Pulse Wave Velocity in Normal Pulmonary Arteries by CMR;

a Comparison between Respiratory Gated and Non-Respiratory Gated Acquisition

W. Bradlow, P Gatehouse, R. Hughes, D. Firmin, R. Mohiaddin

Cardiovascular Magnetic Resonance Unit, The Royal Brompton Hospital, London, UK.

Introduction

Pulse wave velocity (PWV), calculated by dividing the distance separating two

points in a vessel by the time taken for the pulse wave to move between them, is a

useful marker of arterial wall stiffness. PWV measurement in normal pulmonary

arteries is currently being investigated by cardiac magnetic resonance (CMR), a

technique proven in similar analysis of the aorta 1. We have previously reported a

flow sequence where data was acquired at end-expiration and whose high

temporal resolution and use of interleaved slices allowed pulmonary PWV to be

calculated (Bradlow et al, Euro CMR Zurich, 2005).This may subsequently

provide a means with which to study abnormalities in arteries subject to

pulmonary hypertension.

Due to changes in intrathoracic pressure, caval flow and lung inflation, pressure-

flow waves, and their corresponding wave velocities, are subject to respiratory

variation. Methods to address this issue have been suggested for aortic PWV by

other non invasive means 2, but have not been fully explored in the assessment of

pulmonary PWV by CMR. Aim

To compare PWV data acquired at end-expiration with that acquired throughout

the respiratory cycle in the pulmonary arteries of adult volunteers.

Methods

Non-segmented through-plane phase velocity mapping (at 85cm/s VENC) was

applied to three slices transecting the main, left and right pulmonary arteries

(MPA,LPA,RPA) during free breathing (Figure 1). The use of an external

electrocardiogram system (with short filtering delays) to trigger the sequence

minimised the period between R wave and first RF pulse. Reference data

acquisition for the three slices was interleaved for 80 cine frames per slice within

each cardiac cycle, and repeated with velocity encoding on the subsequent cycle.

Velocity images were reconstructed by subtracting both phase images and

background velocity errors (measured by imaging the same planes in a stationary

phantom). Using maximum gradient and RF performance, and inverting the

slice-selection gradient for velocity encoding, TR 1.9ms was achieved, giving

TR 5.7ms for each of the three vessels in turn. Voxel size was FE 1.8 mm by PE

2.4 mm by SLT 8mm, echo time 1.1ms and flip angle 15o.

14 volunteers were studied and the sequence repeated three times with

diaphragm navigator (respiratory gated to end-expiration) and without (non-

navigated). A central region of interest was applied to each artery in each phase

and the mean velocity within it calculated (in-plane motion of MPA was

followed manually). Mean velocities were plotted against time (Figure 2). Pulse

arrival time was derived automatically without operator intervention. Baseline

and peak velocities were found and a velocity halfway between the two

calculated (V ½). V ½ was identified on the leading edge of the flow wave and a

straight line fitted to data points within +/-4ms of it. Arrival time was defined by

the intersection of this line and V ½. Path length was measured from multislice

transverse images.

Wilcoxon signed rank test was used to compare median values for navigated and

non-navigated data.

References

1. Lehmann E. Clinical value of aortic pulse-wave velocity measurement. Lancet

1999; 354:528-529.

2. Asmar R. Factors affecting Pulse Wave Velocity. Arterial Stiffness and Pulse

Wave Velocity Clincal Applications. Elsevier; 1999.p 82.

Figure 1

Figure shows typical sites of diaphragm navigator (small arrow) and vessel

slices (arrowhead)

Arrival of Flow Waves

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 20 40 60 80 100 120 140 160 180 200 220 240

Time (ms) after R-wave

Sp

eed

(m

/s)

MPA

LPA

RPA

Figure 2

Note measurable delay between onset of flow in MPA and that in RPA/LPA

Results

No statistically significant difference was found between navigated and non-

navigated data (Figure 3) (LPA p = 0.826, LPA p = 0.258).For clarity, three

volunteers who gave erratic (>10m/s or negative) LPA PWV values (found in

both navigated and non-navigated acquisition) and one outlier (non navigated

RPA; 4.85 m/s) are not included in the graph. They were all included in the

analysis.

Figure 3

Discussion

These results might be expected when one considers that end expiration

constitutes the majority of the free breathing cycle. In addition, respiratory

variations are likely to be attenuated as the derived PWV represents an average

value for the whole examination. Interleaving acquisition of the three imaging

planes is important in canceling out differences noted when planes were acquired

separately. A major source of error remains in the pulse arrival time detection;

further work in progress aims to improve this.

Conclusion

No significant difference in pulmonary PWV derived by navigator end-

expiratory gating acquisition compared with non-navigated acquisition was

identified. This supports the future use of the simpler non-navigated

approach.