Coronary magnetic resonance angiography.

Coronary magnetic resonance angiography (MRA) is a powerful noninvasive technique with high soft-tissue contrast for the visualization of the coronary anatomy without X-ray exposure. Due to the small dimensions and tortuous nature of the coronary arteries, a high spatial resolution and sufficient volumetric coverage have to be obtained. However, this necessitates scanning times that are typically much longer than one cardiac cycle. By collecting image data during multiple RR intervals, one can successfully acquire coronary MR angiograms. However, constant cardiac contraction and relaxation, as well as respiratory motion, adversely affect image quality. Therefore, sophisticated motion-compensation strategies are needed. Furthermore, a high contrast between the coronary arteries and the surrounding tissue is mandatory. In the present article, challenges and solutions of coronary imaging are discussed, and results obtained in both healthy and diseased states are reviewed. This includes preliminary data obtained with state-of-the-art techniques such as steady-state free precession (SSFP), whole-heart imaging, intravascular contrast agents, coronary vessel wall imaging, and high-field imaging. Simultaneously, the utility of electron beam computed tomography (EBCT) and multidetector computed tomography (MDCT) for the visualization of the coronary arteries is discussed.

Computational anatomy for studying use-dependant brain plasticity.

In this article we provide a comprehensive literature review on the in vivo assessment of use-dependant brain structure changes in humans using magnetic resonance imaging (MRI) and computational anatomy. We highlight the recent findings in this field that allow the uncovering of the basic principles behind brain plasticity in light of the existing theoretical models at various scales of observation. Given the current lack of in-depth understanding of the neurobiological basis of brain structure changes we emphasize the necessity of a paradigm shift in the investigation and interpretation of use-dependent brain plasticity. Novel quantitative MRI acquisition techniques provide access to brain tissue microstructural properties (e.g., myelin, iron, and water content) in-vivo, thereby allowing unprecedented specific insights into the mechanisms underlying brain plasticity. These quantitative MRI techniques require novel methods for image processing and analysis of longitudinal data allowing for straightforward interpretation and causality inferences.

Contrast agent-enhanced, free-breathing, three-dimensional coronary magnetic resonance angiography.

For free-breathing, high-resolution, three-dimensional coronary magnetic resonance angiography (MRA), the use of intravascular contrast agents may be helpful for contrast enhancement between coronary blood and myocardium. In six patients, 0.1 mmol/kg of the intravascular contrast agent MS-325/AngioMARK was given intravenously followed by double-oblique, free-breathing, three-dimensional inversion-recovery coronary MRA with real-time navigator gating and motion correction. Contrast-enhanced, three-dimensional coronary MRA images were compared with images obtained with a T2 prepulse (T2Prep) without exogenous contrast. The contrast-enhanced images demonstrated a 69% improvement in the contrast-to-noise ratio (6.6 +/- 1.1 vs. 11.1 +/- 2.5; P < 0.01) compared with the T2Prep approach. By using the intravascular agent, extensive portions (> 80 mm) of the native left and right coronary system could be displayed consistently with sub-millimeter in-plane resolution. The intravascular contrast agent, MS-325/AngioMARK, leads to a considerable enhancement of the blood/muscle contrast for coronary MRA compared with T2Prep techniques. The clinical value of the agent remains to be defined in a larger patient series. J. Magn. Reson. Imaging 1999;10:790-799.

Wear of two artificial tooth materials in vivo: a 12-month pilot study.

STATEMENT OF PROBLEM: Wear of methacrylate artificial teeth resulting in vertical loss is a problem for both dentists and patients. PURPOSE: The purpose of this study was to quantify wear of artificial teeth in vivo and to relate it to subject and tooth variables. MATERIAL AND METHODS: Twenty-eight subjects treated with complete dentures received 2 artificial tooth materials (polymethyl methacrylate (PMMA)/double-cross linked PMMA fillers; 35%/59% (SR Antaris DCL, SR Postaris DCL); experimental 48%/46%). At baseline and after 12 months, impressions of the dentures were poured with improved stone. After laser scanning, the casts were superimposed and matched. Maximal vertical loss (mm) and volumetric loss (mm(3)) were calculated for each tooth and log-transformed to reduce variability. Volumetric loss was related to the occlusally active surface area. Linear mixed models were used to study the influence of the factors jaw, tooth, and material on adjusted (residual) wear values (alpha=.05). RESULTS: Due to drop outs (n=5) and unmatchable casts (n=3), 69% of all teeth were analyzed. Volumetric loss had a strong linear relationship to surface area (P<.001); this was less pronounced for vertical loss (P=.004). The factor showing the highest influence was the subject. Wear was tooth dependent (increasing from incisors to molars). However, these differences diminished once the wear rates were adjusted for occlusal area, and only a few remained significant (anterior versus posterior maxillary teeth). Another influencing factor was the age of the subject. CONCLUSIONS: Clinical wear of artificial teeth is higher than previously measured or expected. The presented method of analyzing wear of artificial teeth using a laser-scanning device seemed suitable.

Management of patient dose and image noise in routine pediatric CT abdominal examinations.

The aim was to propose a strategy for finding reasonable compromises between image noise and dose as a function of patient weight. Weighted CT dose index (CTDI(w)) was measured on a multidetector-row CT unit using CTDI test objects of 16, 24 and 32 cm in diameter at 80, 100, 120 and 140 kV. These test objects were then scanned in helical mode using a wide range of tube currents and voltages with a reconstructed slice thickness of 5 mm. For each set of acquisition parameter image noise was measured and the Rose model observer was used to test two strategies for proposing a reasonable compromise between dose and low-contrast detection performance: (1) the use of a unique noise level for all test object diameters, and (2) the use of a unique dose efficacy level defined as the noise reduction per unit dose. Published data were used to define four weight classes and an acquisition protocol was proposed for each class. The protocols have been applied in clinical routine for more than one year. CTDI(vol) values of 6.7, 9.4, 15.9 and 24.5 mGy were proposed for the following weight classes: 2.5-5, 5-15, 15-30 and 30-50 kg with image noise levels in the range of 10-15 HU. The proposed method allows patient dose and image noise to be controlled in such a way that dose reduction does not impair the detection of low-contrast lesions. The proposed values correspond to high- quality images and can be reduced if only high-contrast organs are assessed.

Differentiation of focal liver lesions: usefulness of parametric imaging with contrast-enhanced US.

Purpose: To evaluate whether parametric imaging with contrast material-enhanced ultrasonography (US) is superior to visual assessment for the differential diagnosis of focal liver lesions (FLLs). Materials and Methods: This study had institutional review board approval, and verbal patient informed consent was obtained. Between August 2005 and October 2008, 146 FLLs in 145 patients (63 women, 82 men; mean age, 62.5 years; age range, 22-89 years) were imaged with real-time low-mechanical-index contrast-enhanced US after a bolus injection of 2.4 mL of a second-generation contrast agent. Clips showing contrast agent uptake kinetics (including arterial, portal, and late phases) were recorded and subsequently analyzed off-line with dedicated image processing software. Analysis of the dynamic vascular patterns (DVPs) of lesions with respect to adjacent parenchyma allowed mapping DVP signatures on a single parametric image. Cine loops of contrast-enhanced US and results from parametric imaging of DVP were assessed separately by three independent off-site readers who classified each lesion as benign, malignant, or indeterminate. Sensitivity, specificity, accuracy, and positive and negative predictive values were calculated for both techniques. Interobserver agreement (κ statistics) was determined. Results: Sensitivities for visual interpretation of cine loops for the three readers were 85.0%, 77.9%, and 87.6%, which improved significantly to 96.5%, 97.3%, and 96.5% for parametric imaging, respectively (P < .05, McNemar test), while retaining high specificity (90.9% for all three readers). Accuracy scores of parametric imaging were higher than those of conventional contrast-enhanced US for all three readers (P < .001, McNemar test). Interobserver agreement increased with DVP parametric imaging compared with conventional contrast-enhanced US (change of κ from 0.54 to 0.99). Conclusion: Parametric imaging of DVP improves diagnostic performance of contrast-enhanced US in the differentiation between malignant and benign FLLs; it also provides excellent interobserver agreement.

Continuous arterial spin labeling of mouse cerebral blood flow using an actively-detuned two-coil system at 9.4T.

Among numerous magnetic resonance imaging (MRI) techniques, perfusion MRI provides insight into the passage of blood through the brain's vascular network non-invasively. Studying disease models and transgenic mice would intrinsically help understanding the underlying brain functions, cerebrovascular disease and brain disorders. This study evaluates the feasibility of performing continuous arterial spin labeling (CASL) on all cranial arteries for mapping murine cerebral blood flow at 9.4 T. We showed that with an active-detuned two-coil system, a labeling efficiency of 0.82 ± 0.03 was achieved with minimal magnetization transfer residuals in brain. The resulting cerebral blood flow of healthy mouse was 99 ± 26 mL/100g/min, in excellent agreement with other techniques. In conclusion, high magnetic fields deliver high sensitivity and allowing not only CASL but also other MR techniques, i.e. (1)H MRS and diffusion MRI etc, in studying murine brains.

Quantification of the local heartwall motion by magnetic resonance myocardial tagging.

Sophisticated magnetic resonance tagging techniques provide powerful tools for the non-invasive assessment of the local heartwall motion towards a deeper fundamental understanding of local heart function. For the extraction of motion data from the time series of magnetic resonance tagged images and for the visualization of the local heartwall motion a new image analysis procedure has been developed. New parameters have been derived which allows quantification of the motion patterns and are highly sensitive to any changes in these patterns. The new procedure has been applied for heart motion analysis in healthy volunteers and in patient collectives with different heart diseases. The achieved results are summarized and discussed.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Performance of a new gadolinium-based intravascular contrast agent in free-breathing inversion-recovery 3D coronary MRA.

In three-dimensional (3D) coronary magnetic resonance angiography (MRA), the in-flow contrast between the coronary blood and the surrounding myocardium is attenuated as compared to thin-slab two-dimensional (2D) techniques. The application of a gadolinium (Gd)-based intravascular contrast agent may provide an additional source of signal and contrast by reducing T(1blood) and supporting the visualization of more distal or branching segments of the coronary arterial tree. In six healthy adults, the left coronary artery (LCA) system was imaged pre- and postcontrast with a 0.075-mmol/kg bodyweight dose of the intravascular contrast agent B-22956. For imaging, an optimized free-breathing, navigator-gated and -corrected 3D inversion recovery (IR) sequence was used. For comparison, state-of-the-art baseline 3D coronary MRA with T(2) preparation for non-exogenous contrast enhancement was acquired. The combination of IR 3D coronary MRA, sophisticated navigator technology, and B-22956 allowed for an extensive visualization of the LCA system. Postcontrast, a significant increase in both the signal-to-noise ratio (SNR; 46%, P < 0.05) and contrast-to-noise ratio (CNR; 160%, P < 0.01) was observed, while vessel sharpness of the left anterior descending (LAD) artery and the left coronary circumflex (LCX) were improved by 20% (P < 0.05) and 18% (P < 0.05), respectively.

Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Model-based Segmentation and Image Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

For radiotherapy treatment planning of retinoblastoma inchildhood, Computed Tomography (CT) represents thestandard method for tumor volume delineation, despitesome inherent limitations. CT scan is very useful inproviding information on physical density for dosecalculation and morphological volumetric information butpresents a low sensitivity in assessing the tumorviability. On the other hand, 3D ultrasound (US) allows ahigh accurate definition of the tumor volume thanks toits high spatial resolution but it is not currentlyintegrated in the treatment planning but used only fordiagnosis and follow-up. Our ultimate goal is anautomatic segmentation of gross tumor volume (GTV) in the3D US, the segmentation of the organs at risk (OAR) inthe CT and the registration of both. In this paper, wepresent some preliminary results in this direction. Wepresent 3D active contour-based segmentation of the eyeball and the lens in CT images; the presented approachincorporates the prior knowledge of the anatomy by usinga 3D geometrical eye model. The automated segmentationresults are validated by comparing with manualsegmentations. Then, for the fusion of 3D CT and USimages, we present two approaches: (i) landmark-basedtransformation, and (ii) object-based transformation thatmakes use of eye ball contour information on CT and USimages.

Volume-targeted and whole-heart coronary magnetic resonance angiography using an intravascular contrast agent.

PURPOSE: To compare volume-targeted and whole-heart coronary magnetic resonance angiography (MRA) after the administration of an intravascular contrast agent. MATERIALS AND METHODS: Six healthy adult subjects underwent a navigator-gated and -corrected (NAV) free breathing volume-targeted cardiac-triggered inversion recovery (IR) 3D steady-state free precession (SSFP) coronary MRA sequence (t-CMRA) (spatial resolution = 1 x 1 x 3 mm(3)) and high spatial resolution IR 3D SSFP whole-heart coronary MRA (WH-CMRA) (spatial resolution = 1 x 1 x 2 mm(3)) after the administration of an intravascular contrast agent B-22956. Subjective and objective image quality parameters including maximal visible vessel length, vessel sharpness, and visibility of coronary side branches were evaluated for both t-CMRA and WH-CMRA. RESULTS: No significant differences (P = NS) in image quality were observed between contrast-enhanced t-CMRA and WH-CMRA. However, using an intravascular contrast agent, significantly longer vessel segments were measured on WH-CMRA vs. t-CMRA (right coronary artery [RCA] 13.5 +/- 0.7 cm vs. 12.5 +/- 0.2 cm; P < 0.05; and left circumflex coronary artery [LCX] 11.9 +/- 2.2 cm vs. 6.9 +/- 2.4 cm; P < 0.05). Significantly more side branches (13.3 +/- 1.2 vs. 8.7 +/- 1.2; P < 0.05) were visible for the left anterior descending coronary artery (LAD) on WH-CMRA vs. t-CMRA. Scanning time and navigator efficiency were similar for both techniques (t-CMRA: 6.05 min; 49% vs. WH-CMRA: 5.51 min; 54%, both P = NS). CONCLUSION: Both WH-CMRA and t-CMRA using SSFP are useful techniques for coronary MRA after the injection of an intravascular blood-pool agent. However, the vessel conspicuity for high spatial resolution WH-CMRA is not inferior to t-CMRA, while visible vessel length and the number of visible smaller-diameter vessels and side-branches are improved.

Baseline Results of an Acute Ischemic Stroke Registry Including Acute Multimodal Imaging (ASTRAL)

Background: The DEFUSE (n_74) and EPITHET (n_101) studies have in common that a baseline MRI was obtained prior to treatment (tPA in DEFUSE; tPA or placebo in EPITHET) in the 3-6 hour time-window. There were however important methodological differences between the studies. A standardized reanalysis of pooled data was undertaken to determine the effect of these differences on baseline characteristics and study outcomes. Methods: To standardize the studies 1) the DWI and PWI source images were reprocessed and segmented using automated image processing software (RAPID); 2) patients were categorized according to their baseline MRI profile as either Target Mismatch (PWITmax_6/DWI ratio_ 1.8 and an absolute mismatch _15mL), Malignant (DWI or PWITmax_10 lesion _ 100 mL), or No Mismatch. 3) favorable clinical response was defined as NIHSS score of 0-1 or a _8 points improvement on the NIHSSS at day 90. Results: Prior to standardization there was no difference in the proportion of Target Mismatch patients between EPITHET and DEFUSE (54% vs 49%, p_0.6), but the EPITHET study had more patients with the Malignant profile than DEFUSE (35% vs 9%, p_0.01) and fewer patients that had No Mismatch (11% vs 42%, p_0.01). These differences in baseline MRI profiles between EPITHET and DEFUSE were largely eliminated by standardized processing of PWI and DWI images with RAPID software (Target Mismatch 49% vs 48%; Malignant 15% vs 8%; No Mismatch 36% vs 25%; p_NS for all comparisons) Reperfusion was strongly associated with a favorable clinical response in mismatch patients (figure). This relationship was not affected by the standardization procedures (pooled odds ratio of 8.8 based on original data and 6.6 based on standardized data). Conclusion: Standardization of image analyses procedures in acute stroke is important as non-standardized techniques introduce significant variability in DWI and PWI imaging characteristics. Despite methodological differences, the DEFUSE and EPITHET studies show a consistent and robust association between reperfusion and favorable clinical response in Target Mismatch patients regardless of standardization. These data support an RCT of iv tPA in the 3-6 hour time-window for Target Mismatch patients identified using RAPID.