» Articles » PMID: 35769601

A Multi-Atlas-Based [18F]9-Fluoropropyl-(+)-Dihydrotetrabenazine Positron Emission Tomography Image Segmentation Method for Parkinson's Disease Quantification

Overview
Specialty Geriatrics
Date 2022 Jun 30
PMID 35769601
Authors
Affiliations
Soon will be listed here.
Abstract

Objectives: [18F]9-fluoropropyl-(+)-dihydrotetrabenazine ([18F]-FP-DTBZ) positron emission tomography (PET) provides reliable information for the diagnosis of Parkinson's disease (PD). In this study, we proposed a multi-atlas-based [18F]-FP-DTBZ PET image segmentation method for PD quantification assessment.

Methods: A total of 99 subjects from Xuanwu Hospital of Capital Medical University were included in this study, and both brain PET and magnetic resonance (MR) scans were conducted. Data from 20 subjects were used to generate atlases, based on which a multi-atlas-based [18F]-FP-DTBZ PET segmentation method was developed especially for striatum and its subregions. The proposed method was compared with the template-based method through striatal subregion parcellation performance and the standard uptake value ratio (SUVR) quantification accuracy. Discriminant analysis between healthy controls (HCs) and PD patients was further performed.

Results: Segmentation results of the multi-atlas-based method showed better consistency than the template-based method with the ground truth, yielding a dice coefficient of 0.81 over 0.73 on the full striatum. The SUVRs calculated by the multi-atlas-based method had an average interclass correlation coefficient (ICC) of 0.953 with the standardized result, whereas the template-based method only reached 0.815. The SUVRs of HCs were generally higher than that of patients with PD and showed significant differences in all of the striatal subregions (all < 0.001). The median and posterior putamen performed best in discriminating patients with PD from HCs.

Conclusion: The proposed multi-atlas-based [18F]-FP-DTBZ PET image segmentation method achieved better performance than the template-based method, indicating great potential in improving accuracy and efficiency for PD diagnosis in clinical routine.

Citing Articles

A systematic review of the challenges, emerging solutions and applications, and future directions of PET/MRI in Parkinson's disease.

Leung I, Strudwick M EJNMMI Rep. 2024; 8(1):3.

PMID: 38748251 PMC: 10962627. DOI: 10.1186/s41824-024-00194-9.

References
1.
Bui V, Hsu L, Shanbhag S, Tran L, Bandettini W, Chang L . Improving multi-atlas cardiac structure segmentation of computed tomography angiography: A performance evaluation based on a heterogeneous dataset. Comput Biol Med. 2020; 125:104019. PMC: 7655721. DOI: 10.1016/j.compbiomed.2020.104019. View

2.
Martinez D, Slifstein M, Broft A, Mawlawi O, Hwang D, Huang Y . Imaging human mesolimbic dopamine transmission with positron emission tomography. Part II: amphetamine-induced dopamine release in the functional subdivisions of the striatum. J Cereb Blood Flow Metab. 2003; 23(3):285-300. DOI: 10.1097/01.WCB.0000048520.34839.1A. View

3.
Pirker W, Djamshidian S, Asenbaum S, Gerschlager W, Tribl G, Hoffmann M . Progression of dopaminergic degeneration in Parkinson's disease and atypical parkinsonism: a longitudinal beta-CIT SPECT study. Mov Disord. 2002; 17(1):45-53. DOI: 10.1002/mds.1265. View

4.
Alavi A, Werner T, Hoilund-Carlsen P, Zaidi H . Correction for Partial Volume Effect Is a Must, Not a Luxury, to Fully Exploit the Potential of Quantitative PET Imaging in Clinical Oncology. Mol Imaging Biol. 2017; 20(1):1-3. DOI: 10.1007/s11307-017-1146-y. View

5.
Thomas B, Cuplov V, Bousse A, Mendes A, Thielemans K, Hutton B . PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography. Phys Med Biol. 2016; 61(22):7975-7993. DOI: 10.1088/0031-9155/61/22/7975. View