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A Nomogram of Magnetic Resonance Imaging for Preoperative Assessment of Microvascular Invasion and Prognosis of Hepatocellular Carcinoma.
Wang, Lili; Zhang, Yanyan; Li, Junfeng; Guo, Shunlin; Ren, Jialiang; Li, Zhihao; Zhuang, Xin; Xue, Jingmei; Lei, Junqiang.
Affiliation
  • Wang L; First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
  • Zhang Y; Department of Radiology, First Hospital of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
  • Li J; Department of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, 100069, China.
  • Guo S; First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
  • Ren J; Department of Infectious Diseases, Institute of Infectious Diseases, First Hospital of Lanzhou University, Chengguan District, Donggang Road No. 1, Lanzhou, 730000, China.
  • Li Z; First Clinical Medical School of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
  • Zhuang X; Department of Radiology, First Hospital of Lanzhou University, Chengguan District, Donggangxi Road No. 1, Lanzhou, 730000, China.
  • Xue J; GE Healthcare China, Daxing District, Tongji South Road No. 1, Beijing, 100176, China.
  • Lei J; GE Healthcare China, Yanta District, 12th Jinye Road, Xi'an, 710076, Shanxi, China.
Dig Dis Sci ; 68(12): 4521-4535, 2023 12.
Article in En | MEDLINE | ID: mdl-37794295
ABSTRACT

BACKGROUND:

Microvascular invasion (MVI) is a predictor of recurrence and overall survival in hepatocellular carcinoma (HCC), the preoperative diagnosis of MVI through noninvasive methods play an important role in clinical treatment.

AIMS:

To investigate the effectiveness of radiomics features in evaluating MVI in HCC before surgery.

METHODS:

We included 190 patients who had undergone contrast-enhanced MRI and curative resection for HCC between September 2015 and November 2021 from two independent institutions. In the training cohort of 117 patients, MVI-related radiomics models based on multiple sequences and multiple regions from MRI were constructed. An independent cohort of 73 patients was used to validate the proposed models. A final Clinical-Imaging-Radiomics nomogram for preoperatively predicting MVI in HCC patients was generated. Recurrence-free survival was analyzed using the log-rank test.

RESULTS:

For tumor-extracted features, the performance of signatures in fat-suppressed T1-weighted images and hepatobiliary phase was superior to that of other sequences in a single-sequence model. The radiomics signatures demonstrated better discriminatory ability than that of the Clinical-Imaging model for MVI. The nomogram incorporating clinical, imaging and radiomics signature showed excellent predictive ability and achieved well-fitted calibration curves, outperforming both the Radiomics and Clinical-Radiomics models in the training and validation cohorts.

CONCLUSIONS:

The Clinical-Imaging-Radiomics nomogram model of multiple regions and multiple sequences based on serum alpha-fetoprotein, three MRI characteristics, and 12 radiomics signatures achieved good performance for predicting MVI in HCC patients, which may help clinicians select optimal treatment strategies to improve subsequent clinical outcomes.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Hepatocellular / Liver Neoplasms Type of study: Prognostic_studies Limits: Humans Language: En Journal: Dig Dis Sci Year: 2023 Type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Carcinoma, Hepatocellular / Liver Neoplasms Type of study: Prognostic_studies Limits: Humans Language: En Journal: Dig Dis Sci Year: 2023 Type: Article Affiliation country: China