Arteriovenous Malformation

Phantom, volunteer, and patient studies were performed to assess the efficacy of corrections and image quality. Data were acquired covering a 22×22×22 cm³ field of view with 0.6 mm isotropic resolution (nominal). A 75% fractional echo was used with a 62.50 kHz readout and 125 kHz receiver bandwidth. The velocity encoding (VENC) was set to 60 cm/s, resulting in a TR of 11.6 ms and TE’s of 3.5 and 6.1ms. A 15° flip angle was used in all cases, chosen based on empirical observations to minimize signal saturation. A total of 14,000 projections (28000 TRs) were collected for a total scan time of 5:24 minutes, representing an under sampling factor of 11 with respect to Nyquist. Trajectory calibrations were performed using 16 averages per direction with a 15° flip angle and a 40 ms TR; adding an additional 23 s to the exams. For all experiments an 8 channel phased array head coil was used for acquisition (HD Brain Coil, GE Healthcare, Milwaukee, WI). All reconstructions were performed using an optimized gridding operation (20 (link)) with conjugate phase reconstruction performed using least squares interpolations of 7 evenly spaced frequencies (21 (link)). Off-resonance maps were created using low-resolution phase images between echoes, with phase aliasing removed using a simple region growing algorithm. From the reconstructed velocity and magnitude images, an angiographic image was created using:
$$\mathit{CD}=\{\begin{array}{cc}\hfill M\cdot \sin (\frac{\pi }{2}\cdot \mid \overrightarrow{V}\mid ∕V_A)\hfill & \hfill \mid \overrightarrow{V}\mid <V_A\hfill \\ \hfill M\hfill & \hfill \text{otherwise}\hfill \end{array}\phantom{\}}$$
Where CD is the angiographic image, M is the magnitude, $\overrightarrow{V}$ is the velocity as determined from phase processing, and V_A is an arbitrarily defined threshold velocity. This weighting scheme mimics complex difference processing (22 (link)), but allows use of balanced 4-point imaging and phase difference processing. For all reconstructed images reported here, V_A was set to the VENC of 60 cm/s.
A standard quality assurance phantom was imaged for the evaluation of off-resonance and trajectory corrections. Magnitude phantom images were reconstructed without off-resonance or trajectory corrections, with off-resonance corrections, with trajectory corrections, and with both trajectory and off-resonance corrections. These images were then qualitatively evaluated for image distortions and artifacts as compared to the known geometry.
Subsequently, five normal volunteers and five patients with known arteriovenous malformations (AVM) were examined with institutional board approval and informed patient consent for an in-vivo assessment of the extended PC VIPR acquisition technique. Image quality comparisons were made, examining background suppression, edge sharpness and vessel visualization, between corrected (off-resonance + trajectory) and uncorrected angiographic images by 2 board certified, blinded readers, with criteria defined in Table 1. Edge sharpness and background suppression were evaluated over the entire volume, while vessel visualization was evaluated individually on the carotids, middle cerebral arteries (MCA), anterior cerebral/communication arteries (ACA/ACOMM), vertebral (VERT), and posterior cerebral arties (PCA). Statistical significance of differences in scores was determined using a Friedman test (n=5) for each category and across observers using both patient an volunteer populations. The significance image quality differences between volunteer and patient populations were determined using a Friedman test (n=5) of corrected images, across all categories.

We assessed correlation between intracranial aneurysms and other traits using LDHub and LD-score regression (LDSR) with LDSC. To assess genetic correlation between intracranial aneurysms and many non-stroke-related traits, we used LD Hub^{41 (link)}
. This platform uses LDSR to assess genetic correlation with a large number of publicly available GWASs. For the correlation of intracranial aneurysms and other stroke subtypes, we obtained summary statistics for All Stroke (AS), Cardioembolic Stroke (CE), Any Ischemic Stroke (AnyIS), Large Artery Stroke (LAS), Small Vessel Disease (SVD)^{42 (link)}
, Deep, Lobar, and combined Intracerebral Hemorrhage (ICH)^{63 (link)}
, carotid- and vertebral artery dissection^{44 (link)}
, Arteriovenous Malformation (AVM)^{43 (link)}
and Abdominal Aortic Aneurysms (AAA)^{45 (link)}
. We used LDSC to calculate genetic correlation. LD scores from European ancestry individuals from 1000G were calculated for SNPs in the HapMap 3 SNP set and used to calculate genetic correlation. Since the heritability estimate was negative for AVM, due to the small sample size, we performed a SNP lookup of the Stage 2 intracranial aneurysm loci that passed the multiple testing threshold (P<5·10^-8) from the GWAS of AVM^{43 (link)}
.