Most ovarian cancers are diagnosed at advanced stages due to the lack of efficacious screening techniques. Photoacoustic tomography (PAT) has a potential to image tumor angiogenesis and detect early neovascular changes of the ovary. We have developed a coregistered PAT and ultrasound (US) prototype system for real-time assessment of ovarian masses. Features extracted from PAT and US angular beams, envelopes, and images were input to a logistic classifier and a support vector machine (SVM) classifier to diagnose ovaries as benign or malignant. A total of 25 excised ovaries of 15 patients were studied and the logistic and SVM classifiers achieved sensitivities of 70.4 and 87.7%, and specificities of 95.6 and 97.9%, respectively. Furthermore, the ovaries of two patients were noninvasively imaged using the PAT/US system before surgical excision. By using five significant features and the logistic classifier, 12 out of 14 images (86% sensitivity) from a malignant ovarian mass and all 17 images (100% specificity) from a benign mass were accurately classified; the SVM correctly classified 10 out of 14 malignant images (71% sensitivity) and all 17 benign images (100% specificity). These initial results demonstrate the clinical potential of the PAT/US technique for ovarian cancer diagnosis.
A spatial frequency domain imaging (SFDI) system was developed for characterizing ex vivo human ovarian tissue using wide-field absorption and scattering properties and their spatial heterogeneities. Based on the observed differences between absorption and scattering images of different ovarian tissue groups, six parameters were quantitatively extracted. These are the mean absorption and scattering, spatial heterogeneities of both absorption and scattering maps measured by a standard deviation, and a fitting error of a Gaussian model fitted to normalized mean Radon transform of the absorption and scattering maps. A logistic regression model was used for classification of malignant and normal ovarian tissues. A sensitivity of 95%, specificity of 100%, and area under the curve of 0.98 were obtained using six parameters extracted from the SFDI images. The preliminary results demonstrate the diagnostic potential of the SFDI method for quantitative characterization of wide-field optical properties and the spatial distribution heterogeneity of human ovarian tissue. SFDI could be an extremely robust and valuable tool for evaluation of the ovary and detection of neoplastic changes of ovarian cancer.
In this paper, wavelength selection for multispectral photoacoustic/ultrasound tomography was optimized to obtain accurate images of hemoglobin oxygen saturation (sO2) in vivo. Although wavelengths can be selected by theoretical methods, in practice the accuracy of reconstructed images will be affected by wavelength-specific and system-specific factors such as laser source power and ultrasound transducer sensitivity. By performing photoacoustic spectroscopy of mouse tumor models using 14 different wavelengths between 710 and 840 nm, we were able to identify a wavelength set which most accurately reproduced the results obtained using all 14 wavelengths via selection criteria. In clinical studies, the optimal wavelength set was successfully used to image human ovaries in vivo and noninvasively. Although these results are specific to our co-registered photoacoustic/ultrasound imaging system, the approach we developed can be applied to other functional photoacoustic and optical imaging systems.
We have estimated the micro-mechanical properties of ovarian tissue using phase-sensitive swept source optical coherence tomography. Ovary samples were mechanically excited by periodical vibration of an ultrasound transducer. The displacement and strain of the tissues were calculated during loading. Significant difference in strain was observed between the normal and malignant ovary groups, which indicates much softer and heterogeneous tissue structure for malignant ovaries. The initial results show that the phase sensitive swept source optical coherence elastography (OCE) can be an effective tool for characterization of stiffness and other micro-mechanical properties of normal and malignant ovarian tissue.
Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of “textons”—frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations—is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.
In this paper, human ovarian tissues with malignant and benign features were imaged ex vivo by using an opticalresolution photoacoustic microscopy (OR-PAM) system. Several features were quantitatively extracted from PAM images to describe photoacoustic signal distributions and fluctuations. 106 PAM images from 18 human ovaries were classified by applying those extracted features to a logistic prediction model. 57 images from 9 ovaries were used as a training set to train the logistic model, and 49 images from another 9 ovaries were used to test our prediction model. We assumed that if one image from one malignant ovary was classified as malignant, it is sufficient to classify this ovary as malignant. For the training set, we achieved 100% sensitivity and 83.3% specificity; for testing set, we achieved 100% sensitivity and 66.7% specificity. These preliminary results demonstrate that PAM could be extremely valuable in assisting and guiding surgeons for in vivo evaluation of ovarian tissue.
We characterized ovarian tissue by using polarization-sensitive optical coherence tomography (PS-OCT). Phase retardation changing rate along with optical scattering coefficient and phase retardation were extracted from 33 ex vivo human ovaries from 18 patients. By using phase retardation changing rate as a classifier, we could achieve 71% sensitivity and 100% specificity. Combining those three parameters together, we could achieve 100% sensitivity and 100% specificity. These initial results showed that the quantitative analysis of PS-OCT could be a useful tool to characterize normal and malignant ovarian tissue.
Angle-resolved optical scattering properties of ovarian tissue on different optical coherence tomography (OCT) imaging planes were quantitatively measured by fitting the compounded OCT A-lines into a single scattering model. Higher cross correlation value of angle-resolved scattering coefficients between different OCT imaging planes was found in normal ovaries than was present in malignant ovaries. The mean cross correlation coefficient (MCC) was introduced in this pilot study to characterize and differentiate normal and malignant ovaries. A specificity of 100% and a sensitivity of 100% were achieved by setting MCC threshold at 0.6 in the limited sample population. The collagen properties such as content, structure and directivity were found to be different within OCT imaging penetration depth between normal and malignant ovarian tissue. The homogeneous three-dimensional collagen fiber network observed in the normal ovary effectively explains the stronger cross correlation of angle-resolved scattering properties on different imaging planes while the heterogeneity observed in the malignant ovary suggests a weaker correlation.
In this paper, we present the construction of an optical-resolution photoacoustic microscopy (OR-PAM) system and
studies done on the characterization of human ovarian tissue with malignant and benign features ex vivo. PAM images of
the ovaries showed more detailed blood vessel distributions with much higher resolution compared with conventional
photoacoustic images obtained with array transducers. In all, 29 PAM images (20 from normal ovaries and 9 from
malignant ovaries) were studied. Eight different features were extracted quantitatively from the PAM images, and a
generalized linear model (GLM) was used to classify the ovaries as normal or malignant. By using the GLM, a
specificity of 100% and a sensitivity of 100% were obtained for the training set. These preliminary results demonstrate
the feasibility of our PAM system in mapping microvasculature networks, as well as characterizing the ovarian tissue,
and could be extremely valuable in assisting surgeons for in vivo evaluation of ovarian tissue.
Angle-resolved optical scattering properties of ovarian tissue, on different optical coherence tomography (OCT) imaging planes, were quantitatively measured by fitting the compounded OCT A-lines into a single scattering model. Higher cross correlation value of angle-resolved scattering coefficients between different OCT imaging planes was found in normal ovaries than was present in malignant ovaries. The mean cross correlation coefficient (MCC) was introduced in this pilot study to characterize and differentiate normal, n=6 , and malignant, n=4 , ovaries. A specificity of 100 percent and a sensitivity of 100 percent were achieved by setting MCC threshold at 0.6. Collagen properties, within the OCT imaging penetration depth, were also qualitatively studied in terms of their content, structure and directivity. The homogeneous three-dimensional collagen fiber network, observed in the normal ovary, effectively explains the stronger cross correlation of angle-resolved scattering properties on different imaging planes while the heterogeneity, observed in the malignant ovary, suggests a weaker correlation.
Second-harmonic-generation (SHG) imaging of mouse ovaries ex vivo was used to detect collagen structure changes accompanying ovarian cancer development. Dosing with 4-vinylcyclohexene diepoxide and 7,12-dimethylbenz[a]anthracene resulted in histologically confirmed cases of normal, benign abnormality, dysplasia, and carcinoma. Parameters for each SHG image were calculated using the Fourier transform matrix and gray-level co-occurrence matrix (GLCM). Cancer versus normal and cancer versus all other diagnoses showed the greatest separation using the parameters derived from power in the highest-frequency region and GLCM energy. Mixed effects models showed that these parameters were significantly different between cancer and normal (P<0.008). Images were classified with a support vector machine, using 25% of the data for training and 75% for testing. Utilizing all images with signal greater than the noise level, cancer versus not-cancer specimens were classified with 81.2% sensitivity and 80.0% specificity, and cancer versus normal specimens were classified with 77.8% sensitivity and 79.3% specificity. Utilizing only images with greater than of 75% of the field of view containing signal improved sensitivity and specificity for cancer versus normal to 81.5% and 81.1%. These results suggest that using SHG to visualize collagen structure in ovaries could help with early cancer detection.
In this paper, we report an intraoperative approach by combining optical coherence tomography (OCT) and position
detection to detect and characterize ovarian cancers. A total of 18 ovaries were studied ex vivo. Based on histopathology
result, they were classified into normal and malignant groups, respectively. On average positron count rate of 8.0-fold
higher was found between malignant and normal ovaries. OCT imaging of ovaries revealed many detailed morphologic
features that could be potentially valuable for detecting early malignant changes in ovarian tissue. Optical scattering
coefficients of these ovaries were estimated from OCT A-lines. Normal ovarian tissue showed higher scattering
coefficient than that of malignant ovarian tissue. Using a threshold of 2.00 mm-1 for all ovaries, a sensitivity of 100% and a
specificity of 100% were achieved. This initial data shows our intraoperative probe based on OCT and positron detection
has a great potential for ovarian cancer detection and characterization.
Optical scattering coefficient from ex-vivo unfixed normal and malignant ovarian tissue was quantitatively extracted by
fitting optical coherence tomography (OCT) A-line signals to a single scattering model. 1097 average A-line
measurements at a wavelength of 1310nm were performed at 108 sites obtained from 18 ovaries. The average scattering
coefficient obtained from normal group consisted of 833 measurements from 88 sites was 2.41 mm-1 (±0.59), while the
average coefficient obtained from malignant group consisted of 264 measurements from 20 sites was 1.55 mm-1 (±0.46).
Using a threshold of 2 mm-1 for each ovary, a sensitivity of 100% and a specificity of 100% were achieved. The amount of
collagen within OCT imaging depth was analyzed from the tissue histological section stained with Sirius Red. The average
collagen area fraction (CAF) obtained from normal group was 48.4% (±12.3%), while the average CAF obtained from
malignant group was 11.4% (±4.7%). Statistical significance of the collagen content was found between the two groups
(p < 0.001). The preliminary data demonstrated that quantitative extraction of optical scattering coefficient from OCT
images could be a potential powerful method for ovarian cancer detection and diagnosis.
Optical scattering coefficient from ex vivo unfixed normal and malignant ovarian tissue was quantitatively extracted by fitting optical coherence tomography (OCT) A-line signals to a single scattering model. 1097 average A-line measurements at a wavelength of 1310 nm were performed at 108 sites obtained from 18 ovaries. The average scattering coefficient obtained from the normal tissue group consisted of 833 measurements from 88 sites was 2.41 mm−1 (±0.59), while the average coefficient obtained from the malignant tissue group consisted of 264 measurements from 20 sites was 1.55 mm−1 (±0.46). The malignant ovarian tissue showed significant lower scattering than the normal group (p < 0.001). The amount of collagen within OCT imaging depth was analyzed from the tissue histological section stained with Sirius Red. The average collagen area fraction (CAF) obtained from the normal tissue group was 48.4% (±12.3%), while the average CAF obtained from the malignant tissue group was 11.4% (±4.7%). A statistical significance of the collagen content was found between the two groups (p < 0.001). These results demonstrated that quantitative measurements of optical scattering coefficient from OCT images could be a potential powerful method for ovarian cancer detection.
Our goal is to use optical imaging to detect cancer development on the sub cellular scale. By determining the
microscopic changes that precede ovarian cancer we hope to develop a minimally invasive screening test for high risk
patients. A mouse ovarian cancer model has been developed by treating mice with 4-Vinylcyclohexene Diepoxide to
induce ovarian failure and 7, 12-Dimethylbenz[a]anthracene (DMBA) to induce ovarian cancer. Using optical coherence
tomography (OCT) and multiphoton microscopy (MPM) we have obtained co-registered en face images of sixty-seven
mouse ovaries ex vivo and forty-two ovaries in vivo. Preliminary analysis indicates that OCT and MPM can visualize
ovarian microstructure. During the next year we will be completing a long term survival study using post-menopausal
mice that have been treated with DMBA to induce cancer and imaged in vivo at time points before and after treatment.
Currently, most of the cancers in the ovary are detected when they have already metastasized to other parts of
the body. As a result, ovarian cancer has the highest mortality of all gynecological cancers with a 5-year survival rate of
30% or less [1]. The reason is the lack of reliable symptoms as well as the lack of efficacious screening techniques [2,3].
Thus, there is an urgent need to improve the current diagnostic techniques.
We have investigated the potential role of co-registered photoacoustic and ultrasound imaging in ovarian cancer
detection. In an effort to bring this technique closer to clinical application, we have developed a co-registered ultrasound
and photoacoustic transvaginal probe. A fiber coupling assembly has been developed to deliver the light from around the
transducer for reflection geometry imaging. Co-registered ultrasound and photoacoustic images of swine ovaries through
vagina wall muscle and human ovaries using the aforementioned probe, demonstrate the potential of photoacoustic
imaging to non-invasively detect ovarian cancer in vivo.
Ovarian cancer has the lowest survival rate of the gynecologic cancers with a 5-year survival of about 50% in the United
States. With current screening and diagnostic abilities for ovarian cancers, most of the diagnosed patients are already with
advanced stages and the majority of them will die of this deadly disease. In this paper, we report a multimodal imaging
approach which combines optical coherence tomography (OCT) and positron detection for early ovarian cancer detection.
The dual modality system has the capability of providing both functional and morphological images simultaneously. While
the positron detection provides the metabolism activity of the ovary due to the uptake of radiotracer, the OCT provides the
high resolution (25μm X 25μm X 12μm - longitudinal X lateral X axial in air) structural imaging at 20k A-lines per second.
Total 18 ovaries obtained from 10 patients classified as normal, abnormal and malignant ovarian tissues were characterized
ex vivo. Positron counts of 1.2-fold higher was found between abnormal and normal ovaries and 3~30-fold higher was
found between malignant and normal ovaries. OCT imaging of malignant and abnormal ovaries revealed many detailed
morphologic features that could be potentially valuable for detecting early malignant changes in the ovary.
Early detection of ovarian cancer could greatly increase the likelihood of successful treatment. However, present detection techniques are not very effective, and symptoms are more commonly seen in later stage disease. Amino acids, structural proteins, and enzymatic cofactors have endogenous optical properties influenced by precancerous changes and tumor growth. We present the technical details of an optical spectroscopy system used to quantify these properties. A fiber optic probe excites the surface epithelium (origin of 90% of cases) over 270 to 580 nm and collects fluorescence and reflectance at 300 to 800 nm with four or greater orders of magnitude instrument to background suppression. Up to four sites per ovary are investigated on patients giving consent to oophorectomy and the system's in vivo optical evaluation. Data acquisition is completed within 20 s per site. We illustrate design, selection, and development of the components used in the system. Concerns relating to clinical use, performance, calibration, and quality control are addressed. In the future, spectroscopic data will be compared with histological biopsies from the corresponding tissue sites. If proven effective, this technique can be useful in screening women at high risk of developing ovarian cancer to determine whether oophorectomy is necessary.
Ovarian cancer has a five-year survival rate of only 30%, which represents the highest mortality of all
gynecologic cancers. The reason for that is that the current imaging techniques are not capable of detecting ovarian
cancer early. Therefore, new imaging techniques, like photoacoustic imaging, that can provide functional and molecular
contrasts are needed for improving the specificity of ovarian cancer detection and characterization. Using a coregistered
photoacoustic and ultrasound imaging system we have studied thirty-one human ovaries ex vivo, including
normal and diseased. In order to compare the photoacoustic imaging results from all the ovaries, a new parameter using
the RF data has been derived. The preliminary results show higher optical absorption for abnormal and malignant
ovaries than for normal postmenopausal ones. To estimate the quantitative optical absorption properties of the ovaries,
additional ultrasound-guided diffuse optical tomography images have been acquired. Good agreement between the two
techniques has been observed. These results demonstrate the potential of a co-registered photoacoustic and ultrasound
imaging system for the diagnosis of ovarian cancer.
Ovarian cancer has the highest mortality of all gynecologic cancers, with a five-year survival rate of only 30% or less. Current imaging techniques are limited in sensitivity and specificity in detecting early stage ovarian cancer prior to its widespread metastasis. New imaging techniques that can provide functional and molecular contrasts are needed to reduce the high mortality of this disease. One such promising technique is photoacoustic imaging. We develop a 1280-element coregistered 3-D ultrasound and photoacoustic imaging system based on a 1.75-D acoustic array. Volumetric images over a scan range of 80 deg in azimuth and 20 deg in elevation can be achieved in minutes. The system has been used to image normal porcine ovarian tissue. This is an important step toward better understanding of ovarian cancer optical properties obtained with photoacoustic techniques. To the best of our knowledge, such data are not available in the literature. We present characterization measurements of the system and compare coregistered ultrasound and photoacoustic images of ovarian tissue to histological images. The results show excellent coregistration of ultrasound and photoacoustic images. Strong optical absorption from vasculature, especially highly vascularized corpora lutea and low absorption from follicles, is demonstrated.
Ovarian cancer has the highest mortality of all gynecologic cancers with a five-year
survival rate of only 30%. Because current imaging techniques (ultrasound, CT, MRI, PET) are
not capable of detecting ovarian cancer early, most diagnoses occur in later stages (III/IV). Thus
many women are not correctly diagnosed until the cancer becomes widely metastatic. On the
other hand, while the majority of women with a detectable ultrasound abnormality do not harbor a
cancer, they all undergo unnecessary oophorectomy. Hence, new imaging techniques that can
provide functional and molecular contrasts are needed for improving the specificity of ovarian
cancer detection and characterization. One such technique is photoacoustic imaging, which has
great potential to reveal early tumor angiogenesis through intrinsic optical absorption contrast
from hemoglobin or extrinsic contrast from conjugated agents binding to appropriate molecular
receptors.
To better understand the cancer disease process of ovarian tissue using photoacoustic
imaging, it is necessary to first characterize the properties of normal ovarian tissue. We have
imaged ex-vivo ovarian tissue using a 3D co-registered ultrasound and photoacoustic imaging
system. The system is capable of volumetric imaging by means of electronic focusing. Detecting
and visualizing small features from multiple viewing angles is possible without the need for any
mechanical movement. The results show strong optical absorption from vasculature, especially
highly vascularized corpora lutea, and low absorption from follicles. We will present correlation
of photoacoustic images from animals with histology. Potential application of this technology
would be the noninvasive imaging of the ovaries for screening or diagnostic purposes.
Ovarian cancer is the fourth leading cause of cancer-related death among women. If diagnosed at early stages, 5-year survival rate is 94%, but drops to 68% for regional disease and 29% for distant metastasis; only 19% of cases are diagnosed at early, localized stages. Optical coherence tomography is a recently emerging non-destructive imaging technology, achieving high axial resolutions (10-20 µm) at imaging depths up to 2 mm. Previously, we studied OCT in normal and diseased human ovary ex vivo. Changes in collagen were suggested with several images that correlated with changes in collagen seen in malignancy. Areas of necrosis and blood vessels were also visualized using OCT, indicative of an underlying tissue abnormality. We recently developed a custom side-firing laparoscopic OCT (LOCT) probe fabricated for in vivo imaging. The LOCT probe, consisting of a 38 mm diameter handpiece terminated in a 280 mm long, 4.6 mm diameter tip for insertion into the laparoscopic trocar, is capable of obtaining up to 9.5 mm image lengths at 10 µm axial resolution. In this pilot study, we utilize the LOCT probe to image one or both ovaries of 17 patients undergoing laparotomy or transabdominal endoscopy and oophorectomy to determine if OCT is capable of differentiating normal and neoplastic ovary. We have laparoscopically imaged the ovaries of seventeen patients with no known complications. Initial data evaluation reveals qualitative distinguishability between the features of undiseased post-menopausal ovary and the cystic, non-homogenous appearance of neoplastic ovary such as serous cystadenoma and endometroid adenocarcinoma.
The confocal microendoscope is an instrument for imaging the surface of the human ovary. Images taken with this instrument from normal and diseased tissue show significant differences in cellular distribution. A real-time computer-aided system to facilitate the identification of ovarian cancer is introduced. The cellular-level structure present in ex vivo confocal microendoscope images is modeled as texture. Features are extracted based on first-order statistics, spatial gray-level-dependence matrices, and spatial-frequency content. Selection of the features is performed using stepwise discriminant analysis, forward sequential search, a nonparametric method, principal component analysis, and a heuristic technique that combines the results of these other methods. The selected features are used for classification, and the performance of various machine classifiers is compared by analyzing areas under their receiver operating characteristic curves. The machine classifiers studied included linear discriminant analysis, quadratic discriminant analysis, and the k-nearest-neighbor algorithm. The results suggest it is possible to automatically identify pathology based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of a human observer.
Ovarian cancer is the fourth leading cause of cancer-related death among women in the United States. If diagnosed at an
early stage, the 5-year survival rate is 94%, but drops to 68% for regional disease and 29% for distant metastasis; only
19% of all cases are diagnosed at the early, localized stage. Optical coherence tomography is a recently emerging non-destructive
imaging technology, achieving high axial resolutions (10-20 microns) at imaging depths up to 2 mm.
Previously, we studied OCT imaging in normal and diseased human ovary ex vivo to determine the features OCT is
capable of resolving. Changes in collagen were suggested with several of the images that correlated with changes in
collagen seen in malignancy. Areas of necrosis and blood vessels were also visualized using OCT, indicative of an
underlying tissue abnormality. We recently developed a custom side-firing laparoscopic OCT (LOCT) probe fabricated
specifically for in vivo laparoscopic imaging. The LOCT probe consists of a 38 mm diameter handpiece terminated in an
280 mm long, 4.6 mm diameter tip for insertion into the laparoscopic trocar and is capable of obtaining up to 9.5 mm
image lengths at 10 micron axial resolution. In this study, we utilize the LOCT probe to image one or both ovaries of 20
patients undergoing laparotomy or transabdominal endoscopy and oophorectomy to determine if OCT is capable of
identifying and/or differentiating normal and neoplastic ovary. To date, we have laparoscopically imaged the ovaries of
ten patients successfully with no known complications.
A mobile confocal microendoscope for use in a clinical setting has been developed. This system
employs an endoscope consisting of a custom designed objective lens with a fiber optic imaging bundle to
collect in-vivo images of patients. Some highlights and features of this mobile system include frame rates
of up to 30 frames per second, an automated focus mechanism, automated dye delivery, clinician control,
and the ability to be used in an area where there is a single 110V outlet. All optics are self-contained and
the entire enclosure and catheter can be moved between surgical suites, sterilized and brought online in
under 15 minutes. At this time, all data have been collected with a 488 nm laser, but the system is able to
have a second laser line added to provide additional imaging capability. Preliminary in vivo results of
images from the ovaries using topical fluorescein as a contrast agent are shown. Future plans for the system include use of acridine orange (AO) or SYTO-16 as a nucleic acid stain.
Ovarian cancer is the fifth leading cause of cancer death in women, in part because of the limited knowledge about early stage disease. We develop a novel rat model of ovarian cancer and perform a pilot study to examine the harvested ovaries with complementary optical imaging modalities. Rats are exposed to repeated daily dosing (20 days) with 4-vinylcyclohexene diepoxide (VCD) to cause early ovarian failure (model for postmenopause), and ovaries are directly exposed to 7,12-dimethylbenz(a)anthracene (DMBA) to cause abnormal ovarian proliferation and neoplasia. Harvested ovaries are examined with optical coherence tomography (OCT) and light-induced fluorescence (LIF) at one, three, and five months post-DMBA treatment. VCD causes complete ovarian follicle depletion within 8 months after onset of dosing. DMBA induces abnormal size, cysts, and neoplastic changes. OCT successfully visualizes normal and abnormal structures (e.g., cysts, bursa, follicular remnant degeneration) and the LIF spectra show statistically significant changes in the ratio of average emission intensity at 390:450 nm between VCD-treated ovaries and both normal cycling and neoplastic DMBA-treated ovaries. Overall, this pilot study demonstrates the feasibility of both the novel animal model for ovarian cancer and the ability of optical imaging techniques to visualize ovarian function and health.
In order to understand the distribution of endogenous fluorescence in the ovary, ovarian biopsies were maintained with a viable tissue imaging system and characterized with multiphoton imaging. It was imperative to maintain a stable in vitro environment so that tissue images could provide accurate correlative data for in vivo spectroscopic measurements. Evaluating tissue viability in real time poses a difficult task given that viability assays are tailored for cell culture. The focus of this study was to design a robust in vitro imaging chamber for assessment of ovarian autofluorescence and simple, reliable viability assays for tissue status monitoring.
Non-invasive monitoring of cellular metabolism offers promising insights into areas ranging from biomarkers for drug activity to cancer diagnosis. Fluorescence spectroscopy can be utilized in order to exploit endogenous fluorophores, typically metabolic co-factors nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD), and estimate the redox status of the sample. Fluorescence spectroscopy was applied to follow metabolic changes in epithelial ovarian cells as well as bladder epithelial cancer cells during treatment with a chemopreventive drug that initiates cellular quiescence. Fluorescence signals consistent with NADH, FAD, and tryptophan were measured to monitor cellular activity, redox status, and protein content. Cells were treated with varying concentrations of N-4-(hydroxyphenyl) retinamide (4-HPR) and measured in a stable environment with a sensitive fluorescence spectrometer. A subset of measurements was completed on a low concentration of cells to demonstrate feasibility for medical application such as in bladder or ovary washes. Results suggest that all of the cells responded with similar dose dependence but started at different estimated redox ratio baseline levels correlating with cell cycle, growth inhibition, and apoptosis assays. NADH and tryptophan related fluorescence changed significantly while FAD related fluorescence remained unaltered. Fluorescence data collected from approximately 1000 - 2000 cells, comparable to a bladder or ovary wash, was measurable and useful for future experiments. This study suggests that future intrinsic biomarker measurements may need to be most sensitive to changes in NADH and tryptophan related fluorescence while using FAD related fluorescence to help estimate the baseline redox ratio and predict response to chemopreventive agents.
The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.
Epithelial ovarian cancer has the highest mortality rate among the gynecologic cancers. Early detection would significantly improve survival and quality of life of women at increased risk to develop ovarian cancer. We have constructed a device to investigate endogenous signals of the ovarian tissue surface in the UV C to visible range and describe our initial investigation of the use of optical spectroscopy to characterize the condition of the ovary. We have acquired data from more than 33 patients. A table top spectroscopy system was used to collect endogenous fluorescence with a fiberoptic probe that is compatible with endoscopic techniques. Samples were broken into five groups: Normal-Low Risk (for developing ovarian cancer) Normal-High Risk, Benign, and Cancer. Rigorous statistical analysis was applied to the data using variance tests for direct intensity versus diagnostic group comparisons and principal component analysis (PCA) to study the variance of the whole data set. We conclude that the diagnostically most useful excitation wavelengths are located in the UV. Furthermore, our results indicate that UV B and C are most useful. A safety analysis indicates that UV-C imaging can be conducted at exposure levels below safety thresholds. We found that fluorescence excited in the UV-C and UV-B range increases from benign to normal to cancerous tissues. This is in contrast to the emission created with UV-A excitation which decreased in the same order. We hypothesize that an increase of protein production and a decrease of fluorescence contributions of the extracellular matrix could explain this behavior. Variance analysis also identified fluctuation of fluorescence at 320/380 which is associated with collagen cross link residues. Small differences were observed between the group at high risk and normal risk for ovarian cancer. High risk samples deviated towards the cancer group and low risk samples towards benign group.
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