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Updated: Jul 17, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Segmentation-based MR attenuation correction including bones also affects quantitation in brain studies: an initial
Hongyoon Choi1, Gi Jeong Cheon2, Han-Joon Kim3
1Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Korea Department of Molecular Medicine and Biopharmaceutical Science, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Korea.
Unlabelled:
Attenuation correction (AC) with an ultrashort echo time (UTE) sequence has recently been used in combination with segmentation for cortical bone identification for brain PET/MR studies. The purpose of this study was to evaluate the quantification of (18)F-fluoropropyl-carbomethoxyiodophenylnortropane ((18)F-FP-CIT) binding in brain PET/MR, particularly focusing on effects of UTE-based AC including bone segmentation.
Methods:
Sixteen patients with initially suspected parkinsonism were prospectively enrolled. An emission scan was acquired 110 min after (18)F-FP-CIT injection on a dedicated PET/MR scanner, immediately followed by another emission scan using a PET/CT scanner 120 min after the injection. A UTE-based attenuation map was used to classify the voxels into 3 tissues: bone, soft tissue, and air. All PET images were spatially normalized, and a specific-to-nonspecific dopamine transporter (DAT) binding ratio (BR) was calculated using statistical probabilistic anatomic mapping. The level of agreement was assessed with intraclass correlation coefficients (ICCs). Voxelwise comparison between PET images acquired from PET/MR and PET/CT was performed. We compared non-attenuation-corrected images to analyze UTE-based AC effects on DAT quantification.
Results:
BR in the putamen obtained from PET/MR and PET/CT showed low interequipment variability, whereas BR in the caudate nucleus showed significant variability (ICC = 0.967 and 0.682 for putamen and caudate nucleus, respectively). BR in the caudate nucleus was significantly underestimated by PET/MR, compared with PET/CT (mean difference of BR = 0.66, P < 0.0001). Voxelwise analysis revealed that PET/MR showed significantly low BR in the periventricular regions, which was caused by a misclassification of the ventricle as air on the attenuation map. We also compared non-AC images, revealing low interequipment variability even in the caudate nucleus (ICC = 0.937 and 0.832 for putamen and caudate nucleus, respectively).
Conclusion:
Our data demonstrate spatial bias of the DAT BR on (18)F-FP-CIT PET/MR. Voxelwise analysis and comparison to non-AC images identified the misclassification of ventricle as air to be the cause of bias. To obtain reliable quantification for brain PET/MR studies including (18)F-FP-CIT PET, alternative and more reliable segmentation strategies are required.
