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Abstract #4331

Simultaneously T2 and T2* mapping via MOLED acquisition and deep learning for oxygen extraction fraction measurement

Zejun Wu1, Qinqin Yang1, Nuowei Ge1, Jiechao Wang1, Zhigang Wu2, Liangjie Lin2, Liuhong Zhu3, Jianjun Zhou3, Jianfeng Bao4, Shuhui Cai1, and Congbo Cai1
1Department of Electronic Science, Xiamen University, Xiamen, China, 2Clinical & Technical Support, Philips Healthcare, Shenzhen, China, 3Department of Radiology, Zhongshan Hospital Fudan University Xiamen Branch, Xiamen, China, 4Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China

Synopsis

Keywords: Signal Modeling, Data Analysis, OEF

Motivation: Quantitative MRI for the measurement of oxygen extraction fraction (OEF) offers the advantage of being radiation-free. However, the quantification of T2 and T2 parameters still suffers from long acquisition time, especially in dynamic imaging.

Goal(s): To evaluate the applicability of ultrafast dynamic multiple overlapping-echo detachment (MOLED) imaging for OEF research.

Approach: The MOLED imaging was utilized for rapidly and synchronously mapping T2 and T2 to dynamically track OEF changes during both breathing and breath-holding conditions.

Results: The time envelope of mean OEF under both breathing and breath-holding is in agreement with the literature reported.

Impact: Owing to its fast and dynamic imaging capabilities, the multiple overlapping-echo detachment (MOLED) T2-T2* acquisition has shown great potential in the quantitative measurement of the brain's oxygen metabolism, which holds significant relevance in assisting the diagnosis of diseases.

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Keywords