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A Cox Nomogram for Assessing Recurrence Free Survival in Hepatocellular Carcinoma Following Surgical Resection Using Dynamic Contrast-Enhanced MRI Radiomics

  • Xinshan Cao
  • , Haoran Yang
  • , Xin Luo
  • , Linxuan Zou
  • , Qiang Zhang
  • , Qilin Li
  • , Juntao Zhang
  • , Xiangfeng Li
  • , Yan Shi
  • , Chenwang Jin
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Binzhou Medical University
  • Zibo Central Hospital
  • GE Healthcare Precision Health Institution
  • The Fourth People Hospital of Zibo

科研成果: 期刊稿件文章同行评审

14 引用 (Scopus)

摘要

Background: The prognosis of hepatocellular carcinoma (HCC) is difficult to predict and carries high mortality. This study utilized radiomic techniques with clinical examinations to assess recurrence in HCC. Purpose: To develop a Cox nomogram to assess the risk of postoperative recurrence in HCC using radiomic features of three volumes of interest (VOIs) in preoperative dynamic contrast-enhanced MRI (DCE-MRI), along with clinical findings. Study Type: Retrospective. Subjects: 249 patients with pathologically proven HCCs undergoing surgical resection at three institutions were selected. Field Strength/Sequence: Fat saturated T2-weighted, Fat saturated T1-weighted, and DCE-MRI performed at 1.5 T and 3.0 T. Assessment: Three VOIs were generated; the tumor VOI corresponds to the area from the tumor core to the outer perimeter of the tumor, the tumor +10 mm VOI represents the area from the tumor perimeter to 10 mm distal to the tumor in all directions, finally, the background liver parenchyma VOI represents the hepatic tissue outside the tumor. Three models were generated. The total radiomic model combined information from the three listed VOI's above. The clinical–radiological model combines physical examination findings with imaging characteristics such as tumor size, margin features, and metastasis. The combined radiomic model includes features from both models listed above and showed the highest reliability for assessing 24-month survival for HCC. Statistical Tests: The least absolute shrinkage and selection operator (LASSO) Cox regression, univariable, and multivariable Cox regression, Kmeans clustering, and Kaplan–Meier analysis. The discrimination performance of each model was quantified by the C-index. A P value <0.05 was considered statistically significant. Results: The combined radiomic model, which included features from the radiomic VOI's and clinical imaging provided the highest performance (C-index: training cohort = 0.893, test cohort = 0.851, external cohort = 0.797) in assessing the survival of HCC. Conclusion: The combined radiomic model provides superior ability to discern the possibility of recurrence-free survival in HCC over the total radiomic and the clinical–radiological models. Evidence Level: 4. Technical Efficacy: Stage 2.

源语言英语
页(从-至)1930-1941
页数12
期刊Journal of Magnetic Resonance Imaging
58
6
DOI
出版状态已出版 - 12月 2023
已对外发布

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