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Abstract #3717

Optimizing and Evaluating Fast 3D MulTiPlex (MTP) Imaging for Infant Brain Imaging

Zhuoyang Gu1, Xinyi Cai1, Lixuan Zhu1, Weijia Zhang1, Qing Yang1, Tianli Tao1, Weijun Zhang2, Yongquan Ye3, Dinggang Shen1,4,5, Xiaopeng Zong1, and Han Zhang1,5
1School of Biomedical Engineering, ShanghaiTech University, Shanghai, China, 2United Imaging Healthcare, Shanghai, China, 3United Imaging Healthcare America, Houston, TX, United States, 4United Imaging Intelligence, Shanghai, China, 5Shanghai Clinical Research and Trial Center, Shanghai, China

Synopsis

Keywords: Quantitative Imaging, Quantitative Imaging, Multiparametric Imaging, Infant Brain Imaging

Motivation: The novel MulTiPlex (MTP) technique can generate high-resolution, multi-contrast, qualitative/quantitative images, but its reliability and potential for infant study have not been investigated.

Goal(s): To optimize MTP parameters and evaluate its reliability and validity for infant study.

Approach: n this study, we systematically assessed MTP’s test-retest reliability, compared MTP with varied accelerating rates using AI-assisted Compressed Sensing (ACS), followed by a comprehensive appraisal of its applicability in infant brain imaging, with both qualitative and quantitative methods.

Results: The findings indicate that MTP exhibits commendable reliability and holds significant promise for building large infant MRI database.

Impact: MTP generates assorted images with varied spectrum of contrasts and precious quantitative images that take hours to acquire conventionally. Our established MTP protocol combines these merits with fast acquisition, warranting its significant usefulness in infant development and clinical studies.

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