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Abstract #3520

Improved fat suppression of head and neck MRI using 3D modified mDixon-TSE with deep learning constrained Compressed SENSE.

Yutaka Hamatani1, Masami Yoneyama2, Yasutomo Katsumata2, Michinobu Nagao3, Yasuhiro Goto1, Isao Shiina1, Kazuo Kodaira1, Takumi Ogawa1, Mana Kato1, and Shuji Sakai3
1Department of Radiological Services, Tokyo Women's Medical University Hospital, Tokyo, Japan, 2Philips Japan, Tokyo, Japan, 3Department of Diagnostic imaging & Nuclear Medicine, Tokyo Women's Medical University Hospital, Tokyo, Japan

Synopsis

Keywords: Fat & Fat/Water Separation, Fat and Fat/Water Separation

Motivation: Conventional 3D T1WI in head and neck MRI has difficulty in obtaining uniform fat suppression images within a feasible examination time.

Goal(s): The purpose of this study is to realize a 3D MRI of the head and neck region with uniform fat suppression.

Approach: We evaluated the feasibility of high-resolution MRI with uniform fat suppression in the orbit and larynx with 3D 3-point mDixon TSE using Deep Learning constrained Compressed SENSE (CS-AI).

Results: The 3D 3-point mDixon TSE with CS-AI was able to provide high-resolution images of the orbit and larynx with robust fat suppression within a feasible scan time.

Impact: 3D 3-point mDixon TSE with CS-AI provides high-resolution MRI images with uniform fat suppression. This technique is expected to accurately delineate small lesions and tissue structures in the head and neck region.

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Keywords