Objectives: To assess the accuracy of computed tomography (CT)-based machine learning models for differentiating subclinical pheochromocytoma (sPHEO) from lipid-poor adenoma (LPA) in patients with adrenal incidentalomas.Patients and Methods: The study included 188 tumors in the 183 patients with LPA and 92 tumors in 86 patients with sPHEO. Pre-enhanced CT imaging features of the tumors were evaluated. Machine learning prediction models and scoring systems for differentiating sPHEO from LPA were built using logistic regression (LR), support vector machine (SVM) and random forest (RF) approaches.Results: The LR model performed better than other models. The LR model (M1) including three CT features: CT_pre value, shape, and necrosis/cystic changes had an area under the receiver operating characteristic curve (AUC) of 0.917 and an accuracy of 0.864. The LR model (M2) including three CT features: CT_pre value, shape and homogeneity had an AUC of 0.888 and an accuracy of 0.832. The S2 scoring system (sensitivity: 0.859, specificity: 0.824) had comparable diagnostic value to S1 (sensitivity: 0.815; specificity: 0.910).Conclusions: Our results indicated the potential of using a non-invasive imaging method such as CT-based machine learning models and scoring systems for predicting histology of adrenal incidentalomas. This approach may assist the diagnosis and personalized care of patients with adrenal tumors.

Background and Purpose: Computerized tomography (CT) scans are commonly performed to assist in diagnosis and treatment of locally advanced rectal cancer (LARC). This study assessed the usefulness of pretreatment CT-based radiomics for predicting pathological complete response (pCR) of LARC to neoadjuvant chemoradiotherapy (nCRT).Materials and Methods: Patients with LARC who underwent nCRT followed by total mesorectal excision surgery from July 2010 to December 2018 were enrolled in this retrospective study. A total of 340 radiomic features were extracted from pretreatment contrast-enhanced CT images. The most relevant features to pCR were selected using the least absolute shrinkage and selection operator (LASSO) method and a radiomic signature was generated. Predictive models were built with radiomic features and clinico-pathological variables. Model performance was assessed with decision curve analysis and was validated in an independent cohort.Results: The pCR was achieved in 44 of the 216 consecutive patients (20.4%) in this study. The model with the best performance used both radiomics and clinical variables including radiomic signatures, distance to anal verge, lymphocyte-to-monocyte ratio, and carcinoembryonic antigen. This combined model discriminated between patients with and without pCR with an area under the curve of 0.926 and 0.872 in the training and the validation cohorts, respectively. The combined model also showed better performance than models built with radiomic or clinical variables alone.Conclusion: Our combined predictive model was robust in differentiating patients with and without response to nCRT.

Purpose: To assess the safety and efficacy of local ablation plus PD-1 inhibitor toripalimab in previously treated unresectable hepatocellular carcinoma (HCC). Patients and Methods: In the multicenter, two-stage, and randomized phase 1/2 trial, patients were randomly assigned to receive toripalimab alone (240 mg, every 3 weeks), subtotal local ablation followed by toripalimab starting on post-ablation day 3 (Schedule D3), or on post-ablation day 14 (Schedule D14). The first endpoint of stage 1 was to determine which combination schedule could continue and progression-free survival (PFS) as the primary endpoint for stage 1/2. Results: A total of 146 patients were recruited. During stage 1, Schedule D3 achieved numerically higher objective response rate (ORR) than Schedule D14 for non-ablation lesions (37.5% vs. 31.3%), and was chosen for stage 2 evaluation. For the entire cohort of both stages, patients with Schedule D3 had a significantly higher ORR than with toripalimab alone (33.8% vs. 16.9%; P = 0.027). Moreover, patients with Schedule D3 had improved median PFS (7.1 vs. 3.8 months; P < 0.001) and median overall survival (18.4 vs. 13.2 months; P = 0.005), as compared with toripalimab alone. In addition, six (9%) patients with toripalimab, eight (12%) with Schedule D3, and 4 (25%) with Schedule D14 developed grade 3 or 4 adverse events, and one patient (2%) with Schedule D3 manifested grade 5 treatment-related pneumonitis. Conclusions: In patients with previously treated unresectable HCC, subtotal ablation plus toripalimab improved the clinical efficacy as compared with toripalimab alone, with an acceptable safety profile.