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Thin-slice Two-dimensional T2-weighted Imaging with Deep Learning-based Reconstruction: Improved Lesion Detection in the Brain of Patients with Multiple Sclerosis by Masatoshi Iwamura; Satoru Ide; Kenya Sato; Akihisa Kakuta; Soichiro Tatsuo; Atsushi Nozaki; Tetsuya Wakayama; Tatsuya Ueno; Rie Haga; Misako Kakizaki; Yoko Yokoyama; Ryoichi Yamauchi; Fumiyasu Tsushima; Koichi Shibutani; Masahiko Tomiyama; Shingo Kakeda is a Medicine article available to read on EtoBox.

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## Purpose Brain MRI with high spatial resolution allows for a more detailed delineation of multiple sclerosis (MS) lesions. The recently developed deep learning-based reconstruction (DLR) technique enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice 2D MRI. We, therefore, assessed the diagnostic value of 1 mm-slice-thickness 2D T2-weighted imaging (T2WI) with DLR (1 mm T2WI with DLR) compared with conventional MRI for identifying MS lesions. ## Methods Conventional MRI (5 mm T2WI, 2D and 3D fluid-attenuated inversion recovery) and 1 mm T2WI with DLR (imaging time: 7 minutes) were performed in 42 MS patients. For lesion detection, two neuroradiologists counted the MS lesions in two reading sessions (conventional MRI interpretation with 5 mm T2WI and MRI interpretations with 1 mm T2WI with DLR). The numbers of lesions per region category (cerebral hemisphere, basal ganglia, brain stem, cerebellar hemisphere) were then compared between the two reading sessions. ## Results For the detection of MS lesions by 2 neuroradiologists, the total number of detected MS lesions was significantly higher for MRI interpretation with 1 mm T2

Who reads Thin-slice Two-dimensional T2-weighted Imaging with Deep Learning-based Reconstruction: Improved Lesion Detection in the Brain of Patients with Multiple Sclerosis?

Author

Masatoshi Iwamura; Satoru Ide; Kenya Sato; Akihisa Kakuta; Soichiro Tatsuo; Atsushi Nozaki; Tetsuya Wakayama; Tatsuya Ueno; Rie Haga; Misako Kakizaki; Yoko Yokoyama; Ryoichi Yamauchi; Fumiyasu Tsushima; Koichi Shibutani; Masahiko Tomiyama; Shingo Kakeda

Publisher

Japanese Society for Magnetic Resonance in Medicine

Published

2023

Language

EN

Field

Medicine (Health Sciences)