Using spectral imaging for the analysis of abnormalities for colorectal cancer: When is it helpful?

© 2018 Awan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The spectral imaging technique has been shown to provide more discriminative information than the RGB images and has been proposed for a range of problems. There are many studies demonstrating its potential for the analysis of histopathology images for abnormality detection but there have been discrepancies among previous studies as well. Many multispectral based methods have been proposed for histopathology images but the significance of the use of whole multispectral cube versus a subset of bands or a single band is still arguable. We performed comprehensive analysis using individual bands and different subsets of bands to determine the effectiveness of spectral information for determining the anomaly in colorectal images. Our multispectral colorectal dataset consists of four classes, each represented by infra-red spectrum bands in addition to the visual spectrum bands. We performed our analysis of spectral imaging by stratifying the abnormalities using both spatial and spectral information. For our experiments, we used a combination of texture descriptors with an ensemble classification approach that performed best on our dataset. We applied our method to another dataset and got comparable results with those obtained using the state-of-the-art method and convolutional neural network based method. Moreover, we explored the relationship of the number of bands with the problem complexity and found that higher number of bands is required for a complex task to achieve improved performance. Our results demonstrate a synergy between infra-red and visual spectrum by improving the classification accuracy (by 6%) on incorporating the infra-red representation. We also highlight the importance of how the dataset should be divided into training and testing set for evaluating the histopathology image-based approaches, which has not been considered in previous studies on multispectral histopathology images.This publication was made possible using a grant from the Qatar National Research Fund through National Priority Research Program (NPRP) No. 6-249-1-053. The content of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Qatar National Research Fund or Qatar University

An Innovative Platform Merging Elemental Analysis and Ftir Imaging for Breast Tissue Analysis

Histopathology and immunohistology remain the gold standard for breast cancer diagnostic. Yet, these approaches do not usually provide a sufficiently detailed characterization of the pathology. The purpose of this work is to demonstrate for the first time that elemental analysis and Fourier transform infrared spectroscopy microscopic examination of breast tissue sections can be merged into one dataset to provide a single set of markers based on both organic molecules and inorganic trace elements. For illustrating the method, 6 mammary tissue sections were used. Fourier transform infrared (FTIR) spectroscopy images reported a fingerprint of the organic molecules present in the tissue section and laser ablation elemental analysis (LA-ICP-MS) images brought inorganic element profiles. The 6 tissue sections provided 31 106 and 150,000 spectra for FTIR and LA-ICP-MS spectra respectively. The results bring the proof of concept that breast tissue can be analyzed simultaneously by FTIR spectroscopy and laser ablation elemental analysis (LA-ICP-MS) to provide in both case reasonably high resolution images. We show how to bring the images obtained by the two methods to a same spatial resolution and how to use image registration to analyze the data originating from both techniques as one block of data. We finally demonstrates the elemental analysis is orthogonal to all FTIR markers as no significant correlation is found between FTIR and LA-ICP-MS data. Combining FTIR and LA-ICP-MS imaging becomes possible, providing two orthogonal methods which can bring an unprecedented diversity of information on the tissue. This opens a new avenue of tissue section analyses providing unprecedented diagnostic potential. - 2019, The Author(s).This study was made possible by a NPRP Award [7–1267–3–328] from the Qatar National Research Fund (a member of The Qatar Foundation). E.G. is Research Director with the National Fund for Scientific Research (Belgium). The statements made herein are solely the responsibility of the authors.Scopu

Assessment of OMT-28, a synthetic analog of omega-3 epoxyeicosanoids, in patients with persistent atrial fibrillation: Rationale and design of the PROMISE-AF phase II study.

We designed a placebo controlled, double-blind, randomized, dose-finding phase II study on OMT-28 in the maintenance of sinus rhythm after electrical cardioversion (DCC) in patients with persistent atrial fibrillation (PROMISE-AF). OMT-28 is a first-in-class, synthetic analog of 17,18-epoxyeicosatetetraenoic acid, a bioactive lipid mediator generated by cytochrome P450 enzymes from the omega-3 fatty acid eicosapentaenoic acid. OMT-28 improves Ca2+-handling and mitochondrial function in cardiomyocytes and reduces pro-inflammatory signaling. This unique mode of action may provide a novel approach to target key mechanism contributing to AF pathophysiology. In a recent phase I study, OMT-28 was safe and well tolerated and showed favorable pharmacokinetics. The PROMISE-AF study (NCT03906799) is designed to assess the efficacy (primary objective), safety, and population pharmacokinetics (secondary objectives) of three different doses of OMT-28, administered once daily, versus placebo until the end of the follow-up period. Recruitment started in March 2019 and the study will include a total of 120 patients. The primary efficacy endpoint is the AF burden (% time with any AF), evaluated over a 13-week treatment period after DCC. AF burden is calculated based on continuous ECG monitoring using an insertable cardiac monitor (ICM). The primary efficacy analysis will be conducted on the modified intention-to-treat (mITT) population, whereas the safety analysis will be done on the safety population. Although ICMs have been used in other interventional studies to assess arrhythmia, PROMISE-AF will be the first study to assess antiarrhythmic efficacy and safety of a novel rhythm-stabilizing drug after DCC by using ICMs

Construction of an interactive online phytoplasma classification tool, iPhyClassifier, and its application in analysis of the peach X-disease phytoplasma group (16SrIII)

Phytoplasmas, the causal agents of numerous plant diseases, are insect-vector-transmitted, cell-wall-less bacteria descended from ancestral low-G+C-content Gram-positive bacteria in the Bacillus–Clostridium group. Despite their monophyletic origin, widely divergent phytoplasma lineages have evolved in adaptation to specific ecological niches. Classification and taxonomic assignment of phytoplasmas have been based primarily on molecular analysis of 16S rRNA gene sequences because of the inaccessibility of measurable phenotypic characters suitable for conventional microbial characterization. In the present study, an interactive online tool, iPhyClassifier, was developed to expand the efficacy and capacity of the current 16S rRNA gene sequence-based phytoplasma classification system. iPhyClassifier performs sequence similarity analysis, simulates laboratory restriction enzyme digestions and subsequent gel electrophoresis and generates virtual restriction fragment length polymorphism (RFLP) profiles. Based on calculated RFLP pattern similarity coefficients and overall sequence similarity scores, iPhyClassifier makes instant suggestions on tentative phytoplasma 16Sr group/subgroup classification status and ‘Candidatus Phytoplasma’ species assignment. Using iPhyClassifier, we revised and updated the classification of strains affiliated with the peach X-disease phytoplasma group. The online tool can be accessed at http://www.ba.ars.usda.gov/data/mppl/iPhyClassifier.html

A Regional Reduction in Ito and IKACh in the Murine Posterior Left Atrial Myocardium Is Associated with Action Potential Prolongation and Increased Ectopic Activity.

BACKGROUND: The left atrial posterior wall (LAPW) is potentially an important area for the development and maintenance of atrial fibrillation. We assessed whether there are regional electrical differences throughout the murine left atrial myocardium that could underlie regional differences in arrhythmia susceptibility. METHODS: We used high-resolution optical mapping and sharp microelectrode recordings to quantify regional differences in electrical activation and repolarisation within the intact, superfused murine left atrium and quantified regional ion channel mRNA expression by Taqman Low Density Array. We also performed selected cellular electrophysiology experiments to validate regional differences in ion channel function. RESULTS: Spontaneous ectopic activity was observed during sustained 1Hz pacing in 10/19 intact LA and this was abolished following resection of LAPW (0/19 resected LA, P<0.001). The source of the ectopic activity was the LAPW myocardium, distinct from the pulmonary vein sleeve and LAA, determined by optical mapping. Overall, LAPW action potentials (APs) were ca. 40% longer than the LAA and this region displayed more APD heterogeneity. mRNA expression of Kcna4, Kcnj3 and Kcnj5 was lower in the LAPW myocardium than in the LAA. Cardiomyocytes isolated from the LAPW had decreased Ito and a reduced IKACh current density at both positive and negative test potentials. CONCLUSIONS: The murine LAPW myocardium has a different electrical phenotype and ion channel mRNA expression profile compared with other regions of the LA, and this is associated with increased ectopic activity. If similar regional electrical differences are present in the human LA, then the LAPW may be a potential future target for treatment of atrial fibrillation

The determinants of stroke phenotypes were different from the predictors (CHADS2 and CHA2DS2-VASc) of stroke in patients with atrial fibrillation: a comprehensive approach

<p>Abstract</p> <p>Background</p> <p>Atrial fibrillation (AF) is a leading cause of fatal ischemic stroke. It was recently reported that international normalized ratio (INR) levels were associated with infarct volumes. However, factors other than INR levels that affect stroke phenotypes are largely unknown. Therefore, we evaluated the determinants of stroke phenotypes (pattern and volume) among patients with AF who were not adequately anticoagulated.</p> <p>Methods</p> <p>We analyzed data pertaining to consecutive AF patients admitted over a 6-year period with acute MCA territory infarcts. We divided the patients according to DWI (diffusion-weighted imaging) lesion volumes and patterns, and the relationship between stroke predictors (the CHADS₂and CHA₂DS₂-VASc score), systemic, and local factors and each stroke phenotype were then evaluated.</p> <p>Results</p> <p>The stroke phenotypes varied among 231 patients (admission INR median 1.06, interquartile range (IQR) 1.00-1.14). Specifically, (1) the DWI lesion volumes ranged from 0.04-338.62 ml (median 11.86 ml; IQR, 3.07-44.20 ml) and (2) 46 patients had a territorial infarct pattern, 118 had a lobar/deep pattern and 67 had a small scattered pattern. Multivariate testing revealed that the CHADS₂and CHA₂DS₂-VASc score were not related to either stroke phenotype. Additionally, the prior use of antiplatelet agents was not related to the stroke phenotypes. Congestive heart failure and diastolic dysfunction were not associated with stroke phenotypes.</p> <p>Conclusions</p> <p>The results of this study indicated that the determinants of stroke phenotypes were different from the predictors (i.e., CHADS2 and CHA₂DS₂-VASc score) of stroke in patients with AF.</p

An Innovative Platform Merging Elemental Analysis and Ftir Imaging for Breast Tissue Analysis

Histopathology and immunohistology remain the gold standard for breast cancer diagnostic. Yet, these approaches do not usually provide a sufficiently detailed characterization of the pathology. The purpose of this work is to demonstrate for the first time that elemental analysis and Fourier transform infrared spectroscopy microscopic examination of breast tissue sections can be merged into one dataset to provide a single set of markers based on both organic molecules and inorganic trace elements. For illustrating the method, 6 mammary tissue sections were used. Fourier transform infrared (FTIR) spectroscopy images reported a fingerprint of the organic molecules present in the tissue section and laser ablation elemental analysis (LA-ICP-MS) images brought inorganic element profiles. The 6 tissue sections provided 31 106 and 150,000 spectra for FTIR and LA-ICP-MS spectra respectively. The results bring the proof of concept that breast tissue can be analyzed simultaneously by FTIR spectroscopy and laser ablation elemental analysis (LA-ICP-MS) to provide in both case reasonably high resolution images. We show how to bring the images obtained by the two methods to a same spatial resolution and how to use image registration to analyze the data originating from both techniques as one block of data. We finally demonstrates the elemental analysis is orthogonal to all FTIR markers as no significant correlation is found between FTIR and LA-ICP-MS data. Combining FTIR and LA-ICP-MS imaging becomes possible, providing two orthogonal methods which can bring an unprecedented diversity of information on the tissue. This opens a new avenue of tissue section analyses providing unprecedented diagnostic potential.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Discrimination of breast cancer from benign tumours using Raman spectroscopy

Breast cancer is the most common cancer among women worldwide, with an estimated 1.7 million cases and 522,000 deaths in 2012. Breast cancer is diagnosed by histopathological examination of breast biopsy material but this is subjective and relies on morphological changes in the tissue. Raman spectroscopy uses incident radiation to induce vibrations in the molecules of a sample and the scattered radiation can be used to characterise the sample. This technique is rapid and non-destructive and is sensitive to subtle biochemical changes occurring at the molecular level. This allows spectral variations corresponding to disease onset to be detected. The aim of this work was to use Raman spectroscopy to discriminate between benign lesions (fibrocystic, fibroadenoma, intraductal papilloma) and cancer (invasive ductal carcinoma and lobular carcinoma) using formalin fixed paraffin preserved (FFPP) tissue. Haematoxylin and Eosin stained sections from the patient biopsies were marked by a pathologist. Raman maps were recorded from parallel unstained tissue sections. Immunohistochemical staining for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2/neu) was performed on a further set of parallel sections. Both benign and cancer cases were positive for ER while only the cancer cases were positive for HER2. Significant spectral differences were observed between the benign and cancer cases and the benign cases could be differentiated from the cancer cases with good sensitivity and specificity. This study has shown the potential of Raman spectroscopy as an aid to histopathological diagnosis of breast cancer, in particular in the discrimination between benign and malignant tumours.Scopu

A simple model for cell type recognition using 2D-correlation analysis of FTIR images from breast cancer tissue

Breast cancer is the second most common cancer after lung cancer. So far, in clinical practice, most cancer parameters originating from histopathology rely on the visualization by a pathologist of microscopic structures observed in stained tissue sections, including immunohistochemistry markers. Fourier transform infrared spectroscopy (FTIR) spectroscopy provides a biochemical fingerprint of a biopsy sample and, together with advanced data analysis techniques, can accurately classify cell types. Yet, one of the challenges when dealing with FTIR imaging is the slow recording of the data. One cm2 tissue section requires several hours of image recording. We show in the present paper that 2D covariance analysis singles out only a few wavenumbers where both variance and covariance are large. Simple models could be built using 4 wavenumbers to identify the 4 main cell types present in breast cancer tissue sections. Decision trees provide particularly simple models to reach discrimination between the 4 cell types. The robustness of these simple decision-tree models were challenged with FTIR spectral data obtained using different recording conditions. One test set was recorded by transflection on tissue sections in the presence of paraffin while the training set was obtained on dewaxed tissue sections by transmission. Furthermore, the test set was collected with a different brand of FTIR microscope and a different pixel size. Despite the different recording conditions, separating extracellular matrix (ECM) from carcinoma spectra was 100% successful, underlying the robustness of this univariate model and the utility of covariance analysis for revealing efficient wavenumbers. We suggest that 2D covariance maps using the full spectral range could be most useful to select the interesting wavenumbers and achieve very fast data acquisition on quantum cascade laser infrared imaging microscopes. ? 2018 The AuthorsThis work was made possible by a NPRP Award [7 - 1267 - 3?328] from the Qatar National Research Fund (a member of The Qatar Foundation). E.G. is Research Director with the National Fund for Scientific Research (Belgium) . The statements made herein are solely the responsibility of the authors