Harmonization of PET image reconstruction parameters in simultaneous PET/MRI
Abstract Objective Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-11-01
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| Series: | EJNMMI Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40658-021-00416-0 |
| _version_ | 1819001435821441024 |
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| author | Richard Laforest Mehdi Khalighi Yutaka Natsuaki Abhejit Rajagopal Dharshan Chandramohan Darrin Byrd Hongyu An Peder Larson Sara St. James John J. Sunderland Paul E. Kinahan Thomas A. Hope |
| author_facet | Richard Laforest Mehdi Khalighi Yutaka Natsuaki Abhejit Rajagopal Dharshan Chandramohan Darrin Byrd Hongyu An Peder Larson Sara St. James John J. Sunderland Paul E. Kinahan Thomas A. Hope |
| author_sort | Richard Laforest |
| collection | DOAJ |
| description | Abstract Objective Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems. Method The NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3–7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction. Results The range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively. Conclusions For two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters. |
| first_indexed | 2024-12-20T22:49:10Z |
| format | Article |
| id | doaj.art-063d1abca2dd44aea3a2102b65498f69 |
| institution | Directory Open Access Journal |
| issn | 2197-7364 |
| language | English |
| last_indexed | 2024-12-20T22:49:10Z |
| publishDate | 2021-11-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EJNMMI Physics |
| spelling | doaj.art-063d1abca2dd44aea3a2102b65498f692022-12-21T19:24:17ZengSpringerOpenEJNMMI Physics2197-73642021-11-018112010.1186/s40658-021-00416-0Harmonization of PET image reconstruction parameters in simultaneous PET/MRIRichard Laforest0Mehdi Khalighi1Yutaka Natsuaki2Abhejit Rajagopal3Dharshan Chandramohan4Darrin Byrd5Hongyu An6Peder Larson7Sara St. James8John J. Sunderland9Paul E. Kinahan10Thomas A. Hope11Mallinckrodt Institute of Radiology, Washington UniversityDepartment of Radiology, Stanford UniversityDepartment of Radiation Oncology, University of California San FranciscoDepartment of Radiology and Biomedical Imaging, University of California San FranciscoDepartment of Radiology and Biomedical Imaging, University of California San FranciscoUniversity of IowaMallinckrodt Institute of Radiology, Washington UniversityDepartment of Radiology and Biomedical Imaging, University of California San FranciscoDepartment of Radiation Oncology, University of California San FranciscoUniversity of IowaUniversity of WashingtonDepartment of Radiology and Biomedical Imaging, University of California San FranciscoAbstract Objective Simultaneous PET/MRIs vary in their quantitative PET performance due to inherent differences in the physical systems and differences in the image reconstruction implementation. This variability in quantitative accuracy confounds the ability to meaningfully combine and compare data across scanners. In this work, we define image reconstruction parameters that lead to comparable contrast recovery curves across simultaneous PET/MRI systems. Method The NEMA NU-2 image quality phantom was imaged on one GE Signa and on one Siemens mMR PET/MRI scanner. The phantom was imaged at 9.7:1 contrast with standard spheres (diameter 10, 13, 17, 22, 28, 37 mm) and with custom spheres (diameter: 8.5, 11.5, 15, 25, 32.5, 44 mm) using a standardized methodology. Analysis was performed on a 30 min listmode data acquisition and on 6 realizations of 5 min from the listmode data. Images were reconstructed with the manufacturer provided iterative image reconstruction algorithms with and without point spread function (PSF) modeling. For both scanners, a post-reconstruction Gaussian filter of 3–7 mm in steps of 1 mm was applied. Attenuation correction was provided from a scaled computed tomography (CT) image of the phantom registered to the MR-based attenuation images and verified to align on the non-attenuation corrected PET images. For each of these image reconstruction parameter sets, contrast recovery coefficients (CRCs) were determined for the SUVmean, SUVmax and SUVpeak for each sphere. A hybrid metric combining the root-mean-squared discrepancy (RMSD) and the absolute CRC values was used to simultaneously optimize for best match in CRC between the two scanners while simultaneously weighting toward higher resolution reconstructions. The image reconstruction parameter set was identified as the best candidate reconstruction for each vendor for harmonized PET image reconstruction. Results The range of clinically relevant image reconstruction parameters demonstrated widely different quantitative performance across cameras. The best match of CRC curves was obtained at the lowest RMSD values with: for CRCmean, 2 iterations-7 mm filter on the GE Signa and 4 iterations-6 mm filter on the Siemens mMR, for CRCmax, 4 iterations-6 mm filter on the GE Signa, 4 iterations-5 mm filter on the Siemens mMR and for CRCpeak, 4 iterations-7 mm filter with PSF on the GE Signa and 4 iterations-7 mm filter on the Siemens mMR. Over all reconstructions, the RMSD between CRCs was 1.8%, 3.6% and 2.9% for CRC mean, max and peak, respectively. The solution of 2 iterations-3 mm on the GE Signa and 4 iterations-3 mm on Siemens mMR, both with PSF, led to simultaneous harmonization and with high CRC and low RMSD for CRC mean, max and peak with RMSD values of 2.8%, 5.8% and 3.2%, respectively. Conclusions For two commercially available PET/MRI scanners, user-selectable parameters that control iterative updates, image smoothing and PSF modeling provide a range of contrast recovery curves that allow harmonization in harmonization strategies of optimal match in CRC or high CRC values. This work demonstrates that nearly identical CRC curves can be obtained on different commercially available scanners by selecting appropriate image reconstruction parameters.https://doi.org/10.1186/s40658-021-00416-0Image reconstructionHarmonizationPET/MRIPhantom |
| spellingShingle | Richard Laforest Mehdi Khalighi Yutaka Natsuaki Abhejit Rajagopal Dharshan Chandramohan Darrin Byrd Hongyu An Peder Larson Sara St. James John J. Sunderland Paul E. Kinahan Thomas A. Hope Harmonization of PET image reconstruction parameters in simultaneous PET/MRI EJNMMI Physics Image reconstruction Harmonization PET/MRI Phantom |
| title | Harmonization of PET image reconstruction parameters in simultaneous PET/MRI |
| title_full | Harmonization of PET image reconstruction parameters in simultaneous PET/MRI |
| title_fullStr | Harmonization of PET image reconstruction parameters in simultaneous PET/MRI |
| title_full_unstemmed | Harmonization of PET image reconstruction parameters in simultaneous PET/MRI |
| title_short | Harmonization of PET image reconstruction parameters in simultaneous PET/MRI |
| title_sort | harmonization of pet image reconstruction parameters in simultaneous pet mri |
| topic | Image reconstruction Harmonization PET/MRI Phantom |
| url | https://doi.org/10.1186/s40658-021-00416-0 |
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