Robert Grimm

Golden‐angle radial sparse parallel MRI: Combination of compressed sensing, parallel imaging, and golden‐angle radial sampling for fast and flexible dynamic volumetric MRI

To develop a fast and flexible free‐breathing dynamic volumetric MRI technique, iterative Golden‐angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed sensing, parallel imaging, and golden‐angle radial sampling.

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.

Motion Correction Strategies for Integrated PET/MR

Integrated whole-body PET/MR facilitates the implementation of a broad variety of respiratory motion correction strategies, taking advantage of the strengths of both modalities. The goal of this study was the quantitative evaluation with clinical data of different MR- and PET-data–based motion correction strategies for integrated PET/MR. Methods: The PET and MR data of 20 patients were simultaneously acquired for 10 min on an integrated PET/MR system after administration of 18F-FDG or 68Ga-DOTANOC. Respiratory traces recorded with a bellows were compared against MR self-gating signals and signals extracted from PET raw data with the sensitivity method, by applying principal component analysis (PCA) or Laplacian eigenmaps and by using a novel variation combining the former and either of the latter two. Gated sinograms and MR images were generated accordingly, followed by image registration to derive MR motion models. Corrected PET images were reconstructed by incorporating this information into the reconstruction. An optical flow algorithm was applied for PET-based motion correction. Gating and motion correction were evaluated by quantitative analysis of apparent tracer uptake, lesion volume, displacement, contrast, and signal-to-noise ratio. Results: The correlation between bellows- and MR-based signals was 0.63 ± 0.19, and that between MR and the sensitivity method was 0.52 ± 0.26. Depending on the PET raw-data compression, the average correlation between MR and PCA ranged from 0.25 ± 0.30 to 0.58 ± 0.33, and the range was 0.25 ± 0.30 to 0.42 ± 0.34 if Laplacian eigenmaps were applied. By combining the sensitivity method and PCA or Laplacian eigenmaps, the maximum average correlation to MR could be increased to 0.74 ± 0.21 and 0.70 ± 0.19, respectively. The selection of the best PET-based signal for each patient yielded an average correlation of 0.80 ± 0.13 with MR. Using the best PET-based respiratory signal for gating, mean tracer uptake increased by 17 ± 19% for gating, 13 ± 10% for MR-based motion correction, and 18 ± 15% for PET-based motion correction, compared with the static images. Lesion volumes were 76 ± 31%, 83 ± 18%, and 74 ± 22% of the sizes in the static images for gating, MR-based motion correction, and PET-based motion correction, respectively. Conclusion: Respiratory traces extracted from MR and PET data are comparable to those based on external sensors. The proposed PET-driven gating method improved respiratory signals and overall stability. Consistent results from MR- and PET-based correction methods enable more flexible PET/MR scan protocols while achieving higher PET image quality.

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.

Dynamic contrast-enhanced MRI of the prostate with high spatiotemporal resolution using compressed sensing, parallel imaging, and continuous golden-angle radial sampling: Preliminary experience

To demonstrate dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) of the prostate with both high spatial and temporal resolution via a combination of golden‐angle radial k‐space sampling, compressed sensing, and parallel‐imaging reconstruction (GRASP), and to compare image quality and lesion depiction between GRASP and conventional DCE in prostate cancer patients.

Histogram analysis of apparent diffusion coefficient at 3.0t: Correlation with prognostic factors and subtypes of invasive ductal carcinoma

To evaluate apparent diffusion coefficient (ADC) histogram parameters that show correlations with prognostic factors and subtypes of breast cancer.

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.

Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer.

To investigate the usefulness of apparent diffusion coefficient (ADC) values derived from histogram analysis of the whole rectal cancer as a quantitative parameter to evaluate pathologic complete response (pCR) on preoperative magnetic resonance imaging (MRI).

Markerless estimation of patient orientation, posture and pose using range and pressure imaging

PurposeIn diagnostic tomographic imaging, patient setup and scanner initialization is a manual, tedious procedure in clinical practice. A fully-automatic detection of the patient’s position, orientation, posture and pose on the patient table holds great potential for optimizing this part of the imaging workflow. We propose a markerless framework that is capable of extracting this information within seconds from either range imaging (RI) or pressure imaging (PI) data.MethodsThe proposed method is composed of three stages: First, the position and orientation of the reclined patient are determined. Second, the patient’s posture is classified. Third, based on the estimated orientation and posture, an approximate body pose is recovered by fitting an articulated model to the observed RI/PI data. Being a key issue for clinical application, our approach does not require an initialization pose.ResultsIn a case study on real data from 16 subjects, the performance of the proposed system was evaluated quantitatively with a 3-D time-of-flight RI camera and a pressure sensing mattress (PI). The patient orientation was successfully determined for all subjects, independent of the modality. At the posture recognition stage, our method achieved mean classification rates of 79.4% for RI and 95.5% for PI data, respectively. Concerning the approximate body pose estimation, anatomical body landmarks were localized with an accuracy of ±5.84cm (RI) and ±5.53cm (PI).ConclusionsThe results indicate that an estimation of the patient’s position, orientation, posture and pose using RI and PI sensors, respectively, is feasible, and beneficial for optimizing the workflow in diagnostic tomographic imaging. Both modalities achieved comparable pose estimation results using different models that account for modality-specific characteristics. PI outperforms RI in discriminating between prone and supine postures due to the distinctive pressure distribution of the human body.

One-Stop Shop: Free-Breathing Dynamic Contrast-Enhanced Magnetic Resonance Imaging of the Kidney Using Iterative Reconstruction and Continuous Golden-Angle Radial Sampling.

Aims and ObjectivesThe purpose of the present study was to evaluate a recently introduced technique for free-breathing dynamic contrast-enhanced renal magnetic resonance imaging (MRI) applying a combination of radial k-space sampling, parallel imaging, and compressed sensing. The technique allows retrospective reconstruction of 2 motion-suppressed sets of images from the same acquisition: one with lower temporal resolution but improved image quality for subjective image analysis, and one with high temporal resolution for quantitative perfusion analysis. Materials and MethodsIn this study, 25 patients underwent a kidney examination, including a prototypical fat-suppressed, golden-angle radial stack-of-stars T1-weighted 3-dimensional spoiled gradient-echo examination (GRASP) performed after contrast agent administration during free breathing. Images were reconstructed at temporal resolutions of 55 spokes per frame (6.2 seconds) and 13 spokes per frame (1.5 seconds). The GRASP images were evaluated by 2 blinded radiologists. First, the reconstructions with low temporal resolution underwent subjective image analysis: the radiologists assessed the best arterial phase and the best renal phase and rated image quality score for each patient on a 5-point Likert-type scale.In addition, the diagnostic confidence was rated according to a 3-point Likert-type scale. Similarly, respiratory motion artifacts and streak artifacts were rated according to a 3-point Likert-type scale.Then, the reconstructions with high temporal resolution were analyzed with a voxel-by-voxel deconvolution approach to determine the renal plasma flow, and the results were compared with values reported in previous literature. ResultsReader 1 and reader 2 rated the overall image quality score for the best arterial phase and the best renal phase with a median image quality score of 4 (good image quality) for both phases, respectively. A high diagnostic confidence (median score of 3) was observed. There were no respiratory motion artifacts in any of the patients. Streak artifacts were present in all of the patients, but did not compromise diagnostic image quality.The estimated renal plasma flow was slightly higher (295 ± 78 mL/100 mL per minute) than reported in previous MRI-based studies, but also closer to the physiologically expected value. ConclusionsDynamic, motion-suppressed contrast-enhanced renal MRI can be performed in high diagnostic quality during free breathing using a combination of golden-angle radial sampling, parallel imaging, and compressed sensing. Both morphologic and quantitative functional information can be acquired within a single acquisition.