Hyun Joon An1, Seongho Seo2, Hyejin Kang3, Hongyoon Choi3, Gi Jeong Cheon4, Han-Joon Kim5, Dong Soo Lee6, In Chan Song7, Yu Kyeong Kim8, Jae Sung Lee9. 1. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea. 2. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea. 3. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea. 4. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Institute of Radiation Medicine, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea. 5. Department of Neurology, Seoul National University College of Natural Sciences, Seoul, Korea. 6. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Institute of Radiation Medicine, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Suwon, Korea. 7. Department of Radiology, Seoul National University College of Medicine, Seoul, Korea; and. 8. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Department of Nuclear Medicine, Seoul Metropolitan Government Boramae Medical Center, Seoul, Korea jaes@snu.ac.kr yk3181@snu.ac.kr. 9. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Korea Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Korea Institute of Radiation Medicine, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea jaes@snu.ac.kr yk3181@snu.ac.kr.
Abstract
UNLABELLED: Inaccuracy in MR image-based attenuation correction (MR-AC) leads to errors in quantification and the misinterpretation of lesions in brain PET/MRI studies. To resolve this problem, we proposed an improved ultrashort echo time MR-AC method that was based on a multiphase level-set algorithm with main magnetic field (B0) inhomogeneity correction. We also assessed the feasibility of this level-set-based MR-AC method (MR-AC(level)), compared with CT-AC and MR-AC provided by the manufacturer of the PET/MRI scanner (MR-AC(mMR)). METHODS: Ten healthy volunteers and 20 Parkinson disease patients underwent(18)F-FDG and(18)F-fluorinated-N-3-fluoropropyl-2-β-carboxymethoxy-3-β-(4-iodophenyl)nortropane ((18)F-FP-CIT) PET scans, respectively, using both PET/MRI and PET/CT scanners. The level-set-based segmentation algorithm automatically delimited air, bone, and soft tissue from the ultrashort echo time MR images. For the comparison, MR-AC maps were coregistered to reference CT. PET sinogram data obtained from PET/CT studies were then reconstructed using the CT-AC, MR-AC(mMR), and MR-AC(level) maps. The accuracies of SUV, SUVr (SUV and its ratio to the cerebellum), and specific-to-nonspecific binding ratios obtained using MR-AC(level) and MR-AC(mMR) were compared with CT-AC using region-of-interest- and voxel-based analyses. RESULTS: There was remarkable improvement in the segmentation of air cavities and bones and the quantitative accuracy of PET measurement using the level set. Although the striatal and cerebellar activities in (18)F-FP-CIT PET and frontal activity in (18)F-FDG PET were significantly underestimated by the MR-AC(mMR), the MR-AC(level) provided PET images almost equivalent to the CT-AC images. PET quantification error was reduced by a factor of 3 using MR-AC(level) (SUV error < 10% in MR-AC(level) and < 30% in MR-AC(mMR) [version VB18P], and < 5% in MR-AC(level) and < 15% in MR-AC(mMR) [VB20P]). CONCLUSION: The results of this study indicate that our new multiphase level-set-based MR-AC method improves the quantitative accuracy of brain PET in PET/MRI studies.
UNLABELLED: Inaccuracy in MR image-based attenuation correction (MR-AC) leads to errors in quantification and the misinterpretation of lesions in brain PET/MRI studies. To resolve this problem, we proposed an improved ultrashort echo time MR-AC method that was based on a multiphase level-set algorithm with main magnetic field (B0) inhomogeneity correction. We also assessed the feasibility of this level-set-based MR-AC method (MR-AC(level)), compared with CT-AC and MR-AC provided by the manufacturer of the PET/MRI scanner (MR-AC(mMR)). METHODS: Ten healthy volunteers and 20 Parkinson diseasepatients underwent(18)F-FDG and(18)F-fluorinated-N-3-fluoropropyl-2-β-carboxymethoxy-3-β-(4-iodophenyl)nortropane ((18)F-FP-CIT) PET scans, respectively, using both PET/MRI and PET/CT scanners. The level-set-based segmentation algorithm automatically delimited air, bone, and soft tissue from the ultrashort echo time MR images. For the comparison, MR-AC maps were coregistered to reference CT. PET sinogram data obtained from PET/CT studies were then reconstructed using the CT-AC, MR-AC(mMR), and MR-AC(level) maps. The accuracies of SUV, SUVr (SUV and its ratio to the cerebellum), and specific-to-nonspecific binding ratios obtained using MR-AC(level) and MR-AC(mMR) were compared with CT-AC using region-of-interest- and voxel-based analyses. RESULTS: There was remarkable improvement in the segmentation of air cavities and bones and the quantitative accuracy of PET measurement using the level set. Although the striatal and cerebellar activities in (18)F-FP-CIT PET and frontal activity in (18)F-FDG PET were significantly underestimated by the MR-AC(mMR), the MR-AC(level) provided PET images almost equivalent to the CT-AC images. PET quantification error was reduced by a factor of 3 using MR-AC(level) (SUV error < 10% in MR-AC(level) and < 30% in MR-AC(mMR) [version VB18P], and < 5% in MR-AC(level) and < 15% in MR-AC(mMR) [VB20P]). CONCLUSION: The results of this study indicate that our new multiphase level-set-based MR-AC method improves the quantitative accuracy of brain PET in PET/MRI studies.
Authors: Paul Kyu Han; Debra E Horng; Kuang Gong; Yoann Petibon; Kyungsang Kim; Quanzheng Li; Keith A Johnson; Georges El Fakhri; Jinsong Ouyang; Chao Ma Journal: Med Phys Date: 2020-05-11 Impact factor: 4.071