Phase contrast MRI with flow compensation view sharing (FCVS)

PURPOSE
To develop and evaluate a technique for accelerating phase contrast MRI (PC-MRI) acquisitions without significant compromise in flow quantification accuracy.


METHODS
PC-MRI is commonly acquired using interleaved flow-compensated (FC) and flow-encoded (FE) echoes. We hypothesized that FC data, which represent background phase, do not change significantly over time. Therefore, we proposed to undersample the FC data and use an FC view sharing (FCVS) approach to synthesize a composite FC frame for each corresponding FE frame. FCVS was evaluated in a flow phantom and healthy volunteers and compared with a standard FC/FE PC-MRI.


RESULTS
The FCVS sequence resulted in an error of 0.0% for forward flow and 2.0% for reverse flow volume when compared with FC/FE PC-MRI in a flow phantom. Measurements in the common carotid arteries showed that the FCVS method had -1.16 cm/s bias for maximum peak velocity and -0.019 mL bias in total flow, when compared with FC/FE with the same temporal resolution, but double the total acquisition time. These results represent ≤1.3% bias error in velocity and volumetric flow quantification.


CONCLUSION
FCVS can accelerate PC-MRI acquisitions while maintaining flow and velocity measurement accuracy when there is limited temporal variation in the FC data.


Phase contrast MRI with flow compensation view sharing (FCVS)
Da Wang 1,2* , Jiaxin Shao 1 , Stanislas Rapacchi 1 , Matthew J Middione 1,2 , Daniel B Ennis 1,2 , Peng Hu 1,2 From 17th Annual SCMR Scientific Sessions New Orleans, LA, USA. 16-19 January 2014 Background Phase-contrast MRI (PC-MRI) is routinely used for quantification of blood flow and velocity in clinical. In a typical PC-MRI exam, flow compensated (FC) and flow encoded (FE) images are alternatively acquired as shown in Figure 1(a). However, in common carotid artery (CCA), FC images are very consistency due to limited physiological motion and background phase changes. In this regard, we propose to accelerate PC-MRI by using sliding window temporal view sharing of the FC data (FCVS) as shown in Figure 1(b). FCVS can improve both the temporal resolution and temporal footprint.

Methods
Six healthy volunteers were recruited in the prospective study and were scanned by the standard FCFE PC-MRI sequence and FCVS sequence under free breathing. The in vivo study were performed on SIEMENS 1.5 T Avanto scanner with 6-channel head and neck coils. FC k-space lines were acquired after every five FE lines and generated a sliding window under-sampled pattern by a rate RFC = 6. For each corresponding FE frame, a composite FC frame was synthesized by sharing data from adjacent frames. The 5/6 under-sampling of FE data due to FC data acquisition were recovered by TGRAPPA reconstruction. The peak velocity and total volumetric flow measurements of FCVS are compared with standard FCFE with same temporal resolution but double total acquisition time.

Results
The FC signal phase of a randomly selected pixel within a volunteer's CCA (  http://www.jcmr-online.com/content/16/S1/O7 rad) was stable through cardiac cycle. An example of a healthy volunteer's peak velocity measurements with: 1) FCFE PC-MRI with 2 views-per-segment and 34 ms temporal resolution, 2) FCVS with 2 views-per-segment and 17 ms-temporal-resolution, and 3) FCFE PC-MRI with 1 view-per-segment with 17 ms-temporal-resolution are shown in Figure 2b. The 34 ms-temporal-resolution FCFE scan failed to capture the maximum peak velocity at around 90 ms into the cardiac cycle. The 17 ms FCVS scan provided similar peak velocity values as the 17 ms FCFE scan albeit at half of the total acquisition time. A Bland-Altman plot of total 24 volumetric flow values (left and right CCA in the six volunteers with 17 ms and 34 ms temporal resolutions) measured by FCVS and standard FCFE PC-MRI are shown in Figure 2c. The bias was 0.05 mL and the 95% confidence interval was [-0.25, 0.35] mL. The bias error in volumetric flow quantification was ≤1.3%.

Conclusions
FCVS can accelerate PC-MRI acquisitions while maintaining flow and velocity measurement accuracy when there is limited temporal variation in the FC data.

Funding
No funding. Figure 2 (a) The FC signal phase as a function of the cardiac frames for a randomly selected pixel within the CCA (mean/± SD: -2.51/± 0.065). (b) Peak velocity waveforms from the standard FCFE PC-MRI (gray curve) with 17 ms-temporal-resolution, FCVS (blue curve) with 17 mstemporal-resolution, standard FCFE PC-MRI (red curve) with 34 ms-temporal-resolution. The FCVS results are highly correlated with the measurements from standard FCFE PC-MRI at the same temporal resolution but FCVS only requires 50% of the acquisition time. The standard FCFE PC-MRI fails to capture the peak velocity at approximately 75 ms or the transient dip at 320 ms when its temporal resolution is halved to match the total acquisition time of FCVS. (c) The Bland-Altman plot of total volumetric flow measurements between standard FCFE PC-MRI and FCVS with two different temporal resolutions (17 ms and 34 ms) in the left and right CCA in six volunteers for a total 24 flow measurement.