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Abstract #3999

Diffusion–Based Virtual MR Elastography as a Potential Biomarker for Predicting Recurrence of Hepatocellular Carcinoma

Chen Jiejun1, Sun Wei1, Wang Wentao1, Fu Caixia2, and Rao Shengxiang1
1Zhongshan hospital, Fudan University, Shanghai, China, 2MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China

Synopsis

Keywords: Liver, Liver

Motivation: Preoperative prediction of tumor recurrence is essential for surveillance and management of patients with hepatocellular carcinoma (HCC).

Goal(s): To explore the diagnostic performance of virtual magnetic resonance elastography (vMRE) derived from preoperative diffusion-weighted images in predicting HCC recurrence after hepatectomy.

Approach: Eighty patients who underwent magnetic resonance imaging with a dedicated diffusion-weighted imaging sequence were retrospectively recruited. The parameters derived from vMRE, together with image features, were used to predict tumor recurrence after hepatectomy.

Results: The μdiff values of vMRE and corona enhancement are potential biomarkers for the preoperative prediction of recurrence after hepatectomy in patients with HCC.

Impact: Our results revealed that preoperative diffusion–based virtual magnetic resonance elastography could be used for preoperative prediction of HCC recurrence without using additional hardware, which might help in deciding on treatment and formulating management strategies for patients with HCC.

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