Detection of Cerebral Microbleeds in MR Images Using a Single-Stage Triplanar Ensemble Detection Network (TPE-Det).

BACKGROUND: Cerebral microbleeds (CMBs) are microscopic brain hemorrhages with implications for various diseases. Automated detection of CMBs is a challenging task due to their wide distribution throughout the brain, small size, and visual similarity to their mimics. For this reason, most of the previously proposed methods have been accomplished through two distinct stages, which may lead to difficulties in integrating them into clinical workflows. PURPOSE: To develop a clinically feasible end-to-end CMBs detection network with a single-stage structure utilizing 3D information. This study proposes triplanar ensemble detection network (TPE-Det), ensembling 2D convolutional neural networks (CNNs) based detection networks on axial, sagittal, and coronal planes. STUDY TYPE: Retrospective. SUBJECTS: Two datasets (DS1 and DS2) were used: 1) 116 patients with 367 CMBs and 12 patients without CMBs for training, validation, and testing (70.39 ± 9.30 years, 68 women, 60 men, DS1); 2) 58 subjects with 148 microbleeds and 21 subjects without CMBs only for testing (76.13 ± 7.89 years, 47 women, 32 men, DS2). FIELD STRENGTH/SEQUENCE: A 3 T field strength and 3D GRE sequence scan for SWI reconstructions. ASSESSMENT: The sensitivity, FPavg (false-positive per subject), and precision measures were computed and analyzed with statistical analysis. STATISTICAL TESTS: A paired t-test was performed to investigate the improvement of detection performance by the suggested ensembling technique in this study. A P value < 0.05 was considered significant. RESULTS: The proposed TPE-Det detected CMBs on the DS1 testing set with a sensitivity of 96.05% and an FPavg of 0.88, presenting statistically significant improvement. Even when the testing on DS2 was performed without retraining, the proposed model provided a sensitivity of 85.03% and an FPavg of 0.55. The precision was significantly higher than the other models. DATA CONCLUSION: The ensembling of multidimensional networks significantly improves precision, suggesting that this new approach could increase the benefits of detecting lesions in the clinic. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Trends in Cardiovascular Health Metrics among Korean Adults.

BACKGROUND: American Heart Association (AHA) defined 7 cardiovascular health metrics for the general population to improve cardiovascular health in 2010: not smoking; having normal blood pressure; being physically active; normal body mass index, blood glucose, and total cholesterol levels; and eating a healthy diet. To investigate trends in cardiovascular health metrics in Korea, we used data from the third and fourth Korean National Health and Nutrition Examination Surveys. METHODS: We defined seven cardiovascular health metrics similar to the one defined by AHA but physical activity, body mass index, and healthy diet were properly redefined to be suited for the Korean population. We compared each cardiovascular health metric and calculated the sum of cardiovascular health metrics after dichotomizing each health metric to ideal (scored 1) and poor (scored 0). RESULTS: Health metric scores of smoking in males (P value for trend < 0.001), physical activity both in males and females (P-value for trend < 0.001 both), body mass index in females (P-value for trend = 0.030), and blood pressure both in males and females (P-value for trend < 0.001, both) were improved. On the other hand, health metric scores of healthy diet in males (P-value for trend = 0.002), and fasting blood glucose both in males and females (P-value for trend < 0.001 both) got worse. The total scores of seven health metrics were stationary. CONCLUSION: Total scores were not changed but each metric showed various trends. A long-term study is necessary for analyzing exact trends.