Christoph Kolbitsch

Cardiac magnetic resonance and electroanatomical mapping of acute and chronic atrial ablation injury: a histological validation study

AIMS To provide a comprehensive histopathological validation of cardiac magnetic resonance (CMR) and endocardial voltage mapping of acute and chronic atrial ablation injury. METHODS AND RESULTS 16 pigs underwent pre-ablation T2-weighted (T2W) and late gadolinium enhancement (LGE) CMR and high-density voltage mapping of the right atrium (RA) and both were repeated after intercaval linear radiofrequency ablation. Eight pigs were sacrificed following the procedure for pathological examination. A further eight pigs were recovered for 8 weeks, before chronic CMR, repeat RA voltage mapping and pathological examination. Signal intensity (SI) thresholds from 0 to 15 SD above a reference SI were used to segment the RA in CMR images and segmentations compared with real lesion volumes. The SI thresholds that best approximated histological volumes were 2.3 SD for LGE post-ablation, 14.5 SD for T2W post-ablation and 3.3 SD for LGE chronically. T2-weighted chronically always underestimated lesion volume. Acute histology showed transmural injury with coagulative necrosis. Chronic histology showed transmural fibrous scar. The mean voltage at the centre of the ablation line was 3.3 mV pre-ablation, 0.6 mV immediately post-ablation, and 0.3 mV chronically. CONCLUSION This study presents the first histopathological validation of CMR and endocardial voltage mapping to define acute and chronic atrial ablation injury, including SI thresholds that best match histological lesion volumes. An understanding of these thresholds may allow a more informed assessment of the underlying atrial substrate immediately after ablation and before repeat catheter ablation for atrial arrhythmias.

Retrospective Rigid Motion Correction in k-Space for Segmented Radial MRI

Motion occurring during magnetic resonance imaging acquisition is a major factor of image quality degradation. Self-navigation can help reduce artefacts by estimating motion from the acquired data to enable motion correction. Popular self-navigation techniques rely on the availability of a fully-sampled motion-free reference to register the motion corrupted data with. In the proposed technique, rigid motion parameters are derived using the inherent correlation between radial segments in k-space. The registration is performed exclusively in k-space using the Phase Correlation Method, a popular registration technique in computer vision. Robust and accurate registration has been carried out from radial segments composed of as few as 32 profiles. Successful self-navigation has been performed on 2-D dynamic brain scans corrupted with continuous motion for six volunteers. Retrospective motion correction using the derived self-navigation parameters resulted in significant improvement of image quality compared to the conventional sliding window. This work also demonstrates the benefits of using a bit-reversed ordering scheme to limit undesirable effects specific to retrospective motion correction on radial trajectories. This method provides a fast and efficient mean of measuring rigid motion directly in k-space from dynamic radial data under continuous motion.

A 3D MR-acquisition scheme for nonrigid bulk motion correction in simultaneous PET-MR

PURPOSE Positron emission tomography (PET) is a highly sensitive medical imaging technique commonly used to detect and assess tumor lesions. Magnetic resonance imaging (MRI) provides high resolution anatomical images with different contrasts and a range of additional information important for cancer diagnosis. Recently, simultaneous PET-MR systems have been released with the promise to provide complementary information from both modalities in a single examination. Due to long scan times, subject nonrigid bulk motion, i.e., changes of the patients position on the scanner table leading to nonrigid changes of the patients anatomy, during data acquisition can negatively impair image quality and tracer uptake quantification. A 3D MR-acquisition scheme is proposed to detect and correct for nonrigid bulk motion in simultaneously acquired PET-MR data. METHODS A respiratory navigated three dimensional (3D) MR-acquisition with Radial Phase Encoding (RPE) is used to obtain T1- and T2-weighted data with an isotropic resolution of 1.5 mm. Healthy volunteers are asked to move the abdomen two to three times during data acquisition resulting in overall 19 movements at arbitrary time points. The acquisition scheme is used to retrospectively reconstruct dynamic 3D MR images with different temporal resolutions. Nonrigid bulk motion is detected and corrected in this image data. A simultaneous PET acquisition is simulated and the effect of motion correction is assessed on image quality and standardized uptake values (SUV) for lesions with different diameters. RESULTS Six respiratory gated 3D data sets with T1- and T2-weighted contrast have been obtained in healthy volunteers. All bulk motion shifts have successfully been detected and motion fields describing the transformation between the different motion states could be obtained with an accuracy of 1.71 ± 0.29 mm. The PET simulation showed errors of up to 67% in measured SUV due to bulk motion which could be reduced to less than 10% with the proposed motion compensation approach. CONCLUSIONS A MR acquisition scheme which yields both high resolution 3D anatomical data and highly accurate nonrigid motion information without an increase in scan time is presented. The proposed method leads to a strong improvement in both MR and PET image quality and ensures an accurate assessment of tracer uptake.

Cardiac and respiratory motion correction for simultaneous cardiac PET-MR

Cardiac PET is a versatile imaging technique providing important diagnostic information about ischemic heart diseases. Respiratory and cardiac motion of the heart can strongly impair image quality and therefore diagnostic accuracy of cardiac PET scans. The aim of this study was to investigate a new cardiac PET/MR approach providing respiratory and cardiac motion–compensated MR and PET images in less than 5 min. Methods: Free-breathing 3-dimensional MR data were acquired and retrospectively binned into multiple respiratory and cardiac motion states. Three-dimensional cardiac and respiratory motion fields were obtained with a nonrigid registration algorithm and used in motion-compensated MR and PET reconstructions to improve image quality. The improvement in image quality and diagnostic accuracy of the technique was assessed in simultaneous 18F-FDG PET/MR scans of a canine model of myocardial infarct and was demonstrated in a human subject. Results: MR motion fields were successfully used to compensate for in vivo cardiac motion, leading to improvements in full width at half maximum of the canine myocardium of 13% ± 5%, similar to cardiac gating but with a 90% ± 57% higher contrast-to-noise ratio between myocardium and blood. Motion correction led to an improvement in MR image quality in all subjects, with an increase in sharpness of the canine coronary arteries of 85% ± 72%. A functional assessment showed good agreement with standard MR cine scans with a difference in ejection fraction of −2% ± 3%. MR-based respiratory and cardiac motion information was used to improve the PET image quality of a human in vivo scan. Conclusion: The MR technique presented here provides both diagnostic and motion information that can be used to improve MR and PET image quality. Reliable respiratory and cardiac motion correction could make cardiac PET results more reproducible.

Manifold learning based ECG-free free-breathing cardiac CINE MRI

To present and validate a manifold learning (ML)‐based method that can estimate both cardiac and respiratory navigator signals from electrocardiogram (ECG)‐free free‐breathing cardiac magnetic resonance imaging (MRI) data to achieve self‐gated retrospective CINE reconstruction.

A novel Bayesian respiratory motion model to estimate and resolve uncertainty in image-guided cardiac interventions

In image-guided cardiac interventions, respiratory motion causes misalignments between the pre-procedure roadmap of the heart used for guidance and the intra-procedure position of the heart, reducing the accuracy of the guidance information and leading to potentially dangerous consequences. We propose a novel technique for motion-correcting the pre-procedural information that combines a probabilistic MRI-derived affine motion model with intra-procedure real-time 3D echocardiography (echo) images in a Bayesian framework. The probabilistic model incorporates a measure of confidence in its motion estimates which enables resolution of the potentially conflicting information supplied by the model and the echo data. Unlike models proposed so far, our method allows the final motion estimate to deviate from the model-produced estimate according to the information provided by the echo images, so adapting to the complex variability of respiratory motion. The proposed method is evaluated using gold-standard MRI-derived motion fields and simulated 3D echo data for nine volunteers and real 3D live echo images for four volunteers. The Bayesian method is compared to 5 other motion estimation techniques and results show mean/max improvements in estimation accuracy of 10.6%/18.9% for simulated echo images and 20.8%/41.5% for real 3D live echo data, over the best comparative estimation method.

MR-Based Cardiac and Respiratory Motion-Compensation Techniques for PET-MR Imaging.

Cardiac and respiratory motion cause image quality degradation in PET imaging, affecting diagnostic accuracy of the images. Whole-body simultaneous PET-MR scanners allow for using motion information estimated from MR images to correct PET data and produce motion-compensated PET images. This article reviews methods that have been proposed to estimate motion from MR images and different techniques to include this information in PET reconstruction, in order to overcome the problem of cardiac and respiratory motion in PET-MR imaging. MR-based motion correction techniques significantly increase lesion detectability and contrast, and also improve accuracy of uptake values in PET images.

Cardiac functional assessment without electrocardiogram using physiological self-navigation

Electrocardiogram (ECG)‐gated cine MRI provides highly accurate functional assessment of the heart. Nevertheless, reliable ECG signals are not always available due to patients electrophysiology or due to high MR field strengths. Here, a novel framework for cardiac functional assessment using physiological information is presented, which is obtained from MR image data.

3D high-resolution atrial wall thickness maps using black-blood PSIR

Background Atrial fibrillation (AF) is the most common cardiac arrhythmia. It is often treated using catheter ablation, which aims to isolate arrhythmogenic regions by delivering localized energy. Whereas an insufficient energy delivery can lead to AF recurrence, excessive power can cause potentially lethal complications. Knowledge of atrial wall thickness can help select an optimal amount of energy, but clinical imaging does not currently provide atrial wall thickness data for patients. Even ex-vivo studies have only measured the thickness of the atrial wall in discrete locations using CT or post-mortem samples. In this study, we apply black-blood MR imaging to reconstruct both epiand endocardial surfaces of the entire atria and compute wall thickness maps in healthy volunteers. To our knowledge, this is the first study to provide a complete 3D map of the wall thickness of both right and left atria.

Novel MRI Technique Enables Non-Invasive Measurement of Atrial Wall Thickness

Knowledge of atrial wall thickness (AWT) has the potential to provide important information for patient stratification and the planning of interventions in atrial arrhythmias. To date, information about AWT has only been acquired in post-mortem or poor-contrast computed tomography (CT) studies, providing limited coverage and highly variable estimates of AWT. We present a novel contrast agent-free MRI sequence for imaging AWT and use it to create personalized AWT maps and a biatrial atlas. A novel black-blood phase-sensitive inversion recovery protocol was used to image ten volunteers and, as proof of concept, two atrial fibrillation patients. Both atria were manually segmented to create subject-specific AWT maps using an average of nearest neighbors approach. These were then registered non-linearly to generate an AWT atlas. AWT was 2.4 ± 0.7 and 2.7 ± 0.7 mm in the left and right atria, respectively, in good agreement with post-mortem and CT data, where available. AWT was 2.6 ± 0.7 mm in the left atrium of a patient without structural heart disease, similar to that of volunteers. In a patient with structural heart disease, the AWT was increased to 3.1 ± 1.3 mm. We successfully designed an MRI protocol to non-invasively measure AWT and create the first whole-atria AWT atlas. The atlas can be used as a reference to study alterations in thickness caused by atrial pathology. The protocol can be used to acquire personalized AWT maps in a clinical setting and assist in the treatment of atrial arrhythmias.