Real-time aortic pulse wave velocity measurement during exercise stress testing.

BACKGROUND: Pulse wave velocity (PWV), a measure of arterial stiffness, has been demonstrated to be an independent predictor of adverse cardiovascular outcomes. This can be derived non-invasively using cardiovascular magnetic resonance (CMR). Changes in PWV during exercise may reveal further information on vascular pathology. However, most known CMR methods for quantifying PWV are currently unsuitable for exercise stress testing. METHODS: A velocity-sensitive real-time acquisition and evaluation (RACE) pulse sequence was adapted to provide interleaved acquisition of two locations in the descending aorta (at the level of the pulmonary artery bifurcation and above the renal arteries) at 7.8 ms temporal resolution. An automated method was used to calculate the foot-to-foot transit time of the velocity pulse wave. The RACE method was validated against a standard gated phase contrast (STD) method in flexible tube phantoms using a pulsatile flow pump. The method was applied in 50 healthy volunteers (28 males) aged 22-75 years using a MR-compatible cycle ergometer to achieve moderate work rate (38 ± 22 W, with a 31 ± 12 bpm increase in heart rate) in the supine position. Central pulse pressures were estimated using a MR-compatible brachial device. Scan-rescan reproducibility was evaluated in nine volunteers. RESULTS: Phantom PWV was 22 m/s (STD) vs. 26 ± 5 m/s (RACE) for a butyl rubber tube, and 5.5 vs. 6.1 ± 0.3 m/s for a latex rubber tube. In healthy volunteers PWV increased with age at both rest (R(2) = 0.31 p < 0.001) and exercise (R(2) = 0.40, p < 0.001). PWV was significantly increased at exercise relative to rest (0.71 ± 2.2 m/s, p = 0.04). Scan-rescan reproducibility at rest was -0.21 ± 0.68 m/s (n = 9). CONCLUSIONS: This study demonstrates the validity of CMR in the evaluation of PWV during exercise in healthy subjects. The results support the feasibility of using this method in evaluating of patients with systemic aortic disease.

Estimation of myocardial strain from non-rigid registration and highly accelerated cine CMR.

Sparsely sampled cardiac cine accelerated acquisitions show promise for faster evaluation of left-ventricular function. Myocardial strain estimation using image feature tracking methods is also becoming widespread. However, it is not known whether highly accelerated acquisitions also provide reliable feature tracking strain estimates. Twenty patients and twenty healthy volunteers were imaged with conventional 14-beat/slice cine acquisition (STD), 4× accelerated 4-beat/slice acquisition with iterative reconstruction (R4), and a 9.2× accelerated 2-beat/slice real-time acquisition with sparse sampling and iterative reconstruction (R9.2). Radial and circumferential strains were calculated using non-rigid registration in the mid-ventricle short-axis slice and inter-observer errors were evaluated. Consistency was assessed using intra-class correlation coefficients (ICC) and bias with Bland-Altman analysis. Peak circumferential strain magnitude was highly consistent between STD and R4 and R9.2 (ICC = 0.876 and 0.884, respectively). Average bias was -1.7 ± 2.0 %, p < 0.001, for R4 and -2.7 ± 1.9 %, p < 0.001 for R9.2. Peak radial strain was also highly consistent (ICC = 0.829 and 0.785, respectively), with average bias -11.2 ± 18.4 %, p < 0.001, for R4 and -15.0 ± 21.2 %, p < 0.001 for R9.2. STD circumferential strain could be predicted by linear regression from R9.2 with an R2 of 0.82 and a root mean squared error of 1.8 %. Similarly, radial strain could be predicted with an R2 of 0.67 and a root mean squared error of 21.3 %. Inter-observer errors were not significantly different between methods, except for peak circumferential strain R9.2 (1.1 ± 1.9 %) versus STD (0.3 ± 1.0 %), p = 0.011. Although small systematic differences were observed in strain, these were highly consistent with standard acquisitions, suggesting that accelerated myocardial strain is feasible and reliable in patients who require short acquisition durations.