Hepatocellular carcinoma: radiomics nomogram on gadoxetic acid-enhanced MR imaging for early postoperative recurrence prediction.

Autor: Zhang Z; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Jiang H; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Chen J; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Wei Y; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Cao L; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Ye Z; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China., Li X; GE Healthcare China, Beijing, China., Ma L; GE Healthcare China, Beijing, China., Song B; Department of Radiology, West China Hospital of Sichuan University, No.37 Guo Xue Xiang, Chengdu, 610041, China. songb_radiology@163.com.
Jazyk: angličtina
Zdroj: Cancer imaging : the official publication of the International Cancer Imaging Society [Cancer Imaging] 2019 May 14; Vol. 19 (1), pp. 22. Date of Electronic Publication: 2019 May 14.
DOI: 10.1186/s40644-019-0209-5
Abstrakt: Background: This study was performed to prospectively develop and validate a radiomics nomogram for predicting postoperative early recurrence (≤1 year) of hepatocellular carcinoma (HCC) using whole-lesion radiomics features on preoperative gadoxetic acid-enhanced magnetic resonance (MR) images.
Methods: In total, 155 patients (training cohort: n = 108; validation cohort: n = 47) with surgically confirmed HCC were enrolled in this IRB-approved prospective study. Three-dimensional whole-lesion regions of interest were manually delineated along the tumour margins on multi-sequence MR images. Radiomics features were generated and selected to build a radiomics score using the least absolute shrinkage and selection operator (LASSO) method. Clinical characteristics and qualitative imaging features were identified by two independent radiologists and combined to establish a clinical-radiological nomogram. A radiomics nomogram comprising the radiomics score and clinical-radiological risk factors was constructed based on multivariable logistic regression analysis. Diagnostic performance and clinical usefulness were measured by receiver operation characteristic (ROC) and decision curves.
Results: In total, 14 radiomics features were selected to construct the radiomics score. For the clinical-radiological nomogram, the alpha-fetoprotein (AFP) level, gross vascular invasion and non-smooth tumour margin were included. The radiomics nomogram integrating the radiomics score with clinical-radiological risk factors showed better discriminative performance (AUC = 0.844, 95%CI, 0.769 to 0.919) than the clinical-radiological nomogram (AUC = 0.796, 95%CI, 0.712 to 0.881; P = 0.045), with increased clinical usefulness confirmed using a decision curve analysis.
Conclusions: Incorporating multiple predictive factors, the radiomics nomogram demonstrated great potential in the preoperative prediction of early HCC recurrence after surgery.
Databáze: MEDLINE
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