Rashindra Manniesing

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 Hessians 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.

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 methods 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 methods 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.

MR venography of the human brain using susceptibility weighted imaging at very high field strength

ObjectiveWe investigate the implications of high magnetic field strength on MR venography based on susceptibility-weighted imaging (SWI) and estimate the optimum echo time to obtain maximum contrast between blood and brain tissue.Materials and methodsWe measured tissue contrast and T2* relaxation times at 7xa0T of gray matter, white matter, and venous blood in vivo.ResultsT2* relaxation times of gray matter, white matter, and venous blood in vivo yielded 32.9 ±xa02.3, 27.7 ±xa04.3, and 7.4 ±xa01.4xa0ms, respectively. Optimum TE was found to be 15xa0ms which is supported by theoretical considerations. Using this optimum TE, we acquired 3D high resolution datasets with a large volume coverage in a short measurement time that show very detailed microanatomical structures of the human brain such as intracortical veins and laminar cortical substructures.ConclusionsBy applying optimised vessel filters (vesselness filter and vessel enhancing diffusion) whole brain MR venograms can be obtained at 7 T with a significantly reduced measurement time compared to 3 T.

Vessel Axis Tracking Using Topology Constrained Surface Evolution

An approach to 3-D vessel axis tracking based on surface evolution is presented. The main idea is to guide the evolution of the surface by analyzing its skeleton topology during evolution, and imposing shape constraints on the topology. For example, the intermediate topology can be processed such that it represents a single vessel segment, a bifurcation, or a more complex vascular topology. The evolving surface is then reinitialized with the newly found topology. Reinitialization is a crucial step since it creates probing behavior of the evolving front, encourages the segmentation process to extract the vascular structure of interest and reduces the risk on leaking of the curve into the background. The method was evaluated in two computed tomography angiography applications: 1) extracting the internal carotid arteries including the region in which they traverse through the skull base, which is challenging due to the proximity of bone structures and overlap in intensity values; 2) extracting the carotid bifurcations including many cases in which they are severely stenosed and contain calcifications. The vessel axis was found in 90% (18/20 internal carotids in ten patients) and 70% (14/20 carotid bifurcations in a different set of ten patients) of the cases

Abdominal Fat in Children Measured by Ultrasound and Computed Tomography

The prevalence of childhood obesity is increasing rapidly. Visceral fat plays an important role in the pathogenesis of metabolic and cardiovascular diseases. Currently, computed tomography (CT) is broadly seen as the most accurate method of determining the amount of visceral fat. The main objective was to examine whether measures of abdominal visceral fat can be determined by ultrasound in children and whether CT can be replaced by ultrasound for this purpose. To assess whether preperitoneal fat thickness and area are good approximations of visceral fat at the umbilical level, we first retrospectively examined 47 CT scans of nonobese children (body mass index <30kg/m(2); median age 7.9 y [95% range 1.2 to 16.2]). Correlation coefficients between visceral and preperitoneal fat thickness and area were 0.58 (p<0.001) and 0.76 (p<0.001), respectively. Then, to assess how preperitoneal and subcutaneous fat thicknesses and areas measured by ultrasound compare with these parameters in CT, we examined 34 nonobese children (median age 9.5 [95% range 0.3 to 17.0]) by ultrasound and CT. Ultrasound measurements of preperitoneal and subcutaneous fat were correlated with CT measurements, with correlation coefficients ranging from 0.75-0.97 (all p<0.001). Systematic differences of up to 24.0cm(2) for preperitoneal fat area (95% confidence interval -29.9 to 77.9cm(2)) were observed when analyzing the results described by the Bland-Altman method. Our findings suggest that preperitoneal fat can be used as an approximation for visceral fat in children and that measuring abdominal fat with ultrasound in children is a valid method for epidemiological and clinical studies. However, the exact agreement between the ultrasound and CT scan was limited, which indicates that ultrasound should be used carefully for obtaining exact fat distribution measurements in individual children.

Fetal and infant growth patterns associated with total and abdominal fat distribution in school-age children

CONTEXTnHigher infant growth rates are associated with an increased risk of obesity in later life.nnnOBJECTIVEnWe examined the associations of longitudinally measured fetal and infant growth patterns with total and abdominal fat distribution in childhood.nnnDESIGN, SETTING, AND PARTICIPANTSnWe performed a population-based prospective cohort study among 6464 children. We measured growth characteristics in the second and third trimesters of pregnancy, at birth, and at 6, 12, and 24 months.nnnMAIN OUTCOME MEASURESnBody mass index, fat mass index (body fat mass/height(2)), lean mass index (body lean mass/height(2)), android/gynoid fat ratio measured by dual-energy x-ray absorptiometry, and sc and preperitoneal abdominal fat measured by ultrasound at the median age of 6.0 years (90% range, 5.7-7.4).nnnRESULTSnWe observed that weight gain in the second and third trimesters of fetal life and in early, mid, and late infancy were independently and positively associated with childhood body mass index (P < .05). Only infant weight gain was associated with higher fat mass index, android/gynoid fat ratio, and abdominal fat in childhood (P < .05). Children with both fetal and infant growth acceleration had the highest childhood body mass index, fat mass index, and sc abdominal fat, whereas children with fetal growth deceleration and infant growth acceleration had the highest value for android/gynoid fat ratio and the lowest value for lean mass index (P < .05).nnnCONCLUSIONSnGrowth in both fetal life and infancy affects childhood body mass index, whereas only infant growth directly affects measured total body and abdominal fat. Fetal growth deceleration followed by infant growth acceleration may lead to an adverse body fat distribution in childhood.

4D-CTA in Neurovascular Disease: A Review

SUMMARY: CT angiography is a widely used technique for the noninvasive evaluation of neurovascular pathology. Because CTA is a snapshot of arterial contrast enhancement, information on flow dynamics is limited. Dynamic CTA techniques, also referred to as 4D-CTA, have become available for clinical practice in recent years. This article provides a description of 4D-CTA techniques and a review of the available literature on the application of 4D-CTA for the evaluation of intracranial vascular malformations and hemorrhagic and ischemic stroke. Most of the research performed to date consists of observational cohort studies or descriptive case series. These studies show that intracranial vascular malformations can be adequately depicted and classified by 4D-CTA, with DSA as the reference standard. In ischemic stroke, 4D-CTA better estimates thrombus burden and the presence of collateral vessels than conventional CTA. In intracranial hemorrhage, 4D-CTA improves the detection of the “spot” sign, which represents active ongoing bleeding.

Segmentation of the Outer Vessel Wall of the Common Carotid Artery in CTA

A novel method is presented for carotid artery vessel wall segmentation in computed tomography angiography (CTA) data. First the carotid lumen is semi-automatically segmented using a level set approach initialized with three seed points. Subsequently, calcium regions located within the vessel wall are automatically detected and classified using multiple features in a GentleBoost framework. Calcium regions segmentation is used to improve localization of the outer vessel wall because it is an easier task than direct outer vessel wall segmentation. In a third step, pixels outside the lumen area are classified as vessel wall or background, using the same GentleBoost framework with a different set of image features. Finally, a 2-D ellipse shape deformable model is fitted to a cost image derived from both the calcium and vessel wall classifications. The method has been validated on a dataset of 60 CTA images. The experimental results show that the accuracy of the method is comparable to the interobserver variability.

Bayesian tracking of tubular structures and its application to carotid arteries in CTA

This paper presents a Bayesian framework for tracking of tubular structures such as vessels. Compared to conventional tracking schemes, its main advantage is its non-deterministic character, which strongly increases the robustness of the method. A key element of our approach is a dedicated observation model for tubular structures in regions with varying intensities. Furthermore, we show how the tracking method can be used to obtain a probabilistic segmentation of the tracked tubular structure. The method has been applied to track the internal carotid artery from CT angiography data of 14 patients (28 carotids) through the skull base. This is a challenging problem, owing to the close proximity of bone, overlap in intensity values of lumen voxels and (partial volume) bone voxels, and the tortuous path of the vessels. The tracking was successful in 25 cases, and the extracted path were found to be close (< 1.0mm) to manually traced paths by two observers.

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.