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BACKGROUND: To evaluate the value of computed tomography (CT) radiomics in predicting the risk of developing epidermal growth factor receptor (EGFR) T790M resistance mutation for metastatic non-small lung cancer (NSCLC) patients before first-line EGFR-tyrosine kinase inhibitors (EGFR-TKIs) therapy. METHODS: A total of 162 metastatic NSCLC patients were recruited and split into training and testing cohort. Radiomics features were extracted from tumor lesions on nonenhanced CT (NECT) and contrast-enhanced CT (CECT). Radiomics score (rad-score) of two CT scans was calculated respectively. A nomogram combining two CT scans was developed to evaluate T790M resistance within up to 14 months. Patients were followed up to calculate the time of T790M occurrence. Models were evaluated by area under the curve at receiver operating characteristic analysis (ROC-AUC), calibration curve, and decision curve analysis (DCA). The association of the nomogram with the time of T790M occurrence was evaluated by Kaplan-Meier survival analysis. RESULTS: The nomogram constructed with the rad-score of NECT and CECT for predicting T790M resistance within 14 months achieved the highest ROC-AUCs of 0.828 and 0.853 in training and testing cohorts, respectively. The DCA showed that the nomogram was clinically useful. The Kaplan-Meier analysis showed that the occurrence time of T790M difference between the high- and low-risk groups distinguished by the rad-score was significant (p

ObjectivesMultidrug-resistant TB (MDR-TB) is a severe burden and public health threat worldwide. This study aimed to develop a radiomics model based on the tree-in-bud (TIB) sign and nodules and validate its predictive performance for MDR-TB.MethodsWe retrospectively recruited 454 patients with proven active TB from two hospitals and classified them into three training and testing cohorts: TIB (n = 295, 102), nodules (n = 302, 97), and their combination (n = 261, 81). Radiomics features relating to TIB and nodules were separately extracted. The maximal information coefficient and recursive feature elimination were used to select informative features per the two signs. Two radiomics models were constructed to predict MDR-TB using a random forest classifier. Then, a combined model was built incorporating radiomics features based on these two signs. The capability of the models in the combined training and testing cohorts was validated with ROC curves.ResultsSixteen features were extracted from TIB and 15 from nodules. The AUCs of the combined model were slightly higher than those of the TIB model in the combined training cohort (0.911 versus 0.877, p > 0.05) and testing cohort (0.820 versus 0.786, p  0.05) and testing cohort (0.820 versus 0.855, p > 0.05).ConclusionsThe CT-based radiomics models hold promise for use as a non-invasive tool in the prediction of MDR-TB.Clinical relevance statementOur study revealed that complementary information regarding MDR-TB can be provided by radiomics based on the TIB sign and nodules. The proposed radiomics models may be new markers to predict MDR in active TB patients.Key points• This is the first study to build, validate, and apply radiomics based on tree-in-bud sign and nodules for the prediction of MDR-TB. • The radiomics model showed a favorable performance for the identification of MDR-TB. • The combined model holds potential to be used as a diagnostic tool in routine clinical practice.

Infection following inguinal hernia repair (IHR) is uncommon. Rational use of antibiotics can significantly improve the prognosis of patients. However, accurately identifying the pathogen involved is usually challenging. This case report describes a patient who developed intermittent fever after undergoing open preperitoneal tension-free repair of a bilateral inguinal hernia. The scrotal fluid specimen was cultured and subjected to metagenomic next-generation sequencing (mNGS). Culture revealed the presence of Enterococcus faecalis (a facultative anaerobe). However, mNGS detected E. faecalis along with multiple anaerobic bacteria including Bacteroides thetaiotaomicron, Parabacteroides distasonis, and Levyella massiliensis. The patient was finally diagnosed with a mixed infection of E. faecalis and multiple anaerobes, and his condition was effectively controlled after timely adjustment of the antibiotic regimen. Treating postoperative infections with multiple concurrent conditions can be challenging. mNGS is valuable for the accurate diagnosis and treatment of infections, as it not only can further verify the culture results, but also assist clinicians in ruling out pulmonary infection caused by hematogenous dissemination after IHR in patients.