Combined hematology, tumor morphology, and magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: a clinical study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: Microvascular invasion (MVI) is an independent risk factor for postoperative recurrence in hepatocellular carcinoma (HCC), making preoperative prediction clinically critical. This study aimed to identify factors associated with MVI and develop a clinically applicable predictive model using patient-derived variables, including serological markers, tumor morphology, and magnetic resonance imaging (MRI) features. Methods: A retrospective analysis was conducted on 236 patients with HCC who underwent surgical resection between January 1, 2019, and December 31, 2022, at the Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Hospital of Guangdong Medical University. Patients were randomly assigned to training and validation cohorts at a 1:1 ratio. Significant factors identified through univariate analysis with P values adjusted via the Benjamini-Hochberg method (adjusted P<0.05) were subjected to binary logistic regression to determine the independent risk factors for MVI in HCC. These factors were used to develop a nomogram for MVI prediction, with its diagnostic performance assessed through receiver operating characteristic (ROC) curves. Additionally, k-fold cross-validation (k=5) was performed to evaluate model stability. Results: There were 236 patients included, with 118 in each cohort. Logistic regression identified four independent risk factors for MVI: arterial phase edge enhancement [odds ratio (OR) =4.610, P=0.011], incomplete tumor capsule (OR =4.513, P=0.013), alpha-fetoprotein (AFP) >800 ng/mL (OR =3.407, P=0.035), and intratumoral vascular enhancement (OR =6.300, P=0.022). In the training cohort, the area under the curve (AUC), sensitivity, specificity and Youden index (YI) of the nomogram were 0.871 (P<0.001), 78.8%, 80.0% and 0.645, respectively; while in the validation cohort, they were 0.878 (P<0.001), 83.9%, 86.2% and 0.689, respectively, with both cohorts' AUC results consistent with the average AUC of 0.860 from k-fold cross-validation. Decision curve analysis and calibration curve results confirmed high model accuracy and clinical benefit. Conclusions: AFP >800 ng/mL, intratumoral vascular enhancement, arterial phase enhancement, and incomplete tumor capsule are independent risk factors for MVI in HCC. Combining serological, morphological, and MRI characteristics offers robust utility and accuracy in predicting MVI in HCC.
Language: English
Subfield: Hepatology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7125981933