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Abstract #4619

Comparison of Quantitative Artifact Level in TGRAPPA and TSENSE Reconstruction During Deep Breathing

Mihaela Jekic1, Yu Ding2, Yiu-Cho Chung3, Subha V. Raman4, Jennifer Dickerson4, Sven Zuehlsdorff3, Sonia Nielles-Vallespin3, Orlando P. Simonetti

1Biomedical Engineering, The Ohio State University, Columbus, OH, USA; 2Davis Heart and Lung Research Institute, The Ohio State University; 3Siemens Healthcare; 4The Ohio State University Medical Center

We quantitatively compared the artifact performance of TGRAPPA and TSENSE real-time cine imaging under the condition of deep breathing, which can cause the chest wall to move in and out of the FOV and also can create a mismatch between the coil sensitivity map and the actual coil position. We applied an autocorrelation-based approach to quantify the artifacts in 30 myocardial slices, exploiting their spatially fixed nature at 1/3 and 2/3 FOV for rate 3 acceleration. We found that TGRAPPA performed better than TSENSE in terms of quantitative artifact level, which was in agreement with qualitative physician-assigned artifact scores.