Optical assessment of pathology in surgically resected tissues

Multi-spectral spatially modulated light is used to guide localized spectroscopy of surgically resected tissues for cancer involvement. Modulated imaging rapidly quantifies near-infrared optical parameters with sub-millimeter resolution over the entire field for identification of residual disease in resected tissues. Suspicious lesions are further evaluated using a spectroscopy platform designed to image thick tissue samples at a spatial resolution sensitive to the diagnostic gold standard, pathology. MI employs a spatial frequency domain sampling and model-based analysis of the spatial modulation transfer function to interpret a tissue's absorption and scattering parameters at depth. The spectroscopy platform employs a scanning-beam, telecentric dark-field illumination and confocal detection to image fields up to 1cm2 with a broadband source (480:750nm). The sampling spot size (100μm lateral resolution) confines the volume of tissue probed to within a few transport pathlengths so that multiple-scattering effects are minimized and simple empirical models may be used to analyze spectra. Localized spectroscopy of Intralipid and hemoglobin phantoms demonstrate insensitivity of recovered scattering parameters to changes in absorption, but a non-linear dependence of scattering power on Intralipid concentration is observed due to the phase sensitivity of the measurement system. Both systems were validated independently in phantom and murine studies. Ongoing work focuses on assessing the combined utility of these systems to identify cancer involvement in vitro, particularly in the margins of resected breast tumors

Automatic pigmented lesion segmentation through a dermoscopy-guided OCT approach for early diagnosis

Early diagnosis of pigmented lesions, specially melanoma, is an unmet clinical need that would help to improve patient prognosis. Apart from histopathological biopsy, the only gold standard non-invasive imaging technique during diagnosis is dermatoscopy (DD). Over the last years, new medical imaging techniques are being developed and Optical Coherence Tomography (OCT) has demonstrated to be very helpful on dermatology. OCT is non-invasive and provides in-depth structural microscopic information of the skin in real-time. In comparison with other novel techniques, as Reflectance Confocal Microscopy (RCM), the acquisition time is lower and the field-of-view higher. Hence, consolidated diagnosis techniques and novel imaging modalities can be combined to improve decision making during diagnosis and treatment. With actual methods, the delineation of lesion margins directly on OCT images during early stages of the disease is still really challenging and, at the same time, relevant from a prognosis perspective. This work proposes combining DD and OCT images to take advantage of their complementary information. The goal is to guide lesions delineation on OCT images considering the clinical features on DD images. The developed method applies image processing techniques to DD image to automatically segment the lesion; later, and after a calibration procedure, DD and OCT images become coregistered. In a final step the DD segmentation is transferred into the OCT image. Applying advanced image processing techniques and the proposed strategy of lesion delimitation, histopathological characteristics of the segmented lesion can be studied on OCT images afterwards. This proposal can lead to early, real-time and non-invasive diagnosis of pigmented lesions.This work has been developed thanks to the funding of the ECSEL European project ASTONISH (ID.692470) and Basque Country (Spain) ELKARTEK projects MELAMICS (KK-2016-00036) and MELAMICS II (KK-2017/00041). Special thanks to the dermatologists and personnel of the Cruces University Hospital (Cruces, Spain) and the Basurto University Hospital (Bilbao, Spain) for their collaboration on the generation of the annotated database from real patients

Successful fiber sensing technologies and hot topics for the near future

Inside the Photonics field Optical Fiber Sensors (OFS) are currently being used and will still be used in the future in a wide number of applications because its properties present technical advantages over traditional techniques or, sometimes, is practically the only feasible solution. In this paper, the more successful techniques will be reviewed. Then a prospective for the near future of the market and hot topics in which invest research resources will be suggested

Characterization of Optical Coherence Tomography Images for Colon Lesion Differentiation under Deep Learning

(1) Background: Clinicians demand new tools for early diagnosis and improved detection of colon lesions that are vital for patient prognosis. Optical coherence tomography (OCT) allows microscopical inspection of tissue and might serve as an optical biopsy method that could lead to in-situ diagnosis and treatment decisions; (2) Methods: A database of murine (rat) healthy, hyperplastic and neoplastic colonic samples with more than 94,000 images was acquired. A methodology that includes a data augmentation processing strategy and a deep learning model for automatic classification (benign vs. malignant) of OCT images is presented and validated over this dataset. Comparative evaluation is performed both over individual B-scan images and C-scan volumes; (3) Results: A model was trained and evaluated with the proposed methodology using six different data splits to present statistically significant results. Considering this, 0.9695 (_0.0141) sensitivity and 0.8094 (_0.1524) specificity were obtained when diagnosis was performed over B-scan images. On the other hand, 0.9821 (_0.0197) sensitivity and 0.7865 (_0.205) specificity were achieved when diagnosis was made considering all the images in the whole C-scan volume; (4) Conclusions: The proposed methodology based on deep learning showed great potential for the automatic characterization of colon polyps and future development of the optical biopsy paradigm.This work was partially supported by PICCOLO project. This project has received funding from the European Union’s Horizon2020 Research and Innovation Programme under grant agreement No. 732111. This research has also received funding from the Basque Government’s Industry Department under the ELKARTEK program’s project ONKOTOOLS under agreement KK-2020/00069 and the industrial doctorate program UC- DI14 of the University of Cantabria

Fractal analysis of scatter imaging signatures to distinguish breast pathologies

Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object’s complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.This work has been supported by CYCIT projects DA2TOI (FIS2010-19860) and TFS (TEC2010-20224-C02-02), as well as FPU PhD Scholarship (FPU12/04130), all funded by the Spanish Government

Multispectral reflectance enhancement for breast cancer visualization in the operating room

A color enhancement method to optimize the visualization of breast tumors in cancer pathology is proposed. Light scattering measurements are minimally invasive, and allow the estimation of tissue morphology and composition to guide the surgeon in resection surgeries. The usability of scatter and absorption signatures acquired with a microsampling reflectance spectral imaging system was improved employing an empirical approximation to the Mie theory to estimate the scattering power on a per-pixel basis. The proposed methodology generates a new image with blended color and diagnostic purposes coming from the emphasis or highlighting of specific wavelengths or features. These features can be the specific absorbent tissue components (oxygenated and deoxygenated hemoglobin, etc.), additional parameters as scattering power or amplitude or even the combination of both. The goal is to obtain an improved and inherent tissue contrast working only with the local reflectance of tissue. To this aim, it is provided a visual interpretation of what is considered non-malignant (normal epithelia and stroma, benign epithelia and stroma, inflammation), malignant (DCIS, IDC, ILC) and adipose tissue. Consequently, a fast visualization map of the intracavity area can be offered to the surgeon providing relevant diagnostic information. No labeling or extrinsic indicators are required for proposed methodology and therefore the possibility of transferring absorption and scattering features simultaneously into visualization, fusing their effects into a single image, can guide surgeons efficiently.This work has been supported by the Spanish Government through the CYCIT projects DA2TOI (FIS2010-19860) and TEC2013-47264-C2-1-R

Melanoma and nevi subtype histopathological characterization with optical coherence tomography

Background: Melanoma incidence has continued to rise in the latest decades, and the forecast is not optimistic. Non-invasive diagnostic imaging techniques such as optical coherence tomography (OCT) are largely studied; however, there is still no agreement on its use for the diagnosis of melanoma. For dermatologists, the differentiation of non-invasive (junctional nevus, compound nevus, intradermal nevus, and melanoma in-situ) versus invasive (superficial spreading melanoma and nodular melanoma) lesions is the key issue in their daily routine. Methods: This work performs a comparative analysis of OCT images using haematoxylin-eosin (HE) and anatomopathological features identified by a pathologist. Then, optical and textural properties are extracted from OCT images with the aim to identify subtle features that could potentially maximize the usefulness of the imaging technique in the identification of the lesion?s potential invasiveness. Results: Preliminary features reveal differences discriminating melanoma in-situ from superficial spreading melanoma and also between melanoma and nevus subtypes that pose a promising baseline for further research. Conclusions: Answering the final goal of diagnosing non-invasive versus invasive lesions with OCT does not seem feasible in the short term, but the obtained results demonstrate a step forward to achieve this.This work has been funded by the Department of Economic Development, Sustainability and the Environment of the Basque Government (Spain) ELKARTEK projects ONKOTOOLS with grant numbers KK-2020/00069, the Spanish Ministry of Science and Education CERVERA project AI4ES with grant numbers CER-20211030, and by the ECSEL JU European project ASTONISH with the grant number 692470, UC Industrial Doctorate DI14

Combined fluorescence and reflectance spectroscopy for in vivo quantification of cancer biomarkers in low - and high- grade glioma surgery

Biomarkers are indicators of biological processes and hold promise for the diagnosis and treatment of disease. Gliomas represent a heterogeneous group of brain tumors with marked intra- and inter-tumor variability. The extent of surgical resection is a significant factor influencing post-surgical recurrence and prognosis. Here, we used fluorescence and reflectance spectral signatures for in vivo quantification of multiple biomarkers during glioma surgery, with fluorescence contrast provided by exogenously-induced protoporphyrin IX (PpIX) following administration of 5-aminolevulinic acid. We performed light-transport modeling to quantify multiple biomarkers indicative of tumor biological processes, including the local concentration of PpIX and associated photoproducts, total hemoglobin concentration, oxygen saturation, and optical scattering parameters.We developed a diagnostic algorithm for intra-operative tissue delineation that accounts for the combined tumor-specific predictive capabilities of these quantitative biomarkers. Tumor tissue delineation achieved accuracies of up to 94% (specificity=94%, sensitivity=94%) across a range of glioma histologies beyond current state-of-the-art optical approaches, including state-of-the-art fluorescence image guidance. This multiple biomarker strategy opens the door to optical methods for surgical guidance that use quantification of well-established neoplastic processes. Future work would seek to validate the predictive power of this proof-of-concept study in a separate larger cohort of patients

Custom scanning hyperspectral imaging system for biomedical applications: modeling, benchmarking, and specifications

Prototyping hyperspectral imaging devices in current biomedical optics research requires taking into consideration various issues regarding optics, imaging, and instrumentation. In summary, an ideal imaging system should only be limited by exposure time, but there will be technological limitations (e.g., actuator delay and backlash, network delays, or embedded CPU speed) that should be considered, modeled, and optimized. This can be achieved by constructing a multiparametric model for the imaging system in question. The article describes a rotating-mirror scanning hyperspectral imaging device, its multiparametric model, as well as design and calibration protocols used to achieve its optimal performance. The main objective of the manuscript is to describe the device and review this imaging modality, while showcasing technical caveats, models and benchmarks, in an attempt to simplify and standardize specifications, as well as to incentivize prototyping similar future designs.This research, as well as APC charges, was funded by: CIBER-BBN; MINECO (Ministerio de Economía y Competitividad) and Instituto de Salud Carlos III (ISCIII), grant numbers DTS15/00238, DTS17/00055, and TEC2016-76021-C2-2-R; Instituto de Investigación Sanitaria Valdecilla (IDIVAL), grant number INNVAL16/02; Ministry of Education, Culture and Sports, PhD grant number FPU16/05705