Abstract #0064

Multi-site Multi-vendor Randomized Controlled Trial of Quantitative Knee MRI using a Novel MSK Relaxometry Phantom

Jeehun Kim^1,2, Zhiyuan Zhang^1,2,3, Richard Lartey^1,2, Mei Li^1,2, Stefan Zbyn^1,2, Sercan Tosun^1,2,4, Stephen E. Russek⁵, Karl F. Stupic⁵, Cassandra M. Stoffer⁵, Kathryn E. Keenan⁵, David Rutkowski⁶, Jeff Kammerman⁶, Jean H. Brittain⁶, Carl S. Winalski^1,2,4, and Xiaojuan Li^1,2,4

¹Program of Advanced Musculoskeletal Imaging (PAMI), Cleveland Clinic, Cleveland, OH, United States, ²Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States, ³Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ⁴Department of Diagnostic Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ⁵National Institute of Standards and Technology (NIST), Boulder, CO, United States, ⁶Calimetrix, Madison, WI, United States

Synopsis

Keywords: Phantoms, Phantoms, Multi-site trial, Quantitative Relaxometry

Motivation: Quantitative MRI measurements require careful quality assurance due to their sensitivity to factors such as B0 and B1 inhomogeneity.

Goal(s): Set up a robust and rigorous workflow for QA using a novel MSK MRI relaxometry phantom.

Approach: The phantom was used to standardize the scan protocol and harmonize scanner-related variations of a total of ten 3-Tesla MR scanners (two vendors: GE and Siemens) from nine sites of the PIKASO trial.

Results: We were able to achieve less than 4% inter-site inter-vendor coefficient of variation (CV) with inversion recovery T1, single-echo spin-echo T2, and MAPSS T2 and T1rho.

Impact: We established a QA process for knee MRI relaxometry using a novel MSK relaxometry phantom for large-scale multi-site studies. By identifying discrepancies in measurements during the study, the QA process will ensure data quality in multi-site studies.

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