Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

Q: What are the key findings of this study?

Sudden arrhythmic death syndrome cases exhibited significantly reduced residual myocardium in overall tissue (53% vs. 56%) and endocardial regions (49% vs. 54%) compared to controls.

Q: What is the clinical evidence from this study?

Study design: Case-Control. Population: Sudden arrhythmic death syndrome (SADS) (n=118). Intervention: Sudden arrhythmic death syndrome (SADS) vs. Age- and sex-matched controls. Primary outcome: Residual myocardium in overall tissue (p=0.02).

Pernille Heimdal Holm; Thomas Hartvig Lindkær Jensen; Joseph Westaby; Mary N. Sheppard; Stine Bøttcher Jacobsen; Mikkel Eriksen Dupont; Jeppe Dyrberg Andersen; Bo Gregers Winkel; Jacob Tfelt-Hansen; Jytte Banner; Kari Joseph Olsen

doi:10.1111/apm.70169

March 1, 2026Open Access

Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

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Key result

Sudden arrhythmic death syndrome linked to ~3 percentage points less residual myocardium vs. controls.

P=0.02
n=118

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Why the study?

Sudden arrhythmic death syndrome is a major cause of sudden cardiac death in young individuals, but despite guideline-recommended family screening, postmortem phenotyping remains challenging.

Does quantitative histology and deep-learning-based image processing identify morphological differences between morphologically normal hearts of SADS cases and matched non-cardiac controls?

Key Points

To investigate subtle morphological and cellular cardiac features in sudden arrhythmic death syndrome compared to non-cardiac controls using automated quantitative histology and deep learning.
Conducted a retrospective autopsy study comparing 77 sudden arrhythmic death syndrome (SADS) cases with 41 age- and sex-matched controls aged 1–49 years who died from trauma or suicide.
Quantified cardiac histology using QuPath and deep learning-based cell segmentation (Quan10), then identified discriminating variables via Random Forest classification and recursive feature elimination.
SADS cases exhibited significantly lower myocardial tissue percentages in total tissue (53% vs. 56%, p = 0.02), the endocardial region (49% vs. 54%, p < 0.001), septum (55% vs. 61%, p = 0.007), and right ventricle (40% vs. 47%, p = 0.002).
The Random Forest model differentiated SADS from controls with an AUC of 0.73, accuracy of 72.4%, sensitivity of 66.7%, and specificity of 78.6%, identifying endocardial adipocyte density as the primary discriminator.
Targeted genetic analysis identified likely pathogenic variants across six SADS cases (PKP2, RBM20, TTN, SCN5A, and DSP) and three control cases (TTN).

Study Design

Type

Case-Control (n=118)

Multicenter

No

Structured PICO

Does quantitative histology and deep-learning-based image processing identify morphological differences between morphologically normal hearts of SADS cases and matched non-cardiac controls?

P

Population

118 autopsy cases, including 77 individuals aged 1-49 years who died from sudden arrhythmic death syndrome and 41 age- and sex-matched controls who died from trauma or suicide, analyzed for quantitative histological differences.

E

Exposure

Quantitative histology and deep-learning-based cell segmentation (QuPath and Quan10) applied to postmortem cardiac tissue.

C

Comparator

Age- and sex-matched control group with morphologically normal hearts who died of accidental or suicidal causes without cardiac disease.

O

Outcome

Morphological differences in cardiac tissue (percentage of myocardium, fibrosis, and adipocyte density) between SADS cases and controls.surrogate

Main Result

Absolute Event Rate: 53% vs 56%

p-value: p=0.02

Limitations

Retrospective autopsy design with potential selection bias.
Did not include sampling of the right ventricular outflow tract (RVOT).
Variable tissue quality and suboptimal picrosirius red staining due to formalin-fixed paraffin-embedded tissue degradation.
Variable reliability of medical history data regarding substance abuse and psychiatric diseases.
Limited sampling that did not include the right ventricular outflow tract (RVOT).
Reliance on retrospective clinical data regarding substance abuse and psychiatric diseases from police reports and relatives, which varies in reliability.
Tissue quality issues with some FFPE samples showing faint staining or degradation.
Potential confounding by extreme outliers with low myocardial percentages due to staining variability or papillary muscle attachment sites within endocardial regions.

Implication

Deep learning-based quantitative histology can detect subtle but significant morphological differences, such as reduced myocardium and altered adipocyte density, in the previously considered structurally normal hearts of SADS victims.

Abstract

Sudden arrhythmic death syndrome (SADS) is a major cause of sudden cardiac death in young individuals, characterized by structurally normal hearts and negative toxicology. Although guidelines recommend family screening, phenotyping remains challenging. This study applied quantitative histology and deep-learning-based cell segmentation to investigate morphological features in SADS compared to controls. We conducted a retrospective autopsy study of 77 SADS cases and 41 age- and sex-matched controls (aged 1-49 years) who died from trauma or suicide. Cardiac tissue was analyzed using QuPath and deep learning-based image processing (Quan10). Random Forest classification and recursive feature elimination were used to identify discriminating features. Quantitative analysis found subtle but significant morphological differences. SADS cases had reduced residual myocardium in overall tissue (53% vs. 56%, p = 0.02) and endocardial regions (49% vs. 54%, p < 0.001). Endocardial and epicardial adipocyte density were key discriminators in the model. Genetic analysis identified pathogenic variants in six cases and three controls. AI-driven histology detected differences in hearts previously considered normal, suggesting subgroups within SADS. These findings support the use of quantitative tools in postmortem phenotyping, with potential to refine diagnosis, guide family screening, and improve understanding of arrhythmic mechanisms.

Discussion

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Cite This Study

Holm et al. (2026) conducted a case-control in Sudden arrhythmic death syndrome (SADS) (n=118). Sudden arrhythmic death syndrome (SADS) vs. Age- and sex-matched controls was evaluated on Residual myocardium in overall tissue (p=0.02). Sudden arrhythmic death syndrome cases exhibited significantly reduced residual myocardium in overall tissue (53% vs. 56%) and endocardial regions (49% vs. 54%) compared to controls.

synapsesocial.com/papers/69a3d873ec16d51705d2f642 https://doi.org/10.1111/apm.70169

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Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

Figures

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

Figures

Key Points

Study Design

Structured PICO

Main Result

Limitations

Implication

Abstract

Discussion

Cite This Study

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