Till Illies

Territorial and Microvascular Perfusion Impairment in Brain Arteriovenous Malformations

BACKGROUND AND PURPOSE: Both the existence and clinical relevance of a steal phenomenon in brain arteriovenous malformations (AVMs) remains a matter of debate. This study aimed to assess perfusion in the brain adjacent to brain AVMs and to relate these to macrovascular blood flow in a single measurement. MATERIALS AND METHODS: Twenty consecutive patients with AVMs with a median age of 37 years were evaluated by 3T MR imaging by using 3D time-resolved MR angiography to determine blood flow and perfusion patterns. Cerebral perfusion was estimated by using an arterial spin-labeling technique in vascular territories around the nidus and in symmetric regions of interest in the ipsilateral and contralateral hemispheres. Mapping of concentric shells around the nidus was used to define the immediate and adjacent brain and relative perfusion reductions >20% of baseline, termed perinidal dip (PND). RESULTS: A significant reduction in perfusion ratios between ipsilateral and contralateral hemispheres remote to the AVMs was demonstrated in the middle and posterior cerebral artery territories. PND was detected in 5 patients, and 17 patients overall showed reduced perfusion in the perinidal region on visual inspection. There was a negative correlation of the hemispheric territorial perfusion with the affected/nonaffected inflow time ratio (R = −0.402, P = .015). CONCLUSIONS: The perfusion impairment in vascular territories adjacent to brain AVMs that we identified as PND may reflect the existence of 2 levels of perfusion impairment: a territorial and a microvascular perfusion disturbance. Although the hemispheric asymmetry in territorial perfusion seems the result of arterioarterial redistribution, the PND was inhomogeneously distributed within a single vascular territory and thus might result from low perfusion pressure in small arteries and arterioles.

3D cerebrovascular segmentation combining fuzzy vessel enhancement and level-sets with anisotropic energy weights

The aim of this work is to present and evaluate a level-set segmentation approach with vesselness-dependent anisotropic energy weights, which focuses on the exact segmentation of malformed as well as small vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) datasets. In a first step, a vesselness filter is used to calculate the vesselness dataset, which quantifies the likeliness of each voxel to belong to a bright tubular-shaped structure and estimate the corresponding vessel directions from a given TOF dataset. The vesselness and TOF datasets are then combined using fuzzy-logic and used for initialization of a variational level-set method. The proposed level-set model has been extended in a way that the weight of the internal energy is locally adapted based on the vessel direction information. Here, the main idea is to weight the internal energy lower if the gradient direction of the level-set is similar to the direction of the eigenvector extracted by the vesselness filter. Furthermore, an additional vesselness force has been integrated in the level-set formulation. The proposed method was evaluated based on ten TOF MRA datasets from patients with an arteriovenous malformation. Manual segmentations from two observers were available for each dataset and used for quantitative comparison. The evaluation revealed that the proposed method yields significantly better segmentation results than four other state-of-the-art segmentation methods tested. Furthermore, the segmentation results are within the range of the inter-observer variation. In conclusion, the proposed method allows an improved delineation of small vessels, especially of those represented by low intensities and high surface curvatures.

Fuzzy-based Vascular Structure Enhancement in Time-of-Flight MRA Images for Improved Segmentation

OBJECTIVES Cerebral vascular malformations might lead to strokes due to occurrence of ruptures. The rupture risk is highly related to the individual vascular anatomy. The 3D Time-of-Flight (TOF) MRA technique is a commonly used non-invasive imaging technique for exploration of the vascular anatomy. Several clinical applications require exact cerebrovascular segmentations from this image sequence. For this purpose, intensity-based segmentation approaches are widely used. Since small low-contrast vessels are often not detected, vesselness filter-based segmentation schemes have been proposed, which contrariwise have problems detecting malformed vessels. In this paper, a fuzzy logic-based method for fusion of intensity and vesselness information is presented, allowing an improved segmentation of malformed and small vessels at preservation of advantages of both approaches. METHODS After preprocessing of a TOF dataset, the corresponding vesselness image is computed. The role of the fuzzy logic is to voxel-wisely fuse the intensity information from the TOF dataset with the corresponding vesselness information based on an analytically designed rule base. The resulting fuzzy parameter image can then be used for improved cerebrovascular segmentation. RESULTS Six datasets, manually segmented by medical experts, were used for evaluation. Based on TOF, vesselness and fused fuzzy parameter images, the vessels of each patient were segmented using optimal thresholds computed by maximizing the agreement to manual segmentations using the Tanimoto coefficient. The results showed an overall improvement of 0.054 (fuzzy vs. TOF) and 0.079 (fuzzy vs. vesselness). Furthermore, the evaluation has shown that the method proposed yields better results than statistical Bayes classification. CONCLUSION The proposed method can automatically fuse the benefits of intensity and vesselness information and can improve the results of following cerebrovascular segmentations.

Persistent Hemodynamic Changes in Ruptured Brain Arteriovenous Malformations

Background and Purpose— Hemodynamic properties of brain arteriovenous malformations (AVMs) with risk factors for a future hemorrhage are essentially unknown. We hypothesized that AVMs with anatomic properties, which are associated with an increased rupture risk, exhibit different hemodynamic characteristics than those without these properties. Methods— Seventy-two consecutive patients with AVMs diagnosed by conventional angiography underwent MRI examination, including time-resolved 3-dimensional MR angiography. Signal-intensity curves derived from the time-resolved 3-dimensional MR angiography datasets were used to calculate relative blood flow transit times through the AVM nidus based on the time-to-peak parameter. For identification of characteristics associated with altered transit times, a multiple normal regression model was fitted with stepwise selection of the following regressors: intracranial hemorrhage, deep nidus location, infratentorial location, deep drainage, associated aneurysm, nidus size, draining venous stenosis, and number of draining veins. Results— A previous intracranial hemorrhage is the only characteristic that was associated with a significant alteration of the relative transit time, leading to an increase of 2.4 seconds (95% CI, 1.2–3.6 seconds;, P<0.001) without adjustment and 2.1 seconds (95% CI, 0.6–3.6 seconds; P=0.007) with adjustment for all other regressors considered. The association was independent of the bleeding age. Conclusion— Hemodynamic parameters do not seem useful for risk assessment of an AVM-related hemorrhage because only a previous AVM rupture leads to a significant and permanent alteration of the hemodynamic situation.

Automatic Brain Segmentation in Time-of-Flight MRA Images

OBJECTIVES Cerebral vascular malformations might, caused by ruptures, lead to strokes. The rupture risk depends to a great extent on the individual anatomy of the vasculature. The 3D Time-of-Flight (TOF) MRA technique is one of the most commonly used non-invasive imaging techniques to obtain knowledge about the individual vascular anatomy. Unfortunately TOF images exhibit drawbacks for segmentation and direct volume visualization of the vasculature. To overcome these drawbacks an initial segmentation of the brain tissue is required. METHODS After preprocessing of the data is applied the low-intensity tissues surrounding the brain are segmented using region growing. In a following step this segmentation is used to extract supporting points at the border of the brain for a graph-based contour extraction. Finally a consistency check is performed to identify local outliers which are corrected using non-linear registration. RESULTS A quantitative validation of the method proposed was performed on 18 clinical datasets based on manual segmentations. A mean Dice coefficient of 0.989 was achieved while in average 99.56% of all vessel voxels were included by the brain segmentation. A comparison to the results yielded by three commonly used tools for brain segmentation revealed that the method described achieves better results, using TOF images as input, which are within the inter-observer variability. CONCLUSION The method suggested allows a robust and automatic segmentation of brain tissue in TOF images. It is especially helpful to improve the automatic segmentation or direct volume rendering of the cerebral vascular system.

Evidence of Rapid Ongoing Brain Development Beyond 2 Years of Age Detected by Fiber Tracking

BACKGROUND AND PURPOSE: Development of callosal fibers is important for psychomotor and cognitive functions. We hypothesized that brain maturation changes are detectable beyond 2 years of age by using diffusion tensor imaging (DTI) of the corpus callosum (CC). MATERIALS AND METHODS: T2 and fractional anisotropy (FA) maps of the brain of 55 healthy subjects between 0.2 and 39 years of age were obtained. Quantitative T2 and FA values were measured at the genu and splenium of the CC (gCC and sCC). Fiber tracking, volumetric determination, and the fiber density calculations of the CC were related to age. A paired t test was used for significant differences between the values at the gCC and sCC. RESULTS: T2 relaxation times at gCC and sCC decrease fast in the first months of life and very little after 2 years of age. The FAgCC increases until 5 years of age and remains nearly constant thereafter; it showed a significant increase from 0 to 2 years versus 2–5 years, whereas there was no difference in the other age groups. FAsCC values showed no significant changes after 2 years of age. The fiber density of the CC shows a tendency of inverse age dependence from childhood to adulthood. CONCLUSION: Rapid ongoing changes in brain maturation (increase in FAgCC) are detectable until 5 years of age. DTI reveals more information about brain maturation than T2 relaxometry.

4D blood flow visualization fusing 3D and 4D MRA image sequences

To present and evaluate the feasibility of a novel automatic method for generating 4D blood flow visualizations fusing high spatial resolution 3D and time‐resolved (4D) magnetic resonance angiography (MRA) datasets.

Classification of Cerebral Arteriovenous Malformations and Intranidal Flow Patterns by Color-Encoded 4D-Hybrid-MRA

BACKGROUND AND PURPOSE: 4D MRA has been evolving as a noninvasive supplement for DSA. The purpose of this study was to evaluate the feasibility of a newly developed blood flow visualization technique for the classification of cerebral AVMs. We hypothesized that 4D-hMRA allows detection of different flow patterns within the nidus as well as differentiation of feeders and draining veins and has very good agreement with DSA regarding the Spetzler-Martin grade. MATERIALS AND METHODS: Thirty-one consecutive patients with AVMs were evaluated by using 4D-hMRA and DSA by 2 blinded raters. Rating criteria included Spetzler-Martin score and other morphologic variables together with a new scale for 3 intranidal flow patterns (homogeneous = 1, unidirectional = 2, heterogeneous = 3). RESULTS: The Spetzler-Martin grades were rated different from DSA in 5 cases by rater 1 and in 3 cases by rater 2 with an excellent interrater reliability of κ = 0.96 (4/31, 1 by size and 3 by drainage). Each reader missed 5 feeders on 4D-hMRA. Draining veins were distinguished in the temporal course in 7 on DSA but in 8 and 12 on 4D-hybrid-MRA (raters 1 and 2 respectively), with κ = 0.79. A type 1 intranidal flow pattern was recognizable in 9 (30%) patients; type 2, in 19 (60%); and type 3, in 3 (10%). CONCLUSIONS: 4D-hMRA allows reliable Spetzler-Martin grading and detection of brain arteriovenous malformation feeding arteries and draining veins, with the drawback that for small vessels DSA is still needed. Draining veins might even be detected with higher sensitivity than on DSA. Discrimination of different intranidal flow patterns is possible, but their relevance for hemorrhage risk assessment and therapy planning requires further study.

Reference-based linear curve fitting for bolus arrival time estimation in 4D MRA and MR perfusion-weighted image sequences.

The bolus arrival time (BAT) based on an indicator dilution curve is an important hemodynamic parameter. As the direct estimation of this parameter is generally problematic, various parametric models have been proposed that describe typical physiological shapes of indicator dilution curves, but it remains unclear which model describes the real physiological background. This article presents a method that indirectly incorporates physiological information derived from the data available. For this, a patient‐specific hemodynamic reference curve is extracted, and the corresponding reference BAT is determined. To estimate a BAT for a given signal curve, the reference curve is fitted linearly to the signal curve. The parameters of the fitting process are then used to transfer the reference BAT to the signal curve. The validation of the method proposed based on Monte Carlo simulations showed that the approach presented is capable of improving the BAT estimation precision compared with standard BAT estimation methods by up to 59% while at the same time reduces the computation time. A major benefit of the method proposed is that no assumption about the underlying distribution of indicator dilution has to be made, as it is implicitly modeled in the reference curve. Magn Reson Med, 2010.

Combination of T2*W and FLAIR abnormalities for the prediction of parenchymal hematoma following thrombolytic therapy in 100 stroke patients.

The objective of our study was to determine whether the combination of hypointense spots (“cerebral microbleeds,” CMBs) with a leukoaraiosis is associated with the risk of parenchymal hematoma (PH) after thrombolytic therapy.