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Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis

Posted by on Friday, February 1, 2013 in Informatics / Big Data, Neuroimaging.

Yurui Gao, Scott S. Burns, Carolyn B. Lauzon, Andrew Fong, David A. Twillie, Michael Wirt, Marc A. Zola, Bret W. Logan, Adam W. Anderson, Bennett A. Landman. “Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2013. Oral Presentation. †

Full text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877247/?report=classic

Abstract

Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.

Overview of the integrated system. Multi-modal DICOM scans (upper left) are pushed to the XNAT/PACS server (upper right) via dcm4che tools. Verified DICOM scans are pulled and distributed to the cluster (bottom right) for further conversion, processing, and analysis by PyXNAT package scripts. The output results are pushed back for storage on XNAT. The online database REDCap (bottom left) provides/stores related information to/from XNAT. Black arrows indicate the directions of the data flow.
Overview of the integrated system. Multi-modal DICOM scans (upper left) are pushed to the XNAT/PACS server (upper right) via dcm4che tools. Verified DICOM scans are pulled and distributed to the cluster (bottom right) for further conversion, processing, and analysis by PyXNAT package scripts. The output results are pushed back for storage on XNAT. The online database REDCap (bottom left) provides/stores related information to/from XNAT. Black arrows indicate the directions of the data flow.

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