A novel computer-assisted image analysis of [123I]β-CIT SPECT images improves the diagnostic accuracy of parkinsonian disorders

Eur J Nucl Med Mol Imaging. 2011 Apr;38(4):702-10. doi: 10.1007/s00259-010-1681-0. Epub 2010 Dec 21.


Purpose: The purpose of this study was to develop an observer-independent algorithm for the correct classification of dopamine transporter SPECT images as Parkinson's disease (PD), multiple system atrophy parkinson variant (MSA-P), progressive supranuclear palsy (PSP) or normal.

Methods: A total of 60 subjects with clinically probable PD (n = 15), MSA-P (n = 15) and PSP (n = 15), and 15 age-matched healthy volunteers, were studied with the dopamine transporter ligand [(123)I]β-CIT. Parametric images of the specific-to-nondisplaceable equilibrium partition coefficient (BP(ND)) were generated. Following a voxel-wise ANOVA, cut-off values were calculated from the voxel values of the resulting six post-hoc t-test maps. The percentages of the volume of an individual BP(ND) image remaining below and above the cut-off values were determined. The higher percentage of image volume from all six cut-off matrices was used to classify an individual's image. For validation, the algorithm was compared to a conventional region of interest analysis.

Results: The predictive diagnostic accuracy of the algorithm in the correct assignment of a [(123)I]β-CIT SPECT image was 83.3% and increased to 93.3% on merging the MSA-P and PSP groups. In contrast the multinomial logistic regression of mean region of interest values of the caudate, putamen and midbrain revealed a diagnostic accuracy of 71.7%.

Conclusion: In contrast to a rater-driven approach, this novel method was superior in classifying [(123)I]β-CIT-SPECT images as one of four diagnostic entities. In combination with the investigator-driven visual assessment of SPECT images, this clinical decision support tool would help to improve the diagnostic yield of [(123)I]β-CIT SPECT in patients presenting with parkinsonism at their initial visit.

Publication types

  • Clinical Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Algorithms
  • Analysis of Variance
  • Brain / diagnostic imaging
  • Brain / metabolism
  • Case-Control Studies
  • Cocaine / analogs & derivatives*
  • Dopamine Plasma Membrane Transport Proteins / metabolism
  • Female
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Male
  • Middle Aged
  • Multiple System Atrophy / diagnostic imaging
  • Multiple System Atrophy / metabolism
  • Parkinson Disease / diagnostic imaging
  • Parkinson Disease / metabolism
  • Parkinsonian Disorders / diagnostic imaging*
  • Parkinsonian Disorders / metabolism
  • Regression Analysis
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Supranuclear Palsy, Progressive / diagnostic imaging
  • Supranuclear Palsy, Progressive / metabolism
  • Tomography, Emission-Computed, Single-Photon / methods*


  • Dopamine Plasma Membrane Transport Proteins
  • 2beta-carbomethoxy-3beta-(4-iodophenyl)tropane
  • Cocaine