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Quantifying Cardiac Tissue Composition Using QuPath and Cellpose: An Accessible Approach to Postmortem Diagnosis
Pernille Heimdal Holm1, Kristine Boisen Olsen1, Richard Denis Maxime De Mets2
1Section of Forensic Pathology, Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Insights
An automated pipeline quantifies cardiac tissue changes postmortem, aiding diagnosis of arrhythmogenic cardiomyopathy. This method offers a free, reproducible template for unbiased evaluation of cardiac diseases.
Area of Science:
- Forensic Pathology
- Cardiovascular Pathology
- Digital Pathology
Background:
- Sudden cardiac death often presents as the first symptom of underlying heart disease.
- Diagnosing arrhythmogenic cardiomyopathy postmortem is challenging due to variable structural changes.
- Concealed cardiomyopathy, diagnosed by genotype, lacks definitive postmortem structural findings.
Purpose of the Study:
- To develop and validate an automated digital pathology pipeline for quantifying postmortem cardiac tissue.
- To assess myocardial fibrosis, residual myocardium, and adipocytes in postmortem cardiac samples.
- To establish a reproducible method for unbiased postmortem cardiac disease evaluation.
Main Methods:
- An automated pipeline using QuPath and Cellpose was developed for image analysis.
- Picrosirius red staining was used to quantify collagen, myocardium, and adipocytes.
- The pipeline was tested on cardiac tissues from autopsied individuals, including arrhythmogenic cardiomyopathy cases and controls.
Main Results:
- The automated pipeline successfully quantified collagen, myocardium, and adipocytes in postmortem cardiac tissue.
- This method provides a quantitative approach to analyzing reactive cardiac changes.
- The developed pipeline is free, easy to implement, and serves as a template for other research.
Conclusions:
- The automated pipeline offers a novel, unbiased method for postmortem cardiac tissue analysis.
- This approach can aid in developing quantitative diagnostic criteria for postmortem cardiac diseases.
- The method facilitates efficient evaluation of cardiac measurements, particularly for rare conditions like arrhythmogenic cardiomyopathy.
Abstract:
Sudden death can be the first symptom of cardiac disease, and establishing a precise postmortem diagnosis is crucial for genetic testing and follow-up of relatives. Arrhythmogenic cardiomyopathy is a structural cardiomyopathy that can be challenging to diagnose postmortem because of differences in structural findings and propagation of the disease at the time of death. Cases can have minimal or no structural findings and later be diagnosed according to genotype, known as concealed cardiomyopathy. Postmortem diagnosis often lacks clinical information, whereas antemortem diagnosis is based on paraclinical investigations that cannot be performed after death. However, the entire substrate is available, which is unique to postmortem diagnosis and research and can provide valuable insights when adding new methods. Reactive changes in the heart, such as myocardial fibrosis and fat, are significant findings. The patterns of these changes in various diseases are not yet fully understood and may be limited by sampling material and conventional microscopic diagnostics. We demonstrate an automated pipeline in QuPath for quantifying postmortem picrosirius red cardiac tissue for collagen, residual myocardium, and adipocytes by integrating Cellpose into a versatile pipeline. This method was developed and tested using cardiac tissues from autopsied individuals. Cases diagnosed with arrhythmogenic cardiomyopathy and age-matched controls were used for validation and testing. This approach is free and easy to implement by other research groups using this paper as a template. This can potentially lead to the development of quantitative diagnostic criteria for postmortem cardiac diseases, eliminating the need to rely on diagnostic criteria from endomyocardial biopsies that are not applicable to postmortem specimens. We propose that this approach serves as a template for creating a more efficient process for evaluating postmortem cardiac measurements in an unbiased manner, particularly for rare cardiac diseases.
