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Abstract #0172

Evaluation of the Diagnostic Performance of Weighted Diffusion Subtraction (WDS) in Differentiating Uterine Sarcomas from Uterine Myomas

Yoshie Omiya1, Koichi Oshio1, Hu Jiajing1, Katsuhiro Sano1, Shigeki Aoki1, and Ryohei Kuwatsuru1
1Juntendo University Hospital, Tokyo, Japan

Synopsis

Keywords: Pelvis, Pelvis, Diffusion Analysis & Visualization

Motivation: Distinguishing uterine sarcomas from benign myomas poses a challenge with conventional ADC due to overlapping values resulting from the T2 shine-through and blackout effects.

Goal(s): To assess diagnostic performance of Weighted Diffusion Subtraction (WDS) , an emerging computed diffusion-weighted imaging technique that aims to address the effects.

Approach: A retrospective study analyzed MRI data from 38 patients with uterine sarcomas and 38 with myomas using WDS and ADC, comparing their diagnostic performances statistically.

Results: WDS enhanced tissue contrast and offered substantially improved differentiation between lesions, resulting in higher diagnostic accuracy compared to conventional ADC.

Impact: This study demonstrates that WDS significantly improves the differentiation of uterine sarcomas from myomas. These findings may enhance diagnostic accuracy and patient management, encourage the clinical adoption of WDS, and inspire further research into its use for other challenging diagnoses.

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