# Integrating medical imaging datasets with blockchain wallets: A case study on ARDS-COVID19 patients

## TL;DR

This paper introduces a blockchain-based system that gives patients control over their medical imaging data, improving access and security in critical care settings.

## Contribution

A novel blockchain-enabled architecture for patient-controlled medical imaging data integration using verifiable credentials and FHIR compliance.

## Key findings

- The system reduced image access time by 67% compared to traditional systems.
- Unauthorized access was completely blocked in the validation scenario.
- Clinicians reported high satisfaction with the system's usability.

## Abstract

Medical imaging plays a critical role in diagnosing and managing acute conditions such as Acute Respiratory Distress Syndrome (ARDS), particularly in intensive care settings. However, radiological data are often siloed across Picture Archiving and Communication Systems (PACS), with limited interoperability, traceability, and patient control. This paper proposes and validates a blockchain-enabled architecture that integrates radiological imaging data into a patient-controlled digital wallet (BioWallet) ecosystem. The system combines verifiable credentials, decentralized identifiers (DIDs), and a FHIR-compliant backend to ensure secure, auditable, and standards-based access to DICOM images and associated metadata. The ledger stores only consent and audit hashes, while clinical data remain off-chain and correctable within FHIR/EHR systems, ensuring auditability without hindering rectification. A validation scenario replicating an ICU emergency was conducted using synthetic ARDS-COVID19 cases to assess latency, consent enforceability, and user experience. Results showed a 67% reduction in image access time compared to traditional systems, 100% success in blocking unauthorized access, and high clinician satisfaction. The architecture supports FAIR-compliant reuse of annotated imaging datasets, enhances transparency in image-driven research, and aligns with GDPR and future European digital identity frameworks. This work demonstrates the feasibility and value of a decentralized, patient-centric approach to imaging data governance in high-stakes clinical environments.