MR‐assisted PET respiratory motion correction using deep‐learning based short‐scan motion fields. Issue 2 (28th March 2022)
- Record Type:
- Journal Article
- Title:
- MR‐assisted PET respiratory motion correction using deep‐learning based short‐scan motion fields. Issue 2 (28th March 2022)
- Main Title:
- MR‐assisted PET respiratory motion correction using deep‐learning based short‐scan motion fields
- Authors:
- Chen, Sihao
Fraum, Tyler J.
Eldeniz, Cihat
Mhlanga, Joyce
Gan, Weijie
Vahle, Thomas
Krishnamurthy, Uday B.
Faul, David
Gach, H. Michael
Binkley, Michael M.
Kamilov, Ulugbek S.
Laforest, Richard
An, Hongyu - Abstract:
- Abstract : Purpose: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep‐learning reconstructed short MRI scan. Methods: The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI‐based MVFs were derived from either 2000 spokes (MoCo2000, 5–6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCoP2P200, 30–40 s acquisition time) using a deep‐learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUVmax, SUVpeak, SUVmean, lesion volume) and a blinded radiological review on lesion conspicuity. Results: MRI‐assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo2000 and MoCoP2P200 PET images had significantly higher SUVmax, SUVpeak, SUVmean and significantly lower lesion volume than non‐motion‐corrected (non‐MoCo) PET images. There was no statistical difference between MoCo2000 and MoCoP2P200 PET images for SUVmax, SUVpeak, SUVmean or lesion volume. Both radiological reviewers found that MoCo2000 and MoCoP2P200 PET significantly improved lesion conspicuity.Abstract : Purpose: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo approach using motion vector fields (MVFs) from a deep‐learning reconstructed short MRI scan. Methods: The evaluation of PET MoCo was performed in a respiratory motion phantom study with varying lesion sizes and tumor to background ratios (TBRs) using a static scan as the ground truth. MRI‐based MVFs were derived from either 2000 spokes (MoCo2000, 5–6 min acquisition time) using a Fourier transform reconstruction or 200 spokes (MoCoP2P200, 30–40 s acquisition time) using a deep‐learning Phase2Phase (P2P) reconstruction and then incorporated into PET MoCo reconstruction. For six patients with hepatic lesions, the performance of PET MoCo was evaluated using quantitative metrics (SUVmax, SUVpeak, SUVmean, lesion volume) and a blinded radiological review on lesion conspicuity. Results: MRI‐assisted PET MoCo methods provided similar results to static scans across most lesions with varying TBRs in the phantom. Both MoCo2000 and MoCoP2P200 PET images had significantly higher SUVmax, SUVpeak, SUVmean and significantly lower lesion volume than non‐motion‐corrected (non‐MoCo) PET images. There was no statistical difference between MoCo2000 and MoCoP2P200 PET images for SUVmax, SUVpeak, SUVmean or lesion volume. Both radiological reviewers found that MoCo2000 and MoCoP2P200 PET significantly improved lesion conspicuity. Conclusion: An MRI‐assisted PET MoCo method was evaluated using the ground truth in a phantom study. In patients with hepatic lesions, PET MoCo images improved quantitative and qualitative metrics based on only 30–40 s of MRI motion modeling data. … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 88:Issue 2(2022)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 88:Issue 2(2022)
- Issue Display:
- Volume 88, Issue 2 (2022)
- Year:
- 2022
- Volume:
- 88
- Issue:
- 2
- Issue Sort Value:
- 2022-0088-0002-0000
- Page Start:
- 676
- Page End:
- 690
- Publication Date:
- 2022-03-28
- Subjects:
- CAPTURE -- deep learning -- free‐breathing -- P2P -- PET/MRI -- respiratory motion correction
Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.29233 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
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- 22129.xml