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Updated: Oct 5, 2025
Quantification of Breast Cancer Cell Invasiveness Using a Three-dimensional 3D Model
Published on: June 11, 2014
Microvascular invasion of small hepatocellular carcinoma can be preoperatively predicted by the 3D quantification of
San-Yuan Dong1, Wen-Tao Wang1, Xiao-Shan Chen1
1Department of Radiology, Institute of Medical Imaging, Zhongshan Hospital, Fudan University, Xuhui District, No. 180 Fenglin Road, Shanghai, 200032, China.
Objectives:
To explore the importance of three-dimensional (3D) quantitative analysis during gadoxetic acid-enhanced magnetic resonance imaging (MRI) of microvascular invasion (MVI) and early recurrence (< 2 years) after surgery of single hepatocellular carcinoma (HCC) ≤ 3 cm.
Methods:
Two hundred fourteen patients with pathologically confirmed HCC (training cohort: n = 169; validation cohort: n = 45) were included retrospectively. The 3D quantitative parameters (volume, sphericity, and compacity) and conventional MRI features were analyzed. The significant predictors for MVI were identified using univariate and multivariate logistic regression analyses. Nomograms were constructed from the prediction model, and the relationship between the significant predictors and early recurrence rates was evaluated using the Kaplan-Meier method.
Results:
Tumor sphericity (odds ratio [OR] = 0.000; p < 0.001), non-smooth tumor margin (OR = 3.353; p = 0.015), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR = 14.067; p = 0.003) were independent significant factors for MVI. When these three factors were combined, the diagnostic specificity of the training and validation cohorts was 97.0 (128/132) and 87.9 (29/33), respectively. The nomogram based on the predictive model performed satisfactorily in the training (C-index: 0.885) and validation (C-index: 0.869) cohorts. Early recurrence rates of patients with two or three significant factors were significantly higher than those with none in the training (29.1% vs. 10.2%, p = 0.007) and validation (36.4% vs. 6.7%, p = 0.037) cohorts.
Conclusions:
Lower sphericity combined with non-smooth tumor margin and peritumoral hypointensity on HBP are potential predictive factors for MVI and associated with early recurrence after surgery of HCC ≤ 3 cm.
Key Points:
• Lower sphericity, non-smooth tumor margin, and peritumoral hypointensity on HBP were important indicators of the occurrence of MVI in HCC. • The combinational model prepared from these findings satisfactorily predicted MVI, and the presence of these predictors was associated with an early recurrence rate after surgical resection in HCC patients. • This model could help clinicians in the preoperative management of small HCC ≤ 3 cm.
