Traumatic Cerebral Microbleeds in the Subacute Phase Are Practical and Early Predictors of Abnormality of the Normal-Appearing White Matter in the Chronic Phase

BACKGROUND AND PURPOSE:In the chronic phase after traumatic brain injury, DTI findings reflect WM integrity. DTI interpretation in the subacute phase is less straightforward. Microbleed evaluation with SWI is straightforward in both phases. We evaluated whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase.MATERIALS AND METHODS:Sixty of 211 consecutive patients 18 years of age or older admitted to our emergency department ≤24 hours after moderate to severe traumatic brain injury matched the selection criteria. Standardized 3T SWI, DTI, and T1WI were obtained 3 and 26 weeks after traumatic brain injury in 31 patients and 24 healthy volunteers. At baseline, microbleed concentrations were calculated. At follow-up, mean diffusivity (MD) was calculated in the normal-appearing WM in reference to the healthy volunteers (MD_z). Through linear regression, we evaluated the relation between microbleed concentration and MD_z in predefined structures.RESULTS:In the cerebral hemispheres, MD_z at follow-up was independently associated with the microbleed concentration at baseline (left: B = 38.4 [95% CI 7.5–69.3], P = .017; right: B = 26.3 [95% CI 5.7–47.0], P = .014). No such relation was demonstrated in the central brain. MD_z in the corpus callosum was independently associated with the microbleed concentration in the structures connected by WM tracts running through the corpus callosum (B = 20.0 [95% CI 24.8–75.2], P < .000). MD_z in the central brain was independently associated with the microbleed concentration in the cerebral hemispheres (B = 25.7 [95% CI 3.9–47.5], P = .023).CONCLUSIONS:SWI-assessed microbleeds in the subacute phase are associated with DTI-based WM integrity in the chronic phase. These associations are found both within regions and between functionally connected regions.

The yearly incidence of traumatic brain injury (TBI) is around 300 per 100,000 persons.^1,2 Almost three-quarters of patients with moderate to severe TBI have traumatic axonal injury (TAI).³ TAI is a major predictor of functional outcome,^4,5 but it is mostly invisible on CT and conventional MR imaging.^6,7DTI provides direct information on WM integrity and axonal injury.^5,8 However, DTI abnormalities are neither specific for TAI nor stable over time. Possibly because of the release of mass effect and edema and resorption of blood products, the effects of concomitant (non-TAI) injury on DTI are larger in the subacute than in the chronic phase (>3 months).^4,9,10 Therefore, DTI findings are expected to reflect TAI more specifically in the chronic than in the subacute phase (1 week–3 months).⁴ Even in regions without concomitant injury, the effects of TAI on DTI are dynamic, possibly caused by degeneration and neuroplastic changes.^6,11,12 These ongoing pathophysiological processes possibly contribute to the emerging evidence that DTI findings in the chronic phase are most closely associated with the eventual functional outcome.^12,13Although DTI provides valuable information, its acquisition, postprocessing, and interpretation in individual patients are demanding. SWI, with which microbleeds can be assessed with high sensitivity, is easier to interpret and implement in clinical practice. In contrast to DTI, SWI-detected traumatic microbleeds are more stable¹ except in the hyperacute^14,15 and the late chronic phases.¹⁶ Traumatic cerebral microbleeds are commonly interpreted as signs of TAI. However, the relation is not straightforward. On the one hand, nontraumatic microbleeds may be pre-existing. On the other hand, even if traumatic in origin, microbleeds represent traumatic vascular rather than axonal injury.¹⁷ Indeed, TAI is not invariably hemorrhagic.¹⁸ Additionally, microbleeds may secondarily develop after trauma through mechanisms unrelated to axonal injury, such as secondary ischemia.¹⁸DTI is not only affected by pathophysiological changes but also by susceptibility.¹⁹ The important susceptibility-effect generated by microbleeds renders the interpretation of DTI findings at the location of microbleeds complex. In the chronic phase, mean diffusivity (MD) is the most robust marker of WM integrity.^4,6 For these reasons, we evaluated MD in the normal-appearing WM.Much TAI research focuses on the corpus callosum because it is commonly involved in TAI^5,18,20 and it can reliably be evaluated with DTI,^5,21 and TAI in the corpus callosum is related to clinical prognosis.^6,20 The corpus callosum consists of densely packed WM tracts that structurally and functionally connect left- and right-sided brain structures.²² The integrity of the corpus callosum is associated with the integrity of the brain structures it connects.²³ Therefore, microbleeds in brain structures that are connected through the corpus callosum may affect callosal DTI findings. Analogous to this, microbleeds in the cerebral hemispheres, which exert their function through WM tracts traveling through the deep brain structures and brain stem,^24,25 may affect DTI findings in the WM of the latter.Our purpose was to evaluate whether the microbleed concentration in the subacute phase is associated with the integrity of normal-appearing WM in the chronic phase. We investigated this relation within the cerebral hemispheres and the central brain and between regions that are functionally connected by WM tracts.     

Brain CT perfusion improves intracranial vessel occlusion detection on CT angiography

Background and purpose

To evaluate whether brain CT perfusion (CTP) aids in the detection of intracranial vessel occlusion on CT angiography (CTA) in acute ischemic stroke.

Automatic carotid artery distensibility measurements from CTA using nonrigid registration

The distensibility of a blood vessel is a marker of atherosclerotic disease. In this paper we investigate the feasibility of measuring carotid artery distensibility on 4D CTA, both manually and using a new automatic method. On 4D CTA datasets manual (n = 38) and automatic (n = 76) measurements of the carotid distensibility were performed. A subset (n = 10) of the manual annotations were repeated by a second observer. The interobserver variability was assessed using a Bland–Altman analysis and appeared to be too large to reliably measure the distensibility using manual annotation. We compared two versions of the automatic method: one using 3D registration and one using a 4D registration method. The latter resulted in a more smooth deformation over time. The automatic method was evaluated using a synthetic deformation and by investigating whether known relations with cardiovascular risk factors could be reproduced. The relation between distensibility and cardiovascular risk factors was tested with a Mann–Whitney U test. Automatic measurements revealed an association with hypertension whereas the manual measurements did not. This relation has been found by other studies too. We conclude that carotid artery distensibility measurements should be performed automatically and that the method described in this paper is suitable for that. All CTA datasets and related clinical data used in this study can be downloaded from our website (http://ctadist.bigr.nl).     

Level set based cerebral vasculature segmentation and diameter quantification in CT angiography

A level set based method is presented for cerebral vascular tree segmentation from computed tomography angiography (CTA) data. The method starts with bone masking by registering a contrast enhanced scan with a low-dose mask scan in which the bone has been segmented. Then an estimate of the background and vessel intensity distributions is made based on the intensity histogram which is used to steer the level set to capture the vessel boundaries. The relevant parameters of the level set evolution are optimized using a training set. The method is validated by a diameter quantification study which is carried out on phantom data, representing ground truth, and 10 patient data sets. The results are compared to manually obtained measurements by two expert observers. In the phantom study, the method achieves similar accuracy as the observers, but is unbiased whereas the observers are biased, i.e., the results are 0.00+/-0.23 vs. -0.32+/-0.23 mm. Also, the method's reproducibility is slightly better than the inter-and intra-observer variability. In the patient study, the method is in agreement with the observers and also, the method's reproducibility -0.04+/-0.17 mm is similar to the inter-observer variability 0.06+/-0.17 mm. Since the method achieves comparable accuracy and reproducibility as the observers, and since the method achieves better performance than the observers with respect to ground truth, we conclude that the level set based vessel segmentation is a promising method for automated and accurate CTA diameter quantification.     

Robust CTA lumen segmentation of the atherosclerotic carotid artery bifurcation in a large patient population

We propose and validate a semi-automatic method for lumen segmentation of the carotid bifurcation in computed tomography angiography (CTA). First, the central vessel axis is obtained using path tracking between three user-defined points. Second, starting from this path, the segmentation is automatically obtained using a level set. The cost and speed functions for path tracking and segmentation make use of intensity and homogeneity slice-based image features. The method is validated on a large data set of 234 carotid bifurcations of 129 ischemic stroke patients with atherosclerotic disease. The results are compared to manually obtained lumen segmentations. Parameter optimization is carried out on a subset of 30 representative carotid bifurcations. With the optimized parameter settings the method successfully tracked the central vessel paths in 201 of the remaining 204 bifurcations (99%) which were not part of the training set. Comparison with manually drawn segmentations shows that the average overlap between the method and observers is similar (for the inter-observer set the results were 92% vs. 87% and for the intra-observer set 94% vs. 94%). Therefore the method has potential to replace the manual procedure of lumen segmentation of the atherosclerotic bifurcation in CTA.     

Vessel enhancing diffusion: a scale space representation of vessel structures

A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom data and compared to linear, regularized Perona-Malik, edge and coherence enhancing diffusion. The method performs better than most of the existing techniques in visualizing vessels with varying radii and in enhancing vessel appearance. A diameter study on phantom data shows that VED least affects the accuracy of diameter measurements. It is shown that using VED as a preprocessing step improves level set based segmentation of the cerebral vasculature, in particular segmentation of the smaller vessels of the vasculature.     

Cerebral arteries: fully automated segmentation from CT angiography--a feasibility study

The purpose of this study was to retrospectively assess the feasibility of a fully automated image postprocessing tool for the segmentation of the arterial cerebrovasculature from computed tomographic (CT) angiography in 27 patients (nine men, 18 women; mean age, 55 years; age range, 33-76 years) with subarachnoid hemorrhage. The institutional review board approved this study, and informed consent was waived. The proposed method, which does not require the acquisition of an additional CT scan for bone suppression, consists of the following: (a) automatic detection of the main arteries for initialization, (b) segmentation of these arteries through the skull base, and (c) suppression of the large veins near the skull. The parameters of this method were optimized on the training subset of nine patients, and the method was successful at segmentation of the arteries in 15 (83%) of the 18 remaining patients. The difference between automatic and manual diameter measurements was 0.0 mm +/- 0.4 (standard deviation). The study results showed that fully automated segmentation of the cerebral arteries is feasible.     

Automated versus manual segmentation of atherosclerotic carotid plaque volume and components in CTA: associations with cardiovascular risk factors

The purpose of this study was to validate automated atherosclerotic plaque measurements in carotid arteries from CT angiography (CTA). We present an automated method (three initialization points are required) to measure plaque components within the carotid vessel wall in CTA. Plaque components (calcifications, fibrous tissue, lipids) are determined by different ranges of Hounsfield Unit values within the vessel wall. On CTA scans of 40 symptomatic patients with atherosclerotic plaque in the carotid artery automatically segmented plaque volume, calcified, fibrous and lipid percentages were 0.97 ± 0.51 cm(3), 10 ± 11%, 63 ± 10% and 25 ± 5%; while manual measurements by first observer were 0.95 ± 0.60 cm(3), 14 ± 16%, 63 ± 13% and 21 ± 9%, respectively and manual measurement by second observer were 1.05 ± 0.75 cm(3), 11 ± 12%, 61 ± 11% and 27 ± 10%. In 90 datasets, significant associations were found between age, gender, hypercholesterolemia, diabetes, smoking and previous cerebrovascular disease and plaque features. For both automated and manual measurements, significant associations were found between: age and calcium and fibrous tissue percentage; gender and plaque volume and lipid percentage; diabetes and calcium, smoking and plaque volume; previous cerebrovascular disease and plaque volume. Significant associations found only by the automated method were between age and plaque volume, hypercholesterolemia and plaque volume and diabetes and fibrous tissue percentage. Significant association found only by the manual method was between previous cerebrovascular disease and percentage of fibrous tissue. Automated analysis of plaque composition in the carotid arteries is comparable with the manual analysis and has the potential to replace it.