Xin Shen1, Kenichiro Suwa2, Alex J Barker2, Susanne Schnell2, Jeremy D Collins2, James C Carr2, and Michael Markl1,2
1Biomedical Engineering, Northwestern University, Chicago, IL, United States, 2Radiology, Northwestern University, Chicago, IL, United States
Synopsis
Retrograde fraction
stratifies the degree of aortic regurgitation (AR) in patients with aortic
valve disease. The purpose of this study was to develop 4D flow based
voxel-by-voxel regional analysis of forward flow, reverse flow, and retrograde
fraction with full volumetric coverage of the aorta. In a study with 10
subjects (5 healthy controls, 5 patients with AR), reverse flow and retrograde
fraction maps were used to systematically analyze regional flow patterns and
assess differences between standard (plane-wise) and voxel-by-voxel
quantification of AR.
Purpose
Aortic valve
regurgitation (AR) is an important disease of the aorta which is caused by valve
deficiency1. Current methods for the evaluation of aortic valve
regurgitation include 2D phase contrast MRI2 or 4D flow MRI3,4.
AR severity is typically assessed using 2D analysis planes orthogonal to the
aorta, calculating the fraction of retrograde flow (by dividing the net forward
by the net reverse flow over the cardiac cycle through the 2D plane)5.
While this method is used as the standard tool for the diagnosis of aortic
regurgitation, it often misses important regional flow information. For
example, flow recirculation next to forward flow jets may lead to considerable
regional flow reversal – but may not result in net reverse flow for the
standard plane-wise calculation. As a result, standard AR quantification can
yield small or non-existent retrograde fraction although marked regional flow
reversal is present. In addition, AR assessment based on 2D analysis planes may
miss the region with the most pronounced flow reversal. The aim of this study
was to develop 4D flow based voxel-by-voxel regional analysis of forward flow,
reverse flow, and retrograde fraction with full volumetric coverage of the
aorta. Reverse flow and retrograde fraction maps were used to visualize
regional flow patterns and assess differences between standard (plane-wise) and
voxel-by-voxel quantification of AR.Methods
Five healthy
volunteers and 5 patients diagnosed with AR (4 moderate, 1 severe) by
echocardiography were included. All subjects underwent cardiothoracic MRI
including 4D flow MRI with full coverage of the thoracic aorta. Imaging
parameters were as follows: spatial resolution=2.1-3.2 mm x 1.7-2.3 mm x 2.2-3.2 mm, temporal resolution=37.6-42.4 ms, and
TE=2.3-2.8 ms, TR=4.7-5.3 ms, venc=150-200 cm/s. 4D flow data analysis included
corrections for noise, Maxwell terms, eddy currents, and velocity aliasing. A
3D PC MR angiogram was derived from the 4D flow data and used to generate a 3D
segmentation of the aorta (Mimics, Materialise). The workflow for
Voxel-by-voxel assessment of flow and retrograde fraction (programmed Matlab,
The Mathworks, USA) is shown in figure 1. As a first step, an aorta center line
was estimated based on a 2D representation of the 3D aorta segmentation (Fig 1 C, D). After deleting supra-aortic branches,
a 3D aorta center line was calculated (Fig 1 F, G). For each point along the center
line normal vectors were determined and 2D planes orthogonal to the center line
were generated (Fig 1 H). Voxels inside the aorta were considered members of a
2D plane if their distance was < 1mm to each plane. Based on the normal
direction and velocity vector, the forward, reverse flow, and retrograde
fraction (ratio of forward / reverse flow) were calculated for each plane
(standard plane-wise method) and each voxel (voxel-by-voxel analysis) as
illustrated in figure 2. In addition, aortic flow and retrograde fraction maps
were generated by calculating the mean projection and maximum intensity
projection (MIP) are shown in figure 3. For comparison, we also
performed standard plane-wise analysis of flow and retrograde fraction based on
manually positioned 2D analysis planes at the following anatomic landmarks:
aortic ROOT, proximal, mid and distal acceding aorta (AAo1, AAo2, AAo3),
proximal, mid and distal arch (Arch1, Arch2, Arch3), and proximal and distal
descending aorta (DAo1, DAo2) as shown in figure 1.Results
Figure 2 shows
the results from a healthy subject and an AR patient. For each subject, the
individual images show mean projection and MIP, as well as graphs with the
plane-based and voxel-based 3D analysis. As expected, the AR patient demonstrated
increased reverse flow and retrograde fraction compared the healthy subject.
Both the healthy subject and AR patient showed local flow
reversal in some regions (ascending aorta), which was not captured by the plane-wise analysis.
Figure 4
summarizes retrograde fraction quantification for all 2D analysis planes by
different methods. In both groups, healthy subjects and AR patients, the standard
plane and map plane methods were similar (on average, healthy 1.35±1.34% vs 1.46±1.73%, p=0.72, AR 16.10±8.78% vs 16.37±9.06%, p=0.89). In contrast, standard planar analysis
and voxel based methods were significantly different (on average, healthy 1.35±1.34% vs 8.16±5.91%, p<0.001, AR 16.10±8.78% vs 26.63±11.14%, p<0.001). Differences were more pronounce for
patients with AR.
Conclusion
The observed
differences in retrograde fraction by the standard method and voxel-by-voxel
analysis indicate that traditional techniques for the assessment of AR may
substantially underestimate the presence of regional flow reversal. Additional
studies are warranted to investigate this effect in larger cohort with
different severity of aortic valve dysfunction.Acknowledgements
I have no funding.References
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