Elastic Scattering Spectroscopy Research Articles

Optical Imaging in Human Lymph Node Specimens for Detecting Breast Cancer Metastases: A Review.

Assessment of regional lymph node status in breast cancer is of important staging and prognostic value. Even though formal histological examination is the currently accepted standard of care, optical imaging techniques have shown promising results in disease diagnosis. In the present article, we review six spectroscopic techniques and focus on their use as alternative tools for breast cancer lymph node assessment. Elastic scattering spectroscopy (ESS) seems to offer a simple, cost-effective, and reproducible method for intraoperative diagnosis of breast cancer lymph node metastasis. Optical coherence tomography (OCT) provides high-resolution tissue scanning, along with a short data acquisition time. However, it is relatively costly and experimentally complex. Raman spectroscopy proves to be a highly accurate method for the identification of malignant axillary lymph nodes, and it has been further validated in the setting of head and neck cancers. Still, it remains time-consuming. Near-infrared fluorescence imaging (NIRF) and diffuse reflectance spectroscopy (DFS) are related to significant advantages, such as deep tissue penetration and efficiency. Fourier-transform infrared spectroscopy (FTIR) is a promising method but has significant drawbacks. Nonetheless, only anecdotal reports exist on their clinical use for cancerous lymph node detection. Our results indicate that optical imaging methods can create informative and rapid tools to effectively guide surgical decision-making.

Multicenter prospective blinded melanoma detection study with a handheld elastic scattering spectroscopy device

BackgroundThe elastic scattering spectroscopy (ESS) device (DermaSensor Inc., Miami, FL) is a non-invasive, painless, adjunctive tool for skin cancer detection. ObjectivesTo investigate the performance of the ESS device in the detection of melanoma. MethodsA prospective, investigator-blinded, multicenter study was conducted at 8 United States (US) and 2 Australian sites. All eligible skin lesions were clinically concerning for melanoma, examined with the ESS device, subsequently biopsied according to dermatologists’ standard of care, and evaluated with histopathology. A total of 311 participants with 440 lesions were enrolled, including 44 melanomas (63.6% in situ and 36.4% invasive) and 44 severely dysplastic nevi. ResultsThe observed sensitivity of the ESS device for melanoma detection was 95.5% (95% CI, 84.5%-98.8%, 42 of 44 melanomas), and the observed specificity was 32.5% (95% CI, 27.2%-38.3%). The positive and negative predictive values were 16.0% and 98.1%, respectively. LimitationsThe device was tested in a high-risk population with lesions selected for biopsy based on clinical and dermoscopic assessments of board-certified dermatologists. Most enrolled lesions were pigmented. ConclusionThe ESS device’s high sensitivity and NPV for the detection of melanoma suggest the device may be a useful adjunctive, point-of-care tool for melanoma detection.

Use of an elastic-scattering spectroscopy and artificial intelligence device in the assessment of lesions suggestive of skin cancer: A comparative effectiveness study

Skin cancer is the most common form of cancer worldwide. As artificial intelligence (AI) expands its scope within dermatology, leveraging technology may aid skin cancer detection. To assess the safety and effectiveness of an elastic-scattering spectroscopy (ESS) device in evaluating lesions suggestive of skin cancer. This prospective, multicenter clinical validation study was conducted at 4 US investigational sites. Patients with skin lesions suggestive of melanoma and nonmelanoma skin cancers were clinically assessed by expert dermatologists and evaluated by a device using AI algorithms comparing current ESS lesion readings with training data sets. Statistical analyses included sensitivity, specificity, AUROC, negative predictive value (NPV), and positive predictive value (PPV). Overall device sensitivity was 97.04%, with subgroup sensitivity of 96.67% for melanoma, 97.22% for basal cell carcinoma, and 97.01% for squamous cell carcinoma. No statistically significant difference was found between the device and dermatologist performance (P=.8203). Overall specificity of the device was 26.22%. Overall NPV of the device was 89.58% and PPV was 57.54%. The ESS device demonstrated high sensitivity in detecting skin cancer. Use of this device may assist primary care clinicians in assessing suspicious lesions, potentially reducing skin cancer morbidity and mortality through expedited and enhanced detection and intervention.

42036 The Effectiveness of a Handheld Elastic Scattering Spectroscopy (ESS) Device in Detecting Melanoma and Non-Melanoma Skin Cancers

42036 The Effectiveness of a Handheld Elastic Scattering Spectroscopy (ESS) Device in Detecting Melanoma and Non-Melanoma Skin Cancers

Clinical Utility of an AI-powered, Handheld Elastic Scattering Spectroscopy Device on the Diagnosis and Management of Skin Cancer by Primary Care Physicians.

Patients with lesions suspicious for skin cancer often present to primary care physicians (PCPs), who may have limited training in skin cancer diagnosis. To measure the impact of an adjunctive handheld device for PCPs that employs elastic scattering spectroscopy (ESS) on the diagnosis and management of skin cancer. Fifty-seven PCPs evaluated 50 clinical images of skin lesions (25 malignant and 25 benign), first without and then with knowledge of the handheld ESS device output, and in each case indicated if a lesion was likely to be benign or malignant. The diagnostic sensitivity of the PCPs with and without the use of the ESS device was 88% (95% CI, 84%-92%) and 67% (95% CI, 62%-72%), respectively (P < .0001). In contrast, no significant difference was observed in the diagnostic specificity. The management sensitivity of the physicians with and without the use of the ESS device was 94% (95% CI, 91%-96%) and 81% (95% CI, 77%-85%), respectively (P = .0009). Similarly, no significant difference was observed in the management specificity. The use of the ESS device may have the potential to help improve skin cancer diagnosis and confidence in management decision-making in a primary care setting.

The Clinical Utility of a Handheld Elastic Scattering Spectroscopy Tool and Machine Learning in the Diagnosis and Referral Management of Skin Cancer by Primary Care Physicians

Background Elastic scattering spectroscopy (ESS) is a noninvasive optical biopsy technique that can distinguish between normal and abnormal tissue in vivo. The handheld device measures ESS spectra of skin lesions and classifies lesions with an output of “Investigate Further” or “Monitor.” The algorithm was trained and validated with over 11,000 spectral scans from over 3500 skin lesions. The device performance was also evaluated in an associated clinical study. Objective The aim of this paper was to establish whether the use of a handheld ESS tool can improve the detection of skin malignancies by evaluating clinical performance while emulating a real-world telemedicine clinical care setting. Methods The associated clinical study examined an independent test set of 332 lesions in a prospective multicenter study that compared algorithm performance to biopsy results for diagnosing malignant lesions. A total of 50 cases were randomly selected from the study data base (25 malignant and 25 benign lesions). Device performance on these lesions had a 96% sensitivity. High-resolution digital images and the patient’s clinical information including prior skin cancer history, risk factors, and physical examination results were available for evaluation. A total of 57 primary care physicians participated in this study in 2 phases, the first phase with their standard-of-care diagnostic and the second phase regarding their evaluation with the device output. The physicians were educated on the ESS device before evaluating the cases in a random order. Case evaluation included the physician reporting their diagnosis, management decision, and confidence level without the device output in the first phase and with the device output in the second phase. The results were evaluated for sensitivity and specificity with confidence intervals. Results The diagnostic sensitivity of the readers without and with the use of the handheld ESS device increased significantly from 67% to 88% (P&lt;.001). There was no significant difference in specificity at 40% and 53% (P=.05). The management sensitivity of the readers increased significantly with and without the use of the device, which, respectively, was 94% (91%-96%) and 81% (77%-85%) (P&lt;.001), suggesting that the use of the device may reduce false negatives by 68%. Specificity was comparable for management decisions (P=.36) at 31% compared to 36% without the device. Conclusions The use of the handheld ESS device significantly improved diagnostic and management sensitivity over standard-of-care, with comparable specificity. While telemedicine has shown promise in many fields, studies have shown that in-person skin evaluation is superior to telemedicine evaluations; however, integration with this type of tool has the potential to improve early detection.

The Safety and Effectiveness of Elastic Scattering Spectroscopy and Machine Learning in the Evaluation of Skin Lesions for Cancer

Background Elastic scattering spectroscopy (ESS) is an optical biopsy technique that can distinguish between a normal and abnormal tissue in vivo without the need to remove it. The handheld device measures ESS spectra of skin lesions and classifies lesions as either malignant or benign with an output of “Investigate Further” or “Monitor,” respectively, with positive results accompanied by a spectral score output from 1 to 10, indicating how similar the lesion is to the malignant lesions the device was trained on. The algorithm was trained and validated with over 11,000 spectral scans from over 3500 skin lesions. Objective The purpose of this study was to evaluate the safety and effectiveness of the handheld ESS device in detecting the most common types of skin cancer. Methods A prospective, single-arm, investigator-blinded, multicenter study conducted at 4 investigational sites in the United States was performed. Patients who presented with skin lesions suggestive of melanoma, basal cell carcinoma, squamous cell carcinoma, and other highly atypical lesions were evaluated with the handheld ESS device. A validation performance analysis was performed with 553 lesions from 350 subjects with algorithm version 2.0. An independent test set of 281 lesions was selected and used to evaluate device performance in the detection of melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). Statistical analyses included overall effectiveness analyses for sensitivity and specificity as well as subgroup analyses for lesion diagnoses. Results The overall sensitivity of the device was 92.3% (95% CI: 87.1 to 95.5%). The sensitivity for subgroups of lesions was 95% (95% CI 75.1% to 99.9%) for melanomas, 94.4% (95% CI 86.3% to 98.4%) for BCCs, and 92.5% (95% CI 83.4% to 97.5%) for SCCs. The overall device specificity was 36.6% (95% CI 29.3% to 44.6%). There was no statistically significant difference between the dermatologist performance and the ESS device (P=.2520). The specificity of the device was highest for benign melanocytic nevi (62.5%) and seborrheic keratoses (78.2%). The overall positive predictive value (PPV) was 59.8%, and the negative predictive value (NPV) was 81.9% with the study’s malignancy prevalence rate of 51%. For a prevalence rate of 5%, the PPV was estimated to be 7.1%, and the NPV was estimated to be 98.9%. For a prevalence rate of 7%, the PPV was estimated to be 9.8%, and the NPV was estimated to be 98.4%. For a prevalence rate of 15%, the PPV was estimated to be 20.3%, and the NPV was 96.4%. Conclusions The handheld ESS device has a high sensitivity for the detection of melanoma, BCC, and SCC. Coupled with clinical exam findings, this device can aid physicians in detecting a variety of skin malignancies. The device output can aid teledermatology evaluations by helping frontline providers determine which lesions to share for teledermatologist evaluation as well as potentially benefitting teledermatologists’ virtual evaluation, especially in instances of suboptimal photo quality. Acknowledgments This study was sponsored by Dermasensor Inc. Conflicts of Interest None declared.

Toward optical spectroscopy-guided lung biopsy: Demonstration of tissue-type classification.

The diagnostic yield of standard tissue-sampling modalities of suspected lung cancers, whether by bronchoscopy or interventional radiology, can be nonoptimal, varying with the size and location of lesions. What is needed is an insitu sensor, integrated in the biopsy tool, to objectively distinguish among tissue types in real time, not to replace biopsy with an optical diagnostic, but to verify that the sampling tool is properly located within the target lesion. We investigated the feasibility of elastic scattering spectroscopy (ESS), coupled with machine learning, to distinguish lung lesions from the various nearby tissue types, in a study with freshly-excised lung tissues from surgical resections. Optical spectra were recorded with an ESS fiberoptic probe in different areas of the resected pulmonary tissues, including benign-margin tissue sites as well as the periphery and core of the lesion. An artificial-intelligence model was used to analyze, retrospectively, 2032 measurements from excised tissues of 35 patients. With high accuracy, ESS was able to distinguish alveolar tissue from bronchi, alveolar tissue from lesions, and bronchi from lesions. This ex vivo study indicates promise for ESS fiberoptic probes to be integrated with surgical intervention tools, to improve reliability of pulmonary lesion targeting.

Artificial Intelligence-Based Assessment of Colorectal Polyp Histology by Elastic-Scattering Spectroscopy.

Colonoscopic screening and surveillance for colorectal cancer could be made safer and more efficient if endoscopists could predict histology without the need to biopsy and perform histopathology on every polyp. Elastic-scattering spectroscopy (ESS), using fiberoptic probes integrated into standard biopsy tools, can assess, both in vivo and in real time, the scattering and absorption properties of tissue related to its underlying pathology. The objective of this study was to evaluate prospectively the potential of ESS to predict polyp pathology accurately. We obtained ESS measurements from patients undergoing screening/surveillance colonoscopy using an ESS fiberoptic probe integrated into biopsy forceps. The integrated forceps were used for tissue acquisition, following current standards of care, and optical measurement. All measurements were correlated to the index pathology. A machine learning model was then applied to measurements from 367 polyps in 169 patients to prospectively evaluate its predictive performance. The model achieved sensitivity of 0.92, specificity of 0.87, negative predictive value (NPV) of 0.87, and high-confidence rate (HCR) of 0.84 for distinguishing 220 neoplastic polyps from 147 non-neoplastic polyps of all sizes. Among 138 neoplastic and 131 non-neoplastic polyps ≤ 5mm, the model achieved sensitivity of 0.91, specificity of 0.88, NPV of 0.89, and HCR of 0.83. Results show that ESS is a viable endoscopic platform for real-time polyp histology, particularly for polyps ≤ 5mm. ESS is a simple, low-cost, clinically friendly, optical biopsy modality that, when interfaced with minimally obtrusive endoscopic tools, offers an attractive platform for in situ polyp assessment.

Elastic scattering spectroscopy for monitoring skin cancer transformation and therapy in the near infrared window.

There is a pressing need for monitoring cancerous tissue response to laser therapy. In this work, we evaluate the viability of elastic scattering spectroscopy(ESS) to monitor malignant transformations and effects of laser therapy of induced skin cancer in a hamster model. Skin tumors were induced in 35 mice, half of which were irradiated with 980 nm laser diode. Physiological and morphological transformations in the tumor were monitored over a period of 36 weeks using elastic scattering spectroscopy, in the near infrared window. Analytical model for light scattering was used to derive scattering optical properties for both transformed tissue and laser-treated cancer. The tissue scattering over the wavelength range (700-950 nm) decreased remarkably as the carcinogen-induced tissue transformed towards higher stages. Conversely, reduced scattering coefficient noticeably increased with increasing the number of laser irradiation sessions for the treated tumors. The relative changes in elastic scattering signal for transformed tissue were significantly different (p < .05). Elastic scattering signal intensity for laser-treated tissue was also significantly different (p < .05). Reduced scattering coefficient of treated tissue exhibited nearly 80% recovery of its normal skin value at the end of the experiment, and the treatment outcome could be improved by adjusting the number of sessions, which we can predict through spectroscopic optical feedback. This study demonstrates that ESS can quantitatively provide functional information that closely corresponds to the degree of pathologic transformation. ESS may well be a viable technique to optimize systemic melanoma and non-melanoma skin cancer treatment based on noninvasive tumor response.

Optical Spectroscopy as a Method for Skin Cancer Risk Assessment.

Skin cancer is the most prevalent cancer, and its assessment remains a challenge for physicians. This study reports the application of an optical sensing method, elastic scattering spectroscopy (ESS), coupled with a classifier that was developed with machine learning, to assist in the discrimination of skin lesions that are concerning for malignancy. The method requires no special skin preparation, is non-invasive, easy to administer with minimal training, and allows rapid lesion classification. This novel approach was tested for all common forms of skin cancer. ESS spectra from a total of 1307 lesions were analyzedin a multi-center, non-randomized clinical trial. The classification algorithm was developed on a 950-lesion training dataset, and its diagnostic performance was evaluated against a 357-lesion testing dataset that was independent of the training dataset. The observed sensitivity was 100% (14/14) for melanoma and 94% (105/112) for non-melanoma skin cancer. The overall observed specificity was 36% (84/231). ESS has potential, as an adjunctive assessment tool, to assist physicians to differentiate between common benign and malignant skin lesions.

Towards minimally-invasive, quantitative assessment of chronic kidney disease using optical spectroscopy

The universal pathologic features implicated in the progression of chronic kidney disease (CKD) are interstitial fibrosis and tubular atrophy (IFTA). Current methods of estimating IFTA are slow, labor-intensive and fraught with variability and sampling error, and are not quantitative. As such, there is pressing clinical need for a less-invasive and faster method that can quantitatively assess the degree of IFTA. We propose a minimally-invasive optical method to assess the macro-architecture of kidney tissue, as an objective, quantitative assessment of IFTA, as an indicator of the degree of kidney disease. The method of elastic-scattering spectroscopy (ESS) measures backscattered light over the spectral range 320–900 nm and is highly sensitive to micromorphological changes in tissues. Using two discrete mouse models of CKD, we observed spectral trends of increased scattering intensity in the near-UV to short-visible region (350–450 nm), relative to longer wavelengths, for fibrotic kidneys compared to normal kidney, with a quasi-linear correlation between the ESS changes and the histopathology-determined degree of IFTA. These results suggest the potential of ESS as an objective, quantitative and faster assessment of IFTA for the management of CKD patients and in the allocation of organs for kidney transplantation.

Elastic scattering spectroscopy for early detection of breast cancer: partially supervised Bayesian image classification of scanned sentinel lymph nodes.

Sentinel lymph node biopsy is a standard diagnosis procedure to determine whether breast cancer has spread to the lymph glands in the armpit (the axillary nodes). The metastatic status of the sentinel node (the first node in the axillary chain that drains the affected breast) is the determining factor in surgery between conservative lumpectomy and more radical mastectomy including axillary node excision. The traditional assessment of the node requires sample preparation and pathologist interpretation. An automated elastic scattering spectroscopy (ESS) scanning device was constructed to take measurements from the entire cut surface of the excised sentinel node and to produce ESS images for cancer diagnosis. Here, we report on a partially supervised image classification scheme employing a Bayesian multivariate, finite mixture model with a Markov random field (MRF) spatial prior. A reduced dimensional space was applied to represent the scanning data of the node by a statistical image, in which normal, metastatic, and nonnodal-tissue pixels are identified. Our results show that our model enables rapid imaging of lymph nodes. It can be used to recognize nonnodal areas automatically at the same time as diagnosing sentinel node metastases with sensitivity and specificity of 85% and 94%, respectively. ESS images can help surgeons by providing a reliable and rapid intraoperative determination of sentinel nodal metastases in breast cancer.

Detection of Melanoma Skin Cancer by Elastic Scattering Spectra: A Proposed Classification Method

Introduction: There is a strong need for developing clinical technologies and instruments for prompt tissue assessment in a variety of oncological applications as smart methods. Elastic scattering spectroscopy (ESS) is a real-time, noninvasive, point-measurement, optical diagnostic technique for malignancy detection through changes at cellular and subcellular levels, especially important in early diagnosis of invasive skin cancer, melanoma. In fact, this preliminary study was conducted to provide a classification method for analyzing the ESS spectra. Elastic scattering spectra related to the normal skin and melanoma lesions, which were already confirmed pathologically, were provided as input from an ESS database. Materials and Methods: A program was developed in MATLAB based on singular value decomposition and K-means algorithm for classification. Results: Accuracy and sensitivity of the proposed classifying method for normal and melanoma spectra were 87.5% and 80%, respectively. Conclusion: This method can be helpful for classification of melanoma and normal spectra. However, a large body of data and modifications are required to achieve better sensitivity for clinical applications.

Sizing of single evaporating droplet with Near-Forward Elastic Scattering Spectroscopy

We have developed an optical setup and related numerical models to study evolution of single evaporating micro-droplets by analysis of their spectral properties. Our approach combines the advantages of the electrodynamic trapping with the broadband spectral analysis with the supercontinuum laser illumination. The elastically scattered light within the spectral range of 500–900 nm is observed by a spectrometer placed at the near-forward scattering angles between 4.3 ° and 16.2 ° and compared with the numerically generated lookup table of the broadband Mie scattering. Our solution has been successfully applied to infer the size evolution of the evaporating droplets of pure liquids (diethylene and ethylene glycol) and suspensions of nanoparticles (silica and gold nanoparticles in diethylene glycol), with maximal accuracy of ± 25 nm. The obtained results have been compared with the previously developed sizing techniques: (i) based on the analysis of the Mie scattering images - the Mie Scattering Lookup Table Method and (ii) the droplet weighting. Our approach provides possibility to handle levitating objects with much larger size range (radius from 0.5 µm to 30 µm) than with the use of optical tweezers (typically radius below 8 µm) and analyse them with much wider spectral range than with commonly used LED sources.

Elastic Scattering Spectroscopy (ESS): an Instrument-Concept for Dynamics of Complex (Bio-) Systems From Elastic Neutron Scattering.

A new type of neutron-scattering spectroscopy is presented that is designed specifically to measure dynamics in bio-systems that are difficult to obtain in any other way. The temporal information is largely model-free and is analogous to relaxation processes measured with dielectric spectroscopy, but provides additional spacial and geometric aspects of the underlying dynamics. Numerical simulations of the basic instrument design show the neutron beam can be highly focussed, giving efficiency gains that enable the use of small samples. Although we concentrate on continuous neutron sources, the extension to pulsed neutron sources is proposed, both requiring minimal data-treatment and being broadly analogous with dielectric spectroscopy, they will open the study of dynamics to new areas of biophysics.

Abstract 4294: Addressing the limitations of thyroid biopsies: Using elastic scattering spectroscopy to improve the assessment of indeterminate nodules

Abstract Thyroid cancer is the most common endocrine tumor. The gold standard, fine-needle aspiration biopsy, yields 10-25% indeterminate results necessitating diagnostic surgery. Using the real-time imaging technique of elastic scattering spectroscopy (ESS), a pair of fiber optics are inserted through the lumen of a biopsy needle and placed in contact with the thyroid nodule moments before cell collection occurs. Our research focuses on utilizing this optical-biopsy technique to measure tissue in vivo with broadband light during biopsy. In this study we demonstrate the potential our novel ESS-integrated optical biopsy syringe can have on cancer diagnostics. Spectra from 148 patients were collected. Additional time during biopsy to perform ESS measurements was less than 20 seconds. Cytology results for enrolled patients were as follows: 37 indeterminate, 6 insufficient, 5 malignant and 100 benign. Correlating ESS measurements with cytology, we identified changes in spectra when fiber optics were placed in contact with malignant versus benign tissue. From our enrolled benign and malignant patients, we trained an algorithm to diagnose indeterminate nodules based off of ESS spectra and compared to pathology. Preliminary analysis of spectra show ESS has a NPV of 0.99, a sensitivity of 0.92 and a specificity of 0.85. This data suggests that elastic scattering spectroscopy may improve the reliability, speed, and cost of cancer diagnostics. Citation Format: Jennifer E. Rosen, Nicholas J. Giordano, Eladio Rodriguez-Diaz, Ousama M. A'Amar, Irving J. Bigio, Stephanie L. Lee. Addressing the limitations of thyroid biopsies: Using elastic scattering spectroscopy to improve the assessment of indeterminate nodules. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4294. doi:10.1158/1538-7445.AM2014-4294

Endoscopic histological assessment of colonic polyps by using elastic scattering spectroscopy

Elastic-scattering spectroscopy (ESS) can assess invivo and in real-time the scattering and absorption properties of tissue related to underlying pathologies. To evaluate the potential of ESS for differentiating neoplastic from non-neoplastic polyps during colonoscopy. Pilot study, retrospective data analysis. Academic practice. A total of 83 patients undergoing screening/surveillance colonoscopy. ESS spectra of 218 polyps (133 non-neoplastic, 85 neoplastic) were acquired during colonoscopy. Spectral data were correlated with the classification of biopsy samples by 3 GI pathologists. High-dimensional methods were used to design diagnostic algorithms. Diagnostic performance of ESS. Analysis of spectra from polyps of all sizes (N= 218) resulted in a sensitivity of 91.5%, specificity of 92.2%, and accuracy of 91.9% with a high-confidence rate of 90.4%. Restricting analysis to polyps smaller than 1 cm (n= 179) resulted in a sensitivity of 87.0%, specificity of 92.1%, and accuracy of 90.6% with a high-confidence rate of 89.3%. Analysis of polyps 5mm or smaller (n= 157) resulted in a sensitivity of 86.8%, specificity of 91.2%, and accuracy of 90.1% with a high-confidence rate of 89.8%. Sample size, retrospective validation used to obtain performance estimates. Results indicate that ESS permits accurate, real-time classification of polyps as neoplastic or non-neoplastic. ESS is a simple, low cost, clinically robust method with minimal impact on procedure flow, especially when integrated into standard endoscopic biopsy tools. Performance on polyps 5mm or smaller indicates that ESS may, in theory, achieve Preservation and Incorporation of Valuable Endoscopic Innovations performance thresholds. ESS may one day prove to be a useful tool used in endoscopic screening and surveillance of colorectal cancer.

Elastic scattering spectroscopy as an optical marker of inflammatory bowel disease activity and subtypes.

In 10% to 15% of individuals, inflammatory bowel disease (IBD) is difficult to classify as ulcerative colitis (UC) or Crohn's disease (CD). Previous work has demonstrated that probe-based elastic scattering spectroscopy (ESS) can produce spectra, informed by parameters like tissue ultrastructure and hemoglobin content, capable of differentiating pathologies. This study investigates whether ESS is an in vivo optical biomarker for the presence, activity, and type of IBD in the colon. Pilot study, a retrospective data analysis. ESS spectra of endoscopically normal and inflamed colon were obtained from 48 patients with IBD and 46 non-IBD controls. Measurements from patients with IBD were categorized as CD or UC based on clinical diagnosis. Spectra were analyzed using high-dimensional methods. Leave-one-patient-out cross-validation was used to obtain diagnostic performance estimates. Patients with IBD were distinguishable from non-IBD controls with a sensitivity of 0.93 and specificity of 0.91 based on readings from endoscopically normal mucosa, and 0.94 and 0.93 from inflamed mucosa. In patients with IBD, histologically normal and inflamed colon were distinguishable with per-class accuracies of 0.83 and 0.89, respectively; histologically normal from inactive inflammation with accuracies of 0.73 and 0.89, respectively; and inactive from active colitis with accuracies of 0.87 and 0.84, respectively. The diagnosis of CD versus UC was made with per-class accuracies of 0.92 and 0.87 in normal and 0.87 and 0.85 in inflamed mucosa, respectively. ESS, a simple, low-cost clinically friendly optical biopsy modality, has the potential to enhance the endoscopic assessment of IBD and its activity in real time and may help to distinguish CD from UC.

35 Does Elastic-Scattering Spectroscopy Meet PIVI Thresholds for In Vivo Identification of Colorectal Neoplasia? A Prospective Data Analysis Study

35 Does Elastic-Scattering Spectroscopy Meet PIVI Thresholds for In Vivo Identification of Colorectal Neoplasia? A Prospective Data Analysis Study