Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.

OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: • The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. • Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. • The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.

Detection of small hepatocellular carcinoma using gadoxetic acid-enhanced MRI: Is the addition of diffusion-weighted MRI at 3.0T beneficial?

OBJECTIVE: To determine whether adding diffusion-weighted imaging (DWI) to gadoxetic acid-enhanced 3.0T magnetic resonance imaging (MRI) can improve the detection of hepatocellular carcinoma (HCC), particularly for small lesions (≤2 cm) in patients with liver cirrhosis. METHODS: Data of patients diagnosed with focal liver lesions who had undergone gadoxetic acid-enhanced 3.0T MRI and DWI were retrospectively reviewed. Two radiologists (the observers) reviewed independently MRI images in two reading sessions, that is, gadoxetic acid-enhanced images alone and the combination of DWI (b values: 0 and 600 s/mm(2) ) and gadoxetic acid-enhanced images. They assigned to each lesion a confidence level based on a five-point scale. The area under the receiver operating characteristic curve (AUROC), sensitivity and positive predictive value (PPV) for the detection of HCC were calculated. RESULTS: Both observers found the AUROC of the gadoxetic acid-enhanced images was slightly higher than that of the combined DWI and gadoxetic acid-enhanced MRI images in the detection of HCC (observer 1: 0.947 ± 0.030 vs 0.896 ± 0.042, Z = 1.478, P = 0.139; observer 2: 0.917 ± 0.038 vs 0.868 ± 0.048, Z = 1.296, P = 0.195). The sensitivity for the gadoxetic acid set alone was slightly higher than that for the combined set for observer 1 (97% vs 84%) and slightly lower for observer 2 (74% vs 82%). The PPVs were slightly higher for the gadoxetic acid set alone than for the combined set for both observers (observer 1, 89% vs 80%; observer 2, 93% vs 78%); however, none of the differences were statistically significant (P > 0.05). CONCLUSION: There is no benefit in adding DWI to gadoxetic acid-enhanced MRI for the detection of HCC at 3.0T.

Hepatitis B virus-induced liver fibrosis and cirrhosis: the value of liver and spleen volumetry with multi-detector spiral computed tomography.

OBJECTIVE: To study the correlation of liver and spleen volume with the degree of liver fibrosis and cirrhosis induced by hepatitis B virus infection. METHODS: 128 participants who had undergone liver and spleen volumetry were enrolled. The control group consisted of 41 participants who were potential living liver donors. The liver fibrosis group consisted of 63 histologically proved liver fibrosis patients who were further divided into two subgroups: 44 patients with slight liver fibrosis, and 19 patients with advanced liver fibrosis. The liver cirrhosis group consisted of 24 patients. The following parameters were determined by multi-detector spiral computed tomography (MSCT) examination: total liver volume (TLV), right liver lobe volume (RV), left lateral liver segment volume (LLV), left medial liver segment volume (LMV), caudate lobe volume (CV), and spleen volume (SV). The ratios of CV to TLV (C/T), RV to TLV (R/T), LLV to TLV (LL/T), LMV to TLV (LM/T), and SV to TLV (S/T) were calculated. RESULTS: TLV, RV, LMV tended to decrease and SV, C/T, S/T tended to increase gradually with the increased degree of fibrosis. C/T >or= 3.34% and S/T >or= 47.36% were identified as the cut-off values of fibrosis >or=F3 (advanced liver fibrosis) and cirrhosis, respectively. Their sensitivities were 68.4% and 87.5% and their specificities were 59.1% and 89.5%, respectively. CONCLUSION: Variations in liver and spleen volume correlated with the degree of liver fibrosis and cirrhosis and could be used in the non-invasive follow-up of the development of liver fibrosis.