Integrated pretreatment diffusion kurtosis imaging and serum squamous cell carcinoma antigen levels: a biomarker strategy for early assessment of radiotherapy outcomes in cervical cancer.

OBJECTIVE: This study aims to explore the utility of pretreatment DKI parameters and serum SCC-Ag in evaluating the early therapeutic response of cervical cancer to radiotherapy. MATERIALS AND METHODS: A total of 33 patients diagnosed with cervical cancer, including 31 cases of cervical squamous cell carcinoma and two cases of adenosquamous carcinoma, participated in the study. All patients underwent conventional MRI and DKI scans on a 3T magnetic resonance scanner before radiotherapy and after ten sessions of radiotherapy. The therapeutic response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Patients were categorized into a response group (RG), comprising Complete Remission (CR) and Partial Remission (PR), and a non-response group (NRG), comprising Stable Disease (SD) and Progressive Disease (PD). LASSO was employed to select pretreatment DKI parameters, and ROC curves were generated for the selected parameters and serum SCC-Ag. RESULTS: Significant differences were observed in pretreatment MD, Da, Dr, MK, Ka, Kr, and SCC-Ag between the RG and NRG groups (P < 0.01). However, no significant differences were noted for FA and FAK (P = 0.441&0.928). The two selected parameters (MD and MK) demonstrated area under the curve (AUC), sensitivity, and specificity of 0.810, 0.769, 0.850 and 0.827, 0.846, 0.750, respectively. The combination of MD and MK exhibited an improved AUC of 0.901, sensitivity of 0.692, and specificity of 1.000, with a higher Youden index compared to the individual parameters. Conversely, the AUC, sensitivity, and specificity of the combination of MD, MK, and SCC-Ag were 0.852, 0.615, and 1.000, with a Youden index of 0.615. CONCLUSION: Pretreatment MD, MK, and SCC-Ag demonstrate potential clinical utility, with the combined application of MD and MK showing enhanced efficacy in assessing the early therapeutic response of cervical cancer to radiotherapy. The addition of SCC-Ag did not contribute further to the assessment efficacy.

Bisphenol S exposure promotes cell apoptosis and mitophagy in murine osteocytes by regulating mtROS signaling.

Bisphenol S (BPS), a safer alternative to bisphenol A, is commonly used as a plasticizer to manufacture various food-packaging materials. The accumulated BPS inhibits osteoblastic bone formation and promotes osteoclastogenesis, thereby accelerating remarkable bone destruction, but it is unclear whether BPS affects osteocytes, comprising over 95% of all bone cells. This study aimed to investigate the biological effect of BPS on osteocytes in vitro, as well as the detailed mechanism. Results showed that BPS (200, 400 µmol/L) exposure caused dose-dependently cell death of osteocytes MLO-Y4, and increased cell apoptosis. BPS induced loss of mitochondrial membrane potential (MMP) and mitochondria impairment. Furthermore, BPS upregulated expressions of mitophagy-related proteins including microtubule-associated protein light chain 3 (LC-3) II and PTEN-induced putative kinase (PINK) 1, accompanied by elevation of autophagy flux and the accumulation of acidic vacuoles; whereas p62 level was downregulated after BPS treatment. Additionally, BPS triggered the production of intracellular reactive oxygen species (ROS) and mitochondrial ROS (mtROS), while it decreased expression levels of nuclear factor E2-related factor 2 (Nrf2) and quinone oxidoreductase 1 (NQO1). The specific mtROS scavenger MitoTEMPO reversed cell apoptosis and mitophagy, suggesting that mtROS contributes to BPS exposure-induced apoptosis and mitophagy in MLO-Y4 cells. Our data first provide novel evidence that apoptosis and mitophagy as cellular mechanisms for the toxic effect of BPS on osteocytes, thereby helping our understanding of the potential role of osteocytes in the adverse effect of BPS and its analogs on bone growth, and supporting strategies targeting bone destruction caused by BPS.

Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation study.

BACKGROUND: Accurate detection is essential for brain metastasis (BM) management, but manual identification is laborious. This study developed, validated, and evaluated a BM detection (BMD) system. METHODS: Five hundred seventy-three consecutive patients (10 448 lesions) with newly diagnosed BMs and 377 patients without BMs were retrospectively enrolled to develop a multi-scale cascaded convolutional network using 3D-enhanced T1-weighted MR images. BMD was validated using a prospective validation set comprising an internal set (46 patients with 349 lesions; 44 patients without BMs) and three external sets (102 patients with 717 lesions; 108 patients without BMs). The lesion-based detection sensitivity and the number of false positives (FPs) per patient were analyzed. The detection sensitivity and reading time of three trainees and three experienced radiologists from three hospitals were evaluated using the validation set. RESULTS: The detection sensitivity and FPs were 95.8% and 0.39 in the test set, 96.0% and 0.27 in the internal validation set, and ranged from 88.9% to 95.5% and 0.29 to 0.66 in the external sets. The BMD system achieved higher detection sensitivity (93.2% [95% CI, 91.6-94.7%]) than all radiologists without BMD (ranging from 68.5% [95% CI, 65.7-71.3%] to 80.4% [95% CI, 78.0-82.8%], all P < .001). Radiologist detection sensitivity improved with BMD, reaching 92.7% to 95.0%. The mean reading time was reduced by 47% for trainees and 32% for experienced radiologists assisted by BMD relative to that without BMD. CONCLUSIONS: BMD enables accurate BM detection. Reading with BMD improves radiologists' detection sensitivity and reduces their reading times.