Prediction of Biliary Complications After Human Liver Transplantation Using Hyperspectral Imaging and Convolutional Neural Networks: A Proof-of-concept Study.

BACKGROUND: Biliary complications (BCs) negatively impact the outcome after liver transplantation. We herein tested whether hyperspectral imaging (HSI) generated data from bile ducts (BD) on reperfusion and machine learning techniques for data readout may serve as a novel approach for predicting BC. METHODS: Tissue-specific data from 136 HSI liver images were integrated into a convolutional neural network (CNN). Fourteen patients undergoing liver transplantation after normothermic machine preservation served as a validation cohort. Assessment of oxygen saturation, organ hemoglobin, and tissue water levels through HSI was performed after completing the biliary anastomosis. Resected BD segments were analyzed by immunohistochemistry and real-time confocal microscopy. RESULTS: Immunohistochemistry and real-time confocal microscopy revealed mild (grade I: 1%-40%) BD damage in 8 patients and moderate (grade II: 40%-80%) injury in 1 patient. Donor and recipient data alone had no predictive capacity toward BC. Deep learning-based analysis of HSI data resulted in >90% accuracy of automated detection of BD. The CNN-based analysis yielded a correct classification in 72% and 69% for BC/no BC. The combination of HSI with donor and recipient factors showed 94% accuracy in predicting BC. CONCLUSIONS: Deep learning-based modeling using CNN of HSI-based tissue property data represents a noninvasive technique for predicting postoperative BC.

Characterizing the Mechanical Behavior of Bone and Bone Surrogates in Compression Using pQCT.

Many axial and appendicular skeleton bones are subjected to repetitive loading during daily activities. Until recently, the structural analysis of fractures has been limited to 2D sections, and the dynamic assessment of fracture progression has not been possible. The structural failure was analyzed using step-wise micro-compression combined with time-lapsed micro-computed tomographic imaging. The structural failure was investigated in four different sample materials (two different bone surrogates, lumbar vertebral bodies from bovine and red deer). The samples were loaded in different force steps based on uniaxial compression tests. The micro-tomography images were used to create three-dimensional models from which various parameters were calculated that provide information about the structure and density of the samples. By superimposing two 3D images and calculating the different surfaces, it was possible to precisely analyze which trabeculae failed in which area and under which load. According to the current state of the art, bone mineral density is usually used as a value for bone quality, but the question can be raised as to whether other values such as trabecular structure, damage accumulation, and bone mineralization can predict structural competence better than bone mineral density alone.

Application of Micro-Computed Tomography for the Estimation of the Post-Mortem Interval of Human Skeletal Remains.

It is challenging to estimate the post-mortem interval (PMI) of skeletal remains within a forensic context. As a result of their interactions with the environment, bones undergo several chemical and physical changes after death. So far, multiple methods have been used to follow up on post-mortem changes. There is, however, no definitive way to estimate the PMI of skeletal remains. This research aimed to propose a methodology capable of estimating the PMI using micro-computed tomography measurements of 104 human skeletal remains with PMIs between one day and 2000 years. The present study indicates that micro-computed tomography could be considered an objective and precise method of PMI evaluation in forensic medicine. The measured parameters show a significant difference regarding the PMI for Cort Porosity p < 0.001, BV/TV p > 0.001, Mean1 p > 0.001 and Mean2 p > 0.005. Using a machine learning approach, the neural network showed an accuracy of 99% for distinguishing between samples with a PMI of less than 100 years and archaeological samples.

Hyperspectral Imaging as a Tool for Viability Assessment During Normothermic Machine Perfusion of Human Livers: A Proof of Concept Pilot Study.

Normothermic machine perfusion (NMP) allows for ex vivo viability and functional assessment prior to liver transplantation (LT). Hyperspectral imaging represents a suitable, non-invasive method to evaluate tissue morphology and organ perfusion during NMP. Liver allografts were subjected to NMP prior to LT. Serial image acquisition of oxygen saturation levels (StO2), organ hemoglobin (THI), near-infrared perfusion (NIR) and tissue water indices (TWI) through hyperspectral imaging was performed during static cold storage, at 1h, 6h, 12h and at the end of NMP. The readouts were correlated with perfusate parameters at equivalent time points. Twenty-one deceased donor livers were included in the study. Seven (33.0%) were discarded due to poor organ function during NMP. StO2 (p < 0.001), THI (p < 0.001) and NIR (p = 0.002) significantly augmented, from static cold storage (pre-NMP) to NMP end, while TWI dropped (p = 0.005) during the observational period. At 12-24h, a significantly higher hemoglobin concentration (THI) in the superficial tissue layers was seen in discarded, compared to transplanted livers (p = 0.036). Lactate values at 12h NMP correlated negatively with NIR perfusion index between 12 and 24h NMP and with the delta NIR perfusion index between 1 and 24h (rs = -0.883, p = 0.008 for both). Furthermore, NIR and TWI correlated with lactate clearance and pH. This study provides first evidence of feasibility of hyperspectral imaging as a potentially helpful contact-free organ viability assessment tool during liver NMP.

Application of mid-infrared microscopic imaging for the diagnosis and classification of human lymphomas.

Mid-infrared (MIR) microscopic imaging of indolent and aggressive lymphomas was performed including formalin-fixed and paraffin-embedded samples of six follicular lymphomas and 12 diffuse large B-cell-lymphomas as well as reactive lymph nodes to investigate benefits and challenges for lymphoma diagnosis. MIR images were compared to defined pathological characteristics such as indolent versus aggressive versus reactive, germinal centre versus activated cell-of-origin (COO) subtypes, or a low versus a high proliferative index and level of PD-L1 expression. We demonstrated that MIR microscopic imaging can differentiate between reactive lymph nodes, indolent and aggressive lymphoma samples. Also, it has potential to be used in the subtyping of lymphomas, as shown with the differentiation between COO subtypes, the level of proliferation and PD-L1 expression. MIR microscopic imaging is a promising tool for diagnosis and subtyping of lymphoma and further evaluation is needed to fully explore the advantages and disadvantages of this method for pathological diagnosis.

Hyperspectral imaging as a diagnostic tool to differentiate between amalgam tattoos and other dark pigmented intraoral lesions.

The goal of this project is to identify any in-depth benefits and drawbacks in the diagnosis of amalgam tattoos and other pigmented intraoral lesions using hyperspectral imagery collected from amalgam tattoos, benign, and malignant melanocytic neoplasms. Software solutions capable of classifying pigmented lesions of the skin already exist, but conventional red, green and blue images may be reaching an upper limit in their performance. Emerging technologies, such as hyperspectral imaging (HSI) utilize more than a hundred, continuous data channels, while also collecting data in the infrared. A total of 18 paraffin-embedded human tissue specimens of dark pigmented intraoral lesions (including the lip) were analyzed using visible and near-infrared (VIS-NIR) hyperspectral imagery obtained from HE-stained histopathological slides. Transmittance data were collected between 450 and 900 nm using a snapshot camera mounted to a microscope with a halogen light source. VIS-NIR spectra collected from different specimens, such as melanocytic cells and other tissues (eg, epithelium), produced distinct and diagnostic spectra that were used to identify these materials in several regions of interest, making it possible to distinguish between intraoral amalgam tattoos (intramucosal metallic foreign bodies) and melanocytic lesions of the intraoral mucosa and the lip (each with P < .01 using the independent t test). HSI is presented as a diagnostic tool for the rapidly growing field of digital pathology. In this preliminary study, amalgam tattoos were reliably differentiated from melanocytic lesions of the oral cavity and the lip.

Visible and near-infrared hyperspectral imaging techniques allow the reliable quantification of prognostic markers in lymphomas: A pilot study using the Ki67 proliferation index as an example.

In this study, we examined the suitability of visible and infrared (Vis-NIR) hyperspectral imaging (HSI) for the quantification of prognostic markers in non-Hodgkin lymphoma on the example of the Ki67 proliferation index. Ki67 quantification was done on six follicular lymphomas (FLs) and 12 diffuse large B-cell lymphomas (DLBCLs) by applying classic immunohistochemistry. The Ki67 index was comparatively assessed visually, using HSI-based quantification and a digital imaging analysis (DIA) platform. There was no significant difference between visual assessment (VA), DIA, and HSI in FLs. For DLBCLs, VA resulted in significantly higher Ki67 values than HSI (p = 0.023) and DIA (p = 0.006). No such difference was seen comparing analysis by HSI and DIA (p = 0.724). Cohen's κ revealed a "substantial correlation" of Ki67 values for HSI and DIA in FLs and DLBCLs (κ = 0.667 and 0.657). Here we provide the first evidence that, comparably to traditional DIA, HSI can be used reliably to quantify protein expression, as exemplified by the Ki67 proliferation index. By covering the near-infrared spectrum, HSI might offer additional information on the biochemical composition of pathological specimens, although our study could not show that HSI is clearly superior to conventional DIA. However, the analysis of multiplex immunohistochemistry might benefit from such an approach, especially if overlapping immunohistochemical reactions were possible. Further studies are needed to explore the impact of this method on the analysis and quantification of multiple marker expression in pathological specimens.

Generation of A Mucor circinelloides Reporter Strain-A Promising New Tool to Study Antifungal Drug Efficacy and Mucormycosis.

Invasive fungal infections caused by Mucorales (mucormycosis) have increased worldwide. These life-threatening infections affect mainly, but not exclusively, immunocompromised patients, and are characterized by rapid progression, severe tissue damage and an unacceptably high rate of mortality. Still, little is known about this disease and its successful therapy. New tools to understand mucormycosis and a screening method for novel antimycotics are required. Bioluminescent imaging is a powerful tool for in vitro and in vivo approaches. Hence, the objective of this work was to generate and functionally analyze bioluminescent reporter strains of Mucor circinelloides, one mucormycosis-causing pathogen. Reporter strains were constructed by targeted integration of the firefly luciferase gene under control of the M. circinelloides promoter Pzrt1. The luciferase gene was sufficiently expressed, and light emission was detected under several conditions. Phenotypic characteristics, virulence potential and antifungal susceptibility were indifferent to the wild-type strains. Light intensity was dependent on growth conditions and biomass, being suitable to determine antifungal efficacy in vitro. This work describes for the first time the generation of reporter strains in a basal fungus that will allow real-time, non-invasive infection monitoring in insect and murine models, and the testing of antifungal efficacy by means other than survival.

Application of micro-computed tomography to microstructure studies of the medicinal fungus Hericium coralloides.

The potential of 3-D nondestructive imaging techniques such as micro-computed tomography (micro-CT) was evaluated to study morphological patterns of the potential medicinal fungus Hericium coralloides (Basidiomycota). Micro-CT results were correlated with histological information gained from scanning electron microscopy (SEM) and light microscopy (LM). It is demonstrated that the combination of these imaging methods results in a more distinct picture of the morphology of the edible and potentially medicinal Hericium coralloides basidiomata. In addition we have created 3-D reconstructions and visualizations based on micro-CT imagery from a randomly selected part of the upper region of a fresh H. coralloides basidioma: Analyses for the first time allowed an approximation of the evolutionary effectiveness of this bizarrely formed basidioma type in terms of the investment of tissue biomass and its reproductive output (production of basidiospores).

Characterization of normal and malignant prostate tissue by Fourier transform infrared microspectroscopy.

Prostate cancer has become one of the most common malignancies worldwide. Morphological and histomorphological evaluation of this disease is a well established technique for the cancer classification and has remained relatively unchanged since several decades, although it remains a time consuming and subjective technique, with unsatisfactory levels of inter- and intra-observer discrepancy. Novel approaches for histological recognition are necessary to identify and to investigate cancer in detail. Fourier transform infrared (FTIR) spectroscopic imaging has become an essential tool for the detection, identification and characterization of the molecular components of biological processes, such as those responsible for the dynamic properties of cancer progression. Major advantage of this new technique is the acquisition of local molecular expression profiles while maintaining the topographic integrity of the tissue and avoiding time-consuming extraction, purification and separation steps. By using this method it is possible to investigate the spatial distribution of proteins, lipids, carbohydrates, cholesterols, nucleic acids, phospholipids and small molecules within biological systems by in situ analysis of tissue sections. We applied this technique on prostate cancer patients radical prostatectomy specimens in order to develop new tools for histomorphological analysis and the characterization of snap frozen prostate cancer tissues. As a first step, an optimization of sample preparation, tissue section thickness and IR slide material was performed. Special preparation methods for FTIR imaging are the essential requirements to maintain the spatial arrangement of compounds and avoid delocalization and degradation of the analytes. Subsequently, selected cancer samples were characterized with the prior optimized parameters and analyzed by univariate and cluster analysis. For the interpretation and calibration of the system we correlated the FTIR-images with the histopathological information. With this method it is possible to distinguish between cancer and noncancer areas within a prostate cancer tissue with a resolution of 6.25 µm × 6.25 µm on frozen sections.