Christoph Forman

Self-gated Radial MRI for Respiratory Motion Compensation on Hybrid PET/MR Systems

Accurate localization and uptake quantification of lesions in the chest and abdomen using PET imaging is challenging due to the respiratory motion during the exam. The advent of hybrid PET/MR systems offers new ways to compensate for respiratory motion without exposing the patient to additional radiation. The use of self-gated reconstructions of a 3D radial stack-of-stars GRE acquisition is proposed to derive a high-resolution MRI motion model. The self-gating signal is used to perform respiratory binning of the simultaneously acquired PET raw data. Matching mu-maps are generated for every bin, and post-reconstruction registration is performed in order to obtain a motion-compensated PET volume from the individual gates. The proposed method is demonstrated in-vivo for three clinical patients. Motion-corrected reconstructions are compared against ungated and gated PET reconstructions. In all cases, motion-induced blurring of lesions in the liver and lung was substantially reduced, without compromising SNR as it is the case for gated reconstructions.

Real-time optical motion correction for diffusion tensor imaging†

Head motion is a fundamental problem in brain MRI. The problem is further compounded in diffusion tensor imaging because of long acquisition times, and the sensitivity of the tensor computation to even small misregistration. To combat motion artifacts in diffusion tensor imaging, a novel real‐time prospective motion correction method was introduced using an in‐bore monovision system. The system consists of a camera mounted on the head coil and a self‐encoded checkerboard marker that is attached to the patients forehead. Our experiments showed that optical prospective motion correction is more effective at removing motion artifacts compared to image‐based retrospective motion correction. Statistical analysis revealed a significant improvement in similarity between diffusion data acquired at different time points when prospective correction was used compared to retrospective correction (P < 0.001). Magn Reson Med, 2010.

Self-gated MRI motion modeling for respiratory motion compensation in integrated PET/MRI

Accurate localization and uptake quantification of lesions in the chest and abdomen using PET imaging is challenged by respiratory motion occurring during the exam. This work describes how a stack-of-stars MRI acquisition on integrated PET/MRI systems can be used to derive a high-resolution motion model, how many respiratory phases need to be differentiated, how much MRI scan time is required, and how the model is employed for motion-corrected PET reconstruction. MRI self-gating is applied to perform respiratory gating of the MRI data and simultaneously acquired PET raw data. After gated PET reconstruction, the MRI motion model is used to fuse the individual gates into a single, motion-compensated volume with high signal-to-noise ratio (SNR). The proposed method is evaluated in vivo for 15 clinical patients. The gating requires 5-7 bins to capture the motion to an average accuracy of 2mm. With 5 bins, the motion-modeling scan can be shortened to 3-4 min. The motion-compensated reconstructions show significantly higher accuracy in lesion quantification in terms of standardized uptake value (SUV) and different measures of lesion contrast compared to ungated PET reconstruction. Furthermore, unlike gated reconstructions, the motion-compensated reconstruction does not lead to SNR loss.

Hybrid prospective and retrospective head motion correction to mitigate cross-calibration errors†

Utilization of external motion tracking devices is an emerging technology in head motion correction for MRI. However, cross‐calibration between the reference frames of the external tracking device and the MRI scanner can be tedious and remains a challenge in practical applications. In this study, we present two hybrid methods, both of which combine prospective, optical‐based motion correction with retrospective entropy‐based autofocusing to remove residual motion artifacts. Our results revealed that in the presence of cross‐calibration errors between the optical tracking device and the MR scanner, application of retrospective correction on prospectively corrected data significantly improves image quality. As a result of this hybrid prospective and retrospective motion correction approach, the requirement for a high‐quality calibration scan can be significantly relaxed, even to the extent that it is possible to perform external prospective motion tracking without any prior cross‐calibration step if a crude approximation of cross‐calibration matrix exists. Moreover, the motion tracking system, which is used to reduce the dimensionality of the autofocusing problem, benefits the retrospective approach at the same time. Magn Reson Med, 2012.

Self-encoded marker for optical prospective head motion correction in MRI

The tracking and compensation of patient motion during a magnetic resonance imaging (MRI) acquisition is an unsolved problem. For brain MRI, a promising approach recently suggested is to track the patient using an in-bore camera and a checkerboard marker attached to the patients forehead. However, the possible tracking range of the head pose is limited by the fact that the locally attached marker must be entirely visible inside the cameras narrow field of view (FOV). To overcome this shortcoming, we developed a novel self-encoded marker where each feature on the pattern is augmented with a 2-D barcode. Hence, the marker can be tracked even if it is not completely visible in the camera image. Furthermore, it offers considerable advantages over the checkerboard marker in terms of processing speed, since it makes the correspondence search of feature points and marker-model coordinates, which are required for the pose estimation, redundant. The motion correction with the novel self-encoded marker recovered a rotation of 18° around the principal axis of the cylindrical phantom in-between two scans. After rigid registration of the resulting volumes, we measured a maximal error of 0.39 mm and 0.15° in translation and rotation, respectively. In in vivo experiments, the motion compensated images in scans with large motion during data acquisition indicate a correlation of 0.982 compared to a corresponding motion-free reference.

Reduction of respiratory motion artifacts for free-breathing whole-heart coronary MRA by weighted iterative reconstruction

To combine weighted iterative reconstruction with self‐navigated free‐breathing coronary magnetic resonance angiography for retrospective reduction of respiratory motion artifacts.

Multi-Dimensional Flow-Preserving Compressed Sensing (MuFloCoS) for Time-Resolved Velocity-Encoded Phase Contrast MRI

4-D time-resolved velocity-encoded phase-contrast MRI (4-D PCI) is a fully non-invasive technique to assess hemodynamics in vivo with a broad range of potential applications in multiple cardiovascular diseases. It is capable of providing quantitative flow values and anatomical information simultaneously. The long acquisition time, however, still inhibits its wider clinical use. Acceleration is achieved at present using parallel MRI (pMRI) techniques which can lead to substantial loss of image quality for higher acceleration factors. Both the high-dimensionality and the significant degree of spatio-temporal correlation in 4-D PCI render it ideally suited for recently proposed compressed sensing (CS) techniques. We propose the Multi-Dimensional Flow-preserving Compressed Sensing (MuFloCoS) method to exploit these properties. A multi-dimensional iterative reconstruction is combined with an interleaved sampling pattern (I-VT), an adaptive masked and weighted temporal regularization (TMW) and fully automatically obtained vessel-masks. The performance of the novel method was analyzed concerning image quality, feasibility of acceleration factors up to 15, quantitative flow values and diagnostic accuracy in phantom experiments and an in vivo carotid study with 18 volunteers. Comparison with iterative state-of-the-art methods revealed significant improvements using the new method, the temporal normalized root mean square error of the peak velocity was reduced by 45.32% for the novel MuFloCoS method with acceleration factor 9. The method was furthermore applied to two patient cases with diagnosed high-grade stenosis of the ICA, which confirmed the performance of MuFloCoS to produce valuable results in the presence of pathological findings in 56 s instead of over 8 min (full sampling).

CoroEval: a multi-platform, multi-modality tool for the evaluation of 3D coronary vessel reconstructions

We present a software, called CoroEval, for the evaluation of 3D coronary vessel reconstructions from clinical data. It runs on multiple operating systems and is designed to be independent of the imaging modality used. At this point, its purpose is the comparison of reconstruction algorithms or acquisition protocols, not the clinical diagnosis. Implemented metrics are vessel sharpness and diameter. All measurements are taken from the raw intensity data to be independent of display windowing functions. The user can either import a vessel centreline segmentation from other software, or perform a manual segmentation in CoroEval. An automated segmentation correction algorithm is provided to improve non-perfect centrelines. With default settings, measurements are taken at 1 mm intervals along the vessel centreline and from 10 different angles at each measurement point. This allows for outlier detection and noise-robust measurements without the burden and subjectivity a manual measurement process would incur. Graphical measurement results can be directly exported to vector or bitmap graphics for integration into scientific publications. Centreline and lumen segmentations can be exported as point clouds and in various mesh formats. We evaluated the diameter measurement process using three phantom datasets. An average deviation of 0.03 ± 0.03 mm was found. The software is available in binary and source code form at http://www5.cs.fau.de/CoroEval/.

ToF/RGB Sensor Fusion for 3-D Endoscopy

Acquisition of 3-D anatomical structure in minimally invasive surgery is an important step towards intra-operative guidance. In this context, the rst prototype of a Time-of-Flight/RGB endoscope was engineered for simultaneous range and color data acquisition. Intrinsic and stereo camera calibration are essential to achieve an intuitive visualization of colored surfaces. Due to the early prototype stage, inhomogeneous illumination and low resolution (64×50 px) complicate the calibration signi cantly. To overcome these challenges, we propose a fully automatic multiscale calibration framework using a self-encoded marker for checkerboard detection. A rst application demonstrates the feasibility of intra-operative measurement. Using our calibration scheme, we achieved a reprojection error of less than 0.7 px for the Time-of-Flight camera and 0.5 px of the RGB camera. Our framework eases calibration and enables future applications to use combined range and colored data.

Single-breath-hold 3-D CINE imaging of the left ventricle using Cartesian sampling

Objectives Our objectives were to evaluate a single-breath-hold approach for Cartesian 3-D CINE imaging of the left ventricle with a nearly isotropic resolution of