Relative role of motion and PSF compensation in whole‐body oncologic PET‐MR imaging

Petibon, Yoann; Huang, Chuan; Ouyang, Jinsong; Reese, Timothy G.; Li, Quanzheng; Сыркина, А.Л.; Chen, Yen‐Lin; Fakhri, Georges El

doi:10.1118/1.4868458

Cited by 37 publications

(49 citation statements)

References 47 publications

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“…This finding contrasts with our observation and may hint at the advantages of motion correction incorporated into the reconstruction algorithm, where in the present study for both evaluated methods contrast and SNR were significantly better than in gated images but tracer uptake and volume were not significantly different (resp_bestpet). Petibon et al (24) reconstructed motioncorrected images of one liver case using MR-derived motion information. They reported comparable results, that is, an increase in target-to-background ratio, which was defined identically to contrast as used by Würslin, of between 22% and 45%, whereas apparent lesion volumes decreased by between 13% and 29%, depending on the lesion, if compared with static images.…”

Section: Discussionmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

“…The respective authors derived their results either from animal studies (16) or with simulated or phantom data (17)(18)(19)(20)(21)(22). PET-driven motion correction was assessed with the data of 14 patients (14), whereas MR-based motion correction has so far been evaluated with the data of 5 patients at most (23,24).…”

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Motion Correction Strategies for Integrated PET/MR

et al. 2015

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“…Although a recent study has investigated the role of motion compensation and PSF modeling in PET/MR imaging (16), studies investigating the effect of PSF reconstruction on clinical data in the context of PET/MR hybrid imaging are still sparse. The main objective of our study, thus, was to systematically investigate the impact of PSF-based reconstruction on PET/MR quantitatively and qualitatively in phantom experiments, as well as in patients.…”

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Impact of Point-Spread Function Modeling on PET Image Quality in Integrated PET/MR Hybrid Imaging

et al. 2015

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The aim of this study was to systematically assess the quantitative and qualitative impact of including point-spread function (PSF) modeling into the process of iterative PET image reconstruction in integrated PET/MR imaging. Methods: All measurements were performed on an integrated whole-body PET/MR system. Three substudies were performed: an 18 F-filled Jaszczak phantom was measured, and the impact of including PSF modeling in ordinary Poisson orderedsubset expectation maximization reconstruction on quantitative accuracy and image noise was evaluated for a range of radial phantom positions, iteration numbers, and postreconstruction smoothing settings; 5 representative datasets from a patient population (total n 5 20, all oncologic 18 F-FDG PET/MR) were selected, and the impact of PSF on lesion activity concentration and image noise for various iteration numbers and postsmoothing settings was evaluated; and for all 20 patients, the influence of PSF modeling was investigated on visual image quality and number of detected lesions, both assessed by clinical experts. Additionally, the influence on objective metrics such as changes in SUV mean , SUV peak , SUV max , and lesion volume was assessed using the manufacturer-recommended reconstruction settings. Results: In the phantom study, PSF modeling significantly improved activity recovery and reduced the image noise at all radial positions. This effect was measurable only at a high number of iterations (.10 iterations, 21 subsets). In the patient study, again, PSF increased the detected activity in the patient's lesions at concurrently reduced image noise. Contrary to the phantom results, the effect was notable already at a lower number of iterations (.1 iteration, 21 subsets). Lastly, for all 20 patients, when PSF and no-PSF reconstructions were compared, an identical number of congruent lesions was found. The overall image quality of the PSF reconstructions was rated better when compared with no-PSF data. The SUVs of the detected lesions with PSF were substantially increased in the range of 6%-75%, 5%-131%, and 5%-148% for SUV mean , SUV peak , and SUV max , respectively. A regression analysis showed that the relative increase in SUV mean/peak/max decreases with increasing lesion size, whereas it increases with the distance from the center of the PET field of view. Conclusion: In whole-body PET/MR hybrid imaging, PSF-based PET reconstructions can improve activity recovery and image noise, especially at lateral positions of the PET field of view. This has been demonstrated quantitatively in phantom experiments as well as in patient imaging, for which additionally an improvement of image quality could be observed. Si multaneous hybrid imaging with PET and MR (PET/MR) combines MR's excellent soft-tissue contrast with the high sensitivity and quantitative information of radiotracer metabolism imaged in PET (1-5). It was shown that PET/MR may provide early detection of metastases and guidance in therapy selection and can also improve the process of clinical patient man...

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“…The breathing is modeled here as a rigid transformation (only translations, no rotation) by a 3D anisotropic kernel with the maximum amplitudes, 50 but the location-specific motion, i.e., larger at the liver dome, and smaller toward the inferior part, can be applied, requiring a combination of rigid and nonrigid transformations. 50,60 In this scenario, image correction would be challenging, due to the limited number of features provided by commercial software. 61 However, some authors claimed that considering a rigid motion, the error is of the order of 3 mm.…”

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Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

et al. 2016

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Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of 99m Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a "liver's segment," or distributing multiple uptaking nodules ("nonuniform liver"), with a tumoral liver/healthy parenchyma ratio of 5:1. Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and 99m Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the "gold standard," GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%-14% for a liver segment, and by 7%-12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver's segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy paren...

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Relative role of motion and PSF compensation in whole‐body oncologic PET‐MR imaging

Cited by 37 publications

References 47 publications

Motion Correction Strategies for Integrated PET/MR

Motion Correction Strategies for Integrated PET/MR

Impact of Point-Spread Function Modeling on PET Image Quality in Integrated PET/MR Hybrid Imaging

Impact of SPECT corrections on 3D‐dosimetry for liver transarterial radioembolization using the patient relative calibration methodology

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