Sonne Williford (smokecoal90)

7 %) in 29 patients (49.2 %). A significantly higher detection rate of PSMA PET/CT was observed on a lesion-based analysis (p < 0.0001) and on a patient based analysis (p < 0.0001). Herein, both Ga- and F-PSMA PET/CT performed significantly better than CT alone (p < 0.0001, respectively). In 9 patients (15.3 %) no relapse was detectable by either modality. All lesions detected by CT were also detected by PSMA PET/CT. selleck chemical In 38 patients PSMA PET/CT detected more lesions than CT alone, altering the treatment approach in 22 of these patients. PSMA PET/CT is superior to CT alone in detecting biochemical recurrence in PCa patients after radical prostatectomy and offered additional therapeutic options in a substantial number of patients. PSMA PET/CT is superior to CT alone in detecting biochemical recurrence in PCa patients after radical prostatectomy and offered additional therapeutic options in a substantial number of patients. To explore whether CT texture analysis can identify thin-cap fibroatheroma (TCFA) determined by optical coherence tomography (OCT). Thirty-three patients with 43 lesions who underwent both CCTA and OCT within 3 months were retrospectively included. 12 conventional CT-derived plaque features, fat attenuation index (FAI) and 1691 plaque radiomics features were extracted to discriminate TCFA lesions and non-TCFA lesions determined by OCT. Minimum redundancy and maximum relevance (mRMR) method was employed to select radiomics features. The top ranked features were used to construct a forward stepwise logistic radiomics model. The performance of radiomics model was compared with the conventional high-risk plaque (HRP) features model and FAI model for the detection of TCFA. Out of 1691 features, 35 features were significantly different between TCFA and non-TCFA lesions (all p＜0.05) while only low attenuation plaque (LAP) was more frequent in TCFA group (p = 0.004). There was no significant difference in FAI between TCFA and non-TCFA lesions. Five features were ultimately integrated into the radiomics model after mRMR analysis, which demonstrated significantly higher AUC for the detection of TCFA (0.952; 95 % CI 0.897-1.000) compared with the conventional HRP features model (0.621; 95 % CI 0.469-0.773, p < 0.001) and FAI model (0.52; 95 % CI 0.33-0.70, p < 0.001). CT texture analysis performs better at identifying TCFA determined by OCT compared with conventional CT-derived plaque parameters and FAI. Texture analysis may serve as a potential non-invasive method of evaluating vulnerable plaque. CT texture analysis performs better at identifying TCFA determined by OCT compared with conventional CT-derived plaque parameters and FAI. Texture analysis may serve as a potential non-invasive method of evaluating vulnerable plaque.Respiratory viruses are the most common causes of acute respiratory infections. However, identification of the underlying viral pathogen may not always be easy. Clinical presentations of respiratory viral infections usually overlap and may mimic those of diseases caused by bacteria. However, certain imaging morphologic patterns may suggest a particular viral pathogen as the cause of the infection. Although definitive diagnosis cannot be made on the basis of clinical or imaging features alone, the use of a combination of clinical and radiographic findings can substantially improve the accuracy of diagnosis. The purpose of this review is to present the clinical, epidemiological and radiological patterns of lower respiratory tract viral pathogens providing a comprehensive approach for their diagnosis and identification in hospitals and community outbreaks.Despite the rationale that early anti-platelet would lower the risk of major organ dysfunction, the effectiveness of this approach remains controversial. Therefore, we perform a systematic review and meta-analysis to investigate the effect