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

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

Tissue classification of breast cancer by hyperspectral unmixing

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Review: in vivo optical spectral tissue sensing-how to go from research to routine clinical application?

Innovations in optical spectroscopy have helped the technology reach a point where performance previously seen only in laboratory settings can be translated and tested in real-world applications. In the field of oncology, spectral tissue sensing (STS) by means of optical spectroscopy is considered to have major potential for improving diagnostics and optimizing treatment outcome. The concept has been investigated for more than two decades and yet spectral tissue sensing is not commonly employed in routine medical practice. It is therefore important to understand what is needed to translate technological advances and insights generated through basic scientific research in this field into clinical practice. The aim of the discussion presented here is not to provide a comprehensive review of all work published over the last decades but rather to highlight some of the challenges found in literature and encountered by our group in the quest to translate optical technologies into useful clinical tools. Furthermore, an outlook is proposed on how translational researchers could proceed to eventually have STS incorporated in the process of clinical decision-makin

Discriminating between absorption and scattering coefficients in optical characterisation measurements on gold nanoparticle based photoacoustic contrast agents \ud

Plasmon resonant nanoparticles such as gold nanoshells and gold nanorods can be tuned to possess sharp interaction peaks in the near-infrared wavelength regions. These have great importance as contrast agents in photoacoustic imaging and as photothermal agents for therapeutic applications due to their high absorptions. While the optical properties of the particles are can be described using Mie theory and/or numerical methods such as the Discrete Dipole Approximation, discriminating between their optical absorption and scattering in experiments is not easy. In this paper we discuss for the first time a novel method based on a two-fiber spectrometer that allows measurement of the scattering and absorption coefficients of gold nanoparticles in solution. This technique, called Differential Path length Spectroscopy, has been developed earlier for measurement in highly diffusive media such as tissue. We demonstrate this concept on gold nanospheres and nanoshells of various sizes. We believe that this will develop into a fast and reliable method able to work on small samples (<1 ml) of nanoparticles to obtain scattering and absorbing spectr

Sistema de correcció de programes: preparació per a un entorn de producció

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2013, Director: Lluís Garrido OstermannThe idea for this project came during the implementation of the Degree of Computing at the University of Barcelona. This degree is framed in the European Higher Education Area (EHEA), which enhances the student's continuous assessment. The students are usually required to perform a greater number of practices and therefore increases the student's need to learn autonomously. It also increases the workload of the teacher correction given the high number of practices to review. The main idea Correction System Program (SCP) is to help students when making their deliveries, giving it autonomy in their review and benefiting the fact of receiving a direct answer after making the delivery. In addition, the teacher also benefits by avoiding the hard process of correcting these and the workload involved. The main application functionality SCP is self-review practices undertaken by the students, so that students can make the delivery of a program and know at the moment whether it's correct or not. The teacher is able to watch the results and the student code through the system, avoiding the manual correction process in which the teacher has to compile and run the code sent by students

Single fiber reflectance spectroscopy calibration

To accurately determine sample optical properties using single fiber reflectance spectroscopy (SFR), an absolute calibration of the reflectance is required. We investigated two SFR calibration methods, using a calibrated mirror and using the Fresnel reflection at the fiber tip as a reference. We compared these to commonly used calibration methods, using either Intralipid-20% in combination with Monte Carlo simulations or Spectralon as a reference. The Fresnel reflection method demonstrated the best reproducibility and yielded the most reliable result. We therefore recommend the Fresnel reflection method for the measured absolute reflectance calibration of SFR

Layer thickness prediction and tissue classification in two-layered tissue structures using diffuse reflectance spectroscopy

During oncological surgery, it can be challenging to identify the tumor and establish adequate resection margins. This study proposes a new two-layer approach in which diffuse reflectance spectroscopy (DRS) is used to predict the top layer thickness and classify the layers in two-layered phantom and animal tissue. Using wavelet-based and peak-based DRS spectral features, the proposed method could predict the top layer thickness with an accuracy of up to 0.35 mm. In addition, the tissue types of the first and second layers were classified with an accuracy of 0.95 and 0.99. Distinguishing multiple tissue layers during spectral analyses results in a better understanding of more complex tissue structures encountered in surgical practice.Medical Instruments & Bio-Inspired Technolog

Tissue Classification of Breast Cancer by Hyperspectral Unmixing

(1) Background: Assessing the resection margins during breast-conserving surgery is an important clinical need to minimize the risk of recurrent breast cancer. However, currently there is no technique that can provide real-time feedback to aid surgeons in the margin assessment. Hyperspectral imaging has the potential to overcome this problem. To classify resection margins with this technique, a tissue discrimination model should be developed, which requires a dataset with accurate ground-truth labels. However, establishing such a dataset for resection specimens is difficult. (2) Methods: In this study, we therefore propose a novel approach based on hyperspectral unmixing to determine which pixels within hyperspectral images should be assigned to the ground-truth labels from histopathology. Subsequently, we use this hyperspectral-unmixing-based approach to develop a tissue discrimination model on the presence of tumor tissue within the resection margins of ex vivo breast lumpectomy specimens. (3) Results: In total, 372 measured locations were included on the lumpectomy resection surface of 189 patients. We achieved a sensitivity of 0.94, specificity of 0.85, accuracy of 0.87, Matthew’s correlation coefficient of 0.71, and area under the curve of 0.92. (4) Conclusion: Using this hyperspectral-unmixing-based approach, we demonstrated that the measured locations with hyperspectral imaging on the resection surface of lumpectomy specimens could be classified with excellent performance