Quantifying aortic valve regurgitation in patients with congenital aortic valve disease by 2D and 4D flow magnetic resonance analysis.

BACKGROUND: In congenital aortic valve disease, quantifying aortic regurgitation (AR) varies by the measurement site. Our study aimed to identify the optimal site for AR assessment using 2D and 4D MR flow measurements, with a focus on vortices. METHODS: We retrospectively analysed 31 patients with congenital aortic valve disease, performing 2D and 4D MR flow measurements at the aortic valve, sinotubular junction (STJ), ascending aorta (AAo), and using midpulmonary artery measurements as a reference. We assessed percentage AR and net forward volumes, calculated linear correlations, and plotted Bland-Altman plots. Net forward flow at all aortic sites were correlated with the main pulmonary artery. Differences in AR between 2D and 4D flows were linked to vortices detected by 4D streamlines. RESULTS: The best agreement in % AR between 2D and 4D flows was at the aortic valve (mean difference 4D2D -2.9%, limits of agreement 8.7% to -14.3%; r2 = 0.7). Correlations weakened at STJ and AAo. Vortices in the ascending aorta led to AR overestimation in 2D measurements. Net forward flow at the aortic valve by 4D flow correlated closer with main pulmonary artery than did 2D flow. (Mean difference for 2D and 4D MR flow 7.5 ml and 4.2 ml, respectively). CONCLUSIONS: For congenital aortic valve disease, the most accurate AR quantification occurs at the aortic valve using 2D and 4D MR flow. Notably, vortices in the ascending aorta can result in AR overestimation with 2D MR flow.

Interrelation Between Cerebrospinal Fluid Pressure, Intracranial Morphology and Venous Hemodynamics Studied by 4D Flow MRI.

PURPOSE: To quantify the effects of CSF pressure alterations on intracranial venous morphology and hemodynamics in idiopathic intracranial hypertension (IIH) and spontaneous intracranial hypotension (SIH) and assess reversibility when the underlying cause is resolved. METHODS: We prospectively examined venous volume, intracranial venous blood flow and velocity, including optic nerve sheath diameter (ONSD) as a noninvasive surrogate of CSF pressure changes in 11 patients with IIH, 11 age-matched and sex-matched healthy controls and 9 SIH patients, before and after neurosurgical closure of spinal dural leaks. We applied multiparametric MRI including 4D flow MRI, time-of-flight (TOF) and T2-weighted half-Fourier acquisition single-shot turbo-spin echo (HASTE). RESULTS: Sinus volume overlapped between groups at baseline but decreased after treatment of intracranial hypotension (p = 0.067) along with a significant increase of ONSD (p = 0.003). Blood flow in the middle and dorsal superior sagittal sinus was remarkably lower in patients with higher CSF pressure (i.e., IIH versus controls and SIH after CSF leak closure) but blood flow velocity was comparable cross-sectionally between groups and longitudinally in SIH. CONCLUSION: We were able to demonstrate the interaction of CSF pressure, venous volumetry, venous hemodynamics and ONSD using multiparametric brain MRI. Closure of CSF leaks in SIH patients resulted in symptoms suggestive of increased intracranial pressure and caused a subsequent decrease of intracranial venous volume and of blood flow within the superior sagittal sinus while ONSD increased. In contrast, blood flow parameters from 4D flow MRI did not discriminate IIH, SIH and controls as hemodynamics at baseline overlapped at most vessel cross-sections.

A simulation-based phantom model for generating synthetic mitral valve image data-application to MRI acquisition planning.

PURPOSE: Numerical phantom methods are widely used in the development of medical imaging methods. They enable quantitative evaluation and direct comparison with controlled and known ground truth information. Cardiac magnetic resonance has the potential for a comprehensive evaluation of the mitral valve (MV). The goal of this work is the development of a numerical simulation framework that supports the investigation of MRI imaging strategies for the mitral valve. METHODS: We present a pipeline for synthetic image generation based on the combination of individual anatomical 3D models with a position-based dynamics simulation of the mitral valve closure. The corresponding images are generated using modality-specific intensity models and spatiotemporal sampling concepts. We test the applicability in the context of MRI imaging strategies for the assessment of the mitral valve. Synthetic images are generated with different strategies regarding image orientation (SAX and rLAX) and spatial sampling density. RESULTS: The suitability of the imaging strategy is evaluated by comparing MV segmentations against ground truth annotations. The generated synthetic images were compared to ones acquired with similar parameters, and the result is promising. The quantitative analysis of annotation results suggests that the rLAX sampling strategy is preferable for MV assessment, reaching accuracy values that are comparable to or even outperform literature values. CONCLUSION: The proposed approach provides a valuable tool for the evaluation and optimization of cardiac valve image acquisition. Its application to the use case identifies the radial image sampling strategy as the most suitable for MV assessment through MRI.

Virtual reality in cardiac interventions-New tools or new toys?

Improvementsin medical imaging and a steady increase in computing power are leading to new possibilities in the field of cardiovascular interventions. Interventions can be planned in advance in greater detail, even to the point of simulating procedures. Nevertheless, all techniques are at an early stage of development. It is of utmost importance that tools, especially if they can be used as decision support are intensively validated and their accuracy is demonstrated. In our commentary, we summarize current techniques for impprovements in planning and guiding of procedures, but also critically discuss the downsides of these techniques. Following the work of Kenichi and colleagues, we also discuss necessary steps in advancing new tools and techniques, particularly as they are used in routine clinical practice. We also discuss the role of artificial intelligence, which could play a crucial role in this context in the future.

Fully automated quantification of in vivo viscoelasticity of prostate zones using magnetic resonance elastography with Dense U-net segmentation.

Magnetic resonance elastography (MRE) for measuring viscoelasticity heavily depends on proper tissue segmentation, especially in heterogeneous organs such as the prostate. Using trained network-based image segmentation, we investigated if MRE data suffice to extract anatomical and viscoelastic information for automatic tabulation of zonal mechanical properties of the prostate. Overall, 40 patients with benign prostatic hyperplasia (BPH) or prostate cancer (PCa) were examined with three magnetic resonance imaging (MRI) sequences: T2-weighted MRI (T2w), diffusion-weighted imaging (DWI), and MRE-based tomoelastography, yielding six independent sets of imaging data per patient (T2w, DWI, apparent diffusion coefficient, MRE magnitude, shear wave speed, and loss angle maps). Combinations of these data were used to train Dense U-nets with manually segmented masks of the entire prostate gland (PG), central zone (CZ), and peripheral zone (PZ) in 30 patients and to validate them in 10 patients. Dice score (DS), sensitivity, specificity, and Hausdorff distance were determined. We found that segmentation based on MRE magnitude maps alone (DS, PG: 0.93 ± 0.04, CZ: 0.95 ± 0.03, PZ: 0.77 ± 0.05) was more accurate than magnitude maps combined with T2w and DWI_b (DS, PG: 0.91 ± 0.04, CZ: 0.91 ± 0.06, PZ: 0.63 ± 0.16) or T2w alone (DS, PG: 0.92 ± 0.03, CZ: 0.91 ± 0.04, PZ: 0.65 ± 0.08). Automatically tabulated MRE values were not different from ground-truth values (P>0.05). In conclusion, MRE combined with Dense U-net segmentation allows tabulation of quantitative imaging markers without manual analysis and independent of other MRI sequences and can thus contribute to PCa detection and classification.

Cascaded neural network-based CT image processing for aortic root analysis.

PURPOSE: Careful assessment of the aortic root is paramount to select an appropriate prosthesis for transcatheter aortic valve implantation (TAVI). Relevant information about the aortic root anatomy, such as the aortic annulus diameter, can be extracted from pre-interventional CT. In this work, we investigate a neural network-based approach for segmenting the aortic root as a basis for obtaining these parameters. METHODS: To support valve prosthesis selection, geometric measures of the aortic root are extracted from the patient's CT scan using a cascade of convolutional neural networks (CNNs). First, the image is reduced to the aortic root, valve, and left ventricular outflow tract (LVOT); within that subimage, the aortic valve and ascending aorta are segmented; and finally, the region around the aortic annulus. From the segmented annulus region, we infer the annulus orientation using principal component analysis (PCA). The area-derived diameter of the annulus is approximated based on the segmentation of the aortic root and LVOT and the plane orientation resulting from the PCA. RESULTS: The cascade of CNNs was trained using 90 expert-annotated contrast-enhanced CT scans routinely acquired for TAVI planning. Segmentation of the aorta and valve within the region of interest achieved an F1 score of 0.94 on the test set of 36 patients. The area-derived diameter within the annulus region was determined with a mean error below 2 mm between the automatic measurement and the diameter derived from annotations. The calculated diameters and resulting errors are comparable to published results of alternative approaches. CONCLUSIONS: The cascaded neural network approach enabled the assessment of the aortic root with a relatively small training set. The processing time amounts to 30 s per patient, facilitating time-efficient, reproducible measurements. An extended training data set, including different levels of calcification or special cases (e.g., pre-implanted valves), could further improve this method's applicability and robustness.

CARDIOKIN1: Computational Assessment of Myocardial Metabolic Capability in Healthy Controls and Patients With Valve Diseases.

BACKGROUND: Many heart diseases can result in reduced pumping capacity of the heart muscle. A mismatch between ATP demand and ATP production of cardiomyocytes is one of the possible causes. Assessment of the relation between myocardial ATP production (MVATP) and cardiac workload is important for better understanding disease development and choice of nutritional or pharmacologic treatment strategies. Because there is no method for measuring MVATP in vivo, the use of physiology-based metabolic models in conjunction with protein abundance data is an attractive approach. METHOD: We developed a comprehensive kinetic model of cardiac energy metabolism (CARDIOKIN1) that recapitulates numerous experimental findings on cardiac metabolism obtained with isolated cardiomyocytes, perfused animal hearts, and in vivo studies with humans. We used the model to assess the energy status of the left ventricle of healthy participants and patients with aortic stenosis and mitral valve insufficiency. Maximal enzyme activities were individually scaled by means of protein abundances in left ventricle tissue samples. The energy status of the left ventricle was quantified by the ATP consumption at rest (MVATP[rest]), at maximal workload (MVATP[max]), and by the myocardial ATP production reserve, representing the span between MVATP(rest) and MVATP(max). RESULTS: Compared with controls, in both groups of patients, MVATP(rest) was increased and MVATP(max) was decreased, resulting in a decreased myocardial ATP production reserve, although all patients had preserved ejection fraction. The variance of the energetic status was high, ranging from decreased to normal values. In both patient groups, the energetic status was tightly associated with mechanic energy demand. A decrease of MVATP(max) was associated with a decrease of the cardiac output, indicating that cardiac functionality and energetic performance of the ventricle are closely coupled. CONCLUSIONS: Our analysis suggests that the ATP-producing capacity of the left ventricle of patients with valvular dysfunction is generally diminished and correlates positively with mechanical energy demand and cardiac output. However, large differences exist in the energetic state of the myocardium even in patients with similar clinical or image-based markers of hypertrophy and pump function. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03172338 and NCT04068740.

Interactive editing of virtual chordae tendineae for the simulation of the mitral valve in a decision support system.

PURPOSE: Decision support systems for mitral valve disease are an important step toward personalized surgery planning. A simulation of the mitral valve apparatus is required for decision support. Building a model of the chordae tendineae is an essential component of a mitral valve simulation. Due to image quality and artifacts, the chordae tendineae cannot be reliably detected in medical imaging. METHODS: Using the position-based dynamics framework, we are able to realistically simulate the opening and closing of the mitral valve. Here, we present a heuristic method for building an initial chordae model needed for a successful simulation. In addition to the heuristic, we present an interactive editor to refine the chordae model and to further improve pathology reproduction as well as geometric approximation of the closed valve. RESULTS: For evaluation, five mitral valves were reconstructed based on image sequences of patients scheduled for mitral valve surgery. We evaluated the approximation of the closed valves using either just the heuristic chordae model or a manually refined model. Using the manually refined models, prolapse was correctly reproduced in four of the five cases compared to two of the five cases when using the heuristic. In addition, using the editor improved the approximation in four cases. CONCLUSIONS: Our approach is suitable to create realistically parameterized mitral valve apparatus reconstructions for the simulation of normally and abnormally closing valves in a decision support system.

Time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI) reveals altered blood flow patterns in the ascending aorta of patients with valve-sparing aortic root replacement.

OBJECTIVE: The aim of this study was to compare aortic flow patterns in patients after David valve-sparing aortic root replacement with physiologically shaped sinus prostheses or conventional tube grafts in healthy volunteers. METHODS: Twelve patients with sinus prostheses (55 ± 15 years), 6 patients with tube grafts (58 ± 12 years), 12 age-matched, healthy volunteers (55 ± 6 years), and 6 young, healthy volunteers (25 ± 3 years) were examined with time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI). Primary and secondary helical, as well as vortical flow patterns, were evaluated. Aortic arch anatomy as a flow influencing factor was determined. RESULTS: Compared with volunteers, both sinus prostheses and tube grafts developed more than 4 times as many secondary flow patterns in the ascending aorta (sinus prostheses n = 1.6 ± 0.8; tube grafts n = 1.3 ± 0.6; age-matched, healthy volunteers n = 0.3 ± 0.5; young, healthy volunteers n = 0; P ≤ .012) associated with a kinking of the prosthesis itself or at its distal anastomosis. As opposed to round aortic arches in volunteers (n = 16/18), cubic or gothic-shaped arches predominated in patients (n = 16/18, P < .001). In all but 3 volunteers, 2 counter-rotating helices were confirmed in the ascending aorta and were defined as a primary flow pattern. This primary flow pattern did not develop in patients who underwent valve-sparing aortic root replacement. CONCLUSIONS: In patients after valve-sparing aortic root replacement, there was an increased number of secondary flow patterns in the ascending aorta. This seems to be related to surgically altered aortic geometry with kinking. Because flow alterations are known to affect wall shear stress, there seems to be an increased risk for vessel wall remodeling. Compared with previous 4D Flow MRI studies, primary flow patterns in the ascending aorta in healthy subjects were confirmed to be more complex. This underlines the importance of thorough examination of 4D Flow MRI data.

Combining position-based dynamics and gradient vector flow for 4D mitral valve segmentation in TEE sequences.

PURPOSE: For planning and guidance of minimally invasive mitral valve repair procedures, 3D+t transesophageal echocardiography (TEE) sequences are acquired before and after the intervention. The valve is then visually and quantitatively assessed in selected phases. To enable a quantitative assessment of valve geometry and pathological properties in all heart phases, as well as the changes achieved through surgery, we aim to provide a new 4D segmentation method. METHODS: We propose a tracking-based approach combining gradient vector flow (GVF) and position-based dynamics (PBD). An open-state surface model of the valve is propagated through time to the closed state, attracted by the GVF field of the leaflet area. The PBD method ensures topological consistency during deformation. For evaluation, one expert in cardiac surgery annotated the closed-state leaflets in 10 TEE sequences of patients with normal and abnormal mitral valves, and defined the corresponding open-state models. RESULTS: The average point-to-surface distance between the manual annotations and the final tracked model was [Formula: see text]. Qualitatively, four cases were satisfactory, five passable and one unsatisfactory. Each sequence could be segmented in 2-6 min. CONCLUSION: Our approach enables to segment the mitral valve in 4D TEE image data with normal and pathological valve closing behavior. With this method, in addition to the quantification of the remaining orifice area, shape and dimensions of the coaptation zone can be analyzed and considered for planning and surgical result assessment.

User-dependent variability in mitral valve segmentation and its impact on CFD-computed hemodynamic parameters.

PURPOSE: While novel tools for segmentation of the mitral valve are often based on automatic image processing, they mostly require manual interaction by a proficient user. Those segmentations are essential for numerical support of mitral valve treatment using computational fluid dynamics, where the reconstructed geometry is incorporated into a simulation domain. To quantify the uncertainty and reliability of hemodynamic simulations, it is crucial to examine the influence of user-dependent variability in valve segmentation. METHODS: Previously, the inter-user variability of landmarks in mitral valve segmentation was investigated. Here, the inter-user variability of geometric parameters of the mitral valve, projected orifice area (OA) and projected annulus area (AA), is investigated for 10 mitral valve geometries, each segmented by three users. Furthermore, the propagation of those variations into numerically calculated hemodynamics, i.e., the blood flow velocity, was investigated. RESULTS: Among the three geometric valve parameters, AA was least user-dependent. Almost all deviations to the mean were below 10%. Larger variations were observed for OA. Variations observed for the numerically calculated hemodynamics were in the same order of magnitude as those of geometric parameters. No correlation between variation of geometric parameters and variation of calculated hemodynamic parameters was found. CONCLUSION: Errors introduced due to the user-dependency were of the same size as the variations of calculated hemodynamics. The variation was thereby of the same scale as deviations in clinical measurements of blood flow velocity using Doppler echocardiography. Since no correlation between geometric and hemodynamic uncertainty was found, further investigation of the complex relationship between anatomy, leaflet shape and flow is necessary.

Virtual downsizing for decision support in mitral valve repair.

PURPOSE: Various options are available for the treatment of mitral valve insufficiency, including reconstructive approaches such as annulus correction through ring implants. The correct choice of general therapy and implant is relevant for an optimal outcome. Additional to guidelines, decision support systems (DSS) can provide decision aid by means of virtual intervention planning and predictive simulations. Our approach on virtual downsizing is one of the virtual intervention tools that are part of the DSS workflow. It allows for emulating a ring implantation based on patient-specific lumen geometry and vendor-specific implants. METHODS: Our approach is fully automatic and relies on a lumen mask and an annulus contour as inputs. Both are acquired from previous DSS workflow steps. A virtual surface- and contour-based model of a vendor-specific ring design (26-40 mm) is generated. For each case, the ring geometry is positioned with respect to the original, patient-specific annulus and additional anatomical landmarks. The lumen mesh is parameterized to allow for a vertex-based deformation with respect to the user-defined annulus. Derived from post-interventional observations, specific deformation schemes are applied to atrium and ventricle and the lumen mesh is altered with respect to the ring location. RESULTS: For quantitative evaluation, the surface distance between the deformed lumen mesh and segmented post-operative echo lumen close to the annulus was computed for 11 datasets. The results indicate a good agreement. An arbitrary subset of six datasets was used for a qualitative evaluation of the complete lumen. Two domain experts compared the deformed lumen mesh with post-interventional echo images. All deformations were deemed plausible. CONCLUSION: Our approach on virtual downsizing allows for an automatic creation of plausible lumen deformations. As it takes only a few seconds to generate results, it can be added to a virtual intervention toolset without unnecessarily increasing the pipeline complexity.

Extraction of open-state mitral valve geometry from CT volumes.

PURPOSE: The importance of mitral valve therapies is rising due to an aging population. Visualization and quantification of the valve anatomy from image acquisitions is an essential component of surgical and interventional planning. The segmentation of the mitral valve from computed tomography (CT) acquisitions is challenging due to high variation in appearance and visibility across subjects. We present a novel semi-automatic approach to segment the open-state valve in 3D CT volumes that combines user-defined landmarks to an initial valve model which is automatically adapted to the image information, even if the image data provide only partial visibility of the valve. METHODS: Context information and automatic view initialization are derived from segmentation of the left heart lumina, which incorporates topological, shape and regional information. The valve model is initialized with user-defined landmarks in views generated from the context segmentation and then adapted to the image data in an active surface approach guided by landmarks derived from sheetness analysis. The resulting model is refined by user landmarks. RESULTS: For evaluation, three clinicians segmented the open valve in 10 CT volumes of patients with mitral valve insufficiency. Despite notable differences in landmark definition, the resulting valve meshes were overall similar in appearance, with a mean surface distance of [Formula: see text] mm. Each volume could be segmented in 5-22 min. CONCLUSIONS: Our approach enables an expert user to easily segment the open mitral valve in CT data, even when image noise or low contrast limits the visibility of the valve.

Development of a modeling pipeline for the prediction of hemodynamic outcome after virtual mitral valve repair using image-based CFD.

PURPOSE: Severe mitral valve regurgitation can either be treated by a replacement or a repair of the valve. The latter is recommended due to lower perioperative mortality and better long-term survival. On the other hand, recurrence rates after mitral valve repair are high compared to those after replacements and the repair intervention can cause induced mitral valve stenosis. So far, there are no methods to predict the hemodynamic outcome of a chosen treatment or to compare different treatment options in advance. To overcome this, diastolic mitral valve hemodynamics are simulated using computational fluid dynamics after different virtual treatments of the valve. METHODS: The left ventricular geometry of one patient was reconstructed using trans-esophageal echocardiography and computed tomography data. Pre-op hemodynamics are simulated using a referenced wall model to avoid expansive modeling of wall motion. Subsequently, the flow structures are compared to in vivo measurements. After manipulating the patient-specific geometry in order to mimic a restrictive mitral annuloplasty as well as a MitraClip intervention, hemodynamics results are calculated. RESULTS: Good agreements exist between calculated pre-op hemodynamics and in vivo measurements. The virtual annuloplasty did not result in any remarkable change of hemodynamics. Neither the pressure drop nor the velocity field showed strong differences. In contrast, the virtual MitraClip intervention led to a complete change in blood flow structures as well as an elevated pressure drop across the valve. CONCLUSION: The presented approach allows fast simulation of the diastolic hemodynamic situation before and after treatment of a mitral valve insufficiency. However, this approach is limited to the early diastolic phase of the cardiac cycle and needs to be validated using a larger sample size.

Time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI) analysis of hemodynamics in valve-sparing aortic root repair with an anatomically shaped sinus prosthesis.

OBJECTIVE: The anatomically shaped sinus prosthesis (Uni-Graft W SINUS; Braun, Melsungen, Germany) used in valve-sparing aortic root replacement promises physiological hemodynamics believed to grant physiologic valve function. Using time-resolved 3-dimensional magnetic resonance phase contrast imaging (4D Flow MRI), we analyzed sinus vortex formation and transvalvular pressure gradients in patients with sinus prosthesis compared with age-matched and young healthy volunteers. METHODS: Twelve patients with sinus prosthesis (55 ± 15 years), 12 age-matched and 6 young healthy volunteers (55 ± 6 years, 25 ± 3 years, respectively) were examined at 3T with a 4D flow magnetic resonance imaging sequence. Sinus vortices visualized by streamlines and time-resolved particle paths were graded on a 4-point Likert scale. Time resolved pressure differences of the left ventricular outflow tract and the ascending aorta to a reference point in the aortic bulb as well as the transvalvular pressure gradient were evaluated. RESULTS: 4D flow visualizations revealed a propensity of the sinus prosthesis toward intermediate (50%) and large (28%) vortices compared with age-matched volunteers with small (61%) and intermediate (36%) vortices. Vortices in sinus prostheses had a similar configuration compared with those in volunteers. The peak transvalvular pressure gradient did not vary significantly between patients and age-matched volunteers (4.0 ± 0.9 mm Hg, 3.8 ± 0.7 mm Hg, P = .373), its temporal evolution resembled that of volunteers with a prolonged positive phase in patients. CONCLUSIONS: Hemodynamics closely relating to those of volunteers were confirmed in sinus prostheses, believed to grant physiological valve function. Minor differences are presumably attributed to graft compliance and temporal resolution of the acquisition. Nevertheless, long-term deterioration of valve function as it was described for straight grafts could potentially be decelerated using sinus prostheses.

Interactive virtual stent planning for the treatment of coarctation of the aorta.

PURPOSE: The coarctation of the aorta (CoA), a local narrowing of the aortic arch, accounts for 7 % of all congenital heart defects. Stenting is a recommended therapy to reduce the pressure gradient. This procedure is associated with complications such as the development of adverse flow conditions. A computer-aided treatment planning based on flow simulations can help to predict possible complications. The virtual stent planning is an important, intermediate step in the treatment planning pipeline. We present a novel approach that automatically suggests a stent setup and provides a set of intuitive parameters that allow for an interactive adaption of the suggested stent placement and induced deformation. METHODS: A high-quality mesh and a centerline are automatically generated. The stent-induced deformation is realized through a deformation of the centerline and a vertex displacement with respect to the deformed centerline and additional stent parameters. The parameterization is automatically derived from the underlying data and can be optionally altered through a condensed set of clinically sound parameters. RESULTS: The automatic deformation can be generated in about 25 s on a consumer system. The interactive adaption can be performed in real time. Compared with manual expert reconstructions of the stented vessel section, the mean difference of vessel path and diameter is below 1 mm. CONCLUSION: Our approach enables a medical user to easily generate a plausibly deformed vessel mesh which is necessary as input for a simulation-based treatment planning of CoA.

Real-time magnetic resonance imaging of cardiac function and flow-recent progress.

Cardiac structure, function and flow are most commonly studied by ultrasound, X-ray and magnetic resonance imaging (MRI) techniques. However, cardiovascular MRI is hitherto limited to electrocardiogram (ECG)-synchronized acquisitions and therefore often results in compromised quality for patients with arrhythmias or inabilities to comply with requested protocols-especially with breath-holding. Recent advances in the development of novel real-time MRI techniques now offer dynamic imaging of the heart and major vessels with high spatial and temporal resolution, so that examinations may be performed without the need for ECG synchronization and during free breathing. This article provides an overview of technical achievements, physiological validations, preliminary patient studies and translational aspects for a future clinical scenario of cardiovascular MRI in real time.

3D fusion of functional cardiac magnetic resonance imaging and computed tomography coronary angiography: accuracy and added clinical value.

PURPOSE: To evaluate the accuracy and added diagnostic value of 3-dimensional (3D) image fusion of computed tomography coronary angiography (CTCA) and functional cardiac magnetic resonance (CMR) for assessing hemodynamically relevant coronary artery disease (CAD). METHODS: Twenty-seven patients with significant coronary stenoses on prospectively electrocardiography-gated dual-source CTCA, confirmed by catheter angiography and perfusion defects on CMR at 1.5 T were included. Surface representations and volume-rendered images from 3D-fused CTCA/CMR data were generated using a software prototype. Fusion accuracy was evaluated by calculating surface distances of blood pools and Dice similarity coefficients. Two independent, blinded readers assigned myocardial defects to culprit coronary arteries with side-by side analysis of CTCA and CMR and using fused CTCA/CMR. Added value of fused CTCA/CMR was defined as change in assignment of culprit coronary artery to myocardial defect compared with side-by-side analysis. RESULTS: 3D fusion of CTCA/CMR was feasible and accurate (surface distance of blood pools: 4.1 ± 1.3 mm, range: 2.4-7.1 mm; Dice similarity coefficients: 0.78 ± 0.08, range: 0.51-0.86) in all patients. Side-by-side analysis of CTCA and CMR allowed no assignment of a single culprit artery to a myocardial defect in 6 of 27 (22%) patients. Fused CTCA/CMR allowed further confinement of culprit coronary arteries in 3 of these 6 patients (11%). Myocardial defects were reassigned in 2 of 27 (7%) patients using fused CTCA/CMR, whereas the results remained unchanged in 22 of 27 (81%) patients. Interobserver agreement for assignment of culprit arteries to myocardial defects increased with fused CTCA/CMR (k = 0.66-0.89). CONCLUSION: 3D fusion of low-dose CTCA and functional CMR is feasible and accurate, and adds, at a low radiation dose, diagnostic value for the assessment of hemodynamically relevant CAD as compared with side-by-side analysis alone. This technique can be clinically useful for the following: planning of surgical or interventional procedures in patients having a high prevalence of CAD and for improved topographic assignment of coronary stenoses to corresponding myocardial perfusion defects.

Survey of the visual exploration and analysis of perfusion data.

Dynamic contrast-enhanced image data (perfusion data) are used to characterize regional tissue perfusion. Perfusion data consist of a sequence of images, acquired after a contrast agent bolus is applied. Perfusion data are used for diagnostic purposes in oncology, ischemic stroke assessment or myocardial ischemia. The diagnostic evaluation of perfusion data is challenging, since the data is complex and exhibits various artifacts, e.g., motion artifacts. We provide an overview on existing methods to analyze, and visualize CT and MR perfusion data. The integrated visualization of several 2D parameter maps, the 3D visualization of parameter volumes and exploration techniques are discussed. An essential aspect in the diagnosis of perfusion data is the correlation between perfusion data and derived time-intensity curves as well as with other image data, in particular with high resolution morphologic image data. We discuss visualization support with respect to the three major application areas: ischemic stroke diagnosis, breast tumor diagnosis and the diagnosis of coronary heart disease.

Three-dimensional visualization and virtual simulation of resections in pediatric solid tumors.

PURPOSE: Three-dimensional visualization of solid tumors is possible because of high-resolution computed tomography and magnetic resonance imaging scans. However, additional preoperative information is often desirable in complex malignancies. For the first time, the authors present a model of preoperative 3-dimensional visualization and virtual resections in pediatric solid tumors. METHODS: Image analysis of various pediatric tumors was performed using the research software HepaVision2 (MeVis, Bremen). Organs, tumors, and the vascular system were extracted from multislice computed tomography scans. After hierarchical analysis of the vascular system, territories supplied or drained by the major vascular branches were calculated. Results were explored and virtual resections of organs were carried out using the research software InterventionPlanner (MeVis, Bremen). Data were correlated to intraoperative findings. RESULTS: Four hepatic malignancies, 4 renal tumors, and 3 other neoplasms were analyzed. The technique of 3-dimensional visualization was feasible for all investigated children (mean age 5 years and 9 months). Spatial relations between physiological and pathological structures were identified, and anatomical structures (vessels, tumor tissue, and organ parenchyma) were determined using colorimetric encoding. Virtual simulations of tumor resection were used successfully for planning of surgical procedures in the hepatic and renal tumors. CONCLUSIONS: The technique of 3-dimensional tumor visualization and virtual simulation of tumor resections provides the basis for a successful planning of complex tumor resections in children. The efficiency of these techniques should be further analyzed in series with higher numbers and differentiations of tumors.