Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/28674
Title: Detection and Quantification of Myocardial Fibrosis Using Stain-Free Infrared Spectroscopic Imaging.
Austin Authors: Zimmermann, Eric;Mukherjee, Sudipta S;Falahkheirkhah, Kianoush;Gryka, Mark C;Kajdacsy-Balla, Andre;Hasan, Wohaib;Giraud, George;Tibayan, Fred;Raman, Jai S ;Bhargava, Rohit
Affiliation: Surgery (University of Melbourne)
Center for Developmental Health, Oregon Health & Science University, Portland
Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign, Urbana
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana
Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana
Department of Surgery, St Vincent's Hospital, University of Melbourne, Victoria, Australia
Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana
Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign, Urbana
Department of Pathology, University of Illinois at Chicago, Chicago
Department of Pathology and Laboratory Medicine, Cedars-Sinai, Los Angeles, California
Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana
Issue Date: 1-Dec-2021
Publication information: Archives of Pathology & Laboratory Medicine 2021; 145(12): 1526-1535
Abstract: Myocardial fibrosis underpins a number of cardiovascular conditions and is difficult to identify with standard histologic techniques. Challenges include imaging, defining an objective threshold for classifying fibrosis as mild or severe, and understanding the molecular basis for these changes. To develop a novel, rapid, label-free approach to accurately measure and quantify the extent of fibrosis in cardiac tissue using infrared spectroscopic imaging. We performed infrared spectroscopic imaging and combined that with advanced machine learning-based algorithms to assess fibrosis in 15 samples from patients belonging to the following 3 classes: (1) patients with nonpathologic (control) donor hearts, (2) patients undergoing transplant, and (3) patients undergoing implantation of a ventricular assist device. Our results show excellent sensitivity and accuracy for detecting myocardial fibrosis, as demonstrated by a high area under the curve of 0.998 in the receiver operating characteristic curve measured from infrared imaging. Fibrosis of various morphologic subtypes were demonstrated with virtually generated picrosirius red images, which showed good visual and quantitative agreement (correlation coefficient = 0.92, ρ = 7.76 × 10-15) with stained images of the same sections. Underlying molecular composition of the different subtypes was investigated with infrared spectra showing reproducible differences presumably arising from differences in collagen subtypes and/or crosslinking. Infrared imaging can be a powerful tool in studying myocardial fibrosis and gleaning insights into the underlying chemical changes that accompany it. Emerging methods suggest that the proposed approach is compatible with conventional optical microscopy, and its consistency makes it translatable to the clinical setting for real-time diagnoses as well as for objective and quantitative research.
URI: https://ahro.austin.org.au/austinjspui/handle/1/28674
DOI: 10.5858/arpa.2020-0635-OA
ORCID: 0000-0002-7691-4779
Journal: Archives of Pathology & Laboratory Medicine
PubMed URL: 33755723
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/33755723/
Type: Journal Article
Appears in Collections:Journal articles

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