Relationship of pulsatility and resistance indices to cerebral arteriovenous malformation angioarchitectural features and hemorrhage

Hemodynamic evaluation of intracranial arteriovenous malformations: Pre- and post-treatment 2D phase-contrast MRI measurements

Background

Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects.

Purpose

To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls.

Materials and Methods

Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography.

Results

Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7 cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls.

Conclusion

Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.

The current landscape of machine learning-based radiomics in arteriovenous malformations: a systematic review and radiomics quality score assessment

Background

Arteriovenous malformations (AVMs) are rare vascular anomalies involving a disorganization of arteries and veins with no intervening capillaries. In the past 10 years, radiomics and machine learning (ML) models became increasingly popular for analyzing diagnostic medical images. The goal of this review was to provide a comprehensive summary of current radiomic models being employed for the diagnostic, therapeutic, prognostic, and predictive outcomes in AVM management.

Methods

A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, in which the PubMed and Embase databases were searched using the following terms: (cerebral OR brain OR intracranial OR central nervous system OR spine OR spinal) AND (AVM OR arteriovenous malformation OR arteriovenous malformations) AND (radiomics OR radiogenomics OR machine learning OR artificial intelligence OR deep learning OR computer-aided detection OR computer-aided prediction OR computer-aided treatment decision). A radiomics quality score (RQS) was calculated for all included studies.

Results

Thirteen studies were included, which were all retrospective in nature. Three studies (23%) dealt with AVM diagnosis and grading, 1 study (8%) gauged treatment response, 8 (62%) predicted outcomes, and the last one (8%) addressed prognosis. No radiomics model had undergone external validation. The mean RQS was 15.92 (range: 10-18).

Conclusion

We demonstrated that radiomics is currently being studied in different facets of AVM management. While not ready for clinical use, radiomics is a rapidly emerging field expected to play a significant future role in medical imaging. More prospective studies are warranted to determine the role of radiomics in the diagnosis, prediction of comorbidities, and treatment selection in AVM management.

Effect of MRI acquisition parameters on accuracy and precision of phase-contrast measurements in a small-lumen vessel phantom

BACKGROUND

Phase-contrast magnetic resonance imaging (PC-MRI) quantifies blood flow and velocity noninvasively. Challenges arise in neurovascular disorders due to small vessels. We evaluated the impact of voxel size, number of signal averages (NSA), and velocity encoding (VENC) on PC-MRI measurement accuracy and precision in a small-lumen vessel phantom.

METHODS

We constructed an in vitro model with a constant flow rate using a 2.2-mm inner diameter plastic tube. A reservoir with a weight scale and timer was used as standard reference. Gradient-echo T1 weighted PC-MRI sequence was performed on a 3-T scanner with varying voxel size (2.5, 5.0, 7.5 mm3), NSA (1, 2, 3), and VENC (200, 300, 400 cm/s). We repeated measurements nine times per setting, calculating mean flow rate, maximum velocity, and least detectable difference (LDD).

RESULTS

PC-MRI flow measurements were higher than standard reference values (mean ranging from 7.3 to 9.5 mL/s compared with 6.6 mL/s). Decreased voxel size improved accuracy, reducing flow rate measurements from 9.5 to 7.3 mL/s. The LDD for flow rate and velocity varied between 1 and 5%. The LDD for flow rate decreased with increased voxel size and NSA (p = 0.033 and 0.042). The LDD for velocity decreased with increased voxel size (p < 10-16). No change was observed when VENC varied.

CONCLUSIONS

PC-MRI overestimated flow. However, it has high precision in a small-vessel phantom with constant flow rate. Improved accuracy was obtained with increasing spatial resolution (smaller voxels). Improved precision was obtained with increasing signal-to-noise ratio (larger voxels and/or higher NSA).

RELEVANCE STATEMENT

Phase-contrast MRI is clinically used in large vessels. To further investigate the possibility of using phase-contrast MRI for smaller intracranial vessels in neurovascular disorders, we need to understand how acquisition parameters affect phase-contrast MRI-measured flow rate and velocity in small vessels.

KEY POINTS

• PC-MRI measures flow and velocity in a small lumen phantom with high precision but overestimates flow rate. • The precision of PC-MRI measurements matches the precision of standard reference for flow rate measurements. • Optimizing PC-MRI settings can enhance accuracy and precision in flow rate and velocity measurements.

Rupture-Risk Stratifying Patients with Cerebral Arteriovenous Malformations Using Quantitative Hemodynamic Flow Measurements

Arteriovenous malformations (AVMs) are high-pressure, low-resistance arterial-venous shunts without intervening capillaries. Up to 60% of AVMs present with an intracranial hemorrhage; however, noninvasive neuroimaging has increasingly diagnosed incidental AVMs. AVM management depends on weighing the lifetime rupture risk against the risks of intervention. Although AVM rupture risk relies primarily on angioarchitectural features, measuring hemodynamic flow is gaining traction. Accurate understanding of AVM hemodynamic flow parameters will help endovascular neurosurgeons and interventional neuroradiologists stratify patients by rupture risk and select treatment plans. This review examines various neuroimaging modalities and their capabilities to quantify AVM flow, as well as the relationship between AVM flow and rupture risk. Quantitative hemodynamic studies on the relationship between AVM flow and rupture risk have not reached a clear consensus; however, the preponderance of data suggests that higher arterial inflow and lower venous outflow in the AVM nidus contribute to increased hemorrhagic risk. Future studies should consider using larger sample sizes and standardized definitions of hemodynamic parameters to reach a consensus. In the meantime, classic angioarchitectural features may be more strongly correlated with AVM rupture than the amount of blood flow.

Digital intravascular pressure wave recording during endovascular treatment reveals abnormal shunting flow in vertebral venous fistula of the vertebral artery: illustrative case

BACKGROUND

An arteriovenous fistula is an abnormal arteriovenous shunt between an artery and a vein, which often leads to venous congestion in the central nervous system. The blood flow near the fistula is different from normal artery flow. A novel method to detect the abnormal shunting flow or pressure near the fistula is needed.

OBSERVATIONS

A 76-year-old woman presented to the authors’ institute with progressive right upper limb weakness. Right vertebral angiography showed a fistula between the right extracranial vertebral artery (VA) and the right vertebral venous plexus at the C7 level. The patient underwent endovascular treatment for shunt flow reduction. Before the procedure, blood pressures were measured at the proximal VA, distal VA near the fistula, and just at the fistula and drainer using a microcatheter. The blood pressure waveforms were characteristically different in terms of resistance index, half-decay time, and appearance of dicrotic notch. The fistula was embolized with coils and N-butyl cyanoacrylate solution.

LESSONS

During endovascular treatment, the authors were able to digitally record the vascular pressure waveform from the tip of the microcatheter and succeeded in calculating several parameters that characterize the shunting flow. Furthermore, these parameters could help recognize the abnormal blood flow, allowing a safer endovascular surgery.

Contrast Time-Density Time on Digital Subtraction Angiography Correlates With Cerebral Arteriovenous Malformation Flow Measured by Quantitative Magnetic Resonance Angiography, Angioarchitecture, and Hemorrhage

BACKGROUND

Digital subtraction angiography (DSA) currently provides angioarchitectural features of cerebral arteriovenous malformations (AVMs) but its role in the hemodynamic evaluation of AVMs is poorly understood.

OBJECTIVE

To assess contrast time-density time (TT) on DSA relative to AVM flow measured using quantitative magnetic resonance angiography (QMRA).

METHODS

Patients seen at our institution between 2007 and 2014 with a supratentorial AVM and DSA and QMRA obtained prior to any treatment were retrospectively reviewed. Regions of interest were selected on the draining veins at the point closest to the nidus. TT on DSA was defined as time needed for contrast to change image intensity from 10% to 100%, 100% to 10%, and 25% to 25%. TT was correlated to AVM total flow, angioarchitectural features, and hemorrhage.

RESULTS

Twenty-eight patients (mean age 35.6 yr) were included. Six patients presented with hemorrhage. Mean AVM volume was 11.42 mL (range 0.3-57.7 mL). Higher total AVM flow significantly correlated with shorter TT100%-10% and TT25%-25% (P = .02, .02, respectively). Presence of venous stenosis correlated significantly with shorter TT100%-10% (P = .04) and TT25%-25% (P = .04). AVMs with a single draining vein exhibited longer TT25%-25% compared to those with multiple draining veins (P = .04). Ruptured AVMs had significantly shorter TT10%-100% compared to unruptured AVMs (P = .05).

CONCLUSION

TT on DSA correlates with cerebral AVM flow measured using QMRA and with AVM angioarchitecture and hemorrhagic presentation. Thus, TT may be used to indirectly estimate AVM flow during angiography in real-time and may also be an indicator of important AVM characteristics associated with outflow resistance and increased rupture risk, such as venous stenosis.

Risk factors for hemorrhage of brain arteriovenous malformation

Patients with brain arteriovenous malformation (bAVM) are at risk of intracranial hemorrhage (ICH). Overall, bAVM accounts for 25% of hemorrhagic strokes in adults <50 years of age. The treatment of unruptured bAVMs has become controversial, because the natural history of these patients may be less morbid than invasive therapies. Available treatments include observation, surgical resection, endovascular embolization, stereotactic radiosurgery, or combination thereof. Knowing the risk factors for bAVM hemorrhage is crucial for selecting appropriate therapeutic strategies. In this review, we discussed several biological risk factors, which may contribute to bAVM hemorrhage.

Standardized Evaluation of Cerebral Arteriovenous Malformations Using Flow Distribution Network Graphs and Dual-venc 4D Flow MRI

BACKGROUND

Cerebral arteriovenous malformations (AVMs) are pathological connections between arteries and veins. Dual-venc 4D flow MRI, an extended 4D flow MRI method with improved velocity dynamic range, provides time-resolved 3D cerebral hemodynamics.

PURPOSE

To optimize dual-venc 4D flow imaging parameters for AVM; to assess the relationship between spatial resolution, acceleration, and flow quantification accuracy; and to introduce and apply the flow distribution network graph (FDNG) paradigm for storing and analyzing complex neurovascular 4D flow data.

STUDY TYPE

Retrospective cohort study.

SUBJECTS/PHANTOM

Scans were performed in a specialized flow phantom: 26 healthy subjects (age 41 ± 17 years) and five AVM patients (age 27-68 years).

FIELD STRENGTH/SEQUENCE

Dual-venc 4D flow with varying spatial resolution and acceleration factors were performed at 3T field strength.

ASSESSMENT

Quantification accuracy was assessed in vitro by direct comparison to measured flow. FDNGs were used to quantify and compare flow, peak velocity (PV), and pulsatility index (PI) between healthy controls with various Circle of Willis (CoW) anatomy and AVM patients.

STATISTICAL TESTS

In vitro measurements were compared to ground truth with Student's t-test. In vivo groups were compared with Wilcoxon rank-sum test and Kruskal-Wallis test.

RESULTS

Flow was overestimated in all in vitro experiments, by an average 7.1 ± 1.4% for all measurement conditions. Error in flow measurement was significantly correlated with number of voxels across the channel (P = 3.11 × 10^-28 ) but not with acceleration factor (P = 0.74). For the venous-arterial PV and PI ratios, a significant difference was found between AVM nidal and extranidal circulation (P = 0.008 and 0.05, respectively), and between AVM nidal and healthy control circulation (P = 0.005 and 0.003, respectively).

DATA CONCLUSION

Dual-venc 4D flow MRI and standardized FDNG analysis might be feasible in clinical applications. Venous-arterial ratios of PV and PI are proposed as network-based biomarkers characterizing AVM nidal hemodynamics.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1718-1730.

A proposed classification for assessing rupture risk in patients with intracranial arteriovenous malformations

Background:

Whether cerebral arteriovenous malformations (AVMs) should be treated remains an ongoing debate. Nevertheless, there is a need for predictive factors that assist in labelling lesions as low or high risk for future rupture. Our aim was to design a new classification that would consider hemodynamic and anatomic factors in the rapid assessment of rupture risk in patients with AVMs.

Methods:

This was a retrospective study that included 639 patients with ruptured and unruptured AVMs. We proposed a new classification score (1–4 points) for AVM rupture risk using three factors: feeding artery mean velocity (Vm), nidus size, and type of venous drainage. We employed descriptive statistics and logistic regression analysis.

Results:

A total of 639 patients with cerebral AVMs, 388 (60%) had unruptured AVMs and 251 (40%) had ruptured AVMs. Logistic regression analysis revealed a significant effect of Vm, nidus size, and venous drainage type in accounting for the variability of rupture odds (P = 0.0001, R² = 0.437) for patients with AVMs. Based in the odds ratios, grades 1 and 2 of the proposed classification were corresponded to low risk of hemorrhage, while grades 3 and 4 were associated with hemorrhage: 1 point OR = (0.107 95% CI; 0.061–0.188), 2 point OR = (0.227 95% CI; 0.153–0.338), 3 point OR = (3.292 95% CI; 2.325–4.661), and 4 point OR = (23.304 95% CI; 11.077–49.027).

Conclusion:

This classification is useful and easy to use, and it may allow for the individualisation of each cerebral AVM and the assessment of rupture risk based on a model of categorisation.

Validation of cerebral arteriovenous malformation hemodynamics assessed by DSA using quantitative magnetic resonance angiography: preliminary study

BACKGROUND

The hemodynamic evaluation of cerebral arteriovenous malformations (AVMs) using DSA has not been validated against true flow measurements.

OBJECTIVE

To validate AVM hemodynamics assessed by DSA using quantitative magnetic resonance angiography (QMRA).

MATERIALS AND METHODS

Patients seen at our institution between 2007 and 2016 with a supratentorial AVM and DSA and QMRA obtained before any treatment were retrospectively reviewed. DSA assessment of AVM flow comprised AVM arterial-to-venous time (A-Vt) and iFlow transit time. A-Vt was defined as the difference between peak contrast intensity in the cavernous internal carotid artery and peak contrast intensity in the draining vein. iFlow transit times were determined using syngo iFlow software. A-Vt and iFlow transit times were correlated with total AVM flow measured using QMRA and AVM angioarchitectural and clinical features.

RESULTS

33 patients (mean age 33 years) were included. Nine patients presented with hemorrhage. Mean AVM volume was 9.8 mL (range 0.3-57.7 mL). Both A-Vt (r=-0.47, p=0.01) and iFlow (r=-0.44, p=0.01) correlated significantly with total AVM flow. iFlow transit time was significantly shorter in patients who presented with seizure but A-Vt and iFlow did not vary with other AVM angioarchitectural features such as venous stenosis or hemorrhagic presentation.

CONCLUSIONS

A-Vt and iFlow transit times on DSA correlate with cerebral AVM flow measured using QMRA. Thus, these parameters may be used to indirectly estimate AVM flow before and after embolization during angiography in real time.