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The Value of LI-RADS and Radiomic Features from MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma within 5 cm.
Feng, Bing; Wang, Leyao; Zhu, Yongjian; Ma, Xiaohong; Cong, Rong; Cai, Wei; Liu, Siyun; Hu, Jiesi; Wang, Sicong; Zhao, Xinming.
Afiliación
  • Feng B; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
  • Wang L; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
  • Zhu Y; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
  • Ma X; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.). Electronic address: maxiaohong@cicams.ac.c
  • Cong R; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
  • Cai W; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
  • Liu S; GE Healthcare (China), 1# Tongji South Road, Daxing District, Beijing, 100176, China (S.L., S.W.).
  • Hu J; Harbin Institute of Technology, HIT Campus of University Town of Shenzhen, Shenzhen, 518055, China (J.H.).
  • Wang S; GE Healthcare (China), 1# Tongji South Road, Daxing District, Beijing, 100176, China (S.L., S.W.).
  • Zhao X; Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China (B.F., L.W., Y.Z., X.M., R.C., W.C., X.Z.).
Acad Radiol ; 31(6): 2381-2390, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38199902
ABSTRACT
RATIONALE AND

OBJECTIVES:

To explore and compare the performance of LI-RADS® and radiomics from multiparametric MRI in predicting microvascular invasion (MVI) preoperatively in patients with solitary hepatocellular carcinoma (HCC)< 5 cm.

METHODS:

We enrolled 143 patients with pathologically proven HCC and randomly stratified them into training (n = 100) and internal validation (n = 43) cohorts. Besides, 53 patients were enrolled to constitute an independent test cohort. Clinical factors and imaging features, including LI-RADS and three other features (non-smooth margin, incomplete capsule, and two-trait predictor of venous invasion), were reviewed and analyzed. Radiomic features from four MRI sequences were extracted. The independent clinic-imaging (clinical) and radiomics model for MVI-prediction were constructed by logistic regression and AdaBoost respectively. And the clinic-radiomics combined model was further constructed by logistic regression. We assessed the model discrimination, calibration, and clinical usefulness by using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision-curve analysis respectively.

RESULTS:

Incomplete tumor capsule, corona enhancement, and radiomic features were related to MVI in solitary HCC<5 cm. The clinical model achieved AUC of 0.694/0.661 (training/internal validation). The single-sequence-based radiomic model's AUCs were 0.753-0.843/0.698-0.767 (training/internal validation). The combination model exhibited superior diagnostic performance to the clinical model (AUC 0.895/0.848 [training/ internal validation]) and yielded an AUC of 0.858 in an independent test cohort.

CONCLUSION:

Incomplete tumor capsule and corona enhancement on preoperative MRI were significantly related to MVI in solitary HCC<5 cm. Multiple-sequence radiomic features potentially improve MVI-prediction-model performance, which could potentially help determining HCC's appropriate therapy.
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Texto completo: 1 Colección: 01-internacional Asunto principal: Imagen por Resonancia Magnética / Carcinoma Hepatocelular / Microvasos / Neoplasias Hepáticas / Invasividad Neoplásica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Asunto principal: Imagen por Resonancia Magnética / Carcinoma Hepatocelular / Microvasos / Neoplasias Hepáticas / Invasividad Neoplásica Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article