Development of an algorithm for automatic classification of right ventricle deformation patterns in arrhythmogenic right ventricular cardiomyopathy

Autor:	Maarten J. Cramer, Arco J. Teske, Pieter A. Doevendans, Karim Taha, Laurens P Bosman, Thomas P. Mast, Marijn H A Groen, Frebus J. van Slochteren, René van Es
Rok vydání:	2020
Předmět:	Heart Ventricles Original Investigations 030204 cardiovascular system & hematology Deformation (meteorology) Best Paper Right ventricular cardiomyopathy 03 medical and health sciences strain 0302 clinical medicine Time frame Humans Medicine Radiology Nuclear Medicine and imaging 030212 general & internal medicine computer algorithm Arrhythmogenic Right Ventricular Dysplasia Original Investigation arrhythmogenic right ventricular cardiomyopathy business.industry Healthy subjects Computer algorithm medicine.anatomical_structure classification Ventricle Mutation Mutation (genetic algorithm) Cardiology and Cardiovascular Medicine Longitudinal deformation business Algorithm Algorithms
Zdroj:	Echocardiography (Mount Kisco, N.y.)
ISSN:	1540-8175 0742-2822
Popis:	Background Different disease stages of arrhythmogenic right ventricular cardiomyopathy (ARVC) can be identified by right ventricle (RV) longitudinal deformation (strain) patterns. This requires assessment of the onset of shortening, (systolic) peak strain, and postsystolic index, which is time‐consuming and prone to inter‐ and intra‐observer variability. The aim of this study was to design and validate an algorithm to automatically classify RV deformation patterns. Methods We developed an algorithm based on specific local characteristics from the strain curves to detect the parameters required for classification. Determination of the onset of shortening by the algorithm was compared to manual determination by an experienced operator in a dataset containing 186 RV strain curves from 26 subjects carrying a pathogenic plakophilin‐2 (PKP2) mutation and 36 healthy subjects. Classification agreement between operator and algorithm was solely based on differences in onset shortening, as the remaining parameters required for classification of RV deformation patterns could be directly obtained from the strain curves. Results The median difference between the onset of shortening determined by the experienced operator and by the automatic detector was 5.3 ms [inter‐quartile range (IQR) 2.7–8.6 ms]. 96% of the differences were within 1 time frame. Both methods correlated significantly with ρ = 0.97 (P
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53b9d18fe6e394dfae96b227c45a8bb9 https://doi.org/10.1111/echo.14671 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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