Fast 4D flow MRI re-emerges as a potential clinical tool for neuroradiology

Deep learning phase error correction for cerebrovascular 4D flow MRI

Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this study, we assessed their impact on cerebrovascular flow volume measurements, evaluated the benefit of manual image-based correction, and assessed the potential of a convolutional neural network (CNN), a form of deep learning, to directly infer the correction vector field. With IRB waiver of informed consent, we retrospectively identified 96 MRI exams from 48 patients who underwent cerebrovascular 4D Flow MRI from October 2015 to 2020. Flow measurements of the anterior, posterior, and venous circulation were performed to assess inflow-outflow error and the benefit of manual image-based phase error correction. A CNN was then trained to directly infer the phase-error correction field, without segmentation, from 4D Flow volumes to automate correction, reserving from 23 exams for testing. Statistical analyses included Spearman correlation, Bland-Altman, Wilcoxon-signed rank (WSR) and F-tests. Prior to correction, there was strong correlation between inflow and outflow (ρ = 0.833-0.947) measurements with the largest discrepancy in the venous circulation. Manual phase error correction improved inflow-outflow correlation (ρ = 0.945-0.981) and decreased variance (p < 0.001, F-test). Fully automated CNN correction was non-inferior to manual correction with no significant differences in correlation (ρ = 0.971 vs ρ = 0.982) or bias (p = 0.82, Wilcoxon-Signed Rank test) of inflow and outflow measurements. Residual background phase error can impair inflow-outflow consistency of cerebrovascular flow volume measurements. A CNN can be used to directly infer the phase-error vector field to fully automate phase error correction.

Quantification and mapping of cerebral hemodynamics before and after carotid endarterectomy, using four-dimensional flow magnetic resonance imaging

BACKGROUND

Carotid stenosis can profoundly affect cerebral hemodynamics, which cannot simply be inferred from the degree of stenosis. We quantified and mapped the distribution of the blood flow rate (BFR) in the cerebral arteries before and after carotid endarterectomy using four-dimensional (4D) phase-contrast (PC) magnetic resonance imaging (MRI).

METHODS

Nineteen patients (age, 71 ± 6 years; 2 women) with symptomatic carotid stenosis (≥50%) undergoing carotid endarterectomy (CEA) were investigated using 4D PC-MRI before and after surgery. The BFR was measured in 17 cerebral arteries and the ophthalmic arteries. Collateral recruitment through the anterior and posterior communicating arteries, ophthalmic arteries, and leptomeningeal arteries was quantified. BFR laterality was significantly different between the paired contralateral and ipsilateral arteries. Subgroups were defined according to the presence of collateral recruitment.

RESULTS

The total cerebral blood flow had increased by 15% (P < .01) after CEA. Before CEA, laterality was seen in the internal carotid artery, anterior cerebral artery, and middle cerebral artery (MCA). On the ipsilateral side, an increased BFR was found after CEA in the internal carotid artery (246 ± 62 mL/min vs 135 ± 80 mL/min; P < .001), anterior cerebral artery (87 ± mL/min vs 38 ± 58 mL/min; P < .01), and MCA (149 ± 43 mL/min vs 119 ± 34 mL/min; P < .01), resulting in a postoperative BFR distribution without signs of laterality. In the nine patients with preoperatively recruited collaterals, BFR laterality was found in the MCA before, but not after, CEA (P < .01). This laterality was not found in the 10 patients without collateral recruitment (P = .2). The degree of stenosis did not differ between the groups with and without collateral recruitment (P = .85).

CONCLUSIONS

Using 4D PC-MRI, we have presented a comprehensive and noninvasive method to evaluate the cerebral hemodynamics due to carotid stenosis before and after CEA. MCA laterality, seen in the patients with collateral recruitment before CEA, pointed toward a hemodynamic disturbance in MCA territory for those patients. This methodologic advancement provides an insight into the pathophysiology of cerebral hemodynamics in patients with carotid stenosis.

Semiautomatic cerebrovascular territory mapping based on dynamic ASL MR angiography without vessel-encoded labeling

PURPOSE

Characterizing vessel territories can provide crucial information for evaluation of cerebrovascular disorders. In this study, we present a novel postprocessing pipeline for vascular territorial imaging of cerebral arteries based on a noncontrast enhanced time-resolved 4D magnetic resonance angiography (MRA).

METHODS

Eight healthy participants, 1 Moyamoya patient, and 1 arteriovenous malformations patient were recruited. Territorial segmentation and relative blood flow rate calculations of cerebral arteries including left and right middle cerebral arteries and left and right posterior cerebral arteries were carried out based on the 4D MRA-derived arterial arrival time maps of intracranial vessels.

RESULTS

Among healthy young subjects, the average relative blood flow rate values corresponding to left and right middle cerebral arteries and left and right posterior cerebral arteries were 35.9 ± 5.9%, 32.9 ± 7.5%, 15.4 ± 3.8%, and 15.9 ± 2.5%, respectively. Excellent agreement was observed between relative blood flow rate values obtained from the proposed 4D MRA-based method and reference 2D phase contrast MRI. Abnormal cerebral circulations were visualized and quantified on both patients using the developed technique.

CONCLUSION

The vascular territorial imaging technique developed in this study allowed for the generation of territorial maps with user-defined level of details within a clinically feasible scan time, and as such may provide useful information to assess cerebral circulation balance in different pathologies.

Blood Flow Lateralization and Collateral Compensatory Mechanisms in Patients With Carotid Artery Stenosis

Background and Purpose- Four-dimensional phase-contrast magnetic resonance imaging enables quantification of blood flow rate (BFR; mL/min) in multiple cerebral arteries simultaneously, making it a promising technique for hemodynamic investigation in patients with stroke. The aim of this study was to quantify the hemodynamic disturbance and the compensatory pattern of collateral flow in patients with symptomatic carotid stenosis. Methods- Thirty-eight patients (mean, 72 years; 27 men) with symptomatic carotid stenosis (≥50%) or occlusion were investigated using 4-dimensional phase-contrast magnetic resonance imaging. For each patient, BFR was measured in 19 arteries/locations. The ipsilateral side to the symptomatic carotid stenosis was compared with the contralateral side. Results- Internal carotid artery BFR was lower on the ipsilateral side (134±87 versus 261±95 mL/min; P<0.001). BFR in anterior cerebral artery (A1 segment) was lower on ipsilateral side (35±58 versus 119±72 mL/min; P<0.001). Anterior cerebral artery territory bilaterally was primarily supplied by contralateral internal carotid artery. The ipsilateral internal carotid artery mainly supplied the ipsilateral middle cerebral artery (MCA) territory. MCA was also supplied by a reversed BFR found in the ophthalmic and the posterior communicating artery routes on the ipsilateral side (-5±28 versus 10±28 mL/min, P=0.001, and -2±12 versus 6±6 mL/min, P=0.03, respectively). Despite these compensations, BFR in MCA was lower on the ipsilateral side, and this laterality was more pronounced in patients with severe carotid stenosis (≥70%). Although comparing ipsilateral MCA BFR between stenosis groups (<70% and ≥70%), there was no difference ( P=0.95). Conclusions- With a novel approach using 4-dimensional phase-contrast magnetic resonance imaging, we could simultaneously quantify and rank the importance of collateral routes in patients with carotid stenosis. An important observation was that contralateral internal carotid artery mainly secured the bilateral anterior cerebral artery territory. Because of the collateral recruitment, compromised BFR in MCA is not necessarily related to the degree of carotid stenosis. These findings highlight the importance of simultaneous investigation of the hemodynamics of the entire cerebral arterial tree.

Optimal 4DFlow MR sequence parameters for the assessment of internal carotid artery stenosis: a simulation study

PURPOSE

In patients with ICA stenosis, increased peak systolic velocity is a marker of stenosis at risk of ischemic stroke. 4DFlow MRI is a reproducible technique to evaluate velocities in ICA stenosis, although it seems to underestimate velocities as compared with Doppler ultrasonography. The purpose of our study was to confirm that velocities were underestimated on a new set of data acquired with a clinical 4DFlow sequence, and to devise optimal acquisition parameters for ICA stenosis exploration based on a numerical simulation.

METHODS

After review board approval, 15 healthy controls and 12 patients presenting ICA stenosis were explored with Doppler ultrasonography and 4DFlow MRI. We created a 2-dimensional simulation of ICA stenosis and its corresponding 4DFlow acquisition, and compared its mean peak systolic velocity underestimation to real MRI and Doppler. We then simulated the acquisition for voxel size ranging from 0.5 to 1.25 mm and number of phases per cardiac cycle ranging from 10 to 25.

RESULTS

On acquired data, 4DFlow MR underestimated peak systolic velocities (mean difference between Doppler and 4DFlow: - 35 cm/s), especially high velocities. With spatial and temporal resolutions equivalent to MR acquisition, our simulation yielded similar underestimation (mean difference: - 31 cm/s, P = 0.30). Simulations showed that 0.7-mm resolution and 20 phases per cardiac cycle would be necessary to record peak systolic velocities up to 250 cm/s.

CONCLUSION

Higher spatial resolution can provide accurate peak systolic velocities measurement with 4DFlow MRI, thus allowing better ICA stenosis assessment. Further studies are needed to validate the proposed parameters.

Semi-automated analysis of 4D flow MRI to assess the hemodynamic impact of intracranial atherosclerotic disease

PURPOSE

This study evaluated the feasibility of using 4D flow MRI and a semi-automated analysis tool to assess the hemodynamic impact of intracranial atherosclerotic disease (ICAD). The ICAD impact was investigated by evaluating pressure drop (PD) at the atherosclerotic stenosis and changes in cerebral blood flow distribution in patients compared to healthy controls.

METHODS

Dual-venc 4D flow MRI was acquired in 25 healthy volunteers and 16 ICAD patients (ICA, N = 3; MCA, N = 13) with mild (<50%), moderate (50-69%), or severe (>70%) intracranial stenosis. A semi-automated analysis tool was developed to quantify velocity and flow from 4D flow MRI and to evaluate cerebral blood flow redistribution. PD at stenosis was estimated using the Bernoulli equation. The PD calculation was examined by an in vitro phantom study against flow simulations.

RESULTS

Flow analysis in controls indicated symmetry in blood flow rate (FR) and peak velocity (PV) between the brain hemispheres. For patients, PV in the affected hemisphere was significantly (65%) higher than the normal side (P = 0.002). However, FR to both hemispheres of the brain was the same. The PD depicted significant correlation with PV asymmetry in patients (ρ = 0.67 and P = 0.02), and it was significantly higher for severe compared to moderate stenosis (3.73 vs. 2.30 mm Hg, P = 0.02).

CONCLUSION

4D flow MRI quantification enables assessment of the hemodynamic impact of ICAD. The significant difference of the PD between patients with severe and moderate stenosis and its correlation with PV asymmetry suggest that PD may be a pertinent hemodynamic biomarker to evaluate ICAD.

Automatic labeling of cerebral arteries in magnetic resonance angiography

OBJECTIVES

In order to introduce 4D flow magnetic resonance imaging (MRI) as a standard clinical instrument for studying the cerebrovascular system, new and faster postprocessing tools are necessary. The objective of this study was to construct and evaluate a method for automatic identification of individual cerebral arteries in a 4D flow MRI angiogram.

MATERIALS AND METHODS

Forty-six elderly individuals were investigated with 4D flow MRI. Fourteen main cerebral arteries were manually labeled and used to create a probabilistic atlas. An automatic atlas-based artery identification method (AAIM) was developed based on vascular-branch extraction and the atlas was used for identification. The method was evaluated by comparing automatic with manual identification in 4D flow MRI angiograms from 67 additional elderly individuals.

RESULTS

Overall accuracy was 93%, and internal carotid artery and middle cerebral artery labeling was 100% accurate. Smaller and more distal arteries had lower accuracy; for posterior communicating arteries and vertebral arteries, accuracy was 70 and 89%, respectively.

CONCLUSION

The AAIM enabled fast and fully automatic labeling of the main cerebral arteries. AAIM functionality provides the basis for creating an automatic and powerful method to analyze arterial cerebral blood flow in clinical routine.

Advanced technologies applied to physiopathological analysis of central nervous system aneurysms and vascular malformations

While depiction and definition of morphological and architectural characteristics of CNS vascular disorders remains the first step of an MR analysis, emerging imaging techniques offer new functional information that might help to characterize rupture risk of CNS vascular disorders. Two main orientations are suggested by recent studies: inflammation of the vessel wall and analysis of physical constraints of blood flow using 4D flow imaging (shear parietal). This paper will focus on radiological application of 4D flow imaging and inflammation imaging, in the characterization of potential prognostic markers of CNS vascular disorders. We will review the basic technical considerations of 4D flow MRA, inflammation imaging and discuss their applications in CNS vascular disorders: aneurysms, arteriovenous malformation, dural arteriovenous fistulas. We will illustrate their potential in the development of individual rupture risk criteria in brain vascular disorders.