[Comparison of Bayesian Estimation and SVD Methods for CT Perfusion in Patients with Acute Stroke].

PURPOSE: There are various analysis methods for CT perfusion (CTP). Although the advantages of Bayesian estimation algorithms have been newly suggested, comparisons with other analysis methods on clinical data are still limited. In this study, we compared the Bayesian estimation method with the singular value decomposition (SVD) method in the evaluation of patients with acute cerebral infarction and examined its usefulness. METHODS: CTP data from 13 patients with acute stroke were analyzed using the SVD and Bayesian estimation methods implemented in Vitrea. Evaluation of visual clarity of the ischemic area and quantitative values of the healthy side-affected side ratio using the mean values of the left and right region of interest (ROI) on the images were compared using the SVD and Bayesian estimation methods. RESULTS: In visual evaluation, there were significant differences in CBV in four cases, and in CBF, MTT, and TTP in many cases. The healthy side-affected side ratio of the SVD and Bayesian estimation methods were as follows: CBF 1.19, 1.84; CBV 1.09, 1.02; MTT 1.12, 1.79; and TTP 1.48, 1.19. For CBF and MTT, the Bayesian estimation method had a larger ratio of the healthy side to the affected side, and for TTP, the SVD method had a larger ratio of the test side to the affected side. CONCLUSION: We suggest that the Bayesian estimation method is more useful than the SVD method for assessing CBF and MTT in CTP analysis of patients with acute stroke.

Obesity and smoking: relationship with waist circumference and obesity-related disorders in men undergoing a health screening.

This study investigated whether smoking habits had a differential influence on waist circumference and obesity-related disorders in nonobese and obese men. We investigated 359 men with smoking habits confirmed by their spouses, including 172 nonobese men (BMI<25) and 187 obese men (BMI>or=25). There were 113 nonobese smokers and 129 obese smokers. Obesity-related disorders were defined as hypertension, dyslipidemia, hyperglycemia, hyperuricemia, or treatment for one or more of these disorders. Nonobese subjects showed no differences of age, BMI, and waist circumference between smokers and nonsmokers, but smokers had a higher incidence of obesity-related disorders. Obese smokers were younger than obese nonsmokers and had a larger waist circumference, but a similar prevalence of obesity-related disorders. The prevalence of obesity-related disorders was similar between obese nonsmokers and smokers, but the smokers were younger. In nonobese subjects, smoking may increase obesity-related disorders by a mechanism other than visceral fat accumulation. In obese subjects, however, smoking may promote visceral fat accumulation. Further investigations will be necessary to better elucidate the relationship between the promotion of visceral fat accumulation in obese subjects by smoking and obesity-related disorders.