How to Optimize Connection Between PACS and Clinical Data Warehouse: A Web Service Approach Based on Full Metadata Integration

Abstract

Clinical image data analysis is an active area of research. Integrating such data in a Clinical Data Warehouse (CDW) implies to unlock the PACS and RIS and to address interoperability and semantics issues. Based on specific functional and technical requirements, our goal was to propose a web service (I4DW) that allows users to query and access pixel data from a CDW by fully integrating and indexing imaging metadata. Here, we present the technical implementation of this workflow as well as the evaluation we carried out using a prostate cancer cohort use case. The query mechanism relies on a Dicom metadata hierarchy dynamically generated during the ETL Process. We evaluated the Dicom data transfer performance of I4DW, and found mean retrieval times of 5.94 seconds and 0.9 seconds to retrieve a complete DICOM series from the PACS and all metadata of a series. We could retrieve all patients and imaging tests of the prostate cancer cohort with a precision of 0.95 and a recall of 1. By leveraging the CMOVE method, our approach based on the Dicom protocol is scalable and domain-neutral. Future improvement will focus on performance optimization and de identification.

Opportunities and Obstacles to the Development of Health Data Warehouses in Hospitals in France: The Recent Experience of Comprehensive Cancer Centers

“…Structured data are described with a repository that allows them to be enriched with semantics, thus, making their exploitation or analysis possible. This description can be standard and then shared by several data producers or local, which complicates the interoperability of the systems producing them [ 28 ], for example, in areas such as radiotherapy [ 20 ] or radiology [ 21 ].…”