Spectral imaging of thermal damage induced during microwave ablation in the liver

Induction of thermal damage to tissue through delivery of microwave energy is frequently applied in surgery to destroy diseased tissue such as cancer cells. Minimization of unwanted harm to healthy tissue is still achieved subjectively, and the surgeon has few tools at their disposal to monitor the spread of the induced damage. This work describes the use of optical methods to monitor the time course of changes to the tissue during delivery of microwave energy in the porcine liver. Multispectral imaging and diffuse reflectance spectroscopy are used to monitor temporal changes in optical properties in parallel with thermal imaging. The results demonstrate the ability to monitor the spatial extent of thermal damage on a whole organ, including possible secondary effects due to vascular damage. Future applications of this type of imaging may see the multispectral data used as a feedback mechanism to avoid collateral damage to critical healthy structures and to potentially verify sufficient application of energy to the diseased tissue.Comment: 4pg,6fig. Copyright 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

Review of photoacoustic imaging plus X

Photoacoustic imaging (PAI) is a novel modality in biomedical imaging technology that combines the rich optical contrast with the deep penetration of ultrasound. To date, PAI technology has found applications in various biomedical fields. In this review, we present an overview of the emerging research frontiers on PAI plus other advanced technologies, named as PAI plus X, which includes but not limited to PAI plus treatment, PAI plus new circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus novel ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. We will discuss each technology's current state, technical advantages, and prospects for application, reported mostly in recent three years. Lastly, we discuss and summarize the challenges and potential future work in PAI plus X area

Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images

Histopathological characterization of colorectal polyps is an important principle for determining the risk of colorectal cancer and future rates of surveillance for patients. This characterization is time-intensive, requires years of specialized training, and suffers from significant inter-observer and intra-observer variability. In this work, we built an automatic image-understanding method that can accurately classify different types of colorectal polyps in whole-slide histology images to help pathologists with histopathological characterization and diagnosis of colorectal polyps. The proposed image-understanding method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks. Our image-understanding method covers all five polyp types (hyperplastic polyp, sessile serrated polyp, traditional serrated adenoma, tubular adenoma, and tubulovillous/villous adenoma) that are included in the US multi-society task force guidelines for colorectal cancer risk assessment and surveillance, and encompasses the most common occurrences of colorectal polyps. Our evaluation on 239 independent test samples shows our proposed method can identify the types of colorectal polyps in whole-slide images with a high efficacy (accuracy: 93.0%, precision: 89.7%, recall: 88.3%, F1 score: 88.8%). The presented method in this paper can reduce the cognitive burden on pathologists and improve their accuracy and efficiency in histopathological characterization of colorectal polyps, and in subsequent risk assessment and follow-up recommendations

Combination oral immunotherapy with IL-10 and IL-12 effectively treats colon tumors via synergistic effects on IL-17 producing T cells and colon epithelial barrier integrity.

In this dissertation, the relationship between colon cancer and inflammation, the utility of novel imaging modalities for diagnosis of colitis and cancer, and the therapeutic efficacy of orally delivered, particle-based immunotherapy for the treatment of colon cancer are evaluated. In Chapters One and Two, multispectral optoacoustic tomography (MSOT) is demonstrated to effectively detect colon inflammation without the use of exogenous contrast prior to detection using conventional colonoscopy. Oral particle uptake is demonstrated in the distal small intestine and proximal colon, confirming site-specific delivery. In Chapter Three, administration of IL-10 and IL-12 containing particles is shown to act synergistically to significantly reduce tumor burden in the setting of established colon tumors. Cellular mechanisms deriving from effects on CD8+ T cells and T17 cells as well as a physiologic mechanism stemming from combination therapy’s strengthening of colon epithelial barrier integrity are described. In Chapter Four, the lack of efficacy of orally administered anti-PD1 therapy is demonstrated. IL-17 and γδ T cells, but not CD4+ T cells, are shown to be critical mediators of treatment failure. The significant anti-tumor effect of combination treatment with either anti-IL-17A or anti- γδ TCR and anti-PD1 demonstrate exciting therapeutic targets for future clinical trials. Finally, in Chapter Five, a clinically relevant model of colon cancer is described. This mutationally-driven model recapitulates the clinical scenario of single adenoma development, adenoma to carcinoma transition, carcinoma progression, and eventual metastasis to the liver. Such a model provides an excellent platform for preclinical evaluation of many different aspects of colon cancer

Multisensor perfusion assessment cohort study: Preliminary evidence toward a standardized assessment of indocyanine green fluorescence in colorectal surgery

Background: Traditional methods of assessing colonic perfusion are based on the surgeon's visual inspection of tissue. Fluorescence angiography provides qualitative information, but there remains disagreement on how the observed signal should be interpreted. It is unclear whether fluorescence correlates with physiological properties of the tissue, such as tissue oxygen saturation. The aim of this study was to correlate fluorescence intensity and colonic tissue oxygen saturation. Methods: Prospective cohort study performed in a single academic tertiary referral center. Patients undergoing colorectal surgery who required an anastomosis underwent dual-modality perfusion assessment of a segment of bowel before transection and creation of the anastomosis, using near-infrared and multispectral imaging. Perfusion was assessed using maximal fluorescence intensity measurement during fluorescence angiography, and its correlation with tissue oxygen saturation was calculated. Results: In total, 18 patients were included. Maximal fluorescence intensity occurred at a mean of 101 seconds after indocyanine green injection. The correlation coefficient was 0.73 (95% confidence interval of 0.65–0.79) with P < .0001, showing a statistically significant strong positive correlation between normalized fluorescence intensity and tissue oxygen saturation. The use of time averaging improved the correlation coefficient to 0.78. Conclusion: Fluorescence intensity is a potential surrogate for tissue oxygenation. This is expected to lead to improved decision making when transecting the bowel and, consequently, a reduction in anastomotic leak rates. A larger, phase II study is needed to confirm this result and form the basis of computational algorithms to infer biological or physiological information from the fluorescence imaging data

Prediction of In Vivo Laser-Induced Thermal Damage with Hyperspectral Imaging Using Deep Learning.

Thermal ablation is an acceptable alternative treatment for primary liver cancer, of which laser ablation (LA) is one of the least invasive approaches, especially for tumors in high-risk locations. Precise control of the LA effect is required to safely destroy the tumor. Although temperature imaging techniques provide an indirect measurement of the thermal damage, a degree of uncertainty remains about the treatment effect. Optical techniques are currently emerging as tools to directly assess tissue thermal damage. Among them, hyperspectral imaging (HSI) has shown promising results in image-guided surgery and in the thermal ablation field. The highly informative data provided by HSI, associated with deep learning, enable the implementation of non-invasive prediction models to be used intraoperatively. Here we show a novel paradigm "peak temperature prediction model" (PTPM), convolutional neural network (CNN)-based, trained with HSI and infrared imaging to predict LA-induced damage in the liver. The PTPM demonstrated an optimal agreement with tissue damage classification providing a consistent threshold (50.6 ± 1.5 °C) for the damage margins with high accuracy (~0.90). The high correlation with the histology score (r = 0.9085) and the comparison with the measured peak temperature confirmed that PTPM preserves temperature information accordingly with the histopathological assessment

Optical Methods in Sensing and Imaging for Medical and Biological Applications

The recent advances in optical sources and detectors have opened up new opportunities for sensing and imaging techniques which can be successfully used in biomedical and healthcare applications. This book, entitled ‘Optical Methods in Sensing and Imaging for Medical and Biological Applications’, focuses on various aspects of the research and development related to these areas. The book will be a valuable source of information presenting the recent advances in optical methods and novel techniques, as well as their applications in the fields of biomedicine and healthcare, to anyone interested in this subject

Active Extraordinary Optical Transmission Metasurfaces Using Phase-Change Materials

The key question that this thesis aims to answer is “can a tuneable bandpass optical filter for the mid-infrared regime be made by combining extraordinary optical transmission (EOT) arrays and phase-change materials (PCMs)?”. It is proposed that such devices may be useful for a wide range of applications where the ability to dynamically change the transmissive (or reflective) properties of a filter is required, include multispectral sensing/imaging and signal modulation amongst others. Current multispectral imaging systems are mainly dependant on either multiple sets of lenses and sensors, or multiple mechanically-exchanged filters exposed through in-sequence; the use of a single, dynamically tuneable phase-change EOT-based filter opens avenues to reducing systems’ size, cost and complexity. The EOT effect is observed with arrays of sub-wavelength-sized holes in thin plasmonic metal (e.g. gold) films, with the transmission peak position dependent on the array geometry and surrounding materials’ optical properties: a PCM layer on top of the array allows shifting of the transmission peak position by switching the PCM phase (and its refractive index) via heat pulses. Specific areas studied in this thesis include the use of different fabrication methods to make phase-change EOT transmission filters for the mid-infrared regime, including electron-beam lithography-based techniques and a novel (and much faster) approach of direct patterning via laser ablation. Tuneable filters for use in various parts of the optical spectrum, especially the mid and long-wave infrared range, were designed, simulated, fabricated and characterised. Good performance was obtained for phase-change EOT filters over a wide range of array pitch sizes. EOT arrays designed for the mid-infrared range and fabricated via wet-etching and measured with FTIR spectroscopy produced very similar spectra to those of finite-element simulations with peak transmittance of Q-factors between 5-6 and a peak transmittance of ~0.8. Laser-ablated arrays showed a similar (though not quite so good) performance, due mainly to slight irregularities in the positioning of holes in the array. The addition of a phase-change layer, specifically Ge2Sb2Te5, to the EOT arrays resulted in a shift in the wavelength of the peak transmission, with the amount of shift depending on the phase-state (crystalline, amorphous, or mixed-state) of the phase-change layer, so demonstrating the ability for dynamic tuning of the filter response by switching of the phase-change layer. An important requirement for proper and prolonged operation of the filter devices was found to be the use of a thin dielectric barrier layer (here Si3N4, between the plasmonic film and the phase-change layer, to prevent inter-diffusion between the two: reflection cavities of Ge2Sb2Te5 on unpatterned gold layers were created to investigate this effect, with resonance features of a 20 nm layer being destroyed without a barrier layer present and the complete assimilation of gold and phase-change layers evident with cross-section TEM imaging