Osteoid Metaplasia in Femoral Artery Plaques Is Associated With the Clinical Severity of Lower Extremity Artery Disease in Men

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Laivuori , M , Tolva , J , Lokki , A I , Linder , N , Lundin , J , Paakkanen , R , Albäck , A , Venermo , M , Mäyränpää , M I , Lokki , M-L & Sinisalo , J 2020 , ' Osteoid Metaplasia in Femoral Artery Plaques Is Associated With the Clinical Severity of Lower Extremity Artery Disease in Men ' , Frontiers in cardiovascular medicine , vol. 7 , 594192 . https://doi.org/10.3389/fcvm.2020.594192

Title: Osteoid Metaplasia in Femoral Artery Plaques Is Associated With the Clinical Severity of Lower Extremity Artery Disease in Men
Author: Laivuori, Mirjami; Tolva, Johanna; Lokki, A. Inkeri; Linder, Nina; Lundin, Johan; Paakkanen, Riitta; Albäck, Anders; Venermo, Maarit; Mäyränpää, Mikko I.; Lokki, Marja-Liisa; Sinisalo, Juha
Contributor: University of Helsinki, HUS Abdominal Center
University of Helsinki, Transplantation Laboratory
University of Helsinki, Transplantation Laboratory
University of Helsinki, Medicum
University of Helsinki, Johan Edvard Lundin / Principal Investigator
University of Helsinki, HUS Heart and Lung Center
University of Helsinki, HUS Abdominal Center
University of Helsinki, Verisuonikirurgian yksikkö
University of Helsinki, HUSLAB
University of Helsinki, Transplantation Laboratory
University of Helsinki, HUS Heart and Lung Center
Date: 2020-12-10
Language: eng
Number of pages: 13
Belongs to series: Frontiers in cardiovascular medicine
ISSN: 2297-055X
URI: http://hdl.handle.net/10138/324653
Abstract: Lamellar metaplastic bone, osteoid metaplasia (OM), is found in atherosclerotic plaques, especially in the femoral arteries. In the carotid arteries, OM has been documented to be associated with plaque stability. This study investigated the clinical impact of OM load in femoral artery plaques of patients with lower extremity artery disease (LEAD) by using a deep learning-based image analysis algorithm. Plaques from 90 patients undergoing endarterectomy of the common femoral artery were collected and analyzed. After decalcification and fixation, 4-μm-thick longitudinal sections were stained with hematoxylin and eosin, digitized, and uploaded as whole-slide images on a cloud-based platform. A deep learning-based image analysis algorithm was trained to analyze the area percentage of OM in whole-slide images. Clinical data were extracted from electronic patient records, and the association with OM was analyzed. Fifty-one (56.7%) sections had OM. Females with diabetes had a higher area percentage of OM than females without diabetes. In male patients, the area percentage of OM inversely correlated with toe pressure and was significantly associated with severe symptoms of LEAD including rest pain, ulcer, or gangrene. According to our results, OM is a typical feature of femoral artery plaques and can be quantified using a deep learning-based image analysis method. The association of OM load with clinical features of LEAD appears to differ between male and female patients, highlighting the need for a gender-specific approach in the study of the mechanisms of atherosclerotic disease. In addition, the role of plaque characteristics in the treatment of atherosclerotic lesions warrants further consideration in the future.
Subject: 3121 General medicine, internal medicine and other clinical medicine
atherosclerosis
lower extremity artery disease (LEAD)
osteoid metaplasia
machine learning
digital pathology
histology
artificial intelligence
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