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240 M. M. Shevchuk
15. Gorin, M. A., Santos Cortes, J. A., Kyle, C. C., Carey, R. I., Bird, V. G. Initial clinical
experience with use of ureteral access sheaths in the diagnosis and treatment of upper
tract urothelial carcinoma. Urology, 78(3): 523–527 (2011).
16. Bus, M. T. J., Muller, B. G., de Bruin, D. M., Faber, D. J., Kamphuis, G. M., van
Leeuwen, T. G., et al. Volumetric in vivo visualization of upper urinary tract tumors
using optical coherence tomography: A pilot study. The Journal of Urology, 190(6):
2236–2242 (2013).
17. Bui,D.,Mach,K.E.,Zlatev,D.V.,Rouse,R.V.,Leppert,J.T.,Liao,J.C.Apilot
study of in vivo confocal laser endomicroscopy of upper tract urothelial carcinoma.
Journal of Endourol, 29(12): 1418–1423 (2015).
18. Villa, L., Cloutier, J., Cotè, J.-F., Salonia, A., Montorsi, F., Traxer, O. Confocal laser
endomicroscopy in the management of endoscopically treated upper urinary tract
transitional cell carcinoma: Preliminary data. Journal of Endourol, 30(2): 237–242
(2015).
19. Breda, A., Territo, A., Guttilla, A., Sanguedolce, F., Manfredi, M., Quaresima, L., et al.
Correlation between confocal laser endomicroscopy (Cellvizio
grading of upper tract urothelial carcinoma: A step forward for a better selection of
patients suitable for conservative management. European Urology Focus, 4(6): 954–
959 (2017).
20. Campbell, S., Uzzo, R. G., Allaf, M. E., Bass, E. B., Cadeddu, J. A., Chang, A.,
et al. Renal mass and localized renal cancer: AUA guideline. The Journal of Urology,
198(3): 520–529 (2017).
21. Ignee, A., Straub, B., Brix, D., Schuessler, G., Ott, M., and Dietrich, C. F. The value
of contrast enhanced ultrasound (CEUS) in the characterisation of patients with renal
masses. Clinical Hemorheology and Microcirculation, 46(4): 275–290 (2010).
22. Su,L.M.,Kuo,J.,Allan,R.W.,Liao,J.C.,Ritari,K.L.,Tomeny,P.E.,et al. Fiberoptic confocal laser endomicroscopy of small renal masses: Toward real-time optical
diagnostic biopsy. The Journal of Urology, 195(2): 486–492 (2016).
23. Krishnamurthy, S., Cortes, A., Lopez, M., Wallace, M., Sabir, S., Shaw, K., et al.
Ex vivo confocal fluorescence microscopy for rapid evaluation of tissues in surgical
pathology practice. Archives of Pathology & Laboratory Medicine, 142(3): 396–401
(2018).
24. Jain, M., Robinson, B. D., Salamoon, B., Thouvenin, O., Boccara, C., and Mukherjee, S. Rapid evaluation of fresh ex vivo kidney tissue with full-field optical
coherence tomography. Journal of Pathology Informatics, 6: 53 (2015). Available from: http://www.pubmedcentral.nih.gov/a rticle render.f cgi?artid$=$4629311
&tool$=$pmcentrez&rendertype$=$abstract.
25. Lee, H.-C., Zhou, C., Cohen, D. W., Mondelblatt, A. E., W ang,Y., Aguirre, A. D., et al.
Integrated optical coherence tomography and optical coherence microscopy imaging
of ex vivo human renal tissues. The Journal of Urology, 187(2): 691–699 (2012).
et al.
) and histological
Genitourinary System 241
26. Jain, M., Robinson, B. D., Aggarwal, A., Shevchuk, M. M., Scherr, D. S., Mukherjee,
S. Multiphoton microscopy for rapid histopathological evaluation of kidney tumours.
British Journal of Urology, 118(1): 118–126 (2016).
27. Jain, M., Robinson, B. D., Wu, B., Khani, F., Mukherjee, S. Exploring multiphoton
microscopy as a novel tool to differentiate chromophobe renal cell carcinoma from
oncocytoma in fixed tissue sections. Archives of Pathology & Laboratory Medicine,
142(3): 383–390 (2018).
28. Couapel, J. P., Senhadji, L., Rioux-Leclercq, N., Verhoest, G., Lavastre, O., De
Crevoisier, R., et al. Optical spectroscopy techniques can accurately distinguish benign
and malignant renal tumours. British Journal of Urology, 111(6): 865–871 (2013).
29. Spether, D., Scharpf, M., Hennenlotter, J., Schwentner, C., Neugebauer, A., Nüßle,
D., et al. Real-time tissue differentiation based on optical emission spectroscopy for
guided electrosurgical tumor resection. Biomedical Optics Express, 6(4): 1419–1428
(2015).
30. Andrews, P. Using optical coherence tomography (OCT) to evaluate human donor
kidneys prior to and following transplantation. Journal of Nephrology, 4: 151 (2017).
Available from: http://www.omicsonline.org/open-access/using-optical-coherencetomography-oct- to-evaluate- human- d onor-kidneys-prior-to-and-following-tr ans
plantat ion-2161-0959.1000151.php?aid$=$22817(2014).
31. Briganti, A., Fossati, N., Catto, J. W. F., Cornford, P., Montorsi, F., Mottet, N., et al.
Activesurveillancefor low-riskprostate cancer: The European Association of Urology
Position in 2018. European Urology, 74(3): 357–368 (2018). Available from: https://
doi.org/10.1016/j.eururo.2018.06.008.
32. Ukimura, O., Coleman, J. A., De La Taille, A., Emberton, M., Epstein, J. I., Freedland,
S. J., et al. Contemporary role of systematic prostate biopsies: Indications, techniques,
and implications for patient care. European Urology, 63(2): 214–230 (2013).
33. Muller,B.G.,deBruin,D.M.,vandenBos,W.,Brandt,M.J.,Velu,J.F.,Bus,M.T.
J., et al. Prostate cancer diagnosis: The feasibility of needle-based optical coherence
tomography. Journal of Medical Imaging, 2(3): 037501 (2015).
34. Lopater, J., Colin, P., Beuvon, F., Sibony, M., Dalimier, E., Cornud, F., et al. Realtime cancer diagnosis during prostate biopsy: Ex vivo evaluation of full-field optical
coherence tomography (FFOCT) imaging on biopsy cores. World Journal of Urology,
34(2): 237–243 (2016).
35. Wang, M., Kimbrell, H. Z., Sholl, A. B., Tulman, D. B., Elfer, K. N., Schlichenmeyer,
T. C. , et al. High-resolution rapid diagnostic imaging of whole prostate biopsies using
video-rate fluorescencestructured illumination microscopy. Cancer Research,75(19):
4032–4041 (2015).
36. Nguyen, T. H., Sridharan, S., Macias, V., Kajdacsy-Balla, A., Melamed, J. Do MN,
et al. Automatic Gleason grading of prostate cancer using quantitative phase imaging
and machine learning. Journal of Biomedical Optics, 22(3): 36015 (2017).
242 M. M. Shevchuk
37. Wiegel, T., Bartkowiak, D., Bottke, D., Bronner, C., Steiner, U., Siegmann, A,
et al. Adjuvant radiotherapy versus wait-and-see after radical prostatectomy: 10-year
follow-up of the ARO 96-02/AUO AP 09/95 trial. European Urology, 66(2): 243–250
(2014).
38. Lopez, A., Zlatev, D. V., Mach, K. E., Bui, D., Liu, J. J., Rouse, R. V., et al. Intraoperative optical biopsy during robotic assisted radical prostatectomy using confocal
endomicroscopy. Journal of Urology, 195(4 Pt 1): 1110–1117 (2016).
39. Wang, M., Tulman, D. B., Sholl, A. B., Kimbrell, H. Z., Mandava, S. H., Elfer, K.N.,
et al. Gigapixel surface imaging of radical prostatectomy specimens for comprehensive detection of cancer-positive surgical margins using structured illumination
microscopy. Scientific Reports, 6: 27419 (2016).
40. Glaser, A. K., Reder, N. P., Chen, Y., McCarty, E. F ., Yin, C., Wei, L., et al. Lightsheet microscopy for slide-free non-destructive pathology of large clinical specimens.
Nature Biomedical Engineering, 1(7): 0084 (2017).
41. Tewari, A. K., Shevchuk, M. M., Sterling, J., Grover, S., Herman, M., Yadav, R., et al.
Multiphoton microscopy for structure identification in human prostate and periprostatic tissue: Implications in prostate cancer surgery. British Journal of Urology,
108(9): 1421–1429 (2011).
42. Sharma, V., Olweny, E. O., Kapur, P., Cadeddu, J. A., Roehrborn, C. G., and Liu,
H. Prostate cancer detection using combined auto-fluorescence and light reflectance
spectroscopy: Ex vivo study of human prostates. Biomedical Optics Express, 5(5):
1512–1529 (2014).
43. Kast, R. E., Tucker, S. C., Killian, K., Trexler, M., Honn, K. V., and Auner, G. W.
Emerging technology: Applications of Raman spectroscopy for prostate cancer. Cancer metastasis reviews, 33(2–3): 673–693 (2014).
44. Trottmann, M., Stepp, H., Sroka, R., Heide, M., Liedl, B., Reese, S., et al. Probebased confocal laser endomicroscopy (pCLE) — A new imaging technique for in situ
localization of spermatozoa. Journal of Biophotonics, 8(5): 415–421 (2015).
45. Trottmann, M., Sroka, R., Stepp, H., Liedl, B., Becker, A. J., Stief, C. G., et al. Probebased confocal laser endomicroscopy (pCLE): A preclinical investigation of the male
genital tract. Lasers in Medical Science, 31(1): 57–65 (2016).
46. Najari, B. B., Ramasamy, R., Sterling, J., Aggarwal, A., Sheth, S., Li, P. S., et al.
Pilot study of the correlation of multiphoton tomography of ex vivo human testis with
histology. The Journal of Urology, 188(2): 538–543 (2012).
47. Shah, P. H., Moreira, D. M., Okhunov, Z., Patel, V . R., Chopra, S., Razmaria, A.A.,
et al. Positive surgical margins increase risk of recurrence after partial nephrectomy
for high risk renal tumors. The Journal of Urology, 196(2): 327–334 (2016). Available
from: http://dx.doi.org/10.1016/j.jur o.2016.02.075.
et al.
© 2024 World Scientific Publishing Company
https://doi.org/10.1142/9789813206984_0013
Gynecologic Tract Chapter
13
Jelena Mirkovic∗and Eric Yang
†
Overview
The effectiveness of in vivo microscopy (IVM) for non-invasive in vivo
diagnosis of gynecologic tract malignancies and their precursor lesions has
been evaluatedin various studies.IVM techniques which are based on light–
tissue interactions aim to provide diagnostic information non-invasively, in
real-time,and in an objectiveand quantitative manner. The potential of IVM
techniques, such as opticalspectroscopy andimaging, confocal microscopy,
and optical coherence tomography (OCT) to image the morphologic and
biochemical changes associated with gynecologic cancers and precursor
lesions has been demonstrated. Promising advances have also been made
in the detection of gynecologic pathology with electric impedance spectroscopy, volume holographic imaging, and other techniques.
∗
Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.
†
Stanford University, Stanford, CA, USA.
243
244 J. Mirkovic & E. Yang
IVM Applications in the Cervix
Cervical cancer, one of the major causes of cancer death in women worldwide particularly in the developing countries, is usually preceded by a
precursor lesion known as cervical squamous intraepithelial lesion (SIL).
SIL typically arises in the cervical transformation zone of the cervix and is
induced by human papilloma virus (HPV) infection. According to the extent
and distribution of epithelial nuclear abnormalities, SIL is divided into two
categories: low-grade SIL (LSIL) and high-grade SIL (HSIL). Alternatively, squamous lesions in the cervix may be termed cervical intraepithelial
neoplasia (CIN). LSIL is equivalent to flat condyloma, exophytic condyloma, and CIN1, while HSIL encompasses CIN2 and CIN3/carcinoma
in situ. LSIL is typically caused by a productive viral infection. They
are associated with multiple low-risk but also high-risk HPV types. These
lesions are usually self-limited and regress spontaneously and thus, typically do not require treatment. HSIL is associated with high-risk HPV types
and, unlike LSIL, has the potential to progress to invasive s quamous cell
carcinoma if left untreated.
The current clinical standard for cervical cancer and its precursor
diagnosis is colposcopy, a procedure that involves visual inspection of the
cervix and biopsy of clinically suspicious tissue, followed by histopathol-
1
The accuracy of colposcopy depends on the colposcopist’s exper-
ogy.
tise. The reported values of sensitivity and specificities of colposcopy vary
widely in the literature.
sensitive (96%) but not specific (48%) for the detection of CIN/cervical
cancer, which may lead to unnecessary biopsies.
invasive to the patient, and specimen processing and diagnosis are timeconsuming, requiring days before a diagnosis can be rendered. In contrast,
optical techniques, which are based on the interaction of light with tissue, have the potential to provide diagnostic information non-invasively, in
real-time, and in an objective and quantitative manner.
A varietyof optical techniques such as spectroscopy and spectroscopic
imaging, optical coherence tomography (OCT), and confocal microscopy
have been developed as tools for cervical neoplasia diagnosis.
2–4
In expert hands, colposcopy was reported to be
3
Sampling of tissue is
Gynecologic Tract 245
Optical spectroscopy and spectroscopic imaging
Spectroscopic techniques, implemented in contact probe manner, as well
as imaging with wide-area surveillance capabilities, have been tested in
various stages of clinical studies of patients with cervical neoplasia, from
pilot to phase III clinical studies.
such as diffuse reflectance spectroscopy (DRS), fluorescence spectroscopy,
and Raman spectroscopy, used either singly or in combination, show the
potential of spectroscopy to guide biopsy during colposcopic examination
to improve the accuracy of disease detection.
Multiple scattering is the dominant light–tissue interaction and is the
basis of DRS. An elastic scattering event redirects an incident light photon
without changing its energy. Elastic scattering arises from both extracellular structures, such as a collagen fiber network, as well as intracellular
structures, such as nuclei, mitochondria, lysosomes, and other organelles.
The properties of the scattered light depend on the density of scattering particles, the particle size, and the ratio of the refractive indices of the particles
relative to the medium. DRS uses the information contained in multiply
scattered light reemitted from tissue to extract the morphological properties of the tissue, as well as its absorption. Physically based models may be
employed to extract parameters from tissue spectra, such as reduced scattering coefficient and absorption coefficient, which are related to the size
and density of the scatterers, total hemoglobin (Hb) concentration, and Hb
oxygen saturation.
Fluorescence spectroscopy evaluates fluorescence emission from tissue, which occurs at a lower energy (longer wavelength) than the absorption energy of the incident light. The main endogenous tissue fluorophores
include the reduced form of nicotinamide adenine dinucleotide(phosphate)
NAD(P)H and flavins, aromatic amino acid tryptophan, the structural protein collagen, and porphyrins. Fluorescence spectra emitted from tissue can
be used to identify fluorophores, monitor their relative concentrations, and
thus identify the progression of disease. Naturally occurring fluorescence
emitted by tissue fluorophores can be significantly distorted by absorption
and scattering events in the turbid media, such as tissue. Fluorescence and
reflectance spectra from the same spot of tissue can be analyzed together
5–19
A variety of spectroscopic techniques,
246 J. Mirkovic & E. Yang
to disentangle the effects of absorption and scattering on native tissue fluorescence.
20
Raman spectroscopy is a technique that measures the frequency shift
and intensity of light inelastically scattered from molecules. The change in
energy of the scattered photon manifests itself as a shift in light frequency,
which corresponds to the transfer of energy to or from the sample’s vibrational or rotational modes. Every molecule has its own distinct set of vibrations, hence its own characteristic frequency shifts. Because each molecule
possesses a unique pattern of Raman shifts, the molecular composition of
the tissue can be determined via Raman spectroscopy. Raman spectroscopy
provides narrow spectral bands, with high information content, that can be
assigned to specific molecular vibrations.
Approaches for signal detection and data processing in cervical tissue
spectroscopy vary and include physically based models (e.g. Monte Carlo
model, the diffusion approximation to the transport equation, and photon
migration theory) and empirical models (e.g. principal component analysis). Physically based models can be used to extract spectroscopic parameters related to cervical tissue properties from tissue spectra and used to
develop diagnostic algorithms.
6,7, 15,21
The advantage of the model-based
spectroscopytechniques is that they provide an understanding of the origins
of spectroscopic contrast between normal tissue and disease, and they diagnose disease based on quantitative information about tissue biochemistry
and morphology.
The sources of contrast in tissue spectra due to the presence of disease
are related to the changes that accompany cervical dysplasia, including loss
of differentiation of the epithelial cells,
by matrix metalloproteinase activity,
22
degradation of stromal collagen
23,24
and angiogenesis.25However,
cervical tissue spectra are affected not only by disease but also by other
conditions, such as age,
menopausal status,
27,28, 30
tions in cervical anatomy.
26–28
time after the application of acetic acid,
body mass index,31parity,31and normal varia-
6,18, 32, 33
For example, spectroscopic differences
29
between normal ectocervix (the outer zone of the cervix lined by stratified
squamous epithelium), endocervix (the inner zone of the cervix characterized by mucus-producing glands lined by columnar cells), and transformation zone (characterized by process of squamous metaplasia, where the
Gynecologic Tract 247
vast majority of SILs occur) have been noted.
6,18, 33
The normal anatomical variations between different areas of the cervix as well as within the
transformation zone must be accounted for when developing spectral diagnostic algorithms. One study demonstrated that the apparent performance
of diagnostic algorithms for identifying HSIL is enhanced when clinically
normal squamous sites a re included, as a result of normal anatomic differences. Both diagnostic parameters and performance metrics depend heavily on how many clinically normal squamous sites are included in the test
33
group.
Since the vast majority of HSILs is found within the transformation
zone and normal ectocervix and endocervix are easily identified by colposcopic examination,
1
spectroscopy must be able to identify HSILs within
the transformation zone in order to improve the accuracy of clinical HSIL
detection.
A decrease in scattering in HSIL sites compared to normal sites has
been observed and attributed to the degradation of the stromal collagen
matrix of the cervix related to both the decomposition of collagen fibers
and a decrease in the concentration of collagen cross-links. Arifler et al.,
34
who used Monte Carlo modeling of cervical tissue, showed that the smaller
stromal-reduced scattering coefficient is the major cause for decreased
reflectance intensity of HSIL compared to normal squamous tissue. In a
13
study of 161 patients, Mirabal et al.
found that there is a gradual decrease
in mean reflectance intensity as the severity of dysplasia increases. Geor-
7
gakoudi et al.
reported a lower reduced scattering coefficient for SILs vs.
biopsied non-SILs. Within the transformation zone, both the fiber-optic
probe-based study and its companion quantitative spectroscopy imaging
system study observed lower values of per-subject normalized reduced
scattering coefficient at 700 nm for HSIL compared to clinically suspicious
non-HSIL.
14,35
Higher hemoglobin concentration of HSIL sites relative to the nonHSIL sites has been observed. Higher hemoglobin concentration in HSIL
sites compared to other tissue types has been noted by Chang et al.
12
tionally, Marin et al.
reported that hemoglobin features of the reflectance
6
Addi-
tissue spectra are more prominent in abnormal tissue compared to normal squamous tissue. Several studies that considered diagnosing HSIL
among clinically suspicious sites, such as Georgakoudi et al.
as Mourant et al.,
15
reported no significant change in the hemoglobin
7
as well
248 J. Mirkovic & E. Yang
concentration between HSIL and non-HSILs. Other studies showed that
per-subject normalized hemoglobin concentration was significantly higher
11,14
Increased NADH fluorescence contribution of SILs compared to nonSILs within the transformation zone has been observed by Georgakoudi
7
et al.
Chang et al.6reported a decreased stromal collagen contribution;
however, this study included clinically normal squamous sites. Decreased
relative contribution of collagen fluorescence for HSIL sites compared to
non-HSIL sites in the transformation zone has also been observed.
Studies by Nordstrom et al. and Huh et al.,
10,16
which utilize 340 nm
11,14
fluorescence, reported no significant differences between HSIL and normal sites in the transformation zone (squamous metaplasia). A study of
18
Ramanujam et al.
reported that 340 nm excitation HSIL sites could not
be differentiated from non-HSIL sites in the transformation zone (CIN 2/3
vs. squamous metaplasia).
Raman spectroscopy has also been extensively evaluated for in vivo
detection of cervical neoplasia.
28,31, 36–44
Mahadevan-Jansen et al. first
showed the potential of Raman spectroscopy to detect cervical dyspla-
41
sia.
With the advancement in fiber-optic technology, Utzinger et al. further studied the utility of Raman spectroscopy to detect cervical precancer
lesions. This study showed increased signal intensity of peaks attributed to
phospholipids and DNA, as the lesions progressed to high-grade dysplasia.
More recently, in a study of 44 patients, Raman spectra were acquired from
normal and dysplastic sites during the colposcopy in the fingerprint (FP,
800–1800 cm
regions.
−1
37
) and high wavenumber (HW, 2800–3700 cm−1) spectral
Differences in Raman spectra of normal and dysplastic cervical
tissues were observed at wavenumbersrelated to proteins, lipids, glycogen,
nucleic acids, and the water in the tissue. The multivariate statistical analysis showed a sensitivity of 85.0% and a specificity of 81.7% for the in vivo
diagnosis of cervical precancerous lesions. In another study of 79 patients,
it was demonstrated that in vivo Raman spectroscopy combined with logistic regression can differentiate HSIL zones from benign conditions with
a similar sensitivity of 89% and a higher specificity of 81% compared to
colposcopy in expert hands.
43
Gynecologic Tract 249
Spectroscopic imaging
The contact-probespectroscopic instrumentscan provide detailedbiochemical and morphological information but only from several 1 mm
2
areas, thus
lacking adequate tissue sampling. In order to screen the entirearea at the risk
of developing cervical cancer, imaging tools have been developed. Several
authors have applied spectroscopy in an imaging mode,
5,10, 45–53
to enable
wide-area diagnosis, as in colposcopy. Using three-color reflectance and
fluorescence spectroscopic imaging, it was demonstrated that CIN emits
at different wavelengths than normal cervical tissues when excited with
45,48
ultraviolet or blue light.
A large multicenter two-arm randomized trial
including 2,299 women evaluated the effectiveness of colposcopy alone
compared to colposcopy and an optical detection system (ODS), a method
based on white light tissue reflectance, fluorescence, and cervical video
5
imaging.
In this study, the use of ODS in conjunction with colposcopy
increased the true positive rate for the detection of CIN2,3 in women with
atypical squamous cells of undetermined significance (ASCUS) and LSIL
referral cytology by 26.5%. The use of ODS did not improve the detection of CIN2,3 in women with HSIL referral cytology. Another study similarly observed that spectroscopic imaging as an adjunct to colposcopy
increased the detection of HSIL by 25% among women with ASC/LSIL
cytology.
10
A quantitative spectroscopic imaging system (QSI), based on the
imaging implementation of quantitative spectroscopy, was developed to
measure tissue properties by using biophysical models of light propagation
to extract information about tissue scatterers, absorbers, and fluorophores
11
from the measured spectra.
QSI wastrained to identifycervical HSIL in 34
patients undergoingthe loop electrosurgical excision procedure (LEEP subjects). QSI’s performance was then prospectively evaluated on the clinically
suspicious biopsy sites from 47 subjects undergoing colposcopy-directed
biopsy. The results showed the per-patient normalized reduced scattering
coefficientat 700 nm (An) and the total hemoglobin concentrationwere significantly different between HSIL and non-HSIL sites in LEEP subjects.
QSI retrospectively distinguishes HSIL from non-HSIL with 89% sensitivity and 83% specificity, and when applied prospectively on the biopsy sites,