noted as a major, clinically significant difference (false
diagnosis/subclassification of tumor), as presented in . Code availability The Python code and executables to convert full-colour MUSE
images to virtual H&E images are freely available on GitHub at https://github.com/UCDavisMUSE/colourmapper . Data availability The authors declare that all data supporting the findings of
this study are available within the paper and its . 

As shown in section, the essential components of a
functional system, based on an inverted microscope geometry, consist of a
UV-transparent stage, one or more obliquely oriented 280-nm LEDs, and a
conventional microscope optical train and imaging sensor. The specimen, which
can be of any thickness, and stained as described below, is supported on
300-μm-thick, UV-transparent sapphire window (GT Advanced Technologies,
Salem, MA, USA). The sample is oriented with a nominally flat surface, created
in most cases using a knife or razor blade, towards the objective. The specimen
can be lightly compressed against the stage to help flatten the tissue. The
sapphire window is held in a custom mount attached to a motorized XYZ
translational stage (433-series, Newport, Irvine, CA, USA) to allow for fully
motorized translational scanning and focus. The current version of the MUSE microscope prototype employs 280-nm
UV-emitting LEDs for sample excitation (MTE280H32-UV, Marktech, Latham, NY,
USA). These UV LEDs had a maximum output of 0.9 mW per LED. The light from one
or more UV-LEDs was focused onto the surface of the sample using
short-focal-length ball lenses in an oblique off-axis orientation, illuminating
an approximately 1-mm 2 area. Note: recently released LEDs in the same
wavelength range (Nikkiso America, San Diego, CA, USA) can have maximum output
of 30 mW or more. The emitted fluorescent light was collected using a variety of
long-working-distance objectives (e.g., 10X NA 0.28, Mitutoyo, Kawasaki, Japan,
and 10X NA, 0.45 Nikon, Tokyo, Japan) and focused using an infinity-corrected
tube lens (Thorlabs-ITL200, F = 200 mm, Thorlabs, Newton, New Jersey,
USA) onto either a grayscale CCD camera (Retiga 2000 EXi, 1.5 megapixel, 6.4
μm/pixel, QImaging, Surrey, Canada), a Bayer-pattern colour CCD camera,
either a Micro Publisher 3.3, 3.1-Mpixel, 3.45 μm/pixel (QImaging,
Surrey, Canada), or a 9.2-Mpixel, 3.7 μm/pixel, colour CCD (Ximea,
Münster, Germany). The grayscale camera was used to collect the dataset
for exploring wavelength-dependent imaging depth, whereas the colour cameras
were used to collect the other images shown (except for ). Using the 9.2-Mpixel colour camera and a 10X
objective, the field of view comprised approximately 1 mm 2 . In addition to the core components described above, the MUSE system was
temporarily augmented with additional optics to allow for a comparison with
conventional epifluorescence excitation ; these included a 405-nm LED, a dichroic mirror
(Thorlabs 500 LP, Thorlabs, Newton, New Jersey, USA) and a long-pass emission
filter (Thorlabs FEL0500, Thorlabs, Newton, New Jersey, USA) To explore the
wavelength-dependent depth of imaging in tissue, a laser system equipped with a
tunable optical parametric oscillator (Vibrant 355I, Opotek, Carlsbad,
California, USA) was used to generate excitation light in the 210-to-350-nm
range. Mirrors were used to guide the laser light onto the sample with oblique
geometry like that used by the LED excitation path, and the emitted fluorescence
was collected as described above, except that a 500-nm long-pass filter was
inserted to ensure that the entire range of excitation wavelengths used would be
prevented from reaching the camera. A convenient feature: the inverted optics design of this configuration
allows the scanning of conventional whole stained slides in brightfield mode
simply by using room light (or appropriately configured built-in white light
sources) in transmission. See for an example image. 

To investigate the depth of penetration of the excitation light into
tissue as a function of wavelength, a specimen of fresh porcine heart was
stained for 16 hours (to allow deep penetration into the tissue) with Hoechst
33342 (Life Technologies, Carlsbad, CA, USA, 500 μg/ml in PBS) a dye
that selectively labels nuclei, and the specimen was then imaged using tunable
laser excitation, a blue long-pass filter, and a monochrome camera (shown in ). The excitation light was tuned from 350 to 210 nm in 10-nm
steps. At each of the 15 wavelengths used, single-field images at 10 focal
depths were collected by moving a 20X-objective lens using a micrometer stage in
4-μm steps. The stack images were projected onto a single image using the maximum
intensity Z-projection algorithm in ImageJ. Thereafter, a rolling-ball algorithm
(ImageJ) was used to highlight the nuclei and suppress background signals
resulted from excess binding of Hoechst to myocyte cytoplasm attributable to
extended exposure to the stain. The nuclei were counted manually, assisted by an
ImageJ cell-counter plugin. 

Microscope control and image acquisition tasks were performed with
custom software written in Microsoft Visual Basic .NET (VB.NET, Microsoft Corp,
Redmond, WA, USA). Grayscale and colour images were captured with exposures that
typically ranged from 0.1 to 0.5 seconds per frame, and were saved in TIFF or
JPEG format. Image processing was performed using open-source ImageJ image
processing and analysis software ( http://imagej.nih.gov/ij/ )
along with open-source GIMP image processing software ( https://www.gimp.org ), and was in most cases confined to
flat-fielding, adjusting brightness and contrast, colour balance, and sharpening
with an unsharp mask tool (with the GIMP default settings, radius 5.0, amount
0.5, threshold 0.0). Using an XYZ translation stage (the Z axis is currently
used for manual focus); multiple fields of view were collected and assembled by
mosaicking single frames together. In many cases, the XYZ stage was sufficiently
precise that the images were simply abutted after flat-fielding to create
acceptable large montages. However, optimal montage results were obtained by
allowing 10% image-to-image spatial overlap and using the Microsoft
Image Composite Editor ( http://research.microsoft.com/en-us/um/redmond/projects/ice/ ) to
perform subpixel registration and image stitching. When extended depth of field imaging was required, multiple Z-stacks
were acquired at 10-micron spacing. See and Note 4
for more information. 

In this study, both fresh and formalin-fixed tissues were used. Human
specimens were sourced through two mechanisms. Predominantly, de-identified
excess patient material was obtained directly from the frozen section or
grossing room at UC Davis Medical Center. These tissue samples were determined
to be exempt from oversight by the UC Davis Institutional Review Board (IRB ID
743439-1). Alternatively, formalin-fixed specimens from patients diagnosed with
primary brain tumors were collected under IRB approval from the Department of
Pathology and Laboratory Medicine at UC Davis Medical Center. Only excess
tissues were retained and reviewed by a board-certified neuropathologist
(co-author ML) for diagnostic purposes and for tissue quality control. Tissue
samples were then coded and de-identified per protocol. Efforts were made to
obtain tissue from both genders and from minorities. Animal tissues were
obtained from the UC Davis Meat Lab from slaughtered animals, or from discarded
experimental animals post-sacrifice; in the latter case, all procedures were
performed under IACUC supervision. Several dyes and dye-combinations were studied, including eosin,
rhodamine, DAPI, Hoechst, acridine orange, propidium iodine, and proflavine.
Eosin and rhodamine stain cytoplasm and the extracellular matrix, making the
bulk of the tissue visible. Hoechst and DAPI fluoresce brightly when bound to
DNA, allowing them to serve as excellent nuclear stains. A suitable combination
proved to be rhodamine B (Sigma Aldrich, St. Louis, MO, USA 500 μg/ml in
PBS) plus Hoechst 33342 (Life Technologies, Carlsbad, CA, USA, 500 μg/ml
in PBS), which were combined in a single solution. Tissues were submerged in
this combination for 10 seconds, and then briefly washed in water (fixed
tissues), or in PBS (fresh tissues). The resulting stained tissue specimens
generated bright enough signals for direct and interpretable visualization
through microscope eyepieces, as the reddish rhodamine contrasts well with blue
nuclear labels. Compared to captured digital images, live binocular viewing
provides better appreciation of surface shape information. Camera-acquired
images, however, benefit from additional digital enhancement, as described
above. For precise correlation between H&E and MUSE, we prepared
conventional FFPE and H&E-stained slides, and then released the remaining
tissue from the paraffin block by deparaffinization (essentially reversing the
solvent steps used in embedding). The cut face of the recovered tissue specimen
was then imaged via MUSE, creating essentially a serial-section rendition, as
illustrated in .
Alternatively, after primary MUSE imaging, samples were then processed for
standard histology; the resulting H&E-stained slides were scanned on an
Aperio AT2 slide scanner. 

A two-staged approach was used to convert original MUSE fluorescence
images to an H&E-stained brightfield appearance. The first step consisted of
unmixing the RGB colour image based on the (3-channel) spectral properties of
the fluorescent dyes, using end-members selected from regions corresponding to
cytoplasm and nuclei, with spectral correction to estimate the colour
coordinates of the pure dye components. The second step converted the
corresponding dye-specific abundance images into simulated H&E
concentrations using a Beer-Lambert physical model of transillumination
microscopy, wherein the absorption RGB values of haematoxylin and eosin are used
to determine the colours in the computed output image. Additional details are
provided in and . 

Standard histological and immunohistochemical (IHC) procedures,
including semiquantitative analyses were performed as previously published . Representative
sections were stained by immunohistochemical labeling using DAKO OMNIS automated
immunohistochemistry system (Dako, Agilent Technologies, Carpinteria, CA) using
the following antibodies: (1) an anti-ATRX (α thalassemia/mental
retardation syndrome X-linked)) rabbit polyclonal antibody (cat. No. HPA001906,
Sigma-Aldrich, a part of Millipore-Sigma, St. Louis, MO); (2) an
anti–Ki-67 mouse monoclonal antibody (GA626, prediluted, Dako, Agilent
Technologies, Carpinteria, CA). Fluorescence in-situ hybridization (FISH)
testing for 1p19q co-deletion on interphase cells was performed on
formalin-fixed paraffin embedded tissue (FFPE): A) FFPE only; B) FFPE after
MUSE. The tumor cells that were labeled with 19q13 Spectrum Orange/19p13
Spectrum Green using Vysis LSI 1p36/1q25 and LSI 19q13/19p13 dual-colour probes
using a previously published protocol . Results are shown in . 

To investigate whether MUSE staining and imaging, steps that involve the
use of intercalating dyes and UV excitation, might affect labile RNA sample
integrity, two core needle “biopsies”—obtained ex-vivo
from a resected specimen—were processed in parallel. One was stained
with Hoechst and rhodamine for 10 seconds as described above, and imaged over
several fields for a total imaging time of about 2 minutes. The unstained and
unimaged paired specimen was kept moist in PBS at room temperature during this
time. After MUSE imaging, both cores were snap-frozen in liquid N 2 and processed for RNA sequencing. Total RNA was isolated using RNeasy Mini Kit
(Qiagen, Inc.). Subsequently, RNA quantity and quality were assessed on a
NanoDrop spectrophotometer and an Agilent 2100 Bioanalyzer. Whole transcriptome
profiling was performed using a directional, strand-specific mRNA-Seq approach
in the UC Davis Genomics Shared Resource (GSR), and indexed RNA-Seq libraries
were prepared. Double-stranded cDNA was generated as described , , and libraries were sequenced on an Illumina MiSeq
System (75-bp, paired-end; ~30 million reads/sample) as described . To compare the results from the MUSE-imaged and control RNA sequencing
runs, de-multiplexed raw sequence data (FASTQ) were aligned to the human genome
(GRCh37) using the DRAGEN™ bioinformatics processor. The aligned reads
(bam format) were analyzed using the RSeQC RNA-Seq Quality Control package , . None of the metrics examined showed
appreciable differences between the MUSE and non-MUSE samples outside of
expected RNA-seq library variation. and summarize a few key metrics. The results provide reassurance that the approach
of using MUSE-imaged small specimens will not seriously impair downstream
molecular diagnostic applications. 

A. General surgical pathology specimens, MUSE vs. H&E 42 cases from the general surgical pathology service at UC Davis
were selected for a comparison between diagnoses obtained via MUSE and
H&E imaging. Excess material beyond that required for patient care was
obtained under an UC Davis IRB exemption allowing study of anonymized tissue
samples. The distribution was weighted towards ovary, kidney, colon, breast,
lung, and prostate, along with a few other sites of origin. Out of the 42
cases, 10 were benign, and the balance was either frankly malignant or
borderline. No effort was made to select text-book examples of common
pathologies, and some of the cases posed considerable degree of diagnostic
difficulty. 8 specimens were examined in the fresh state, and the remainder
had been formalin-fixed for variable periods of time ranging from a few days
to a few weeks. Each case was imaged via MUSE using 10-second staining with
rhodamine and Hoechst, and multiple fields of view were captured at 10X
magnification. Companion tissue was submitted for fixation (if required) and
standard histological processing followed by H&E staining and
whole-slide scanning at 20X. Representative fields reflecting both normal
(if present), adjacent and diagnostic regions were selected and matched by
one of the authors, and then presented to two experienced, board-certified
pathologists, with only tissue of origin information being provided (i.e.,
no age, gender, medical history or procedure). Each reviewer saw approximate
190 images over the 42 cases (mean 4.5 images per case, range 2–11).
One reviewer made diagnosis viewing only the MUSE images (in both
fluorescence and vH&E mode), and similarly, the other viewed only the
H&E images; no communication between the reviewers occurred. Their
diagnoses, along with comments, if any, more or less verbatim, are presented
in . B. Neuropathology specimens A panel of board-certified/eligible practicing anatomic pathologists
and neuropathologists conducted blinded analysis to assess diagnostic
accuracy achievable with MUSE images (primary MUSE and virtual H&E) when
compared with diagnosis obtained by review of the standard FFPE,
microtome-sectioned and H&E-stained glass slides of the same brain tumor
specimens. Given the histopathological heterogeneity of CNS tumors and the
fact that some specimens may contain a mixture of normal and lesional areas
of interest, 2–4 representative images were captured from each case
and selected by an independent board-certified neuropathologist in order to
best represent diagnostic features. 24 adult patients (14 male, 10 female),
mean age 54 years (range 19 – 83 years), who underwent surgical
resection for newly diagnosed brain and spinal cord tumors were included in
the study. 7 (29%) were diagnosed with diffuse astrocytic or
oligodendroglial tumors; 8 (33.5%) with meningiomas; 3
(12.5%) with ependymal and choroid plexus tumors; 3 (12.5%)
with tumors of the cranial or paraspinal nerves and 3 (12.5%) with
metastatic tumors by the conventional methodology. Each pair of test images (primary MUSE and vH&E) was accompanied
by a questionnaire that included a series of potential diagnoses that
included the above diagnoses. The pathologists had to pick the one answer
that represented the correct diagnostic category. Any differences in diagnosis between primary MUSE or vH&E as
compared to the ground-truth diagnoses made by conventional methodology were
noted as a major, clinically significant difference (false
diagnosis/subclassification of tumor), as presented in . Code availability The Python code and executables to convert full-colour MUSE
images to virtual H&E images are freely available on GitHub at https://github.com/UCDavisMUSE/colourmapper . Data availability The authors declare that all data supporting the findings of
this study are available within the paper and its . 

42 cases from the general surgical pathology service at UC Davis
were selected for a comparison between diagnoses obtained via MUSE and
H&E imaging. Excess material beyond that required for patient care was
obtained under an UC Davis IRB exemption allowing study of anonymized tissue
samples. The distribution was weighted towards ovary, kidney, colon, breast,
lung, and prostate, along with a few other sites of origin. Out of the 42
cases, 10 were benign, and the balance was either frankly malignant or
borderline. No effort was made to select text-book examples of common
pathologies, and some of the cases posed considerable degree of diagnostic
difficulty. 8 specimens were examined in the fresh state, and the remainder
had been formalin-fixed for variable periods of time ranging from a few days
to a few weeks. Each case was imaged via MUSE using 10-second staining with
rhodamine and Hoechst, and multiple fields of view were captured at 10X
magnification. Companion tissue was submitted for fixation (if required) and
standard histological processing followed by H&E staining and
whole-slide scanning at 20X. Representative fields reflecting both normal
(if present), adjacent and diagnostic regions were selected and matched by
one of the authors, and then presented to two experienced, board-certified
pathologists, with only tissue of origin information being provided (i.e.,
no age, gender, medical history or procedure). Each reviewer saw approximate
190 images over the 42 cases (mean 4.5 images per case, range 2–11).
One reviewer made diagnosis viewing only the MUSE images (in both
fluorescence and vH&E mode), and similarly, the other viewed only the
H&E images; no communication between the reviewers occurred. Their
diagnoses, along with comments, if any, more or less verbatim, are presented
in . 

A panel of board-certified/eligible practicing anatomic pathologists
and neuropathologists conducted blinded analysis to assess diagnostic
accuracy achievable with MUSE images (primary MUSE and virtual H&E) when
compared with diagnosis obtained by review of the standard FFPE,
microtome-sectioned and H&E-stained glass slides of the same brain tumor
specimens. Given the histopathological heterogeneity of CNS tumors and the
fact that some specimens may contain a mixture of normal and lesional areas
of interest, 2–4 representative images were captured from each case
and selected by an independent board-certified neuropathologist in order to
best represent diagnostic features. 24 adult patients (14 male, 10 female),
mean age 54 years (range 19 – 83 years), who underwent surgical
resection for newly diagnosed brain and spinal cord tumors were included in
the study. 7 (29%) were diagnosed with diffuse astrocytic or
oligodendroglial tumors; 8 (33.5%) with meningiomas; 3
(12.5%) with ependymal and choroid plexus tumors; 3 (12.5%)
with tumors of the cranial or paraspinal nerves and 3 (12.5%) with
metastatic tumors by the conventional methodology. Each pair of test images (primary MUSE and vH&E) was accompanied
by a questionnaire that included a series of potential diagnoses that
included the above diagnoses. The pathologists had to pick the one answer
that represented the correct diagnostic category. Any differences in diagnosis between primary MUSE or vH&E as
compared to the ground-truth diagnoses made by conventional methodology were
noted as a major, clinically significant difference (false
diagnosis/subclassification of tumor), as presented in . Code availability The Python code and executables to convert full-colour MUSE
images to virtual H&E images are freely available on GitHub at https://github.com/UCDavisMUSE/colourmapper . Data availability The authors declare that all data supporting the findings of
this study are available within the paper and its . 

The Python code and executables to convert full-colour MUSE
images to virtual H&E images are freely available on GitHub at https://github.com/UCDavisMUSE/colourmapper . 

The authors declare that all data supporting the findings of
this study are available within the paper and its . 

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