A meta-analysis of the value of MRI-based VBQ scores for evaluating osteoporosis.

Objective: Osteoporosis is the most common skeletal disease in humans. Early onset of osteoporosis is usually asymptomatic, so early diagnosis is critical. The purpose of this study was to analyze the value of MRI-based VBQ scores for evaluating osteoporosis. Methods: We searched PubMed, Embase, the Cochrane Library databases, Web of Science, and some Chinese electronic databases for published articles and the ClinicalTrials.gov site for completed but unpublished studies on evaluating the value of MRI-based VBQ scores for evaluating osteoporosis. We calculated the summarized sensitivity, specificity, the ROC curve (AUC) values and their 95% confidence intervals (CIs) using MetaDiSc 1.4 software and STATA. Results: Our study included 8 studies involving 999 patients of which 660 patients were diagnosed with osteopenia/osteoporosis, and 339 patients were identified as having normal BMD. The pooled sensitivity was 0.809 (95% CI, 0.777-0.838, I2 = 78.8%), the pooled specificity was 0.640 (95% CI, 0.587-0.691, I2 = 85.9%), and the pooled AUC was 0.8375. Conclusion: MRI-based VBQ scores provided high sensitivity and moderate specificity in detecting osteoporosis. Opportunistic use of VBQ scores could be considered, e.g. before lumbar spine surgery. Prospero registration number: CRD42022377024.

Integrating multiple MRI sequences for pelvic organs segmentation via the attention mechanism.

PURPOSE: To create a network which fully utilizes multi-sequence MRI and compares favorably with manual human contouring. METHODS: We retrospectively collected 89 MRI studies of the pelvic cavity from patients with prostate cancer and cervical cancer. The dataset contained 89 samples from 87 patients with a total of 84 valid samples. MRI was performed with T1-weighted (T1), T2-weighted (T2), and Enhanced Dixon T1-weighted (T1DIXONC) sequences. There were two cohorts. The training cohort contained 55 samples and the testing cohort contained 29 samples. The MRI images in the training cohort contained contouring data from radiotherapist α. The MRI images in the testing cohort contained contouring data from radiotherapist α and contouring data from another radiotherapist: radiotherapist ß. The training cohort was used to optimize the convolution neural networks, which included the attention mechanism through the proposed activation module and the blended module into multiple MRI sequences, to perform autodelineation. The testing cohort was used to assess the networks' autodelineation performance. The contoured organs at risk (OAR) were the anal canal, bladder, rectum, femoral head (L), and femoral head (R). RESULTS: We compared our proposed network with UNet and FuseUNet using our dataset. When T1 was the main sequence, we input three sequences to segment five organs and evaluated the results using four metrics: the DSC (Dice similarity coefficient), the JSC (Jaccard similarity coefficient), the ASD (average mean distance), and the 95% HD (robust Hausdorff distance). The proposed network achieved improved results compared with the baselines among all metrics. The DSC were 0.834±0.029, 0.818±0.037, and 0.808±0.050 for our proposed network, FuseUNet, and UNet, respectively. The 95% HD were 7.256±2.748 mm, 8.404±3.297 mm, and 8.951±4.798 mm for our proposed network, FuseUNet, and UNet, respectively. Our proposed network also had superior performance on the JSC and ASD coefficients. CONCLUSION: Our proposed activation module and blended module significantly improved the performance of FuseUNet for multi-sequence MRI segmentation. Our proposed network integrated multiple MRI sequences efficiently and autosegmented OAR rapidly and accurately. We also discovered that three-sequence fusion (T1-T1DIXONC-T2) was superior to two-sequence fusion (T1-T2 and T1-T1DIXONC, respectively). We infer that the more MRI sequences fused, the better the automatic segmentation results.

Association Between Ideal Cardiovascular Health and Executive Function in Chinese Primary School Children.

Aims: Little information exists on the associations of cardiovascular health, a new metric proposed by the American Heart Association, and executive function, particularly in children. We aimed to explore this topic. Methods: We studied 3,798 children aged 6-12 years from 5 schools in Guangzhou, China. The executive function of children was evaluated using parent reports of the Behavioral Rating Inventory of Executive Function, which included 2 composite indexes and 8 subscale scores. We calculated the number of ideal cardiovascular health (range: 0-7) based on smoking, body mass index, physical activity (PA), diet, blood pressure, cholesterol, and glucose. A generalized linear mixed model was used to assess the association of the number of ideal cardiovascular health metrics and executive function. Results: Compared with children exhibiting 1-3 ideal cardiovascular health metrics, decreases of 1.37-2.63 points (indicating better performance) in metacognition index and its 5 subscale indexes (initiate, working memory, plan/organize, organization of materials, and monitor) were observed in children who attained 5 or 6-7 ideal metrics (all p for trend <0.001). Ideal diet and ideal PA were independently associated with lower indexes of behavioral regulation and metacognition. Conclusions: The number of ideal cardiovascular health was positively associated with performance of executive function in children.

Exposure to ambient air pollution and executive function among Chinese primary schoolchildren.

BACKGROUND: Evidence on the associations between particulate matter (PM) and nitrogen dioxide (NO2) exposure with executive function in children is scarce in developing countries. Moreover, few studies investigated ozone (O3) and sulfur dioxide (SO2). This study aimed to investigate the associations between long-term exposure to air pollution and executive function in Chinese children. METHODS: In 2017, we randomly recruited 5028 children aged 6-12 years from 5 schools in Guangzhou city, southern China. Each of 5028 children's executive function were assessed using parent filled questionnaire. We further randomly selected 522 children to take computerized tests to assess working memory, inhibitory control, and cognitive flexibility. The 1-year average residence-based exposure to PM with diameters ≤2.5 (PM2.5) or 10 µm (PM10), NO2, O3, and SO2 exposures were estimated by using an inverse-distance weighting approach. Associations were evaluated by mixed linear regression models. RESULTS: The 1-year average concentrations of PM2.5, PM10, NO2, SO2, and O3 was 39.06 ± 1.12 µg/m3, 60.95 ± 3.49 µg/m3, 53.64 ± 4.44 µg/m3, 12.33 ± 0.79 µg/m3, and 90.07 ± 7.96 µg/m3, respectively. Each interquartile range increment in PM2.5 was associated with 48.04 ms [95% confidence interval (CI): 2.18 to 93.89] increase in inhibitory control and 0.72 (95% CI: -1.14 to -0.29) points decrease in forward recall. PM10 exposure was associated with 0.55 (95% CI: -1.04 to -0.06) and 0.67 points (95% CI: -1.09 to -0.25) reduction in forward and backward recall, respectively. SO2 exposure was associated with 0.69 (95%CI: 0.37 to 1.02) and 0.73 (95%CI: 0.40 to 1.05) high scores of behavioral regulation index and metacognition index, respectively. Significant association was found between O3 exposure and metacognition index (estimate, 95%CI: 0.87, 0.45 to 1.29). No associations for cognitive flexibility were observed. Stratified analyses did not yield any significant modification effects of sex, physical activity, screen time, and parental smoking. CONCLUSIONS: Long-term exposures to PM2.5, PM10, SO2, and O3 were associated with poorer performance in working memory, inhibitory control, behavioral regulation, and metacognition in children.