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The purpose of our study was to elucidate the impact of brain arteriovenous malformation (BAVM) flow and wall shear stress (WSS) on angioarchitecture and to evaluate their association with hemorrhagic presentations.Forty-one patients with BAVMs were evaluated by phase-contrast MR angiography. Volume flow rate and WSS were quantified. Angioarchitectural features such as location, angiogenesis, venous stenosis, venous ectasia, venous phlebitis, venous rerouting, exclusive deep vein and venous sac were evaluated by two neuroradiologists. The correlation between BAVM flow and size was evaluated with Spearman correlation coefficients. Differences of size, flow, and WSS between the hemorrhagic and non-hemorrhagic groups, the seizure and non-seizure groups, and between the different groups based on angioarchitecture were evaluated with Mann-Whitney U tests. Accuracy in predicting hemorrhage was evaluated with receiver operating characteristic curves.BAVM flow was highly correlated with volume (ρ = 0.77). Higher flow was more commonly associated with angiogenesis, venous ectasia, venous rerouting, and venous phlebitis. Flow and angioarchitecture showed similar efficacy in differentiating hemorrhagic from non-hemorrhagic BAVMs. WSS did not demonstrate differences across any clinical groups.Flow quantification and angioarchitecture analysis of BAVMs showed similar efficacy as evaluated by associations with hemorrhagic presentation. High flow affects both arterial and venous angioarchitecture, reflecting the nature of low vascular resistance in BAVMs.

Objective. Four-dimensional (4D) digital subtraction angiography (DSA) offers a method for evaluating hemodynamics. It is, however, unclear how the delivered contrast medium interacts with the physiological blood flow, and how hemodynamic information may be inferred from the mixture of the contrast medium and blood. In this study, we present a theoretical explanation of contrast dynamics, and an accompanying algorithm for estimating blood flow velocity. Approach. We retrospectively recruited 23 patients who underwent both 4D DSA and magnetic resonance (MR) phase-contrast imaging. The 4D DSA-reconstructed contrast dynamics were first studied for the internal carotid arteries. Using physical laws governing fluid motion within a curved tube, we showed that the reconstructed contrast dynamics obeyed a simple advection equation. We then proposed an algorithm for estimating the contrast dynamics using angiographic data, and subsequently estimated the axial blood flow velocity using an advection equation. Main results. The estimated velocities were compared using three techniques: the Fourier technique, Lin’s method, and MR phase contrast. Testing with noise-corrupted artificial data showed that the proposed algorithm was noise resistant. The velocities of 23 patients computed by 4D DSA using the proposed algorithm showed a moderate correlation with the MR phase contrast (r = 0.61), and good correlations with the other two techniques (r = 0.75 and r = 0.72). Significance. The proposed algorithm and has been applied to blood vessel segments with poor signal-to-noise ratios and axial lengths of less than 3 cm, and has a physical basis for computing axial flow velocities using an advection equation. The results of the proposed algorithm are consistent with existing methods.

Background: The efficacy of both quantitative digital subtraction angiography (QDSA) and flat-detector computed tomography perfusion (FD-CTP) is equivalent to that of magnetic resonance perfusion (MRP) in assessing perfusion deficits in carotid stenosis. This study evaluated the feasibility of using FD-CTP to monitor cerebral hemodynamics during carotid stenting. Methods: Thirteen patients with extracranial carotid stenosis (>70%) were included. Both QDSA and two FD-CTP sessions were performed before and after carotid stenting. Cerebral circulation time (CCT) was defined as the difference between the time to peak (TTP) of the parietal vein and the cavernous internal carotid artery. For FD-CTP and MRP, regions of interest (ROIs) were placed in the middle cerebral artery territory at the basal ganglia level of both stenotic and contralateral hemispheres for measurement. The TTP ratio (rTTP) was defined as stenotic TTP divided by contralateral TTP; and ratio of cerebral blood volume (rCBV), ratio of mean transit time (rMTT), and ratio of cerebral blood flow (rCBF) were defined similarly. Both CCT and ratio perfusion parameters were compared during stenting. Results: Before stenting, only rCBF (r = 0.73) and rTTP (r = 0.58) demonstrated correlations between FD-CTP and MRP; CCT correlated with only rMTT in MRP (r = 0.69). After stenting, only rCBF (r = 0.56) indicated a correlation between FD-CTP and MRP. Regarding cerebral flow after stenting, CCT (4.61 ± 1.6 s) was shortened, rMTT (1.12 ± 0.04) and rTTP (r = 1.05 ± 0.03) decreased, and rCBF (0.91 ± 0.16) increased significantly. Conclusion: FD-CTP provides a potentially more comprehensive hemodynamic assessment of parenchymal perfusion changes compared with QDSA during carotid stenting, but FC-CTP requires additional 18 min. FD-CTP confirmed that the normalization of cerebral hemodynamics began immediately and continued for 1–3 days. Keywords: Carotid stenosis, Carotid stenting, Cerebral circulation time, Cerebral hemodynamic, Flat-detector, Perfusion, Quantitative digital subtraction angiography

BackgroundTime-resolved rotational angiography (t-RA) enables interventionists to better comprehend complex arteriovenous malformations (AVMs), thereby facilitating endovascular treatment. However, its use in evaluating hemodynamic changes has rarely been explored.ObjectiveThis study uses t-RA to estimate intravascular flow in patients with AVM to compare this with flow in the normal population.MethodsPatients with available t-RA scans were prospectively categorized into one of three groups: hemorrhagic AVM, non-hemorrhagic AVM and control. Pulsatile time–density curves (TDCs) for C1, C6 and VOIMCA were used for amplitude and velocity estimation. C1 was at the cervical internal carotid artery (ICA), 2–3 cm below the carotid canal, C6 was at the paraclinoid segment of the ICA, and VOIMCA was at the junction of the first and second segment of the middle cerebral artery (MCA). A waveform amplitude ratio was defined as (peak − trough)/trough contrast intensity. VICA was defined as the distance between C6 and C1 divided by the time required for the wave to pass, and correspondingly, the average velocity of MCA (VMCA) was defined as the distance between C6 and VOIMCA divided by the duration for the same peak to travel from C6 and VOIMCA, AVM volume was estimated by MR angiography.ResultsAmplitude ratios AC1 and AC6, and average flow velocities VICA and VMCA were significantly larger in the non-hemorrhagic group than in the control group, while the hemorrhagic AVM group was not significantly different from the controls. VICA and VMCA showed moderate to good correlations with AVM volume (r=0.51 and 0.73, respectively). VMCA (33.0±9.1) was significantly lower than VICA (41.3±13.2) in the control group, but not in the two AVM groups.ConclusionTDC waveform propagation derived from t-RA can quantify hemodynamic differences between AVM and the control group. t-RA provides both real-time anatomic and hemodynamic evaluation, and can thus potentially improve the interventional workflow.

Clinical data analysis is of fundamental importance, as classifications and detailed characterizations of diseases help physicians decide suitable management for patients, individually. In our study, we adopt diffusion maps to embed the data into corresponding lower dimensional representation, which integrate the information of potentially nonlinear progressions of the diseases. To deal with nonuniformaity of the data, we also consider an alternative distance measure based on the estimated local density. Performance of this modification is assessed using artificially generated data. Another clinical dataset that comprises metabolite concentrations measured with magnetic resonance spectroscopy was also classified. The algorithm shows improved results compared with conventional Euclidean distance measure.