Improving Diagnosis through Digital Pathology: A Proof-of-concept Implementation using Smart Contracts and Decentralized file storage (IPFS) (Preprint)

Abstract

\n BACKGROUND\n Recent advancements in digital pathology resulting from advances in imaging and digitization have increased the convenience and usability of pathology for disease diagnosis, especially in oncology, urology, and gastro-enteric diagnosis. However, despite the possibilities to include low-cost diagnosis and viable telemedicine, remote diagnosis potential, digital pathology is not yet accessible due to expensive storage, data security requirements, and network bandwidth limitations to transfer high-resolution images and associated data. The increase in storage, transmission and security complexity concerning data collection and diagnosis makes it even more challenging to use artificial intelligence algorithms for machine-assisted disease diagnosis. We design and prototype a digital pathology system that uses blockchain-based smart contracts using the Non-fungible Token standard and the Inter-Planetary File System (IPFS) for data storage. Our design remediates shortcomings in the existing digital pathology systems infrastructure, which is centralized. The proposed design is extendable to other fields of medicine that require high-fidelity image and data storage. Our solution is implemented in data systems that can improve access, quality of care and reduce the cost of access to specialized pathological diagnosis, reducing cycle times for diagnosis.\n \n \n OBJECTIVE\n The study s main objectives are to highlight the issues in digital pathology and suggest a software architecture-based blockchain and IPFS create a low-cost data storage and transmission technology.\n \n \n METHODS\n We use the design science research method (DSRM) consisting of six stages to inform our design overall. We innovate over existing public-private designs for blockchains but using a two-layered approach that separates actual file storage from meta-data and data persistence.\n \n \n RESULTS\n Here, we identify key challenges to adopting digital pathology, including challenges concerning long-term storage, the transmission of information, etc. Next, using accepted frameworks in non-fungible token-based intelligent contracts and recent innovations in distributed secure storage, we propose a decentralized, secure, and privacy-preserving digital pathology system. Our design and prototype implementation using Solidity, web3.js, Ethereum, and node.js help us address several challenges facing digital pathology. We demonstrate how our solution that combines non-fungible token (NFT) smart contract standard with persistent decentralized file storage to solve most of the challenges of digital pathology and sets the stage for reducing costs and improving patient care and speed of diagnosis.\n \n \n CONCLUSIONS\n We identify technical limitations that increase costs and reduce mass adoption of digital pathology. We present several design innovations by using standards in NFT decentralized storage to prototype a system. We also present implementation details of a unique security architecture for a digital pathology system. We illustrate how this design can overcome privacy, security, network-based storage, and data transmission limitations. We illustrate how improving these factors sets the stage for improving data quality and standardized application of machine learning and Artificial Intelligence to such data\n \n \n CLINICALTRIAL\n Not applicable\n