A histopathological classification scheme for abdominal aortic aneurysm disease
Bruijn, Laura, van Stroe Gómez, Charid, Curci, John, Golledge, Jonathan, Hamming, Jaap, Jones, Gregory, Lee, Regent, Matic, Ljubica, van Rhijn, Connie, Vriens, Patrick, Wågsäter, Dick, Xu, Baohui, Yamanouchi, Dai, and Lindeman, Jan (2021) A histopathological classification scheme for abdominal aortic aneurysm disease. JVS: Vascular Science, 2. pp. 260-273.
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Abstract
Objective: Two consensus histopathological classifications for thoracic aortic aneurysms (TAAs) and inflammatory aortic diseases have been issued to facilitate clinical decision-making and inter-study comparison. However, these consensus classifications do not specifically encompass abdominal aortic aneurysms (AAAs). Given its high prevalence and the existing profound pathophysiologic knowledge gaps, extension of the consensus classification scheme to AAAs would be highly instrumental. The aim of this study was to test the applicability of, and if necessary to adapt, the issued consensus classification schemes for AAAs.
Methods: Seventy-two AAA anterolateral wall samples were collected during elective and emergency open aneurysm repair performed between 2002 and 2013. Histologic analysis (hematoxylin and eosin and Movat Pentachrome) and (semi-quantitative and qualitative) grading were performed in order to map the histological aspects of AAA. Immuno- histochemistry was performed for visualization of aspects of the adaptive and innate immune system, and for a more detailed analysis of atherosclerotic lesions in AAA.
Results: Because the existing consensus classification schemes do not adequately capture the aspects of AAA disease, an AAA-specific 11-point histopathological consensus classification was devised. Systematic application of this classification indicated several universal features for AAA (eg, [almost] complete elastolysis), but considerable variation for other aspects (eg, inflammation and atherosclerotic lesions).
Conclusions: This first multiparameter histopathological AAA consensus classification illustrates the sharp histological contrasts between thoracic and abdominal aneurysms. The value of the proposed scoring system for AAA disease is illustrated by its discriminatory capacity to identify samples from patients with a nonclassical (genetic) variant of AAA disease. (JVSeVascular Science 2021;2:260-73.)
Clinical Relevance: The pathophysiology of abdominal aortic aneurysm (AAA) disease remains an enigma. Histological evaluation is critical for appreciation of the tissue remodeling and spatial aspects of AAA disease. Histopathological classification schemes have been devised for aortic pathology. Unfortunately, these schemes do not specifically address the most common aortic pathology, AAA disease. In order to facilitate interstudy comparisons and pathophysiologic understanding of AAA disease, we here present a multiparameter consensus histopathological AAA classification scheme. The scheme clearly discriminates AAA disease from thoracic aortic aneurysm disease. Systematic implementation of this AAA classification system indicates a substantial biological variation for AAA disease, and stresses the need for adequate group sizes in order to adequately cover the natural variability. Examples illustrating the diagnostic value of the classification system are provided.
Item ID: | 73375 |
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Item Type: | Article (Research - C1) |
ISSN: | 2666-3503 |
Keywords: | abdominal aortic aneurysm; Classification; Histology; Thoracic aortic aneurysm; Vascular remodeling. |
Copyright Information: | Copyright © 2021 by the Society for Vascular Surgery. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/) |
Date Deposited: | 11 May 2022 02:53 |
FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3201 Cardiovascular medicine and haematology > 320199 Cardiovascular medicine and haematology not elsewhere classified @ 100% |
SEO Codes: | 20 HEALTH > 2001 Clinical health > 200105 Treatment of human diseases and conditions @ 100% |
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