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Objectives: Preoperative prediction of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC) is significant for developing appropriate treatment strategies. We aimed to establish a radiomics-based clinical model for preoperative prediction of PHLF in HCC patients using gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI).Methods: A total of 144 HCC patients from two medical centers were included, with 111 patients as the training cohort and 33 patients as the test cohort, respectively. Radiomics features and clinical variables were selected to construct a radiomics model and a clinical model, respectively. A combined logistic regression model, the liver failure (LF) model that incorporated the developed radiomics signature and clinical risk factors was then constructed. The performance of these models was evaluated and compared by plotting the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC) with 95% confidence interval (CI).Results: The radiomics model showed a higher AUC than the clinical model in the training cohort and the test cohort for predicting PHLF in HCC patients. Moreover, the LF model had the highest AUCs in both cohorts [0.956 (95% CI: 0.955–0.962) and 0.844 (95% CI: 0.833–0.886), respectively], compared with the radiomics model and the clinical model.Conclusions: We evaluated quantitative radiomics features from MRI images and presented an externally validated radiomics-based clinical model, the LF model for the prediction of PHLF in HCC patients, which could assist clinicians in making treatment strategies before surgery.

BackgroundInadequate accuracy of ultrasound-guided core needle biopsy (US-CNB) urges further improvement for the diagnosis and management of lymphoma to meet with the practitioners’ increased reliance on this mini-invasive approach.MethodsData related to US-CNB of the deep-sited dominant lesions suspicious of lymphoma detected by computer tomography or positron-emission tomography/computer tomography for eligibility assessment of three prospective clinical trials were collected in advance. A retrospective analysis of the prospective data collection was performed, in which Viable-targeting US-CNB that Color Doppler flow imaging (CDFI) and/or contrast enhanced ultrasound (CEUS) were employed to select viable area for biopsy target compared with Routine US-CNB that routine procedure of evaluation and guidance using gray-scale ultrasound with CDFI in terms of the yield of clinically actionable diagnosis and safety, and determinants for the successful US-CNB that established an actionable diagnosis were explored. The establishment of final diagnosis was based on surgical pathology or medical response to therapy with follow-up at least 6 months.ResultsA total of 245 patients underwent Routine US-CNB (N = 120) or Viable-targeting US-CNB (N = 125), of which 91 (91/120, 75.8%) and 112 (112/125, 89.6%) were revealed with actionable diagnoses, respectively (p = 0.004, OR 0.846, 95% CI: 0.753–0.952). And 239 patients established final diagnoses. Diagnostic yields of actionable diagnosis according to the final diagnoses were 78.4% (91/116) and 91.1% (112/123) (p = 0.006, OR 0.554, 95% CI: 0.333–0.920), 82.6% (90/109) and 92.5% (111/120) for malignancy, 84.0% (84/100) and 91.8% (101/110) for lymphoma, 85.1% (80/94) and 92.3% (96/104) for Non-Hodgkin Lymphoma, 66.7% (4/6) and 83.3% (5/6) for Hodgkin Lymphoma in Routine and Viable-targeting CNB groups, respectively. No major complications were observed. Dominant lesions with actionable diagnosis in US-CNB were with higher FDG-avid Standardized Uptake Value. Binomial logistic regression revealed that actionable diagnosis of US-CNB was correlated with group and ancillary studies.ConclusionViable-Targeting US-CNB was superior to routine US-CNB in term of the yield of actionable diagnosis for deep-sited dominant lesions suspicious of lymphoma, which demonstrated a potential to be the initial approach in this setting.