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Abstract Fractional flow reserve (FFR) has become the gold standard for evaluating coronary lesion-specific ischemia. However, FFR is an invasive method that may cause possible complications in the coronary artery and requires expensive equipment, which limits its use. Promising noninvasive diagnostic methods, such as computed tomography angiography–derived FFR (CT-FFR) and the quantitative flow ratio (QFR), have been proposed. In this study, we evaluated the diagnostic performance of the QFR and CT-FFR in predicting coronary lesion-specific ischemia, with the FFR serving as the reference standard. Patients with suspected or known coronary artery disease who underwent coronary CT angiography revealing 30–90% diameter stenosis in the main coronary artery (≥ 2.0 mm reference diameter) were enrolled. The FFR was measured during invasive coronary angiography (within 15 days after coronary CT angiography). An FFR ≤ 0.8 was the reference standard for coronary lesion-specific ischemia. A total of 103 vessels from 92 consecutive patients (aged 59.8 ± 9.2 years; 60.9% were men) were evaluated. The diagnostic performance of a QFR ≤ 0.80 for predicting coronary lesion-specific ischemia demonstrated good diagnostic accuracy, sensitivity, and specificity (92.2%, 87.2%, and 96.4%, respectively), with an area under the receiver operating characteristic curve (AUC) of 0.987 (P

Abstract Although robotic radical resection for hilar cholangiocarcinoma (HCCA) has been reported in some large hepatobiliary centers, biliary-enteric reconstruction (BER) remains a critical step that hampers the operation’s success. This study aimed to evaluate the feasibility and quality of BER in robotic radical resection of HCCA and propose technical recommendations. A retrospective study was conducted on patients with HCCA who underwent minimally invasive radical resection at Zhejiang Provincial People’s Hospital between January 2016 and July 2023. A 1:2 propensity score matching (PSM), widely used to reduce selection bias, was performed to evaluate the outcomes, especially BER-related data, between the robotic and laparoscopic surgery. Forty-six patients with HCCA were enrolled; ten underwent robotic-assisted resection, while the others underwent laparoscopic surgery. After PSM at a ratio of 1:2, 10 and 20 patients were assigned to the robot-assisted and laparoscopic groups, respectively. The baseline characteristics of both groups were generally well-balanced. The average liver resection time was longer in the robotic group than in the laparoscopic group (139.5 ± 38.8 vs 108.1 ± 35.8 min, P = 0.036). However, the former had less intraoperative blood loss [200 (50–500) vs 310 (100–850) ml], despite no statistical difference (P = 0.109). The number of residual bile ducts was 2.6 ± 1.3 and 2.7 ± 1.2 (P = 0.795), and anastomoses were both 1.6 ± 0.7 in the two groups (P = 0.965). The time of BER was 38.4 ± 13.6 and 59.1 ± 25.5 min (P = 0.024), accounting for 9.9 ± 2.8% and 15.4 ± 4.8% of the total operation time (P = 0.001). Although postoperative bile leakage incidence in laparoscopic group (40%) was higher than that in robotic group (10%), there was no significant difference between the two groups (P = 0.204); 6.7 ± 4.4 and 12.1 ± 11.7 days were observed for tube drawing (P = 0.019); anastomosis stenosis and calculus rate was 10% and 30% (P = 0.372), 0% and 15% (P = 0.532), respectively. Neither group had hemorrhage- or bile leakage-related deaths. Robotic radical resection for HCCA may offer perioperative outcomes comparable to conventional laparoscopic procedures and tends to be advantageous in terms of anastomosis time and quality. We are optimistic about its wide application in the future with the improvement of surgical techniques and experience.

Abstract The objective of this study was to predict the preoperative pathological grading and survival period of Pseudomyxoma peritonei (PMP) by establishing models, including a radiomics model with greater omental caking as the imaging observation index, a clinical model including clinical indexes, and a combined model of these two. A total of 88 PMP patients were selected. Clinical data of patients, including age, sex, preoperative serum tumor markers [CEA, CA125, and CA199], survival time, and preoperative computed tomography (CT) images were analyzed. Three models (clinical model, radiomics model and combined model) were used to predict PMP pathological grading. The models’ diagnostic efficiency was compared and analyzed by building the receiver operating characteristic (ROC) curve. Simultaneously, the impact of PMP’s different pathological grades was evaluated. The results showed that the radiomics model based on the CT’s greater omental caking, an area under the ROC curve ([AUC] = 0.878), and the combined model (AUC = 0.899) had diagnostic power for determining PMP pathological grading. The imaging radiomics model based on CT greater omental caking can be used to predict PMP pathological grading, which is important in the treatment selection method and prognosis assessment.