Automated Analysis of 123I-beta-CIT SPECT Images with Statistical Probabilistic Anatomical Mapping

Jae Seon Eo, Ho Young Lee, Jae Sung Lee, Yu Kyung Kim, Bum Seok Jeon, Dong Soo Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Population-based statistical probabilistic anatomical maps have been used to generate probabilistic volumes of interest for analyzing perfusion and metabolic brain imaging. We investigated the feasibility of automated analysis for dopamine transporter images using this technique and evaluated striatal binding potentials in Parkinson's disease and Wilson's disease. Materials and Methods: We analyzed 2β-Carbomethoxy-3β-(4-123I-iodophenyl)tropane (123I-beta-CIT) SPECT images acquired from 26 people with Parkinson's disease (M:F = 11:15, mean age = 49 ± 12 years), 9 people with Wilson's disease (M: F = 6:3, mean age = 26 ± 11 years) and 17 normal controls (M:F = 5:12, mean age = 39 ± 16 years). A SPECT template was created using striatal statistical probabilistic map images. All images were spatially normalized onto the template, and probability-weighted regional counts in striatal structures were estimated. The binding potential was calculated using the ratio of specific and nonspecific binding activities at equilibrium. Voxel-based comparisons between groups were also performed using statistical parametric mapping. Results: Qualitative assessment showed that spatial normalizations of the SPECT images were successful for all images. The striatal binding potentials of participants with Parkinson's disease and Wilson's disease were significantly lower than those of normal controls. Statistical parametric mapping analysis found statistically significant differences only in striatal regions in both disease groups compared to controls. Conclusion: We successfully evaluated the regional 123I-beta-CIT distribution using the SPECT template and probabilistic map data automatically. This procedure allows an objective and quantitative comparison of the binding potential, which in this case showed a significantly decreased binding potential in the striata of patients with Parkinson's disease or Wilson's disease.

Original languageEnglish
Pages (from-to)47-54
Number of pages8
JournalNuclear Medicine and Molecular Imaging
Volume48
Issue number1
DOIs
Publication statusPublished - 2014 Mar 1

Fingerprint

Corpus Striatum
Single-Photon Emission-Computed Tomography
Hepatolenticular Degeneration
Parkinson Disease
Dopamine Plasma Membrane Transport Proteins
Neuroimaging
Perfusion
RTI 55
Population

Keywords

  • I-beta-CIT
  • Automated analysis
  • Parkinson's disease
  • Statistical probabilistic anatomical mapping
  • Wilson's disease

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Automated Analysis of 123I-beta-CIT SPECT Images with Statistical Probabilistic Anatomical Mapping. / Eo, Jae Seon; Lee, Ho Young; Lee, Jae Sung; Kim, Yu Kyung; Jeon, Bum Seok; Lee, Dong Soo.

In: Nuclear Medicine and Molecular Imaging, Vol. 48, No. 1, 01.03.2014, p. 47-54.

Research output: Contribution to journalArticle

Eo, Jae Seon ; Lee, Ho Young ; Lee, Jae Sung ; Kim, Yu Kyung ; Jeon, Bum Seok ; Lee, Dong Soo. / Automated Analysis of 123I-beta-CIT SPECT Images with Statistical Probabilistic Anatomical Mapping. In: Nuclear Medicine and Molecular Imaging. 2014 ; Vol. 48, No. 1. pp. 47-54.
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