Synopsis

Recent studies point out hemodynamics and wall inflammation as individual risk factors for aneurysm evolution. We investigated on 28 aneurysms in-vivo correlations between hemodynamics and wall inflammation by comparing 4D Flow parameters and quantitative aneurysm wall enhancement. Viscous energy loss and kinetic energy were correlated to maximum values of enhancement with high correlation coefficients (p<0.0001; correlation coefficient 0.79 and p<0.0001; correlation coefficient 0.85, respectively). By showing that flow instability and spatial flow complexity are highly correlated with aneurysm wall enhancement, this study highlights the existence of a link between inflammation process depicted through vessel wall enhancement and hemodynamic patterns.

INTRODUCTION

The incidence of intracranial aneurysms in the general population is 2-6% and ruptures are associated with significant mortality and neurological sequellae.¹ However, optimal management of unruptured aneurysms is poorly defined.² Recent studies point out hemodynamics and wall inflammation as individual risk factors for aneurysm evolution.^3–6 We therefore decided to combine flow parameters given by 4D Flow MRI and arterial wall enhancement on vessel wall MRI, to investigate the in-vivo correlations between hemodynamics and wall inflammation in patients with intracranial aneurysms.

METHODS

After institutional review board approval, we recruited 25 patients with asymptomatic unruptured > 5mm aneurysms. Imaging protocol The MR imaging protocol included a synergistic combination of 4D flow (PCVIPR), vessel wall imaging (3D T1 FSE post gadolinium), and 3D Time-of-Flight (TOF) angiography on a clinical 3T system (Discovery MR 750; GE Healthcare, Waukesha, WI) with a 16-channel head and neck array. 3D T1 FSE was acquired with the following parameters: imaging volume, 23×23×16 cm³; repetition time/echo time, 600/11.5 ms; matrix, 288×288×160 interpolated to 512×512×320; spatial resolution: 0.9×0.9×1 mm3)⁶ post-gadolinium (10 mL of gadoteric acid; Dotarem, Guerbet, France). The total scan time was 4 minutes 16 s. 4D Flow MRI was acquired with a radially undersampled sequence (PCVIPR^7,8) with the following parameters: velocity encoding, 80 cm/sec; imaging volume, 22x22x16 cm³; repetition time /echo time = 6.6/2.8ms; receiver bandwidth, ±83.3 kHz; isotropic spatial resolution, 0.86 mm; imaging time, 5 minutes.

Image analysis

The image analysis flow chart is shown in Figure 1. 3D T1 FSE and 3D TOF images were first registered to the 4D flow dataset, using a rigid registration and mutual information metric with the PC-magnitude images using ANTS.⁹ Segmentation: Hemodynamic quantification is heavily dependent on the accuracy of segmentation routines needed to define boundaries. As such, geometry was derived using manual segmentation software (Mimics 17, Materialise, Leuven, Belgium). Based on its superior depiction of the vessel lumen, 3D TOF images were used for this segmentation.

4D Flow: 4D MR flow data were preprocessed to remove effects from gradient non-linearity, background phase offsets, and cast into a divergence-free flow field for noise reduction. Subsequent data analysis used custom routines developed to measure parameters of interest (Matlab, Natwick, MA, USA) and software packages for visualization of dynamic velocity fields and other quantitative variables (Ensight, CEI, Apex, NC). This included both wall measures (wall shear stress) and flow field features (kinetic energy¹⁰ and viscous energy loss¹¹).

Vessel Wall imaging: The segmented 3D TOF mask of each aneurysm was a 3D surface mesh detailing the location of the vessel wall, and was utilized to measure the T1 signal intensity just outside the vessel lumen. To reduce signal intensity variability between scans, the signal intensity of the aneurysm wall enhancement was normalized to signal from ROIs drawn in the corpus callosum. Statistical analysis: We tested the existence of a correlation between quantitative flow measurements and quantitative analysis of aneurysm wall enhancement using a Pearson test. The correlation between aneurysm size and enhancement was also tested.

RESULTS

Because of motion artifacts, 1 patient was excluded from the analysis. Characteristics of the 28 included aneurysms are summarized in Table 1. No significant correlation was found between values of enhancement (both mean and maximum values of enhancement) and average WSS; nor with average velocity measured inside the aneurysm. There was no correlation between size (neck-to-dome length) of the aneurysm and 4D flow parameters. Viscous energy loss and kinetic energy were correlated to maximum values of enhancement with high correlation coefficients (p<0.0001; correlation coefficient 0.79 and p<0.0001; correlation coefficient 0.85, respectively).

DISCUSSION

Viscous energy loss and kinetic energy are two parameters reflecting the flow disorganization patterns inside the aneurysm pouch. They highly correlate with the maximum value of wall enhancement. By showing that flow instability and spatial flow complexity are highly correlated with aneurysm wall enhancement, this study highlights the existence of a link between vessel wall enhancement (presumably an inflammation process) and hemodynamic patterns. It corroborates the thought that through mechanical transduction, hemodynamics can alter cell regulation, genetics and inflammatory processes.¹²

Table 1:

Aneurysms characteristics:

Size, median(IQR), mm 8,5 (6-10)

Location - MCA, number (percentage) 14 (50%)

Location - ACA, number (percentage) 7 (25%)

Location - ICA, number (percentage) 5 (17,8%)

Location - BA, number (percentage) 2 (7,2%)

Average Velocity (mm/s), median (IQR) 35,5 (16,3-60,7)

Maximum enhancement value, median (IQR) 936 (777-1292)

Average WSS (N/m2), median (IQR) 0,4 (0,3-0,54)

Acknowledgements

References

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