Jens Guehring

Motion correction for myocardial T1 mapping using image registration with synthetic image estimation

Quantification of myocardial T1 relaxation has potential value in the diagnosis of both ischemic and nonischemic cardiomyopathies. Image acquisition using the modified Look‐Locker inversion recovery technique is clinically feasible for T1 mapping. However, respiratory motion limits its applicability and degrades the accuracy of T1 estimation. The robust registration of acquired inversion recovery images is particularly challenging due to the large changes in image contrast, especially for those images acquired near the signal null point of the inversion recovery and other inversion times for which there is little tissue contrast. In this article, we propose a novel motion correction algorithm. This approach is based on estimating synthetic images presenting contrast changes similar to the acquired images. The estimation of synthetic images is formulated as a variational energy minimization problem. Validation on a consecutive patient data cohort shows that this strategy can perform robust nonrigid registration to align inversion recovery images experiencing significant motion and lead to suppression of motion induced artifacts in the T1 map. Magn Reson Med, 2011.

Phase-Sensitive Inversion Recovery for Myocardial T1 Mapping with Motion Correction and Parametric Fitting

The assessment of myocardial fibrosis and extracellular volume requires accurate estimation of myocardial T1s. While image acquisition using the modified Look‐Locker inversion recovery technique is clinically feasible for myocardial T1 mapping, respiratory motion can limit its applicability. Moreover, the conventional T1 fitting approach using the magnitude inversion recovery images can lead to less stable T1 estimates and increased computational cost. In this article, we propose a novel T1 mapping scheme that is based on phase‐sensitive image reconstruction and the restoration of polarity of the MR signal after inversion. The motion correction is achieved by registering the reconstructed images after background phase removal. The restored signal polarity of the inversion recovery signal helps the T1 fitting resulting in improved quality of the T1 map and reducing the computational cost. Quantitative validation on a data cohort of 45 patients proves the robustness of the proposed method against varying image contrast. Compared to the magnitude T1 fitting, the proposed phase‐sensitive method leads to less fluctuation in T1 estimates. Magn Reson Med, 2013.

Myocardial T2 Mapping With Respiratory Navigator and Automatic Nonrigid Motion Correction

Quantitative T2 mapping was recently shown to be superior to T2‐weighted imaging in detecting T2 changes across myocardium. Pixel‐wise T2 mapping is sensitive to misregistration between the images used to generate the parameter map. In this study, utility of two motion‐compensation strategies—(i) navigator gating with prospective slice correction and (ii) nonrigid registration—was investigated for myocardial T2 mapping in short axis and horizontal long axis views. Navigator gating provides respiratory motion compensation, whereas registration corrects for residual cardiac and respiratory motion between images; thus, the two strategies provided complementary functions. When these were combined, respiratory‐motion‐induced T2 variability, as measured by both standard deviation and interquartile range, was comparable to that in breath‐hold T2 maps. In normal subjects, this combined motion‐compensation strategy increased the percentage of myocardium with T2 measured to be within normal range from 60.1% to 92.2% in short axis and 62.3% to 92.7% in horizontal long axis. The new motion‐compensated T2 mapping technique, which combines navigator gating, prospective slice correction, and nonrigid registration to provide through‐plane and in‐plane motion correction, enables a method for fully automatic and robust free‐breathing T2 mapping. Magn Reson Med, 2012.

Combining Registration and Minimum Surfaces for the Segmentation of the Left Ventricle in Cardiac Cine MR Images

This paper describes a system to automatically segment the left ventricle in all slices and all phases of cardiac cine magnetic resonance datasets. After localizing the left ventricle blood pool using motion, thresholding and clustering, slices are segmented sequentially. For each slice, deformable registration is used to align all the phases, candidates contours are recovered in the average image using shortest paths, and a minimal surface is built to generate the final contours. The advantage of our method is that the resulting contours follow the edges in each phase and are consistent over time. We demonstrate using 19 patient examples that the results are very good. The RMS distance between ground truth and our segmentation is only 1.6 pixels (2.7 mm) and the Dice coefficient is 0.89.

Unsupervised Inline Analysis of Cardiac Perfusion MRI

In this paper we first discuss the technical challenges preventing an automated analysis of cardiac perfusion MR images and subsequently present a fully unsupervised workflow to address the problems. The proposed solution consists of key-frame detection, consecutive motion compensation, surface coil inhomogeneity correction using proton density images and robust generation of pixel-wise perfusion parameter maps. The entire processing chain has been implemented on clinical MR systems to achieve unsupervised inline analysis of perfusion MRI. Validation results are reported for 260 perfusion time series, demonstrating feasibility of the approach.

Efficient symmetric and inverse-consistent deformable registration through interleaved optimization

Symmetry and inverse consistency are two important features for deformable image registration in medical imaging analysis. This work presents a novel registration method computing symmetric and inverse-consistent image alignment efficiently while preserving high accuracy and consistency of the mapping. This is achieved by optimizing a symmetric energy functional estimating forward and backward transformations constrained by the transformations being inverse to each other. In other words, this approach uses an interleaved optimization scheme borrowed from multiobjective optimization theory constrained by an inverse-consistency criterium. The new optimization scheme provides an efficient search in the space of diffeomorphisms while solving the symmetric registration problem. Moreover, it is not bound to any specific optimizer or energy functional other than to the requirement of being well-defined. In our experiments on clinical cardiac data, superior performance compared to standard, one-directional registration is achieved. The resulting inverse-consistency and symmetry errors match previously reported values while being computed more efficiently. This general approach addresses a clinical need for consistent, highly accurate image alignment achieved in a practically accepted time-frame.

Cardiac anchoring in MRI through context modeling

Cardiac magnetic resonance imaging (MRI) has advanced to become a powerful diagnostic tool in clinical practice. Robust and fast cardiac modeling is important for structural and functional analysis of the heart. Cardiac anchors provide strong cues to extract morphological and functional features for diagnosis and disease monitoring. We present a fully automatic method and system that is able to detect these cues. The proposed approach explores expert knowledge embedded in a large annotated database. Exemplar cues in our experiments include left ventricle (LV) base plane and LV apex from long-axis images, and right ventricle (RV) insertion points from short-axis images. We evaluate the proposed approach on 8304 long-axis images from 188 patients and 891 short-axis images from 338 patients that are acquired from different vendors. In addition, another evaluation is conducted on an independent 7140 images from 87 patient studies. Experimental results show promise of the proposed approach.

T2‐weighted cardiac MR assessment of the myocardial area‐at‐risk and salvage area in acute reperfused myocardial infarction: Comparison of state‐of‐the‐art dark blood and bright blood T2‐weighted sequences

To compare different state‐of‐the‐art T2‐weighted (T2w) imaging sequences combined with late gadolinium enhancement (LGE) for myocardial salvage area (MSA) assessment by cardiac magnetic resonance (CMR). T2w imaging has been used to assess the myocardial area at risk (AAR) in acute myocardial infarction (AMI) patients, but its clinical application is challenging due to technical and physical limitations.

Cardiac segmentation in MR cine data using inverse consistent deformable registration

This paper proposes a registration-based segmentation technique to fully automatically segment the left ventricle in cardiac cine magnetic resonance studies. We propose an inverse consistent deformable registration algorithm to recover one set of forward and backward deformation fields that allow us to access the deformation from any frame to any other frame in the cardiac sequence. Cardiac phases are segmented using a shortest path algorithm and time consistency is enforced through the deformation fields. We demonstrate on 52 datasets with expert outlined ground truth that the algorithm produces accurate (1.39 pixels median error, 2.10 pixels RMS error, 0.88 Dice coefficient) and fast (0.3 s/image) results.

Evaluation of Rigid and Non-rigid Motion Compensation of Cardiac Perfusion MRI

Although the evaluation of cardiac perfusion using MRI could be of crucial importance for the diagnosis of ischemic heart diseases, it is still not a routinely used technique. The major difficulty is that MR perfusion images are often corrupted by inconsistent myocardial motion. Although motion compensation methods have been studied throughout the past decade, no clinically accepted solution has emerged. This is partly due to the lack of comprehensive validation. To address this deficit we collected a large multi-centre MR perfusion dataset and used this to characterize typical myocardial motion and confirmed that under clinically relevant conditions motion correction is a frequent requirement (67% of all 586 cases). We then developed a proposed solution which includes both rigid/affine and the non-rigid image registration. Quantitative validation has been conducted using 6 different statistics to provide a comprehensive evaluation, showing the proposed techniques to be highly robust to different myocardial anatomy and motion patterns as well as to MR imaging acquisition parameters.