Abstract #3424

User-defined, scanner-integrated, and real-time MRI image analysis in a cloud-based computing environment

Refaat E Gabr¹, William J Allen², Getaneh B Tefera¹, Xiaojun Sun¹, Renjie He¹, Manickam Kumaravel¹, Matthew W Vaughn², and Ponnada A Narayana¹

¹Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX, United States, ²Texas Advacnced Computing Center, University of Texas at Austin, Austin, TX, United States

To enhance the utility of quantitative MRI, we propose a flexible platform for high-performance cloud computing integrated with the MRI scanner. Jetstream, an NSF-sponsored open science platform for high-performance computing resources, was integrated into a clinical 3.0T MRI system for executing user-defined image analysis using the graphical pipeline environment (GRAPE) tool. Integration was achieved through the Agave platform. This framework was used for real-time quantitative T1 mapping for cartilage tissue assessment. Seamless scanner integration enabled immediate access to the results to the interpreting clinician, providing valuable quantitative information which can be incorporated in clinical practice.

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