Objective To review our experience in the diagnosis and surgical management of aberrant right posterior hepatic bile duct injury.Methods Twenty eight patients with aberrant right posterior hepatic bile duct injury treated at the First Affiliated Hospital of Xinjiang Medical University between January 2002 to December 2011 were studied retrospectively.According to the injury type and the time of diagnosis,these patients were divided into three groups.The first group comprised of 10 patients in whom the injury was recognized and repaired at the time of the original surgery.The second group consisted of 10 patients in whom the injured aberrant right posterior hepatic bile duct was diagnosed and treated after operation.The third group comprised of 8 patients who developed an external bile fistula after the aberrant right posterior hepatic bile duct injury.The short and long term complications after surgical repair in the three groups were compared.Results In the first group,1 patient developed an intra-abdominal fluid collection.There was no bile stricture patients in first group.In the second group,1 patient developed bile fistula,2 patients intra-abdominal fluid collections,1 patient wound infection,and 1 patient bile duct stricture.In the third group,2 patients developed bile fistula,1 patient intestinal obstruction,2 patients wound infection,1 patient intra-abdominal hemorrhage,2 patients bile duct stricture and 1 patient an incisional hernia on follow-up.Conclusions Finding and repairing an aberrant right posterior hepatic bile duct injury at the original operation is the best treatment.According to the type and time of diagnosis,different surgical repair methods can be used for the aberrant right posterior hepatic bile duct injury.

Objective:To elucidate the diagnostic utility of clinical features and radiomics characteristics derived from magnetic resonance imaging T2-weighted fat-suppressed images (T2WI-FS) in differentiating brucellosis spondylitis from pyogenic spondylitis.Methods:Clinical records of 26 patients diagnosed with Brucellosis Spondylitis and 23 with Pyogenic Spondylitis were retrospectively reviewed from Xinjiang Medical University First Affiliated Hospital between January 2019 and December 2021. Confirmatory diagnosis was ascertained through histopathological examination and/or microbial culture. Demographic characteristics, symptoms, clinical manifestations, and hematological tests were collected, followed by a univariate analysis to discern clinically significant risk factors. For the radiomics evaluation, preoperative sagittal T2WI-FS images were utilized. Regions of interest (ROIs) were manually outlined by two adept radiologists. Employing the PyRadiomics toolkit, an extensive array of radiomics features encompassing shape, texture, and gray-level attributes were extracted, yielding a total of 1,500 radiomics parameters. Feature normalization and redundancy elimination were implemented to optimize the predictive efficacy of the model. Discriminatory radiomics features were identified through statistical methods like t-tests or rank-sum tests, followed by refinement via least absolute shrinkage and selection operator (LASSO) regression. An integrative logistic regression model incorporated selected clinical risk factors, radiomics attributes, and a composite radiomics score (Rad-Score). The diagnostic performance of three models clinical risk factors alone, Rad-Score alone, and a synergistic combination were appraised using a confusion matrix and receiver operating characteristic (ROC) analysis.Results:The cohort comprised 49 patients, including 36 males and 13 females, with a mean age of 53.79±13.79 years. C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) emerged as significant clinical risk factors ( P<0.005). A total of seven discriminative radiomics features (logarithm glrlm SRLGLE, exponential glcm Imc1, exponential glcm MCC, exponential gldm SDLGLE, square glcm ClusterShade, squareroot glszm SALGLE and wavelet.HHH glrlm Run Variance) were isolated through LASSO regression. Among these selected features, the square glcmClusterShade feature exhibited the best performance, with an area under the curve (AUC) value of 0.780. It demonstrated a sensitivity of 68.8%, specificity of 94.4%, accuracy of 82.4%, precision of 91.7%, and negative predictive value of 0.773. Furthermore, the logarithm glrlm SRLGLE feature had an AUC of 0.736, sensitivity of 68.8%, specificity of 72.2%, accuracy of 76.5%, precision of 72.2%, and negative predictive value of 0.812. The exponential glcm Imc1 feature had an AUC of 0.736, sensitivity of 50.0%, specificity of 94.4%, accuracy of 73.5%, precision of 88.9%, and negative predictive value of 0.680. Three diagnostic models were constructed: the clinical risk factors model, the radiomics score model, and the integrated model (clinical risk factors+radiomics score), which showed AUC values of 0.801, 0.818, and 0.875, respectively. Notably, the integrated model exhibited superior diagnostic efficacy. Conclusion:The amalgamation of clinical and radiomics variables within a sophisticated, integrated model demonstrates promising efficacy in accurately discriminating between Brucellosis Spondylitis and Pyogenic Spondylitis. This cutting-edge methodology underscores its potential in facilitating nuanced clinical decision-making, precise diagnostic differentiation, and the tailoring of therapeutic regimens.