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In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3-second runs (vice versa). This study aimed to determine the efficacy of an advanced deep learning denoising (DLD) technique in mitigating the trade-offs related to radiation dose and image quality during interventional BAE CBCT. This study included BMI-matched patients undergoing 6-second and 3-second BAE CBCT scans. The dose-area product values (DAP) were obtained. All datasets were reconstructed using standard weighted filtered back projection (OR) and a novel DLD software. Objective image metrics were derived from place-consistent regions of interest, including CT numbers of the Aorta and lung, noise, and contrast-to-noise ratio. Three blinded radiologists performed subjective assessments regarding image quality, sharpness, contrast, and motion artifacts on all dataset combinations in a forced-choice setup (−1 = inferior, 0 = equal; 1 = superior). The points were averaged per item for a total score. Statistical analysis ensued using a properly corrected mixed-effects model with post hoc pairwise comparisons. Sixty patients were assessed in 30 matched pairs (age 64 ± 15 years; 10 female). The mean DAP for the 6 s and 3 s runs was 2199 ± 185 µGym² and 1227 ± 90 µGym², respectively. Neither low-dose imaging nor the reconstruction method introduced a significant HU shift (p ≥ 0.127). The 3 s-DLD presented the least noise and superior contrast-to-noise ratio (CNR) (p < 0.001). While subjective evaluation revealed no noticeable distinction between 6 s-DLD and 3 s-DLD in terms of quality (p ≥ 0.996), both outperformed the OR variants (p < 0.001). The 3 s datasets exhibited fewer motion artifacts than the 6 s datasets (p < 0.001). DLD effectively mitigates the trade-off between radiation dose, image noise, and motion artifact burden in regular reconstructed BAE CBCT by enabling diagnostic scans with low radiation exposure and inherently low motion artifact burden at short examination times. [ABSTRACT FROM AUTHOR]

To evaluate 4D Flow magnetic resonance imaging (MRI) sequences for quantitative flow measurements of the pelvic venous vasculature. A prospective study of healthy volunteers was performed. After informed consent all subjects underwent 4D flow sequences at a 3 T MRI scanner with different isotropic resolution and different velocity encoding (Venc) settings: (sequence #1) voxel size (VS) 1.63 mm3, Venc 50 cm/s; (sequence #2) VS 1.63 mm3, Venc 100 cm/s and (sequence #3) VS 2.03 mm3, Venc 50 cm/s. Perfusion parameters were calculated for all venous vessel segments starting at the level of the inferior vena cava and extending caudally to the level of the common femoral vein. For reference, arterial flow was calculated using 1.63 mm3 isotropic resolution with a Venc of 100 cm/s. Ten healthy subjects (median age 28 years, interquartile range [IQR]: 26.25–28 years) were enrolled in this study. Median scanning time was 12:12 minutes (IQR 10:22–13:32 minutes) for sequence #1, 11:02 minutes (IQR 9:57–11:19 minutes) for sequence #2 and 6:10 minutes (IQR 5:44–6:47 minutes) for sequence #3. Flow measurements were derived from all sequences. The venous pelvic vasculature showed similar perfusion parameters compared to its arterial counterpart, for example the right common iliac arterial segment showed a perfusion of 8.32 ml/s (IQR: 6.94–10.68 ml/s) versus 7.29 ml/s (IQR: 4.70–8.90 ml/s) in the corresponding venous segment (P = 0.218). The venous flow measurements obtained from the three investigated sequences did not reveal significant differences. 4D Flow MRI is suitable for quantitative flow measurement of the venous pelvic vasculature. To reduce the scanning time without compromising quantitative results, the resolution can be decreased while increasing the Venc. This technique may be utilized in the future for the diagnosis and treatment response assessment of iliac vein compression syndromes. [ABSTRACT FROM AUTHOR]