An SPM8-based approach for attenuation correction combining segmentation and nonrigid template formation: Application to simultaneous PET/MR Brain Imaging
Journal
Journal of Nuclear Medicine
Journal Volume
55
Journal Issue
11
Pages
1825-1830
Date Issued
2014
Author(s)
Izquierdo-Garcia D.
Hansen A.E.
F?rster S.
Benoit D.
Schachoff S.
F?rst S.
Chen K.T.
Chonde D.B.
Catana C.
Abstract
We present an approach for head MR-based attenuation correction (AC) based on the Statistical Parametric Mapping 8 (SPM8) software, which combines segmentation- and atlas-based features to provide a robust technique to generate attenuation maps (μ maps) from MR data in integrated PET/MR scanners. Methods: Coregistered anatomic MR and CT images of 15 glioblastoma subjects were used to generate the templates. The MR images from these subjects were first segmented into 6 tissue classes (gray matter, white matter, cerebrospinal fluid, bone, soft tissue, and air), which were then nonrigidly coregistered using a diffeomorphic approach. A similar procedure was used to coregister the anatomic MR data for a new subject to the template. Finally, the CT-like images obtained by applying the inverse transformations were converted to linear attenuation coefficients to be used for AC of PET data. The method was validated on 16 new subjects with brain tumors (n 5 12) or mild cognitive impairment (n 5 4) who underwent CT and PET/MR scans. The μ maps and corresponding reconstructed PET images were compared with those obtained using the gold standard CT-based approach and the Dixon-based method available on the Biograph mMR scanner. Relative change (RC) images were generated in each case, and voxel- and regionof- interest-based analyses were performed. Results: The leaveone- out cross-validation analysis of the data from the 15 atlasgeneration subjects showed small errors in brain linear attenuation coefficients (RC, 1.38% ± 4.52%) compared with the gold standard. Similar results (RC, 1.86% ± 4.06%) were obtained from the analysis of the atlas-validation datasets. The voxel- and region-of-interest- based analysis of the corresponding reconstructed PET images revealed quantification errors of 3.87% ± 5.0% and 2.74% ± 2.28%, respectively. The Dixon-based method performed substantially worse (the mean RC values were 13.0% ± 10.25% and 9.38% ± 4.97%, respectively). Areas closer to the skull showed the largest improvement. Conclusion: We have presented an SPM8-based approach for deriving the head μ map from MR data to be used for PET AC in integrated PET/MR scanners. Its implementation is straightforward and requires only the morphologic data acquired with a single MR sequence. The method is accurate and robust, combining the strengths of both segmentation- and atlas-based approaches while minimizing their drawbacks. ? 2014 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
Subjects
fluorodeoxyglucose f 18
gadolinium pentetate meglumine
o (2 fluoroethyl) tyrosine f 18
radiopharmaceutical agent
unclassified drug
air
Article
attenuation correction
bone
brain tumor
cerebrospinal fluid
clinical article
computer assisted tomography
controlled study
data analysis
data analysis software
diagnostic test accuracy study
glioblastoma
gold standard
gray matter
human
image processing
image reconstruction
mild cognitive impairment
neuroimaging
nuclear magnetic resonance imaging
nuclear magnetic resonance scanner
PET-CT scanner
positron emission tomography
quality control procedures
radiation attenuation
soft tissue
white matter
algorithm
brain
brain mapping
cognitive defect
pathology
procedures
reproducibility
scintiscanning
skull
Algorithms
Bone and Bones
Brain
Brain Mapping
Cognition Disorders
Glioblastoma
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Neuroimaging
Positron-Emission Tomography
Reproducibility of Results
Skull
SDGs
Type
journal article