Hyperspectral and multispectral imaging in digital and computational pathology: a systematic review [Invited]

• Type of Material: Article
• Authors: Samuel Ortega, University of Texas Dallas; Martin Halicek, University of Texas Dallas; Himar Fabelo, University of Las Palmas de Gran Canaria; Gustavo M. Callico, University of Las Palmas de Gran Canaria; Baowei Fei, Emory University
• Language: English
• Date: 2020-06-01
• Publisher: Optica Publishing Group
• Publication Version: Final Published Version
• Copyright Statement: © 2020 Optical Society of America.
• License: Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1364/BOE.386338
• Title of Journal or Parent Work: Biomedical Optics Express
• Volume: 11
• Issue: 6
• Start Page: 3195
• End Page: 3233
• Grant/Funding Information: This research was supported in part by the Cancer Prevention and Research Institute of Texas (CPRIT) grant RP190588 and the U.S. National Institutes of Health (NIH) grants (R01CA156775, R01CA204254, R01HL140325, and R21CA231911).; This research was supported in part by the Canary Islands Government through the ACIISI (Canarian Agency for Research, Innovation and the Information Society), ITHACA project under Grant Agreement ProID2017010164 and by the Spanish Government through PLATINO project (TEC2017-86722-C4-4-R).; This work was completed while Samuel Ortega was beneficiary of a pre-doctoral grant given by the “Agencia Canaria de Investigacion, Innovacion y Sociedad de la Información (ACIISI)” of the “Conserjería de Economía, Industria, Comercio y Conocimiento” of the “Gobierno de Canarias”, which is part-financed by the European Social Fund (FSE) (POC 2014-2020, Eje 3 Tema Prioritario 74 (85%)).
• Keywords: Raman spectroscopy; Science & Technology; Biochemical Research Methods; Mapping spectrometer; Confocal fluorescence; Fine needle aspiration; Radiology, Nuclear Medicine & Medical Imaging; Receptor expression; Androgen receptor; Quantitative morpohtry; Breast cancer; Cell segmentation; Biochemistry & Molecular Biology; Unsupervised segmentation; Life Sciences & Biomedicine; Optics; Physical Sciences
• Research Categories: Health Sciences, Radiology; Health Sciences, Oncology; Biology, Molecular; Chemistry, Biochemistry

Abstract

Hyperspectral imaging (HSI) and multispectral imaging (MSI) technologies have the potential to transform the fields of digital and computational pathology. Traditional digitized histopathological slides are imaged with RGB imaging. Utilizing HSI/MSI, spectral information across wavelengths within and beyond the visual range can complement spatial information for the creation of computer-aided diagnostic tools for both stained and unstained histological specimens. In this systematic review, we summarize the methods and uses of HSI/MSI for staining and color correction, immunohistochemistry, autofluorescence, and histopathological diagnostic research. Studies include hematology, breast cancer, head and neck cancer, skin cancer, and diseases of central nervous, gastrointestinal, and genitourinary systems. The use of HSI/MSI suggest an improvement in the detection of diseases and clinical practice compared with traditional RGB analysis, and brings new opportunities in histological analysis of samples, such as digital staining or alleviating the inter-laboratory variability of digitized samples. Nevertheless, the number of studies in this field is currently limited, and more research is needed to confirm the advantages of this technology compared to conventional imagery.