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

Grimm, Robert; Fürst, Sebastian; Souvatzoglou, Michael; Forman, Christoph; Hutter, Jana; Dregely, Isabel; Ziegler, Sibylle; Kiefer, Berthold; Hornegger, Joachim; Block, Kai Tobias; Nekolla, Stephan G.

doi:10.1016/j.media.2014.08.003

Cited by 109 publications

(117 citation statements)

References 41 publications

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“…Recently, the use of data-driven methods has gained substantial interest for both stand-alone and multi-modality imaging systems [185][186][187][188]. Continuous motion tracking can be used for motion compensation of PET and MR images [189,190].…”

Section: Motion Compensationmentioning

confidence: 99%

“…Continuous motion tracking can be used for motion compensation of PET and MR images [189,190]. In thoracic PET imaging, several motion detection techniques have been proposed, through builtin readout of the respiratory position and special radial-self gating sequences, respectively [186,187,191]. Cardiac motion is most commonly estimated by using cine-MR imaging and tagged MR imaging [192].…”

Section: Motion Compensationmentioning

confidence: 99%

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Hybrid Imaging: Instrumentation and Data Processing

et al. 2018

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State-of-the-art patient management frequently requires the use of non-invasive imaging methods to assess the anatomy, function or molecular-biological conditions of patients or study subjects. Such imaging methods can be singular, providing either anatomical or molecular information, or they can be combined, thus, providing "anato-metabolic" information. Hybrid imaging denotes image acquisitions on systems that physically combine complementary imaging modalities for an improved diagnostic accuracy and confidence as well as for increased patient comfort. The physical combination of formerly independent imaging modalities was driven by leading innovators in the field of clinical research and benefited from technological advances that permitted the operation of PET and MR in close physical proximity, for example. This review covers milestones of the development of various hybrid imaging systems for use in clinical practice and small-animal research. Special attention is given to technological advances that helped the adoption of hybrid imaging, as well as to introducing methodological concepts that benefit from the availability of complementary anatomical and biological information, such as new types of image reconstruction and data correction schemes. The ultimate goal of hybrid imaging is to provide useful, complementary and quantitative information during patient work-up. Hybrid imaging also opens the door to multi-parametric assessment of diseases, which will help us better understand the causes of various diseases that currently contribute to a large fraction of healthcare costs.

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Section: Motion Compensationmentioning

confidence: 99%

Section: Motion Compensationmentioning

confidence: 99%

Hybrid Imaging: Instrumentation and Data Processing

et al. 2018

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“…As PET and possibly MR data have to be gated retrospectively, exact knowledge of the corresponding respiratory state is required at any time point during the examination. Within the scope of this study, this was achieved by the acquisition of respiratory signals according to 5 methods, that is, the pressure-sensitive respiratory bellows (resp_bellows) that is shipped with the scanner by default, a prototype implementation of a self-gated MR imaging pulse sequence (resp_mr) (25,26), the PET-based sensitivity method (resp_sens) (9,10), and the application of dimensionality reduction techniques such as principal component analysis (PCA) or Laplacian eigenmaps to the sinogram space (resp_pca and resp_le, respectively) (11,27,28). Before execution of the PET-based methods, the list-mode streams were divided into nonoverlapping 200-ms time frames.…”

Section: Motion Correction Strategiesmentioning

confidence: 99%

Motion Correction Strategies for Integrated PET/MR

et al. 2015

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and 5 Siemens Healthcare MI, Knoxville, TennesseeIntegrated 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 18 F-FDG or 68 Ga-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 PETbased 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 MRbased 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.

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“…Previous studies have revealed that PET/MR provides good performance in the investigation of brain function, tumor, and degenerative diseases (1). The combined MRI system not only delivers detailed brain anatomy, but also can make PET image quality better by correcting partial-volume effects or motion artifacts (2,3). In addition, radiation exposure derived from CT scans was saved by replacing CT with MRI.…”

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confidence: 99%

Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain ¹⁸F-FDG PET/MRI: Comparison with Atlas Attenuation Correction

et al. 2016

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Accurate attenuation correction (AC) on PET/MR is still challenging. The purpose of this study was to evaluate the clinical feasibility of AC based on fast zero-echo-time (ZTE) MRI by comparing it with the default atlas-based AC on a clinical PET/MR scanner. Methods: We recruited 10 patients with malignant diseases not located on the brain. In all patients, a clinically indicated whole-body 18 F-FDG PET/CT scan was acquired. In addition, a head PET/MR scan was obtained voluntarily. For each patient, 2 AC maps were generated from the MR images. One was atlas-AC, derived from T1-weighted liver acquisition with volume acceleration flex images (clinical standard). The other was ZTE-AC, derived from proton-density-weighted ZTE images by applying tissue segmentation and assigning continuous attenuation values to the bone. The AC map generated by PET/CT was used as a silver standard. On the basis of each AC map, PET images were reconstructed from identical raw data on the PET/MR scanner. All PET images were normalized to the SPM5 PET template. After that, these images were qualified visually and quantified in 67 volumes of interest (VOIs; automated anatomic labeling, atlas). Relative differences and absolute relative differences between PET images based on each AC were calculated. 18 F-FDG uptake in all 670 VOIs and generalized merged VOIs were compared using a paired t test. Results: Qualitative analysis shows that ZTE-AC was robust to patient variability. Nevertheless, misclassification of air and bone in mastoid and nasal areas led to the overestimation of PET in the temporal lobe and cerebellum (%diff of ZTE-AC, 2.46% ± 1.19% and 3.31% ± 1.70%, respectively). The j%diffj of all 670 VOIs on ZTE was improved by approximately 25% compared with atlas-AC (ZTE-AC vs. atlas-AC, 1.77% ± 1.41% vs. 2.44% ± 1.63%, P , 0.01). In 2 of 7 generalized VOIs, j%diffj on ZTE-AC was significantly smaller than atlas-AC (ZTE-AC vs. atlas-AC: insula and cingulate, 1.06% ± 0.67% vs. 2.22% ± 1.10%, P , 0.01; central structure, 1.03% ± 0.99% vs. 2.54% ± 1.20%, P , 0.05). Conclusion: The ZTE-AC could provide more accurate AC than clinical atlas-AC by improving the estimation of head-skull attenuation. The misclassification in mastoid and nasal areas must be addressed to prevent the overestimation of PET in regions near the skull base.

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

Cited by 109 publications

References 41 publications

Hybrid Imaging: Instrumentation and Data Processing

Hybrid Imaging: Instrumentation and Data Processing

Motion Correction Strategies for Integrated PET/MR

Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain ¹⁸F-FDG PET/MRI: Comparison with Atlas Attenuation Correction

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

Cited by 109 publications

References 41 publications

Hybrid Imaging: Instrumentation and Data Processing

Hybrid Imaging: Instrumentation and Data Processing

Motion Correction Strategies for Integrated PET/MR

Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain 18F-FDG PET/MRI: Comparison with Atlas Attenuation Correction

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Clinical Evaluation of Zero-Echo-Time Attenuation Correction for Brain ¹⁸F-FDG PET/MRI: Comparison with Atlas Attenuation Correction