Branch Pulmonary Artery Regurgitation in Repaired Tetralogy of Fallot: Correlation with Pulmonary Artery Morphology, Distensibility, and Right Ventricular Function

Background: The aim was to determine the effect of pulmonary artery (PA) morphology on the branch pulmonary artery-regurgitation fraction (BPA-RF), the relationship of pulmonary insufficiency (PI) to BPA-RF and PA-distensibility, and factors (BPA-RF and PA-distensibility) associated with right ventricular function (RVF) in repaired tetralogy of Fallot (rTOF). Methods: A total of 182 rTOF patients (median age 17.1 years) were analyzed for length, angle of PA, BPA-RF, PI, and PA-distensibility, using magnetic resonance imaging. Results: The left PA had a significant greater RF than the right PA (median (interquartile range)): LPA 43.1% (32.6–51.5) and RPA 35.2% (24.7–44.7), p < 0.001. The LPA was shorter with a narrower angle than the RPA (p < 0.001). The anatomy of the branch-PA was not a factor for the greater LPA-RF (odds ratio, 95% confidence interval: CI, p-value): length 0.44 (0.95–2.00), p = 0.28; angle 0.63 (0.13–2.99), p = 0.56. There was a strong positive correlation between PI and BPA-RF-coefficients (95% CI), p-value: LPA 0.78% (0.70–0.86), p < 0.001; RPA 0.78% (0.71–0.84), p < 0.001 and between BPA-RF and distensibility-coefficients (95%CI), p-value: LPA 0.73% (0.37–1.09), p < 0.001; RPA 1.63% (1.22–2.03), p < 0.001, respectively. The adjusted BPA-RF did not predict RVF, RPA (p = 0.434), LPA (p = 0.268). Conclusions: PA morphology is not a significant factor for the differential BPA-RF. The vascular wall in rTOF patients responds to chronic increased intravascular volume by increasing distensibility. BPA-RF is not a determinant of RVF

Spatial up-sampling of HRTF sets using generative adversarial networks: a pilot study

Headphone-based spatial audio simulations rely on Head Related Transfer Functions (HRTFs) in order to reconstruct the sound field at the entrance of the listener’s ears. A HRTF is strongly dependent on the listener’s specific anatomical structures, and it has been shown that virtual sounds recreated with someone else’s HRTF result in worse localisation accuracy, as well as altering other subjective measures such as externalisation and realism. Acoustic measurements of the filtering effects generated by ears, head and torso has proven to be one of the most reliable ways to obtain a personalised HRTF. However this requires a dedicated and expensive setup, and is time-intensive. In order to simplify the measurement setup, thereby improving the scalability of the process, we are exploring strategies to reduce the number of acoustic measurements without degrading the spatial resolution of the HRTF. Traditionally, spatial up sampling of HRTF sets is achieved through barycentric interpolation or by employing the spherical harmonics framework. However, such methods often perform poorly when the provided HRTF data is spatially very sparse. This work investigates the use of generative adversarial networks (GANs) to tackle the up-sampling problem, offering an initial insight about the suitability of this technique. Numerical evaluations based on spectral magnitude error and perceptual model outputs are presented on single spatial dimensions, therefore considering sources positioned only in one of the three main planes: horizontal, median, and frontal. Results suggest that traditional HRTF interpolation methods perform better than the proposed GAN-based one when the distance between measurements is smaller than 90°, but for the sparsest conditions (i.e. one measurement every 120° to 180°), the proposed approach outperforms the others

Cardiovascular magnetic resonance imaging for diagnosis and clinical management of suspected cardiac masses and tumours

To evaluate the diagnostic accuracy of cardiovascular magnetic resonance (CMR) imaging from a risk-stratification and therapeutic-management perspective in patients with suspected cardiac tumours