Simultaneous cholecystectomy for asymptomatic gallstones during elective colorectal cancer surgery.

BACKGROUND: Asymptomatic gallstones are commonly detected using preoperative imaging in patients with colorectal cancer (CRC), but its management remains a topic of debate. METHODS: Clinicopathologic characteristics of patients who had asymptomatic gallstones presenting during the colorectal procedure were retrospectively reviewed. Medical records, including postoperative morbidity, mortality, and long-term gallstone-related diseases, were assessed. RESULTS: Of 134 patients with CRC having asymptomatic gallstones, 89 underwent elective colorectal surgery only (observation group), and 45 underwent elective colorectal surgery with simultaneous cholecystectomy (cholecystectomy group). After propensity score matching (PSM), the complications were similar in the 2 groups. During the follow-up period, biliary complications were noted in 11 patients (12.4%) in the observation group within 2 years after the initial CRC surgery, but no case was found in the cholecystectomy group. After PSM, the incidence of long-term biliary complications remained significantly higher in the observation group than in the cholecystectomy group (26.5% vs 0.0%; P < .01). Multivariable logistic regression analysis identified female gender, old age (≥65 years old), and small multiple gallstones as independent risk factors for the development of long-term gallstone-related diseases in patients from the observation group. CONCLUSION: Simultaneous prophylactic cholecystectomy during prepared, elective CRC surgery did not increase postoperative morbidity or mortality but decreased the risk of subsequent gallstone-related complications. Hence, simultaneous cholecystectomy might be a preferred therapeutic option for patients with CRC having asymptomatic gallstones in cases of elective surgery, especially for older patients (≥65 years old), female patients, and those with small multiple calculi.

Deep neural network for the prediction of KRAS, NRAS, and BRAF genotypes in left-sided colorectal cancer based on histopathologic images.

BACKGROUND: The KRAS, NRAS, and BRAF genotypes are critical for selecting targeted therapies for patients with metastatic colorectal cancer (mCRC). Here, we aimed to develop a deep learning model that utilizes pathologic whole-slide images (WSIs) to accurately predict the status of KRAS, NRAS, and BRAFV600E. METHODS: 129 patients with left-sided colon cancer and rectal cancer from the Third Affiliated Hospital of Sun Yat-sen University were assigned to the training and testing cohorts. Utilizing three convolutional neural networks (ResNet18, ResNet50, and Inception v3), we extracted 206 pathological features from H&E-stained WSIs, serving as the foundation for constructing specific pathological models. A clinical feature model was then developed, with carcinoembryonic antigen (CEA) identified through comprehensive multiple regression analysis as the key biomarker. Subsequently, these two models were combined to create a clinical-pathological integrated model, resulting in a total of three genetic prediction models. RESULT: 103 patients were evaluated in the training cohort (1782,302 image tiles), while the remaining 26 patients were enrolled in the testing cohort (489,481 image tiles). Compared with the clinical model and the pathology model, the combined model which incorporated CEA levels and pathological signatures, showed increased predictive ability, with an area under the curve (AUC) of 0.96 in the training and an AUC of 0.83 in the testing cohort, accompanied by a high positive predictive value (PPV 0.92). CONCLUSION: The combined model demonstrated a considerable ability to accurately predict the status of KRAS, NRAS, and BRAFV600E in patients with left-sided colorectal cancer, with potential application to assist doctors in developing targeted treatment strategies for mCRC patients, and effectively identifying mutations and eliminating the need for confirmatory genetic testing.