Background 17O‐labeled water (PSO17) is a contrast agent developed to measure brain water dynamics and cerebral blood flow. Purpose To evaluate the safety and feasibility of PSO17. Study Type Prospective study. Subjects A total of 12 male healthy volunteers (23.1 ± 1.9 years) were assigned to three groups of four subjects: placebo (normal saline), PSO17 10%, and PSO17 20%. Field Strength/Sequence Dynamic 3D fluid attenuated inversion recovery (FLAIR, fast spin echo with variable refocusing flip angle) scans of the brain were performed with 3‐T MRI. Assessment Contrast agents were injected 5 minutes after the start of a 10‐minute scan. Any symptoms, vital signs, and blood and urine tests were evaluated at five timepoints from preinjection to 4 days after. Blood samples for pharmacokinetic analysis, including half‐life (T1/2), maximum fraction (Cmax), time‐to‐maximum fraction (Tmax), and area under the curve (AUC), were collected at 13 timepoints from preinjection to 168 hours after. Regions of interest were set in the cerebral cortex (CC), basal ganglia/thalamus (BG/TM), and white matter (WM), and 17O concentrations were calculated from signal changes and evaluated using Cmax. Statistical Tests All items were compared among the three groups using Tukey–Kramer's honestly significant difference test. Statistical significance was defined as P < 0.5. Results No safety issues were noted with the intravenous administration of PSO17. The T1/2 was approximately 160 hours, and the AUCs were 1.77 ± 0.10 and 3.75 ± 0.36 in the PSO17 10% and 20% groups, respectively. 17O fractions calculated from MRI signals were higher in the PSO17 20% group than in the 10% and placebo groups. Significant differences were noted between all pairs of groups in the CC and BG/TM, and between PSO17 20% and both placebo and 10% groups in the WM. Data Conclusion PSO17 might be considered safe as a contrast medium. Dynamic 3D‐FLAIR might detect dose‐dependent signal changes and estimate 17O. Evidence Level 1 Technical Efficacy Stage 1

Background Pre- and post-procedural hemodynamic changes which could affect adverse outcomes in aortic stenosis (AS) patients who undergo transcatheter aortic valve replacement (TAVR) have not been well investigated. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) enables accurate analysis of blood flow dynamics such as flow velocity, flow pattern, wall shear stress (WSS), and energy loss (EL). We sought to examine the changes in blood flow dynamics of patients with severe AS who underwent TAVR. Methods We examined 32 consecutive severe AS patients who underwent TAVR between May 2018 and June 2019 (17 men, 82 ± 5 years, median left ventricular ejection fraction 61%, 6 self-expanding valve), after excluding those without CMR because of a contraindication or inadequate imaging from the analyses. We analyzed blood flow patterns, WSS and EL in the ascending aorta (AAo), and those changes before and after TAVR using 4D flow CMR. Results After TAVR, semi-quantified helical flow in the AAo was significantly decreased (1.4 ± 0.6 vs. 1.9 ± 0.8, P = 0.002), whereas vortical flow and eccentricity showed no significant changes. WSS along the ascending aortic circumference was significantly decreased in the left (P = 0.038) and left anterior (P = 0.033) wall at the basal level, right posterior (P = 0.011) and left (P = 0.010) wall at the middle level, and right (P = 0.012), left posterior (P = 0.019) and left anterior (P = 0.028) wall at the upper level. EL in the AAo was significantly decreased (15.6 [10.8–25.1 vs. 25.8 [18.6–36.2]] mW, P = 0.012). Furthermore, a significant negative correlation was observed between EL and effective orifice area index after TAVR (r = − 0.38, P = 0.034). Conclusions In severe AS patients undergoing TAVR, 4D flow CMR demonstrates that TAVR improves blood flow dynamics, especially when a larger effective orifice area index is obtained.

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Background In nasal or sinonasal tumors, orbital invasion beyond periorbita by the tumor is one of the important criteria in the selection of the surgical procedure. We investigated the usefulness of the convolutional neural network (CNN)-based deep learning technique for the diagnosis of orbital invasion, using computed tomography (CT) images. Methods A total of 168 lesions with malignant nasal or sinonasal tumors were divided into a training dataset (n = 119) and a test dataset (n = 49). The final diagnosis (invasion-positive or -negative) was determined by experienced radiologists who carefully reviewed all of the CT images. In a CNN-based deep learning analysis, a slice of the square target region that included the orbital bone wall was extracted and fed into a deep-learning training session to create a diagnostic model using transfer learning with the Visual Geometry Group 16 (VGG16) model. The test dataset was subsequently tested in CNN-based diagnostic models and by two other radiologists who were not specialized in head and neck radiology. At approx. 2 months after the first reading session, two radiologists again reviewed all of the images in the test dataset, referring to the diagnoses provided by the trained CNN-based diagnostic model. Results The diagnostic accuracy was 0.92 by the CNN-based diagnostic models, whereas the diagnostic accuracies by the two radiologists at the first reading session were 0.49 and 0.45, respectively. In the second reading session by two radiologists (diagnosing with the assistance by the CNN-based diagnostic model), marked elevations of the diagnostic accuracy were observed (0.94 and 1.00, respectively). Conclusion The CNN-based deep learning technique can be a useful support tool in assessing the presence of orbital invasion on CT images, especially for non-specialized radiologists.

4D flow MRI allows time-resolved 3D velocity-encoded phase-contrast imaging for 3D visualization and quantification of aortic and intracardiac flow. Radiologists should be familiar with the principles of 4D flow MRI and methods for evaluating blood flow qualitatively and quantitatively. The most substantial benefits of 4D flow MRI are that it enables the simultaneous comprehensive assessment of different vessels, and that retrospective analysis can be achieved in all vessels in any direction in the field of view, which is especially beneficial for patients with complicated congenital heart disease (CHD). For aortic valvular diseases, new parameters such as wall shear stress and energy loss may provide new prognostic values for 4D flow MRI. In this review, we introduce the clinical applications of 4D flow MRI for the visualization of blood flow and quantification of hemodynamic metrics in the setting of aortic valvular disease and CHD, including intracardiac shunt and coronary artery anomaly.