Diffuse reflection spectroscopy at the fingertip:design and performance of a compact side-firing probe for tissue discrimination during colorectal cancer surgery

Optical technologies are widely used for tissue sensing purposes. However, maneuvering conventional probe designs with flat-tipped fibers in narrow spaces can be challenging, for instance during pelvic colorectal cancer surgery. In this study, a compact side-firing fiber probe was developed for tissue discrimination during colorectal cancer surgery using diffuse reflectance spectroscopy. The optical behavior was compared to flat-tipped fibers using both Monte Carlo simulations and experimental phantom measurements. The tissue classification performance was examined using freshly excised colorectal cancer specimens. Using the developed probe and classification algorithm, an accuracy of 0.92 was achieved for discriminating tumor tissue from healthy tissue

Are patients' judgments of health status really different from the general population?

Background: Many studies have found discrepancies in valuations for health states between the general population (healthy people) and people who actually experience illness (patients). Such differences may be explained by referring to various cognitive mechanisms. However, more likely most of these observed differences may be attributable to the methods used to measure these health states. We explored in an experimental setting whether such discrepancies in values for health states exist. It was hypothesized that the more the measurement strategy was incorporated in measurement theory, the more similar the responses of patients and healthy people would be. Methods: A sample of the general population and two patient groups (cancer, rheumatoid arthritis) were included. All three study groups judged the same 17 hypothetical EQ-5D health states, each state comprising the same five health domains. The patients did not know that apart from these 17 states their own health status was also included in the set of states they were assessing. Three different measurement strategies were applied: 1) ranking of the health states; 2) placing all the health states simultaneously on a visual analogue scale (VAS); 3) separately assessing the health states with the time trade-off (TTO) technique. Regression analyses were performed to determine whether differences in the VAS and TTO can be ascribed to specific health domains. In addition, effect of being member of one of the two patient groups and the effect of the assessment of the patients' own health status was analyzed. Results: Except for some moderate divergence, no differences were found between patients and healthy people for the ranking task or for the VAS. For the time trade-off technique, however, large differences were observed between patients and healthy people. The regression analyses for the effect of belonging to one of the patient groups and the effect of the value assigned to the patients' own health state showed that only for the TTO these patient-specific parameters did offer some additional information in explaining the 17 hypothetical EQ-5D states. Conclusions: Patients' assessment of health states is similar to that of the general population when the judgments are made under conditions that are defended by modern measurement theory

Broadband hyperspectral imaging for breast tumor detection using spectral and spatial information

Complete tumor removal during breast-conserving surgery remains challenging due to the lack of optimal intraoperative margin assessment techniques. Here, we use hyperspectral imaging for tumor detection in fresh breast tissue. We evaluated different wavelength ranges and two classification algorithms; a pixel-wise classification algorithm and a convolutional neural network that combines spectral and spatial information. The highest classification performance was obtained using the full wavelength range (450-1650nm). Adding spatial information mainly improved the differentiation of tissue classes within the malignant and healthy classes. High sensitivity and specificity were accomplished, which offers potential for hyperspectral imaging as a margin assessment technique to improve surgical outcome. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreemen

Method for coregistration of optical measurements of breast tissue with histopathology : the importance of accounting for tissue deformations

For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License

Point Projection Mapping System for Tracking, Registering, Labeling and Validating Optical Tissue Measurements

Validation of newly developed optical tissue sensing techniques for tumor detection during cancer surgery requires an accurate correlation with histological results. Additionally, such accurate correlation facilitates precise data labeling for developing high-performance machine-learning tissue classification models. In this paper, a newly developed Point Projection Mapping system will be introduced, which allows non-destructive tracking of the measurement locations on tissue specimens. Additionally, a framework for accurate registration, validation, and labeling with histopathology results is proposed and validated on a case study. The proposed framework provides a more robust and accurate method for tracking and validation of optical tissue sensing techniques, which saves time and resources compared to conventional techniques available

Toward the use of diffuse reflection spectroscopy for intra-operative tissue discrimination during sarcoma surgery

Significance: Accurately distinguishing tumor tissue from normal tissue is crucial to achieve complete resections during soft tissue sarcoma (STS) surgery while preserving critical structures. Incomplete tumor resections are associated with an increased risk of local recurrence and worse patient prognosis. Aim: We evaluate the performance of diffuse reflectance spectroscopy (DRS) to distinguish tumor tissue from healthy tissue in STSs. Approach: DRS spectra were acquired from different tissue types on multiple locations in 20 freshly excised sarcoma specimens. A k -nearest neighbors classification model was trained to predict the tissue types of the measured locations, using binary and multiclass approaches. Results: Tumor tissue could be distinguished from healthy tissue with a classification accuracy of 0.90, sensitivity of 0.88, and specificity of 0.93 when well-differentiated liposarcomas were included. Excluding this subtype, the classification performance increased to an accuracy of 0.93, sensitivity of 0.94, and specificity of 0.93. The developed model showed a consistent performance over different histological subtypes and tumor locations. Conclusions: Automatic tissue discrimination using DRS enables real-time intraoperative guidance, contributing to more accurate STS resections.</p

Optical biopsy of epithelial cancers by optical coherence tomography

Optical coherence tomography (OCT) is an optical technique that measures the backscattering of near-infrared light by tissue. OCT yields in 2D and 3D images at micrometer-scale resolution, thus providing optical biopsies, approaching the resolution of histopathological imaging. The technique has shown to allow in vivo differentiation between benign and malignant epithelial tissue, through qualitative assessment of OCT images, as well as by quantitative evaluation, e.g., functional OCT. This study aims to summarize the principles of OCT and to discuss the current literature on the diagnostic value of OCT in the diagnosis of epithelial (pre)malignant lesions. The authors did a systematic search of the electronic databases PubMed and Embase on OCT in the diagnostic process of (pre)malignant epithelial lesions. OCT is able to differentiate between benign and (pre)malignant lesions of epithelial origin in a wide variety of tissues. In this way, OCT can detect skin cancers, oral, laryngeal, and esophageal cancer as well as genital and bladder cancer. OCT is an innovative technique which enables an optical biopsy of epithelial lesions. The incorporation of OCT in specific tools, like handheld and catheter-based probes, will further improve the implementation of this technology in daily clinical practice