Suv4-20h2 mediates chromatin compaction and is important for cohesin recruitment to heterochromatin.

Cohesin plays an important role in chromatid cohesion and has additional functions in higher-order chromatin organization and in transcriptional regulation. The binding of cohesin to euchromatic regions is largely mediated by CTCF or the mediator complex. However, it is currently unknown how cohesin is recruited to pericentric heterochromatin in mammalian cells. Here we define the histone methyltransferase Suv4-20h2 as a major structural constituent of heterochromatin that mediates chromatin compaction and cohesin recruitment. Suv4-20h2 stably associates with pericentric heterochromatin through synergistic interactions with multiple heterochromatin protein 1 (HP1) molecules, resulting in compaction of heterochromatic regions. Suv4-20h mutant cells display an overall reduced chromatin compaction and an altered chromocenter organization in interphase referred to as "chromocenter scattering." We found that Suv4-20h-deficient cells display chromosome segregation defects during mitosis that coincide with reduced sister chromatid cohesion. Notably, cohesin subunits interact with Suv4-20h2 both in vitro and in vivo. This interaction is necessary for cohesin binding to heterochromatin, as Suv4-20h mutant cells display substantially reduced cohesin levels at pericentric heterochromatin. This defect is most prominent in G0-phase cells, where cohesin is virtually lost from heterochromatin, suggesting that Suv4-20h2 is involved in the initial loading or maintenance of cohesion subunits. In summary, our data provide the first compelling evidence that Suv4-20h2 plays essential roles in regulating nuclear architecture and ensuring proper chromosome segregation.

Combined automated 3D volumetry by pulmonary CT angiography and echocardiography for detection of pulmonary hypertension.

OBJECTIVES: To assess the diagnostic accuracy of automated 3D volumetry of central pulmonary arteries using computed tomography pulmonary angiography (CTPA) for suspected pulmonary hypertension alone and in combination with echocardiography. METHODS: This retrospective diagnostic accuracy study included 70 patients (mean age 66.7, 48 female) assessed for pulmonary hypertension by CTPA and transthoracic echocardiography with estimation of the pulmonary arterial systolic pressure (PASP). Gold standard right heart catheterisation with measurement of the invasive mean pulmonary arterial pressure (invasive mPAP) served as the reference. Volumes of the main, right and left pulmonary arteries (MPA, RPA and LPA) were computed using automated 3D segmentation. For comparison, axial dimensions were manually measured. A linear regression model was established for prediction of mPAP (predicted mPAP). RESULTS: MPA, RPA and LPA volumes were significantly increased in patients with vs. without pulmonary hypertension (all p < 0.001). Of all measures, MPA volume demonstrated the strongest correlation with invasive mPAP (r = 0.76, p < 0.001). Predicted mPAP using MPA volume and echocardiographic PASP as covariates showed excellent correlation with invasive mPAP (r = 0.89, p < 0.001). Area under the curves for predicting pulmonary hypertension were 0.94 for predicted mPAP, compared to 0.90 for MPA volume and 0.92 for echocardiographic PASP alone. A predicted mPAP > 25.8 mmHg identified pulmonary hypertension with sensitivity, specificity, positive and negative predictive values of 86%, 93%, 95% and 81%, respectively. CONCLUSIONS: Automated 3D volumetry of central pulmonary arteries based on CTPA may be used in conjunction with echocardiographic pressure estimates to noninvasively predict mPAP and pulmonary hypertension as confirmed by gold standard right heart catheterisation with higher diagnostic accuracy than either test alone. KEY POINTS: • This diagnostic accuracy study derived a regression model for noninvasive prediction of invasively measured mean pulmonary arterial pressure as assessed by gold standard right heart catheterisation. • This regression model using automated 3D volumetry of the central pulmonary arteries based on CT pulmonary angiography in conjunction with the echocardiographic pressure estimate predicted pulmonary arterial pressure and the presence of pulmonary hypertension with good diagnostic accuracy. • The combination of automated 3D volumetry and echocardiographic pressure estimate in the regression model provided superior diagnostic accuracy compared to each parameter alone.

Rigid and non-rigid registration of polarized light imaging data for 3D reconstruction of the temporal lobe of the human brain at micrometer resolution.

To understand the spatial organization as well as long- and short-range connections of the human brain at microscopic resolution, 3D reconstruction of histological sections is important. We approach this challenge by reconstructing series of unstained histological sections of multi-scale (1.3µm and 64µm) and multi-modal 3D polarized light imaging (3D-PLI) data. Since spatial coherence is lost during the sectioning procedure, image registration is the major step in 3D reconstruction. We propose a non-rigid registration method which comprises of a novel multi-modal similarity metric and an improved regularization scheme to cope with deformations inevitably introduced during the sectioning procedure, as well as a rigid registration approach using a robust similarity metric for improved initial alignment. We also introduce a multi-scale feature-based localization and registration approach for mapping of 1.3µm sections to 64µm sections and a scale-adaptive method that can handle challenging sections with large semi-global deformations due to tissue splits. We have applied our registration method to 126 consecutive sections of the temporal lobe of the human brain with 64µm and 1.3µm resolution. Each step of the registration method was quantitatively evaluated using 10 different sections and manually determined ground truth, and a quantitative comparison with previous methods was performed. Visual assessment of the reconstructed volumes and comparison with reference volumes confirmed the high quality of the registration result.

Quantification of telomere features in tumor tissue sections by an automated 3D imaging-based workflow.

The microscopic analysis of telomere features provides a wealth of information on the mechanism by which tumor cells maintain their unlimited proliferative potential. Accordingly, the analysis of telomeres in tissue sections of patient tumor samples can be exploited to obtain diagnostic information and to define tumor subgroups. In many instances, however, analysis of the image data is conducted by manual inspection of 2D images at relatively low resolution for only a small part of the sample. As the telomere feature signal distribution is frequently heterogeneous, this approach is prone to a biased selection of the information present in the image and lacks subcellular details. Here we address these issues by using an automated high-resolution imaging and analysis workflow that quantifies individual telomere features on tissue sections for a large number of cells. The approach is particularly suited to assess telomere heterogeneity and low abundant cellular subpopulations with distinct telomere characteristics in a reproducible manner. It comprises the integration of multi-color fluorescence in situ hybridization, immunofluorescence and DNA staining with targeted automated 3D fluorescence microscopy and image analysis. We apply our method to telomeres in glioblastoma and prostate cancer samples, and describe how the imaging data can be used to derive statistically reliable information on telomere length distribution or colocalization with PML nuclear bodies. We anticipate that relating this approach to clinical outcome data will prove to be valuable for pretherapeutic patient stratification.

PML induces compaction, TRF2 depletion and DNA damage signaling at telomeres and promotes their alternative lengthening.

The alternative lengthening of telomeres (ALT) mechanism allows cancer cells to escape senescence and apoptosis in the absence of active telomerase. A characteristic feature of this pathway is the assembly of ALT-associated promyelocytic leukemia (PML) nuclear bodies (APBs) at telomeres. Here, we dissected the role of APBs in a human ALT cell line by performing an RNA interference screen using an automated 3D fluorescence microscopy platform and advanced 3D image analysis. We identified 29 proteins that affected APB formation, which included proteins involved in telomere and chromatin organization, protein sumoylation and DNA repair. By integrating and extending these findings, we found that APB formation induced clustering of telomere repeats, telomere compaction and concomitant depletion of the shelterin protein TRF2 (also known as TERF2). These APB-dependent changes correlated with the induction of a DNA damage response at telomeres in APBs as evident by a strong enrichment of the phosphorylated form of the ataxia telangiectasia mutated (ATM) kinase. Accordingly, we propose that APBs promote telomere maintenance by inducing a DNA damage response in ALT-positive tumor cells through changing the telomeric chromatin state to trigger ATM phosphorylation.

How Precise Are Preinterventional Measurements Using Centerline Analysis Applications? Objective Ground Truth Evaluation Reveals Software-Specific Centerline Characteristics.

PURPOSE: To evaluate different centerline analysis applications using objective ground truth from realistic aortic aneurysm phantoms with precisely defined geometry and centerlines to overcome the lack of unknown true dimensions in previously published in vivo validation studies. METHODS: Three aortic phantoms were created using computer-aided design (CAD) software and a 3-dimensional (3D) printer. Computed tomography angiograms (CTAs) of phantoms and 3 patients were analyzed with 3 clinically approved and 1 research software application. The 3D centerline coordinates, intraluminal diameters, and lengths were validated against CAD ground truth using a dedicated evaluation software platform. RESULTS: The 3D centerline position mean error ranged from 0.7±0.8 to 2.9±2.5 mm between tested applications. All applications calculated centerlines significantly different from ground truth. Diameter mean errors varied from 0.5±1.2 to 1.1±1.0 mm among 3 applications, but exceeded 8.0±11.0 mm with one application due to an unsteady distortion of luminal dimensions along the centerline. All tested commercially available software tools systematically underestimated centerline total lengths by -4.6±0.9 mm to -10.4±4.3 mm (maximum error -14.6 mm). Applications with the highest 3D centerline accuracy yielded the most precise diameter and length measurements. CONCLUSION: One clinically approved application did not provide reproducible centerline-based analysis results, while another approved application showed length errors that might influence stent-graft choice and procedure success. The variety and specific characteristics of endovascular aneurysm repair planning software tools require scientific evaluation and user awareness.

Automated Analysis of Single-Molecule Photobleaching Data by Statistical Modeling of Spot Populations.

The number of fluorophores within a molecule complex can be revealed by single-molecule photobleaching imaging. A widely applied strategy to analyze intensity traces over time is the quantification of photobleaching step counts. However, several factors can limit and bias the detection of photobleaching steps, including noise, high numbers of fluorophores, and the possibility that several photobleaching events occur almost simultaneously. In this study, we propose a new approach, to our knowledge, to determine the fluorophore number that correlates the intensity decay of a population of molecule complexes with the decay of the number of visible complexes. We validated our approach using single and fourfold Atto-labeled DNA strands. As an example we estimated the subunit stoichiometry of soluble CD95L using GFP fusion proteins. To assess the precision of our method we performed in silico experiments showing that the estimates are not biased for experimentally observed intensity fluctuations and that the relative precision remains constant with increasing number of fluorophores. In case of fractional fluorescent labeling, our simulations predicted that the fluorophore number estimate corresponds to the product of the true fluorophore number with the labeling fraction. Our method, denoted by spot number and intensity correlation (SONIC), is fully automated, robust to noise, and does not require the counting of photobleaching events.

Performance and sensitivity evaluation of 3D spot detection methods in confocal microscopy.

Reliable 3D detection of diffraction-limited spots in fluorescence microscopy images is an important task in subcellular observation. Generally, fluorescence microscopy images are heavily degraded by noise and non-specifically stained background, making reliable detection a challenging task. In this work, we have studied the performance and parameter sensitivity of eight recent methods for 3D spot detection. The study is based on both 3D synthetic image data and 3D real confocal microscopy images. The synthetic images were generated using a simulator modeling the complete imaging setup, including the optical path as well as the image acquisition process. We studied the detection performance and parameter sensitivity under different noise levels and under the influence of uneven background signal. To evaluate the parameter sensitivity, we propose a novel measure based on the gradient magnitude of the F1 score. We measured the success rate of the individual methods for different types of the image data and found that the type of image degradation is an important factor. Using the F1 score and the newly proposed sensitivity measure, we found that the parameter sensitivity is not necessarily proportional to the success rate of a method. This also provided an explanation why the best performing method for synthetic data was outperformed by other methods when applied to the real microscopy images. On the basis of the results obtained, we conclude with the recommendation of the HDome method for data with relatively low variations in quality, or the Sorokin method for image sets in which the quality varies more. We also provide alternative recommendations for high-quality images, and for situations in which detailed parameter tuning might be deemed expensive.

Aortic morphometry at endograft position as assessed by 3D image analysis affects risk of type I endoleak formation after TEVAR.

PURPOSE: The purpose of this study was to identify morphologic factors affecting type I endoleak formation and bird-beak configuration after thoracic endovascular aortic repair (TEVAR). METHODS: Computed tomography (CT) data of 57 patients (40 males; median age, 66 years) undergoing TEVAR for thoracic aortic aneurysm (34 TAA, 19 TAAA) or penetrating aortic ulcer (n = 4) between 2001 and 2010 were retrospectively reviewed. In 28 patients, the Gore TAG® stent-graft was used, followed by the Medtronic Valiant® in 16 cases, the Medtronic Talent® in 8, and the Cook Zenith® in 5 cases. Proximal landing zone (PLZ) was in zone 1 in 13, zone 2 in 13, zone 3 in 23, and zone 4 in 8 patients. In 14 patients (25%), the procedure was urgent or emergent. In each case, pre- and postoperative CT angiography was analyzed using a dedicated image processing workstation and complimentary in-house developed software based on a 3D cylindrical intensity model to calculate aortic arch angulation and conicity of the landing zones (LZ). RESULTS: Primary type Ia endoleak rate was 12% (7/57) and subsequent re-intervention rate was 86% (6/7). Left subclavian artery (LSA) coverage (p = 0.036) and conicity of the PLZ (5.9 vs. 2.6 mm; p = 0.016) were significantly associated with an increased type Ia endoleak rate. Bird-beak configuration was observed in 16 patients (28%) and was associated with a smaller radius of the aortic arch curvature (42 vs. 65 mm; p = 0.049). Type Ia endoleak was not associated with a bird-beak configuration (p = 0.388). Primary type Ib endoleak rate was 7% (4/57) and subsequent re-intervention rate was 100%. Conicity of the distal LZ was associated with an increased type Ib endoleak rate (8.3 vs. 2.6 mm; p = 0.038). CONCLUSIONS: CT-based 3D aortic morphometry helps to identify risk factors of type I endoleak formation and bird-beak configuration during TEVAR. These factors were LSA coverage and conicity within the landing zones for type I endoleak formation and steep aortic angulation for bird-beak configuration.

Development of in vivo quantitative geometric mapping of the aortic arch for advanced endovascular aortic repair: feasibility and preliminary results.

PURPOSE: To evaluate whether quantitative characterization of aortic arch geometry including its branches is feasible based on in vivo computed tomography (CT) angiography and magnetic resonance (MR) angiography data in healthy and diseased aortic arches. MATERIALS AND METHODS: Ten healthy volunteers, 10 patients with abdominal aortic disease, and 10 patients with aortic arch disease underwent MR angiography (10 volunteers) or CT angiography (20 patients). Commercial software was used for individual segmentation of supraaortic arteries. In-house software was developed for segmentation of aortic arch landmarks based on standardized multiplanar reformations (MPRs) and for subsequent aortic arch mapping. RESULTS: Supraaortic arteries and aortic arch landmarks were successfully segmented in all 30 subjects for CT angiography and MR angiography data. Significant tapering within the first centimeter was observed in all supraaortic arteries (P < .001). The three supraaortic arteries showed significantly different vessel diameters and areas (P < .001). The software developed in-house allowed detailed aortic arch mapping with quantitative definitions of the positional relationships between each supraaortic artery and the aorta. Distances between supraaortic arteries were less than 5 mm in 77.6% (mean 4.1 mm ± 3.8). The brachiocephalic trunk tended to be positioned on the right side of the aortic arch, and the left subclavian and left common carotid arteries tended to be positioned on the left side of the aortic arch. CONCLUSIONS: The feasibility and application of a postprocessing method allowing quantification of geometry of supraaortic arteries and aortic arch mapping were successfully demonstrated. Validation and evaluation of clinical implications are warranted.

Progressive Minimal Path Method for Segmentation of 2D and 3D Line Structures.

We propose a novel minimal path method for the segmentation of 2D and 3D line structures. Minimal path methods perform propagation of a wavefront emanating from a start point at a speed derived from image features, followed by path extraction using backtracing. Usually, the computation of the speed and the propagation of the wave are two separate steps, and point features are used to compute a static speed. We introduce a new continuous minimal path method which steers the wave propagation progressively using dynamic speed based on path features. We present three instances of our method, using an appearance feature of the path, a geometric feature based on the curvature of the path, and a joint appearance and geometric feature based on the tangent of the wavefront. These features have not been used in previous continuous minimal path methods. We compute the features dynamically during the wave propagation, and also efficiently using a fast numerical scheme and a low-dimensional parameter space. Our method does not suffer from discretization or metrication errors. We performed qualitative and quantitative evaluations using 2D and 3D images from different application areas.

Segmentation and quantification of human vessels using a 3-D cylindrical intensity model.

We introduce a new approach for 3-D segmentation and quantification of vessels. The approach is based on a 3-D cylindrical parametric intensity model, which is directly fitted to the image intensities through an incremental process based on a Kalman filter. Segmentation results are the vessel centerline and shape, i.e., we estimate the local vessel radius, the 3-D position and 3-D orientation, the contrast, as well as the fitting error. We carried out an extensive validation using 3-D synthetic images and also compared the new approach with an approach based on a Gaussian model. In addition, the new model has been successfully applied to segment vessels from 3-D MRA and computed tomography angiography image data. In particular, we compared our approach with an approach based on the randomized Hough transform. Moreover, a validation of the segmentation results based on ground truth provided by a radiologist confirms the accuracy of the new approach. Our experiments show that the new model yields superior results in estimating the vessel radius compared to previous approaches based on a Gaussian model as well as the Hough transform.

Localization of anatomical point landmarks in 3D medical images by fitting 3D parametric intensity models.

We introduce a new approach for the localization of 3D anatomical point landmarks. This approach is based on 3D parametric intensity models which are directly fitted to 3D images. To efficiently model tip-like, saddle-like, and sphere-like anatomical structures we introduce analytic intensity models based on the Gaussian error function in conjunction with 3D rigid transformations as well as deformations. To select a suitable size of the region-of-interest (ROI) where model fitting is performed, we also propose a new scheme for automatic selection of an optimal 3D ROI size based on the dominant gradient direction. In addition, to achieve a higher level of automation we present an algorithm for automatic initialization of the model parameters. Our approach has been successfully applied to accurately localize anatomical landmarks in 3D synthetic data as well as 3D MR and 3D CT image data. We have also compared the experimental results with the results of a previously proposed 3D differential approach. It turns out that the new approach significantly improves the localization accuracy.

Automatic 3D Segmentation and Quantification of Lenticulostriate Arteries from High-Resolution 7 Tesla MRA Images.

We propose a novel hybrid approach for automatic 3D segmentation and quantification of high-resolution 7 Tesla magnetic resonance angiography (MRA) images of the human cerebral vasculature. Our approach consists of two main steps. First, a 3D model-based approach is used to segment and quantify thick vessels and most parts of thin vessels. Second, remaining vessel gaps of the first step in low-contrast and noisy regions are completed using a 3D minimal path approach, which exploits directional information. We present two novel minimal path approaches. The first is an explicit approach based on energy minimization using probabilistic sampling, and the second is an implicit approach based on fast marching with anisotropic directional prior. We conducted an extensive evaluation with over 2300 3D synthetic images and 40 real 3D 7 Tesla MRA images. Quantitative and qualitative evaluation shows that our approach achieves superior results compared with a previous minimal path approach. Furthermore, our approach was successfully used in two clinical studies on stroke and vascular dementia.

3D Geometric Analysis of the Pediatric Aorta in 3D MRA Follow-Up Images with Application to Aortic Coarctation.

BACKGROUND: Coarctation of the aorta is one of the most common congenital heart diseases. Despite different treatment opportunities, long-term outcome after surgical or interventional therapy is diverse. Serial morphologic follow-up of vessel growth is necessary, because vessel growth cannot be predicted by primer morphology or a therapeutic option. OBJECTIVES: For the analysis of the long-term outcome after therapy of congenital diseases such as aortic coarctation, accurate 3D geometric analysis of the aorta from follow-up 3D medical image data such as magnetic resonance angiography (MRA) is important. However, for an objective, fast, and accurate 3D geometric analysis, an automatic approach for 3D segmentation and quantification of the aorta from pediatric images is required. METHODS: We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model that requires only relatively few model parameters. Moreover, we include a novel adaptive background-masking scheme used for least-squares model fitting, we use a spatial normalization scheme to align the segmentation results from follow-up examinations, and we determine relevant 3D geometric parameters of the aortic arch. RESULTS: We have evaluated our proposed approach using different 3D synthetic images. Moreover, we have successfully applied the approach to follow-up pediatric 3D MRA image data, we have normalized the 3D segmentation results of follow-up images of individual patients, and we have combined the results of all patients. We also present a quantitative evaluation of our approach for four follow-up 3D MRA images of a patient, which confirms that our approach yields accurate 3D segmentation results. An experimental comparison with two previous approaches demonstrates that our approach yields superior results. CONCLUSIONS: From the results, we found that our approach is well suited for the quantification of the 3D geometry of the aortic arch from follow-up pediatric 3D MRA image data. In future work, this will enable to investigate the long-term outcome of different surgical and interventional therapies for aortic coarctation.

A spherical harmonics intensity model for 3D segmentation and 3D shape analysis of heterochromatin foci.

The genome is partitioned into regions of euchromatin and heterochromatin. The organization of heterochromatin is important for the regulation of cellular processes such as chromosome segregation and gene silencing, and their misregulation is linked to cancer and other diseases. We present a model-based approach for automatic 3D segmentation and 3D shape analysis of heterochromatin foci from 3D confocal light microscopy images. Our approach employs a novel 3D intensity model based on spherical harmonics, which analytically describes the shape and intensities of the foci. The model parameters are determined by fitting the model to the image intensities using least-squares minimization. To characterize the 3D shape of the foci, we exploit the computed spherical harmonics coefficients and determine a shape descriptor. We applied our approach to 3D synthetic image data as well as real 3D static and real 3D time-lapse microscopy images, and compared the performance with that of previous approaches. It turned out that our approach yields accurate 3D segmentation results and performs better than previous approaches. We also show that our approach can be used for quantifying 3D shape differences of heterochromatin foci.

Automated 3D Volumetry of the Pulmonary Arteries based on Magnetic Resonance Angiography Has Potential for Predicting Pulmonary Hypertension.

PURPOSE: To demonstrate feasibility of automated 3D volumetry of central pulmonary arteries based on magnetic resonance angiography (MRA), to assess pulmonary artery volumes in patients with pulmonary hypertension compared to healthy controls, and to investigate the potential of the technique for predicting pulmonary hypertension. METHODS: MRA of pulmonary arteries was acquired at 1.5T in 20 patients with pulmonary arterial hypertension and 21 healthy normotensive controls. 3D model-based image analysis software was used for automated segmentation of main, right and left pulmonary arteries (MPA, RPA and LPA). Volumes indexed to vessel length and mean, minimum and maximum diameters along the entire vessel course were assessed and corrected for body surface area (BSA). For comparison, diameters were also manually measured on axial reconstructions and double oblique multiplanar reformations. Analyses were performed by two cardiovascular radiologists, and by one radiologist again after 6 months. RESULTS: Mean volumes of MPA, RPA and LPA for patients/controls were 5508 ± 1236/3438 ± 749, 3522 ± 934/1664 ± 468 and 3093 ± 692/1812 ± 474 µl/(cm length x m2 BSA) (all p<0.001). Mean, minimum and maximum diameters along the entire vessel course were also significantly increased in patients compared to controls (all p<0.001). Intra- and interobserver agreement were excellent for both volume and diameter measurements using 3D segmentation (intraclass correlation coefficients 0.971-0.999, p<0.001). Area under the curve for predicting pulmonary hypertension using volume was 0.998 (95% confidence interval 0.990-1.0, p<0.001), compared to 0.967 using manually measured MPA diameter (95% confidence interval 0.910-1.0, p<0.001). CONCLUSIONS: Automated MRA-based 3D volumetry of central pulmonary arteries is feasible and demonstrated significantly increased volumes and diameters in patients with pulmonary arterial hypertension compared to healthy controls. Pulmonary artery volume may serve as a superior predictor for pulmonary hypertension compared to manual measurements on axial images but verification in a larger study population is warranted.

True four-dimensional analysis of thoracic aortic displacement and distension using model-based segmentation of computed tomography angiography.

Previous analyses of aortic displacement and distension using computed tomography angiography (CTA) were performed on double-oblique multi-planar reformations and did not consider through-plane motion. The aim of this study was to overcome this limitation by using a novel computational approach for the assessment of thoracic aortic displacement and distension in their true four-dimensional extent. Vessel segmentation with landmark tracking was executed on CTA of 24 patients without evidence of aortic disease. Distension magnitudes and maximum displacement vectors (MDV) including their direction were analyzed at 5 aortic locations: left coronary artery (COR), mid-ascending aorta (ASC), brachiocephalic trunk (BCT), left subclavian artery (LSA), descending aorta (DES). Distension was highest for COR (2.3 ± 1.2 mm) and BCT (1.7 ± 1.1 mm) compared with ASC, LSA, and DES (p < 0.005). MDV decreased from COR to LSA (p < 0.005) and was highest for COR (6.2 ± 2.0 mm) and ASC (3.8 ± 1.9 mm). Displacement was directed towards left and anterior at COR and ASC. Craniocaudal displacement at COR and ASC was 1.3 ± 0.8 and 0.3 ± 0.3 mm. At BCT, LSA, and DES no predominant displacement direction was observable. Vessel displacement and wall distension are highest in the ascending aorta, and ascending aortic displacement is primarily directed towards left and anterior. Craniocaudal displacement remains low even close to the left cardiac ventricle.

3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

INTRODUCTION: Native-MR angiography (N-MRA) is considered an imaging alternative to contrast enhanced MR angiography (CE-MRA) for patients with renal insufficiency. Lower intraluminal contrast in N-MRA often leads to failure of the segmentation process in commercial algorithms. This study introduces an in-house 3D model-based segmentation approach used to compare both sequences by automatic 3D lumen segmentation, allowing for evaluation of differences of aortic lumen diameters as well as differences in length comparing both acquisition techniques at every possible location. METHODS AND MATERIALS: Sixteen healthy volunteers underwent 1.5-T-MR Angiography (MRA). For each volunteer, two different MR sequences were performed, CE-MRA: gradient echo Turbo FLASH sequence and N-MRA: respiratory-and-cardiac-gated, T2-weighted 3D SSFP. Datasets were segmented using a 3D model-based ellipse-fitting approach with a single seed point placed manually above the celiac trunk. The segmented volumes were manually cropped from left subclavian artery to celiac trunk to avoid error due to side branches. Diameters, volumes and centerline length were computed for intraindividual comparison. For statistical analysis the Wilcoxon-Signed-Ranked-Test was used. RESULTS: Average centerline length obtained based on N-MRA was 239.0±23.4 mm compared to 238.6±23.5 mm for CE-MRA without significant difference (P=0.877). Average maximum diameter obtained based on N-MRA was 25.7±3.3 mm compared to 24.1±3.2 mm for CE-MRA (P<0.001). In agreement with the difference in diameters, volumes obtained based on N-MRA (100.1±35.4 cm(3)) were consistently and significantly larger compared to CE-MRA (89.2±30.0 cm(3)) (P<0.001). CONCLUSIONS: 3D morphometry shows highly similar centerline lengths for N-MRA and CE-MRA, but systematically higher diameters and volumes for N-MRA.

Globally optimal curvature-regularized fast marching for vessel segmentation.

We introduce a novel fast marching approach with curvature regularization for vessel segmentation. Since most vessels have a smooth path, curvature can be used to distinguish desired vessels from short cuts, which usually contain parts with high curvature. However, in previous fast marching approaches, curvature information is not available, so it cannot be used for regularization directly. Instead, usually length regularization is used under the assumption that shorter paths should also have a lower curvature. However, for vessel segmentation, this assumption often does not hold and leads to short cuts. We propose an approach, which integrates curvature regularization directly into the fast marching framework, independent of length regularization. Our approach is globally optimal, and numerical experiments on synthetic and real retina images show that our approach yields more accurate results than two previous approaches.