Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort
Pernille Heimdal Holm1,2, Thomas Hartvig Lindkær Jensen3, Joseph Westaby4
1Section of Forensic Pathology, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
APMIS : Acta Pathologica, Microbiologica, Et Immunologica Scandinavica
|February 26, 2026
Summary
Sudden arrhythmic death syndrome (SADS) shows subtle heart differences detectable by AI histology. These quantitative findings may improve diagnosis and family screening for this cause of sudden cardiac death in young people.
Area of Science:
- Cardiovascular Pathology
- Computational Pathology
- Sudden Death Autopsy
Background:
- Sudden arrhythmic death syndrome (SADS) causes sudden cardiac death in young individuals with structurally normal hearts.
- Current family screening for SADS is limited by challenges in postmortem phenotyping.
- Novel quantitative methods are needed to identify subtle cardiac abnormalities in SADS cases.
Purpose of the Study:
- To investigate subtle morphological differences in SADS hearts using quantitative histology and AI-based cell segmentation.
- To identify discriminating histological features for SADS phenotyping.
- To explore the potential of AI-driven histology in refining SADS diagnosis and understanding underlying mechanisms.
Main Methods:
- Retrospective autopsy study of 77 SADS cases and 41 controls (aged 1-49 years).
- Cardiac tissue analysis using QuPath and deep learning (Quan10) for quantitative histology and cell segmentation.
- Random Forest classification and recursive feature elimination for feature discrimination.
- Genetic analysis for pathogenic variants.
Main Results:
- SADS cases exhibited reduced residual myocardium compared to controls (53% vs. 56%, p=0.02) and in endocardial regions (49% vs. 54%, p<0.001).
- Endocardial and epicardial adipocyte density were identified as key discriminating features.
- AI-driven histology detected morphological differences in hearts previously considered normal, suggesting SADS heterogeneity.
Conclusions:
- Quantitative histology and AI-based image analysis can detect subtle cardiac morphological differences in SADS.
- These advanced techniques hold potential for improving postmortem phenotyping, refining SADS diagnosis, and guiding family screening.
- Findings suggest the existence of subgroups within SADS, warranting further investigation into arrhythmic mechanisms.
