R.J. van der Geest

3-D active appearance models: segmentation of cardiac MR and ultrasound images

A model-based method for three-dimensional image segmentation was developed and its performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) images and echocardiographic temporal image sequences. Comprehensive design of a three-dimensional (3-D) active appearance model (AAM) is reported for the first time as an involved extension of the AAM framework introduced by Cootes et al. The models behavior is learned from manually traced segmentation examples during an automated training stage. Information about shape and image appearance of the cardiac structures is contained in a single model. This ensures a spatially and/or temporally consistent segmentation of three-dimensional cardiac images. The clinical potential of the 3-D AAM is demonstrated in short-axis cardiac MR images and four-chamber echocardiographic sequences. The methods performance was assessed by comparison with manually identified independent standards in 56 clinical MR and 64 clinical echo image sequences. The AAM method showed good agreement with the independent standard using quantitative indexes of border positioning errors, endo- and epicardial volumes, and left ventricular mass. In MR, the endocardial volumes, epicardial volumes, and left ventricular wall mass correlation coefficients between manual and AAM were R/sup 2/=0.94,0.97,0.82, respectively. For echocardiographic analysis, the area correlation was R/sup 2/=0.79. The AAM method shows high promise for successful application to MR and echocardiographic image analysis in a clinical setting.

Evidence for a vascular factor in migraine

It has been suggested that migraine is caused by neural dysfunction without involvement of vasodilatation. Because dismissal of vascular mechanisms seemed premature, we examined diameter of extra‐ and intracranial vessels in migraine without aura patients.

A multiresolution image segmentation technique based on pyramidal segmentation and fuzzy clustering

In this paper, an unsupervised image segmentation technique is presented, which combines pyramidal image segmentation with the fuzzy c-means clustering algorithm. Each layer of the pyramid is split into a number of regions by a root labeling technique, and then fuzzy c-means is used to merge the regions of the layer with the highest image resolution. A cluster validity functional is used to find the optimal number of objects automatically. Segmentation of a number of synthetic as well as clinical images is illustrated and two fully automatic segmentation approaches are evaluated, which determine the left ventricular volume (LV) in 140 cardiovascular magnetic resonance (MR) images. First fuzzy c-means is applied without pyramids. In the second approach the regions generated by pyramidal segmentation are merged by fuzzy c-means. The correlation coefficients of manually and automatically defined LV lumen of all 140 and 20 end-diastolic images were equal to 0.86 and 0.79, respectively, when images were segmented with fuzzy c-means alone. These coefficients increased to 0.90 and 0.93 when the pyramidal segmentation was combined with fuzzy c-means. This method can be applied to any dimensional representation and at any resolution level of an image series. The evaluation study shows good performance in detecting LV lumen in MR images.

Preservation of Left Ventricular Function and Attenuation of Remodeling After Transplantation of Human Epicardium-Derived Cells Into the Infarcted Mouse Heart

Background— Proper development of compact myocardium, coronary vessels, and Purkinje fibers depends on the presence of epicardium-derived cells (EPDCs) in embryonic myocardium. We hypothesized that adult human EPDCs might partly reactivate their embryonic program when transplanted into ischemic myocardium and improve cardiac performance after myocardial infarction. Methods and Results— EPDCs were isolated from human adult atrial tissue. Myocardial infarction was created in immunodeficient mice, followed by intramyocardial injection of 4×105 enhanced green fluorescent protein–labeled EPDCs (2-week survival, n=22; 6-week survival, n=15) or culture medium (n=24 and n=18, respectively). Left ventricular function was assessed with a 9.4T animal MRI unit. Ejection fraction was similar between groups on day 2 but was significantly higher in the EPDC-injected group at 2 weeks (short term), as well as after long-term survival at 6 weeks. End-systolic and end-diastolic volumes were significantly smaller in the EPDC-injected group than in the medium-injected group at all ages evaluated. At 2 weeks, vascularization was significantly increased in the EPDC-treated group, as was wall thickness, a development that might be explained by augmented DNA-damage repair activity in the infarcted area. Immunohistochemical analysis showed massive engraftment of injected EPDCs at 2 weeks, with expression of α-smooth muscle actin, von Willebrand factor, sarcoplasmic reticulum Ca2+-ATPase, and voltage-gated sodium channel (α-subunit; SCN5a). EPDCs were negative for cardiomyocyte markers. At 6-weeks survival, wall thickness was still increased, but only a few EPDCs could be detected. Conclusions— After transplantation into ischemic myocardium, adult human EPDCs preserve cardiac function and attenuate ventricular remodeling. Autologous human EPDCs are promising candidates for clinical application in infarcted hearts.

Automatic segmentation and plaque characterization in atherosclerotic carotid artery MR images

In vivo MRI provides a means to non-invasively image and assess the morphological features of atherosclerotic carotid arteries. To assess quantitatively the degree of vulnerability and the type of plaque, the contours of the lumen, outer boundary of the vessel wall and plaque components, need to be traced. Currently this is done manually, which is time-consuming and sensitive to inter- and intra-observer variability. The goal of this work was to develop an automated contour detection technique for tracing the lumen, outer boundary and plaque contours in carotid MR short-axis black-blood images. Seventeen patients with carotid atherosclerosis were imaged using high-resolution in vivo MRI, generating a total of 50 PD- and T1-weighted MR images. These images were automatically segmented using the algorithm presented in this work, which combines model-based segmentation and fuzzy clustering to detect the vessel wall, lumen and lipid core boundaries. The results demonstrate excellent correspondence between automatic and manual area measurements for lumen (r=0.92) and outer (r=0.91), and acceptable correspondence for fibrous cap thickness (r=0.71). Though further optimization is required, our algorithm is a powerful tool for automatic detection of lumen and outer boundaries, and characterization of plaque in atherosclerotic vessels.

Dilation by CGRP of middle meningeal artery and reversal by sumatriptan in normal volunteers

Background: Calcitonin gene–related peptide (CGRP) plays a fundamental role in the pathophysiology of neurovascular headaches. CGRP infusion causes headache and dilation of cranial vessels. However, it is unknown to what extent CGRP-induced vasodilation contributes to immediate head pain and whether the migraine-specific abortive drug sumatriptan, a 5-hydroxytryptamine 1B/1D agonist, inhibits CGRP-induced immediate vasodilation and headache. Methods: We performed a double-blind, randomized, placebo-controlled, crossover study in 18 healthy volunteers. We recorded circumference changes of the middle meningeal artery (MMA) and middle cerebral artery (MCA) using magnetic resonance angiography before and after infusion (20 minutes) of 1.5 μg/min human αCGRP or placebo (isotonic saline) as well as after a 6-mg sumatriptan subcutaneous injection. Results: Compared with placebo, CGRP caused significant dilation of MMA (p = 0.006) and no dilation of MCA (p = 0.69). Sumatriptan caused a marked contraction of MMA (15%–25.2%) and marginal contraction of MCA (3.9% to 5.3%). Explorative analysis revealed that sumatriptan had a more selective action on MMA compared with MCA on the CGRP day (p < 0.0001) and on the placebo day (p = 0.007). Conclusion: These data suggest that exogenous CGRP dilates extracranial vessels and not intracranial, and that sumatriptan exerts part of its antinociceptive action by constricting MMA and not MCA. Classification of evidence: This study provides Class I evidence that IV GCRP causes dilation of the MMA but not the MCA in healthy volunteers, and that sumatriptan reverses the dilation of the MMA caused by CGRP.

Fully Automated Motion Correction in First-Pass Myocardial Perfusion MR Image Sequences

This paper presents a novel method for registration of cardiac perfusion magnetic resonance imaging (MRI). The presented method is capable of automatically registering perfusion data, using independent component analysis (ICA) to extract physiologically relevant features together with their time-intensity behavior. A time-varying reference image mimicking intensity changes in the data of interest is computed based on the results of that ICA. This reference image is used in a two-pass registration framework. Qualitative and quantitative validation of the method is carried out using 46 clinical quality, short-axis, perfusion MR datasets comprising 100 images each. Despite varying image quality and motion patterns in the evaluation set, validation of the method showed a reduction of the average right ventricle (LV) motion from 1.26plusmn0.87 to 0.64plusmn0.46 pixels. Time-intensity curves are also improved after registration with an average error reduced from 2.65plusmn7.89% to 0.87plusmn3.88% between registered data and manual gold standard. Comparison of clinically relevant parameters computed using registered data and the manual gold standard show a good agreement. Additional tests with a simulated free-breathing protocol showed robustness against considerable deviations from a standard breathing protocol. We conclude that this fully automatic ICA-based method shows an accuracy, a robustness and a computation speed adequate for use in a clinical environment.

The influence of through-plane motion on left ventricular volumes measured by magnetic resonance imaging: implications for image acquisition and analysis.

In the evaluation of the left ventricular (LV) function using magnetic resonance imaging (MRI), a stack of parallel short-axis (SA) cine images is acquired that covers the whole LV. The aim of this study is to quantify the contribution to the LV volume parameters, provided by the most basal image plane that shows the LV wall only in end diastole (ED) but not in end systole (ES). In 57 healthy volunteers (31 men, mean body surface area 1.87 m2), a complete set of parallel SA images was acquired (10-mm slice distance) by breathhold segmented k-space cine MRI (7 ky lines per beat). The LV end-diastolic volume (EDV), stroke volume (SV), ejection fraction (EF), and cardiac output (CO) were determined by slice summation. Calculations were performed both with and without inclusion of the most basal slice. With inclusion of the most basal slice, all parameters were significantly (p < 0.001) larger compared with the values obtained by excluding this slice. EDV was 134 +/- 29 ml versus 113 +/- 26 ml; SV was 93 +/- 18 ml versus 72 +/- 16 ml; EF was 70 +/- 4% versus 64 +/- 4%; and CO was 5.3 +/- 1.4 l/min versus 4.1 +/- 1.1 l/min. The inclusion of the most basal slice leads to significantly larger values of LV volume parameters. Thus, this most basal SA image slice should be included in calculating the EDV. Whether or not this basal SA slice also contributes to the ES volume should be decided by using anatomical criteria on the ES image. The projection line onto the ES image of a long-axis view provides an additional criterion.

MRI-derived left ventricular function parameters and mass in healthy young adults: Relation with gender and body size

Purpose: To obtain normal values of left ventricular (LV) end-diastolic volume (EDV), stroke volume (SV), cardiac output (CO) and LV mass, in relation to gender, weight (W), length (L) and body surface area (BSA). Methods: Sixty-one healthy volunteers (32 male, 22.4 ± 2.2 years) were examined, weight was 70.9 ± 12.2 kg, length was 1.78 ± 0.09 m, BSA was 1.88 ± 0.19 m2. Segmented k-space breathhold cine MRI was used to obtain a stack of parallel short-axis images, from which LV volumes and end-diastolic mass were derived by slice summation. Four different body size indices were studied: W, L, L2 and BSA. Results: After indexing for L, L2 and BSA, the gender differences in all LV parameters are still persisting. After indexing for W, gender differences persist for EDV and EDM, but are no longer observed for SV and CO. Separate regression analyses for males and females were performed. EDV, SV, CO and EDM correlated significantly with each body size index, both in males and in females. L or BSA were in general better predictors for LV parameters than W. Linear regression equations of EDV (ml) vs. L(m) were for males: EDV = 275 × L − 359 and for females: EDV = 190 × L − 215. Equations of SV(ml) vs. L were for males: SV = 186 × L − 237 and for females: SV = 118 × L − 121. Equations of LV mass(g) vs. L were for males: Mass = 175 × L − 179 and for females: Mass = 65.8 × L − 10.9. Conclusion: Most gender differences in LV parameters remain even after correction for body size indices. Normal reference values for LV parameters are given in relation to body size indices, by calculating regression coefficients separately for males and females. These normal values serve to obtain more accurate reference values for a patient with given gender, weight and length, and thus to improve the differentiation between normal and abnormal LV parameters.

Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study.

PURPOSE Computed tomography angiography (CTA) is increasingly used for the diagnosis of coronary artery disease (CAD). However, CTA is not commonly used for the assessment of ventricular and atrial function, although functional information extracted from CTA data is expected to improve the diagnostic value of the examination. In clinical practice, the extraction of ventricular and atrial functional information, such as stroke volume and ejection fraction, requires accurate delineation of cardiac chambers. In this paper, we investigated the accuracy and robustness of cardiac chamber delineation using a multiatlas based segmentation method on multicenter and multivendor CTA data. METHODS A fully automatic multiatlas based method for segmenting the whole heart (i.e., the outer surface of the pericardium) and cardiac chambers from CTA data is presented and evaluated. In the segmentation approach, eight atlas images are registered to a new patients CTA scan. The eight corresponding manually labeled images are then propagated and combined using a per voxel majority voting procedure, to obtain a cardiac segmentation. RESULTS The method was evaluated on a multicenter/multivendor database, consisting of (1) a set of 1380 Siemens scans from 795 patients and (2) a set of 60 multivendor scans (Siemens, Philips, and GE) from different patients, acquired in six different institutions worldwide. A leave-one-out 3D quantitative validation was carried out on the eight atlas images; we obtained a mean surface-to-surface error of 0.94 +/- 1.12 mm and an average Dice coefficient of 0.93 was achieved. A 2D quantitative evaluation was performed on the 60 multivendor data sets. Here, we observed a mean surface-to-surface error of 1.26 +/- 1.25 mm and an average Dice coefficient of 0.91 was achieved. In addition to this quantitative evaluation, a large-scale 2D and 3D qualitative evaluation was performed on 1380 and 140 images, respectively. Experts evaluated that 49% of the 1380 images were very accurately segmented (below 1 mm error) and that 29% were accurately segmented (error between 1 and 3 mm), which demonstrates the robustness of the presented method. CONCLUSIONS A fully automatic method for whole heart and cardiac chamber segmentation was presented and evaluated using multicenter/multivendor CTA data. The accuracy and robustness of the method were demonstrated by successfully applying the method to 1420 multicenter/ multivendor data sets.