Recent studies have indicated that multiphase postmortem computed tomography angiography (MPMCTA) allows detection of a pathological enhancement of the myocardium in regions that correlate with the localization of the infarction at histology. The aim of this study was to verify this hypothesis by examining MPMCTA images in cases of myocardial infarction. Therefore, we investigated 10 autopsy cases where death was attributed to myocardial infarction or which showed cardiovascular pathology. As a control group, we selected 10 cases of non-natural (namely, not cardiac) death. The MPMCTA was performed in both groups to ascertain whether a pathological enhancement could be observed. We detected a myocardial enhancement in all cardiac death cases, in the same region that showed infarction at histology. No enhancement was observed in control cases. These results have important implications in the routine management of sudden cardiac death cases. In fact, MPMCTA can not only orient about the cause of death before autopsy, but can especially help to identify affected regions for guiding and improving the sampling for microscopic examination.
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Pharmacoecon Open
January 2025
Optimax Access Ltd, Kenneth Dibben House, Enterprise Rd, Chilworth, Southampton University Science Park, Southampton, UK.
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Stanford Cardiovascular Institute, Stanford, CA, USA.
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Endocrine Division, Department of Medicine, Centre hospitalier de l'Université de Montréal (CHUM), Montreal, Québec, Canada.
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January 2025
Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA.
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January 2025
School of Design, Hunan University, Changsha, 410082, China. Electronic address:
The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to localize myocardial infarction (MI) that is characterized by abnormal waveform patterns on the ECG. MI is a serious cardiovascular disease, and accurate, timely diagnosis is crucial for preventing severe outcomes. Current ECG analysis methods mainly rely on intra- and inter-lead feature extraction, but most models overlook the medical knowledge relevant to disease diagnosis.
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