Use of radiomics containing an effective peritumoral area to predict early recurrence of solitary hepatocellular carcinoma ≤5 cm in diameter

Abstract

BackgroundHepatocellular carcinoma (HCC) is the sixth leading type of cancer worldwide. We aimed to develop a preoperative predictive model of the risk of early tumor recurrence after HCC treatment based on radiomic features of the peritumoral region and evaluate the performance of this model against postoperative pathology.MethodOur model was developed using a retrospective analysis of imaging and clinicopathological data of 175 patients with an isolated HCC ≤5 cm in diameter; 117 patients were used for model training and 58 for model validation. The peritumoral area was delineated layer-by-layer for the arterial and portal vein phase on preoperative dynamic enhanced computed tomography images. The volume area of interest was expanded by 5 and 10 mm and the radiomic features of these areas extracted. Lasso was used to select the most stable features.ResultsThe radiomic features of the 5-mm area were sufficient for prediction of early tumor recurrence, with an area under the curve (AUC) value of 0.706 for the validation set and 0.837 for the training set using combined images. The AUC of the model using clinicopathological information alone was 0.753 compared with 0.786 for the preoperative radiomics model (P >0.05).ConclusionsRadiomic features of a 5-mm peritumoral region may provide a non-invasive biomarker for the preoperative prediction of the risk of early tumor recurrence for patients with a solitary HCC ≤5 cm in diameter. A fusion model that combines the radiomic features of the peritumoral region and postoperative pathology could contribute to individualized treatment of HCC.

Intratumoral and peritumoral radiomics based on contrast-enhanced MRI for preoperatively predicting treatment response of transarterial chemoembolization in hepatocellular carcinoma

“…Previous studies have reported that radiomics analysis of intratumoral combined 3 mm, 5 mm, and 10 mm peritumoral regions can provide valuable information for prognosis prediction in HCC [ 18 , 19 , 30 , 39 , 40 ]. In addition, according to the practice guidelines for the pathological diagnosis of primary liver cancer (2015 update) [ 41 ], the liver tissues within 10 mm surrounding the tumor are defined as the adjacent areas around the cancer, where the probability of MVI is high.…”

“…In our study, T-PTR radiomics models demonstrated better predictive performance compared with the TR radiomics model, which indicated that peritumoral radiomics might potentially enhance the ability of intratumoral radiomics for TACE response prediction. This might be interpreted that arterial peritumoral enhancement and irregular margin presented in the peritumoral area are independent predictors of prognosis in HCC patients [ 18 , 19 ]. Chen et al [ 30 ] found that intratumoral and peritumoral (5 mm, 10 mm, and 20 mm) radiomics models based on contrast-enhanced CT images performed better than the intratumoral radiomics model in predicting the first TACE response with the AUCs of 0.790, 0.810, 0.750, and 0.720, respectively, which was consistent with our study.…”

“…Numerous studies have demonstrated that radiomics-based models effectively identify the diagnosis and pathological characteristics or predict therapeutic efficacy and prognosis of cancer patients for clinical decision-making [ 14 – 17 ]. Recently, there has been increasing interest in evaluating radiomics patterns of the region surrounding the visible tumor [ 15 , 17 – 19 ]. Recurrence or metastasis of HCC is mainly intrahepatic, indicating that the peritumoral liver tissue may be a favorable soil for the spreading hepatoma cells [ 20 ].…”

“…Several scholars have reported that HCC patients with microvascular invasion (MVI), epithelial cell adhesion molecule (EpCAM), programmed death ligand 1 (PD-L1) expression, and higher CD68 + cell density in peritumoral tissues have a significantly higher risk of recurrence or metastasis and cancer-related death [ 21 – 24 ]; thus, peritumoral tissues might have valuable predictive information of HCC prognosis. Several recent studies have reported that CT or MRI-based radiomics on intratumoral and peritumoral regions can effectively predict MVI, vessels encapsulating tumor clusters (VETC), anti-PD-1 treatment efficacy, and prognosis of resection or TACE in patients with HCC, which may achieve an enhanced prediction of the individualized risk estimation [ 15 , 17 – 19 , 25 – 27 ]. However, the value of intratumoral and peritumoral radiomics based on MRI in predicting treatment response of HCC after TACE remains unknown.…”

Effect of multiple peritumoral regions of interest ranges based on computed tomography radiomics for the prediction of early recurrence of hepatocellular carcinoma after resection

“…Several studies have included the peritumoral range for ROI analyses, gradually recognizing the importance of this region for tumor radiomics ROI ( 17 - 19 ). Nevertheless, the choice of the peritumoral ROI range for predicting ER of HCC remains controversial ( 20 , 21 ), and the optimal peritumoral ROI range needs to be further explored.…”