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Abstract #2261

Artificial neural network derived myelin water fraction map with multi-echo gradient echo signal: brain development from infants to adults.

Hyun Gi Kim1, Jae Eun Song2, Dongyeob Han3, Jee Young Kim1, Se Won Oh1, and Dong-Hyun Kim2
1Radiology, The Catholic University of Korea, Seoul, Korea, Republic of, 2Yonsei University, Seoul, Korea, Republic of, 3Siemens Healthcare, Seoul, Korea, Republic of

Myelin water fraction (MWF) values were obtained by an artificial neural network (ANN-MWF) and complex model fitting (CF-MWF) with 3D multi-echo gradient-echo (mGRE) signal. Linear regression test showed high correlation between ANN-MWF and CF-MWF values (R2 = 0.802, p < .001). Bland-Altman plot showed higher ANN-MWF values compared to CF-MWF values in the areas with high MWF values. The ANN-MWF values in the white matter showed a high association with age (R2 = 0.821, p =.005).

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