Cardiovascular magnetic resonance: deeper insights through bioengineering.

Heart disease is the main cause of morbidity and mortality worldwide, with coronary artery disease, diabetes, and obesity being major contributing factors. Cardiovascular magnetic resonance (CMR) can provide a wealth of quantitative information on the performance of the heart, without risk to the patient. Quantitative analyses of these data can substantially augment the diagnostic quality of CMR examinations and can lead to more effective characterization of disease and quantification of treatment benefit. This review provides an overview of the current state of the art in CMR with particular regard to the quantification of motion, both microscopic and macroscopic, and the application of bioengineering analysis for the evaluation of cardiac mechanics. We discuss the current clinical practice and the likely advances in the next 5-10 years, as well as the ways in which clinical examinations can be augmented by bioengineering analysis of strain, compliance, and stress.

MTT and Blood-Brain Barrier Disruption within Asymptomatic Vascular WM Lesions.

BACKGROUND AND PURPOSE: White matter lesions of presumed ischemic origin are associated with progressive cognitive impairment and impaired BBB function. Studying the longitudinal effects of white matter lesion biomarkers that measure changes in perfusion and BBB patency within white matter lesions is required for long-term studies of lesion progression. We studied perfusion and BBB disruption within white matter lesions in asymptomatic subjects. MATERIALS AND METHODS: Anatomic imaging was followed by consecutive dynamic contrast-enhanced and DSC imaging. White matter lesions in 21 asymptomatic individuals were determined using a Subject-Specific Sparse Dictionary Learning algorithm with manual correction. Perfusion-related parameters including CBF, MTT, the BBB leakage parameter, and volume transfer constant were determined. RESULTS: MTT was significantly prolonged (7.88 [SD, 1.03] seconds) within white matter lesions compared with normal-appearing white (7.29 [SD, 1.14] seconds) and gray matter (6.67 [SD, 1.35] seconds). The volume transfer constant, measured by dynamic contrast-enhanced imaging, was significantly elevated (0.013 [SD, 0.017] minutes-1) in white matter lesions compared with normal-appearing white matter (0.007 [SD, 0.011] minutes-1). BBB disruption within white matter lesions was detected relative to normal white and gray matter using the DSC-BBB leakage parameter method so that increasing BBB disruption correlated with increasing white matter lesion volume (Spearman correlation coefficient = 0.44; P < .046). CONCLUSIONS: A dual-contrast-injection MR imaging protocol combined with a 3D automated segmentation analysis pipeline was used to assess BBB disruption in white matter lesions on the basis of quantitative perfusion measures including the volume transfer constant (dynamic contrast-enhanced imaging), the BBB leakage parameter (DSC), and MTT (DSC). This protocol was able to detect early pathologic changes in otherwise healthy individuals.

A 3D Computational Head Model Under Dynamic Head Rotation and Head Extension Validated Using Live Human Brain Data, Including the Falx and the Tentorium.

We employ an advanced 3D computational model of the head with high anatomical fidelity, together with measured tissue properties, to assess the consequences of dynamic loading to the head in two distinct modes: head rotation and head extension. We use a subject-specific computational head model, using the material point method, built from T1 magnetic resonance images, and considering the anisotropic properties of the white matter which can predict strains in the brain under large rotational accelerations. The material model now includes the shear anisotropy of the white matter. We validate the model under head rotation and head extension motions using live human data, and advance a prior version of the model to include biofidelic falx and tentorium. We then examine the consequences of incorporating the falx and tentorium in terms of the predictions from the computational head model.

Inter-scanner Variation Independent Descriptors for Constrained Diffeomorphic Demons Registration of Retina OCT.

PURPOSE: OCT offers high in-plane micrometer resolution, enabling studies of neurodegenerative and ocular-disease mechanisms via imaging of the retina at low cost. An important component to such studies is inter-scanner deformable image registration. Image quality of OCT, however, is suboptimal with poor signal-to-noise ratio and through-plane resolution. Geometry of OCT is additionally improperly defined. We developed a diffeomorphic deformable registration method incorporating constraints accommodating the improper geometry and a decentralized-modality-insensitive-neighborhood-descriptors (D-MIND) robust against degradation of OCT image quality and inter-scanner variability. METHOD: The method, called D-MIND Demons, estimates diffeomorphisms using D-MINDs under constraints on the direction of velocity fields in a MIND-Demons framework. Descriptiveness of D-MINDs with/without denoising was ranked against four other shape/texture-based descriptors. Performance of D-MIND Demons and its variants incorporating other descriptors was compared for cross-scanner, intra- and inter-subject deformable registration using clinical retina OCT data. RESULT: D-MINDs outperformed other descriptors with the difference in mutual descriptiveness between high-contrast and homogenous regions > 0.2. Among Demons variants, D-MIND-Demons was computationally efficient, demonstrating robustness against OCT image degradation (noise, speckle, intensity-non-uniformity, and poor through-plane resolution) and consistent registration accuracy [(4±4 µm) and (4±6 µm) in cross-scanner intra- and inter-subject registration] regardless of denoising. CONCLUSIONS: A promising method for cross-scanner, intra- and inter-subject OCT image registration has been developed for ophthalmological and neurological studies of retinal structures. The approach could assist image segmentation, evaluation of longitudinal disease progression, and patient population analysis, which in turn, facilitate diagnosis and patient-specific treatment.

MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery.

PURPOSE: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. METHOD: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. RESULT: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. CONCLUSIONS: A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

Performance evaluation of MIND demons deformable registration of MR and CT images in spinal interventions.

Accurate intraoperative localization of target anatomy and adjacent nervous and vascular tissue is essential to safe, effective surgery, and multimodality deformable registration can be used to identify such anatomy by fusing preoperative CT or MR images with intraoperative images. A deformable image registration method has been developed to estimate viscoelastic diffeomorphisms between preoperative MR and intraoperative CT using modality-independent neighborhood descriptors (MIND) and a Huber metric for robust registration. The method, called MIND Demons, optimizes a constrained symmetric energy functional incorporating priors on smoothness, geodesics, and invertibility by alternating between Gauss-Newton optimization and Tikhonov regularization in a multiresolution scheme. Registration performance was evaluated for the MIND Demons method with a symmetric energy formulation in comparison to an asymmetric form, and sensitivity to anisotropic MR voxel-size was analyzed in phantom experiments emulating image-guided spine-surgery in comparison to a free-form deformation (FFD) method using local mutual information (LMI). Performance was validated in a clinical study involving 15 patients undergoing intervention of the cervical, thoracic, and lumbar spine. The target registration error (TRE) for the symmetric MIND Demons formulation (1.3 ± 0.8 mm (median ± interquartile)) outperformed the asymmetric form (3.6 ± 4.4 mm). The method demonstrated fairly minor sensitivity to anisotropic MR voxel size, with median TRE ranging 1.3-2.9 mm for MR slice thickness ranging 0.9-9.9 mm, compared to TRE = 3.2-4.1 mm for LMI FFD over the same range. Evaluation in clinical data demonstrated sub-voxel TRE (<2 mm) in all fifteen cases with realistic deformations that preserved topology with sub-voxel invertibility (0.001 mm) and positive-determinant spatial Jacobians. The approach therefore appears robust against realistic anisotropic resolution characteristics in MR and yields registration accuracy suitable to application in image-guided spine-surgery.

Fast determination of regional myocardial strain fields from tagged cardiac images using harmonic phase MRI.

BACKGROUND: Tagged MRI of the heart is difficult to implement clinically because of the lack of fast analytical techniques. We investigated the accuracy of harmonic phase (HARP) imaging for rapid quantification of myocardial strains and for detailed analysis of left ventricular (LV) function during dobutamine stimulation. METHODS AND RESULTS: Tagged MRI was performed in 10 volunteers at rest and during 5 to 20 microg(-1). kg(-1). min(-1) dobutamine and in 9 postinfarct patients at rest. We compared 2D myocardial strains (circumferential shortening, Ecc; maximal shortening, E(2); and E(2), direction) as assessed by a conventional technique and by HARP. Full quantitative analysis of the data was 10 times faster with HARP. For pooled data, the regression coefficient was r=0.93 for each strain (P<0.001). In volunteers, Ecc and E(2) were greater in the free wall than in the septum (P<0.01), but recruitable myocardial strain at peak dobutamine was greater in the LV septum (P<0.01). E(2) orientation shifted away from the circumferential direction at peak dobutamine (P<0.01). HARP accurately detected subtle changes in myocardial strain fields under increasing doses of dobutamine. In patients, HARP-determined Ecc and E(2) values were dramatically reduced in the asynergic segments as compared with remote (P<0.001), and E(2) direction shifted away from the circumferential direction (P<0.001). CONCLUSIONS: HARP MRI provides fast, accurate assessment of myocardial strains from tagged MR images in normal subjects and in patients with coronary artery disease with wall motion abnormalities. HARP correctly indexes dobutamine-induced changes in strains and has the potential for on-line quantitative monitoring of LV function during stress testing.

Transmural contractile reserve after reperfused myocardial infarction in dogs.

OBJECTIVES: The goal of this study was to characterize detailed transmural left ventricular (LV) function at rest and during dobutamine stimulation in subendocardial and transmural experimental infarcts. BACKGROUND: The relation between segmental LV function and the transmural extent of myocardial necrosis is complex. However, its detailed understanding is crucial for the diagnosis of myocardial viability as assessed by inotropic stimulation. METHODS: Short-axis tagged magnetic resonance images were acquired at five to seven levels encompassing the LV from base to apex in seven dogs 2 days after a 90-min closed-chest left anterior descending coronary occlusion, followed by reflow. Myocardial strains were measured transmurally in the entire LV by harmonic phase imaging at rest and 5 ig x kg(-1) x min(-1) dobutamine. Risk regions were assessed by radioactive microspheres, and the transmural extent of the infarct was assessed by 2,3,5 triphenyltetrazolium chloride staining. RESULTS: Circumferential shortening (Ecc), radial thickening (Err) and maximal shortening at rest were greater in segments with subendocardial versus transmural infarcts, both in subepicardium (-1.1+/-1.0 vs. 2.5+/-0.6% for Ecc, -0.5+/-1.9 vs. -1.8+/-1.0% for Err, p < 0.05) and subendocardium (-2.0+/-1.4 vs. 2.8+/-0.8%, 2.4+/-1.7 vs. 0.0+/-0.9%, respectively, p < 0.05). Under inotropic stimulation, risk regions retained maximal contractile reserve. Recruitable deformation was found in outer layers of subendocardial infarcts (p < 0.01 for Ecc and Err) but also in inner layers (p < 0.01). Conversely, no contractile reserve was observed in segments with transmural infarcts. CONCLUSIONS: Under dobutamine challenge, recruitment of myofiber shortening and thickening was observed in inner layers of segments with subendocardial infarcts. These results may have important clinical implications for the detection of myocardial viability.

Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects.

Accuracy in in vivo quantitation of brain function with positron emission tomography (PET) has often been limited by partial volume effects. This limitation becomes prominent in studies of aging and degenerative brain diseases where partial volume effects vary with different degrees of atrophy. The present study describes how the actual gray matter (GM) tracer concentration can be estimated using an algorithm that relates the regional fraction of GM to partial volume effects. The regional fraction of GM was determined by magnetic resonance imaging (MRI). The procedure is designated as GM PET. In computer simulations and phantom studies, the GM PET algorithm permitted a 100% recovery of the actual tracer concentration in neocortical GM and hippocampus, irrespective of the GM volume. GM PET was applied in a test case of temporal lobe epilepsy revealing an increase in radiotracer activity in GM that was undetected in the PET image before correction for partial volume effects. In computer simulations, errors in the segmentation of GM and errors in registration of PET and MRI images resulted in less than 15% inaccuracy in the GM PET image. In conclusion, GM PET permits accurate determination of the actual radiotracer concentration in human brain GM in vivo. The method differentiates whether a change in the apparent radiotracer concentration reflects solely an alteration in GM volume or rather a change in radiotracer concentration per unit volume of GM.

A k-space analysis of MR tagging.

We present a k-space approximation that directly relates a pulse sequence to its residual pattern of z-directed magnetization M(z), in a manner akin to the k-space approximation for small tip-angle excitation. Our approximation is particularly useful for the analysis and design of tagging sequences, in which M(z) is the important quantity-as opposed to the transverse magnetization components M(x) and M(y) considered in selective excitation. We demonstrate that our approximation provides new insights into tagging, can be used to design novel tag patterns, and, more generally, may be applied to selective presaturation sequences for purposes other than tagging.

Optimization of MR pulse sequences for Bayesian image segmentation.

A method for optimizing MR imaging pulse sequence parameters in a statistical framework is presented. Parameters are defined to be optimal when the resulting scalar images yield optimal image segmentations using Bayesian pixel classification. Thus, Bayes risk is used as the objective function to minimize. Approximations are made to give a tractable solution in a four-step procedure. A sample calculation is carried out to determine the optimal TR and flip angle for scalar SPGR imaging of the brain. Overall, this paper gives a new approach to optimize MRI pulse sequences for the specific objective of improved image segmentation.

Bandpass optical flow for tagged MRI.

MR tagging has shown great promise for detailed noninvasive cardiac motion imaging. Our research uses low-frequency tags coupled with gradient-based optical flow estimation to compute cardiac motion. We develop here a novel, fast, fully automated optical flow method for tagged MRI by exploiting the Fourier content of the tagged images. This new method, called bandpass optical flow, works by extracting various subband images from tagged cardiac data, and then formulating multiple optical flow constraints for each subband. The resulting system is solved by least squares pseudo-inversion. The proposed method is validated on simulated and real tagged data.

An active contour model for mapping the cortex.

A new active contour model for finding and mapping the outer cortex in brain images is developed. A cross-section of the brain cortex is modeled as a ribbon, and a constant speed mapping of its spine is sought. A variational formulation, an associated force balance condition, and a numerical approach are proposed to achieve this goal. The primary difference between this formulation and that of snakes is in the specification of the external force acting on the active contour. A study of the uniqueness and fidelity of solutions is made through convexity and frequency domain analyses, and a criterion for selection of the regularization coefficient is developed. Examples demonstrating the performance of this method on simulated and real data are provided.

Reconstruction of 3-D left ventricular motion from planar tagged cardiac MR images: an estimation theoretic approach.

Magnetic resonance (MR) tagging has shown great potential for noninvasive measurement of the motion of a beating heart. In MR tagged images, the heart appears with a spatially encoded pattern that moves with the tissue. The position of the tag pattern in each frame of the image sequence can be used to obtain a measurement of the 3-D displacement field of the myocardium. The measurements are sparse, however, and interpolation is required to reconstruct a dense displacement field from which measures of local contractile performance such as strain can be computed. Here, the authors propose a method for estimating a dense displacement field from sparse displacement measurements. Their approach is based on a multidimensional stochastic model for the smoothness and divergence of the displacement field and the Fisher estimation framework. The main feature of this method is that both the displacement field model and the resulting estimate equation are defined only on the irregular domain of the myocardium. The authors' methods are validated on both simulated and in vivo heart data.

Adaptive fuzzy segmentation of magnetic resonance images.

An algorithm is presented for the fuzzy segmentation of two-dimensional (2-D) and three-dimensional (3-D) multispectral magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities, also known as shading artifacts. The algorithm is an extension of the 2-D adaptive fuzzy C-means algorithm (2-D AFCM) presented in previous work by the authors. This algorithm models the intensity inhomogeneities as a gain field that causes image intensities to smoothly and slowly vary through the image space. It iteratively adapts to the intensity inhomogeneities and is completely automated. In this paper, we fully generalize 2-D AFCM to three-dimensional (3-D) multispectral images. Because of the potential size of 3-D image data, we also describe a new faster multigrid-based algorithm for its implementation. We show, using simulated MR data, that 3-D AFCM yields lower error rates than both the standard fuzzy C-means (FCM) algorithm and two other competing methods, when segmenting corrupted images. Its efficacy is further demonstrated using real 3-D scalar and multispectral MR brain images.

Motion estimation from tagged MR image sequences.

A method for reconstructing motion from sequences of tagged magnetic resonance (MR) images is presented. MR tagging is used to create a spatial pattern of varying magnetization so that objects which may otherwise have constant intensity are textured, which reduces the motion ambiguity associated with the aperture problem in computer vision. To compensate for the decay of the tag pattern, a new optical flow algorithm is developed and implemented. The resulting estimated velocity field is then used to recursively update the implied motion reference map over time, thereby tracking the motion of individual particles. If a segmentation of the object is known at the time the tag pattern is created, then an object may be selectively tracked, using the estimated reference map to update the object's position as time progresses. Results are shown for both simulated and actual MR phantom data.

Image registration based on boundary mapping.

A new two-stage approach for nonlinear brain image registration is proposed. In the first stage, an active contour algorithm is used to establish a homothetic one-to-one map between a set of region boundaries in two images to be registered. This mapping is used in the second step: a two-dimensional transformation which is based on an elastic body deformation. This method is tested by registering magnetic resonance images to atlas images.

Tag and contour detection in tagged MR images of the left ventricle.

Tracking magnetic resonance tags in myocardial tissue promises to be an effective tool for the assessment of myocardial motion. The authors describe a hierarchy of image processing steps which rapidly detects both the contours of the myocardial boundaries of the left ventricle and the tags within the myocardium. The method works on both short axis and long axis images containing radial and parallel tag patterns, respectively. Left ventricular boundaries are detected by first removing the tags using morphological closing and then selecting candidate edge points. The best inner and outer boundaries are found using a dynamic program that minimizes a nonlinear combination of several local cost functions. Tags are tracked by matching a template of their expected profile using a least squares estimate. Since blood pooling, contiguous and adjacent tissue, and motion artifacts sometimes cause detection errors, a graphical user interface was developed to allow user correction of anomalous points. The authors present results on several tagged images of a human. A fully automated run generally finds the endocardial boundary and the tag lines extremely well, requiring very little manual correction. The epicardial boundary sometimes requires more intervention to obtain an acceptable result. These methods are currently being used in the analysis of cardiac strain and as a basis for the analysis of alternate tag geometries.

A vector Wiener filter for dual-radionuclide imaging.

The routine use of a single radionuclide for patient imaging in nuclear medicine can be complemented by studies employing two tracers to examine two different processes in a single organ, most frequently by simultaneous imaging of both radionuclides in two different energy windows. In addition, simultaneous transmission/emission imaging with dual-radionuclides has been described, with one radionuclide used for the transmission study and a second for the emission study. There is thus currently considerable interest in dual-radionuclide imaging. A major problem with all dual-radionuclide imaging is the "crosstalk" between the two radionuclides. Such crosstalk frequently occurs, because scattered radiation from the higher energy radionuclide is detected in the lower energy window, and because the lower energy radionuclide may have higher energy emissions which are detected in the higher energy window. The authors have previously described the use of Fourier-based restoration filtering in single photon emission computed tomography (SPECT) and positron emission tomography (PET) to improve quantitative accuracy by designing a Wiener or other Fourier filter to partially restore the loss of contrast due to scatter and finite spatial resolution effects. The authors describe here the derivation and initial validation of an extension of such filtering for dual-radionuclide imaging that simultaneously 1) improves contrast in each radionuclide's "direct" image, 2) reduces image noise, and 3) reduces the crosstalk contribution from the other radionuclide. This filter is based on a vector version of the Wiener filter, which is shown to be superior [in the minimum mean square error (MMSE) sense] to the sequential application of separate crosstalk and restoration filters.

Imaging heart motion using harmonic phase MRI.

This paper describes a new image processing technique for rapid analysis and visualization of tagged cardiac magnetic resonance (MR) images. The method is based on the use of isolated spectral peaks in spatial modulation of magnetization (SPAMM)-tagged magnetic resonance images. We call the calculated angle of the complex image corresponding to one of these peaks a harmonic phase (HARP) image and show that HARP images can be used to synthesize conventional tag lines, reconstruct displacement fields for small motions, and calculate two-dimensional (2-D) strain. The performance of this new approach is demonstrated using both real and simulated tagged MR images. Potential for use of HARP images in fast imaging techniques and three-dimensional (3-D) analyses are discussed.