Although PET/MRI has the advantages of a simultaneous acquisition of PET and MRI, high soft-tissue contrast of the MRI images, and reduction of radiation exposure, its low profitability and long acquisition time are significant problems in clinical settings. Thus, MRI protocols that meet oncological purposes need to be used in order to reduce examination time while securing detectability. Currently, half-Fourier acquisition single-shot turbo spin echo and 3D-T1 volumetric interpolated breath-hold examination may be the most commonly used sequences for whole-body imaging due to their shorter acquisition time and higher diagnostic accuracy. Although there have been several reports that adding diffusion weighted image (DWI) to PET/MRI protocol has had no effect on tumor detection to date, in cases of liver, kidney, bladder, and prostate cancer, the use of DWI may be beneficial in detecting lesions. Another possible option is to scan each region with different MRI sequences instead of scanning the whole body using one sequence continuously. We herein report a workflow and imaging protocols for whole-body oncologic PET/MRI using an integrated system in the clinical routine, designed for the detection, for example by cancer screening, of metastatic lesions, in order to help future users optimize their workflow and imaging protocols.
The aim of the study is to evaluate whether the prediction of anemia is possible using quantitative analyses of unenhanced cranial computed tomography (CT) with deep learning reconstruction (DLR) compared with conventional methods.
Methods:This cross-sectional retrospective study included 116 participants (76 males; mean age, 66.7) who had hemoglobin (Hb) levels obtained within 24 hours of unenhanced cranial CT, which included 2 reconstruction methods: DLR and hybrid iterative reconstruction. Regions of interest were the confluence of sinuses (CoS) and the right and left transverse sinuses. In addition, edge rise distance of cerebrospinal fluid and venous was measured.Results: Spearman rank correlation coefficient demonstrated a positive association between Hb levels and sinus attenuation values. Among these, the CoS in DLR had the best correlation (r = 0.703, P < 0.001). For the prediction of anemia (Hb < 11 g/dL), the area under the curve of CoS in DLR (area under the curve = 0.874; 95% confidence interval, 0.798-0.949; P < 0.001) was the highest; however, there were no significant differences among reconstruction method and sinus. The attenuation values of DLR were significantly higher than those of hybrid iterative reconstruction ( P < 0.001, paired t test), and the differences between the 2 methods were 4.1 (standard deviation [SD], 1.6) for CoS, 5.2 (SD, 2.2) for right transverse sinuses, and 5.8 (SD, 2.4) for left transverse sinuses. The signal-to-noise ratio ( P < 0.001, paired t test) and edge rise distance ( P < 0.001, Wilcoxon signed rank test) of DLR was significantly higher.
Conclusions:Higher CT attenuation values should be considered for predicting anemia based on brain DLR images.
Background
Self-efficacy is crucial in improving medical students’ communication skills. This study aims to clarify where medical students’ self-efficacy is greatest following an interview with a simulated patient and subsequent feedback.
Methods
A total of 162 medical students (109 men, 53 women) in their fourth or fifth year at a university in Japan participated in this study. The degree of self-efficacy in medical interviewing was measured before and after a medical interview with a simulated patient, and after the subsequent feedback session.
Results
ANOVA analysis revealed that self-efficacy for medical interviews was higher after both the interview and the feedback session than before the interview. Among all three time points, self-efficacy was highest after the feedback session.
Conclusions
Feedback following a simulated interview with a simulated patient is important to improve the self-efficacy of medical students when learning medical interviewing skills.
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