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A Hybrid PACS/FHIR Model for Clinical Genomic Data Management of Cardiomyopathies and Channelopathies: Standardized VCF Archiving for Hereditary Heart Disease

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A Hybrid PACS/FHIR Model for Clinical Genomic Data Management of Cardiomyopathies and Channelopathies: Standardized VCF Archiving for Hereditary Heart Disease

Paolo Marcheschi 1,* Stefano Dalmiani 1 Maria Pisani 1 Martina Modena 2,3 Gunter Zeilinger 4 Vrinda Nayak 4 Divon Mordechai Lan 5 Simona Vittorini 3 Nicoletta Botto 3 Marcel Swennenhuis 4

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1
Reparto BITE, G. Monasterio Foundation, CNR-Regione Toscana, via G. Moruzzi 1, 56124 Pisa, Italy
2
Interdisciplinary Center for Health Sciences, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
3
Molecular Cardiology Laboratory, G. Monasterio Foundation, Ospedale del Cuore, CNR-Regione Toscana, via Aurelia Sud, 54100 Massa, Italy
4
J4care GmbH Enzersdorfer Straße 7, 2340 Mödling, Austria
5
Genozip Limited, Hong Kong, China
*
Authors to whom correspondence should be addressed.

Received: 18 March 2026 Revised: 10 July 2026 Accepted: 13 August 2026 Published: 30 September 2026

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© 2026 The authors. This is an open access article under the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

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Cardiovasc. Sci. 2026, 3(4), 10014; DOI: 10.70322/cvs.2026.10014
ABSTRACT: The precise diagnosis and lifelong management of hereditary heart diseases, particularly cardiomyopathies and channelopathies, are increasingly dependent on the rapid analysis of massive genomic data generated by Next-Generation Sequencing (NGS). This reliance creates a critical challenge: securely and efficiently integrating large Variant Call Format (VCF) files into existing hospital information systems. This technical hurdle must be overcome to realize the promise of personalized cardiovascular medicine. The ability to sequence the human genome has ushered in a new era of personalized medicine, particularly within the field of precision cardiology. By gaining a thorough understanding of each patient’s genetic profile, physicians can now move beyond generalized care to tailor treatment plans to the individual. In clinical follow-up, genomic profiling has become essential to: (1) Diagnose genetic disorders, specifically Inherited Arrhythmias and Cardiomyopathies. (2) Perform family cascade screening to identify at-risk relatives. (3) Contribute to risk stratification for Sudden Cardiac Death (SCD) in the genes for which gene-specific risk models have been validated. (4) Guide life-saving interventions, such as determining the precise timing for Implantable Cardioverter-Defibrillator (ICD) placement. The ability to quickly and easily access all pertinent patient data is the main benefit of an Electronic Health Record (EHR). In this work, we will show how electronic health record systems (EHRS) can access and use genomic information in clinical care, using compression to enable fast, standardized storage and retrieval of data with tools available in a standard hospital setting, and leveraging the corresponding PACS functionality. By storing genomics data in a central repository accessible to EHR systems, healthcare providers can access the data when they need it. This can help to shorten the time spent diagnosing and treating patients. This approach was experimentally implemented and evaluated using the clinical genomic dataset from the FTGM Molecular Cardiology Laboratory, which routinely performs NGS for patients with hereditary heart disease. The J4CARE VNA PACS, based on the Open Source DICOM archive DCM4CHEE Archive 5.x, was selected as the repository for this experimental platform.
Keywords: Electronic Health Records (EHR); Picture Archiving and Communication Systems (PACS); DNA sequencing; Personalized medicine; Genomic information; Clinical care; Fast storage and retrieval of data; Standardized way of storing data; Compression; Central repository for genomics data; Efficiency of healthcare delivery
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