Pathological wave dynamics: a postulate for sudden cardiac death in athletes

Real-time radial tagging for quantification of left ventricular torsion

PURPOSE

To develop a real-time radial tagging MRI for accurate measurement of rotational motion and twist of the left ventricle (LV).

METHODS

A FLASH-based radial tagging sequence with an undersampled radial reading scheme was developed for both single and double-slice imaging in real-time. The Polar Fourier Transform was used for reconstruction to push the undersampling artifacts out of a reduced FOV. The developed technique was used to image five normal subjects during rest, plus one during both exercise and rest conditions. LV rotational motions were estimated for five consecutive cardiac cycles in all cases. The process was validated using a numerical phantom. The real-time measurement of global rotational motion was compared with those measured from a non-real-time exam using linear regression analysis and the Bland-Altman plot.

RESULTS

The real-time acquisition was performed successfully with a temporal resolution of 46.2 ms. Image quality was sufficient for the reproducible calculation of rotation at rest and exercise. The feasibility of double-slice acquisition on human was further studied and a real-time twist of the left ventricle was demonstrated. The difference between LV global rotations from real-time and non-real-time approaches was 0.27 degrees. A significant reverse recoiling, induced by exercise, was reproducibly measured by the technique.

CONCLUSION

A real-time radial tagging MRI technique was developed based on the undersampled radial acquisition and Polar Fourier Transform reconstruction, for accurate measuring of the heart rotational motion and twist. The technique was able to extract a meaningful change of diastolic recoiling under stress test conditions during physical activities (cycling).

Dynamic Effects of Aortic Arch Stiffening on Pulsatile Energy Transmission to Cerebral Vasculature as A Determinant of Brain-Heart Coupling

Aortic stiffness increases with age and is a robust predictor of brain pathology including Alzheimer’s and other dementias. Aging causes disproportionate stiffening of the aorta compared with the carotid arteries, reducing protective impedance mismatches at their interface and affecting transmission of destructive pulsatile energy to the cerebral circulation. Recent clinical studies have measured regional stiffness within the aortic arch using pulse wave velocity (PWV) and have found a stronger association with cerebrovascular events than global stiffness measures. However, effects of aortic arch PWV on the transmission of harmful excessive pulsatile energy to the brain is not well-understood. In this study, we use an energy-based analysis of hemodynamic waves to quantify the effect of aortic arch stiffening on transmitted pulsatility to cerebral vasculature, employing a computational approach using a one-dimensional model of the human vascular network. Results show there exists an optimum wave condition—occurring near normal human heart rates—that minimizes pulsatile energy transmission to the brain. This indicates the important role of aortic arch biomechanics on heart-brain coupling. Our results also suggest that energy-based indices of pulsatility combining pressure and flow data are more sensitive to increased stiffness than using flow or pressure pulsatility indices in isolation.