title: Computer-aided diagnosis of Parkinson's disease based on [(123)I]FP-CIT SPECT binding potential images, using the voxels-as-features approach and support vector machines.
abstract: OBJECTIVE
  The aim of the present study was to develop a fully-automated computational solution for computer-aided diagnosis in Parkinson syndrome based on [(123)I]FP-CIT single photon emission computed tomography (SPECT) images.
  
  
  METHODS
  A dataset of 654 [(123)I]FP-CIT SPECT brain images from the Parkinson's Progression Markers Initiative were used. Of these, 445 images were of patients with Parkinson's disease at an early stage and the remainder formed a control group. The images were pre-processed using automated template-based registration followed by the computation of the binding potential at a voxel level. Then, the binding potential images were used for classification, based on the voxel-as-feature approach and using the support vector machines paradigm.
  
  
  RESULTS
  The obtained estimated classification accuracy was 97.86%, the sensitivity was 97.75% and the specificity 98.09%.
  
  
  CONCLUSIONS
  The achieved classification accuracy was very high and, in fact, higher than accuracies found in previous studies reported in the literature. In addition, results were obtained on a large dataset of early Parkinson's disease subjects. In summation, the information provided by the developed computational solution potentially supports clinical decision-making in nuclear medicine, using important additional information beyond the commonly used uptake ratios and respective statistical comparisons. (ClinicalTrials.gov Identifier: NCT01141023).
authors.affiliation: Institute for Nuclear Sciences Applied to Health (ICNAS-P), and Institute for Biomedical Imaging and Life Sciences (IBILI), Faculty of Medicine, University of Coimbra, Portugal.
authors.forename: Francisco P M
authors.initials: FP
authors.lastname: Oliveira
authors.forename: Miguel
authors.initials: M
authors.lastname: Castelo-Branco
mesh_terms: D050483:Dopamine Plasma Membrane Transport Proteins / Q000378:metabolism*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D057054:Molecular Imaging / Q000379:methods; D010300:Parkinson Disease / Q000000981:diagnostic imaging / Q000378:metabolism*; D010363:Pattern Recognition, Automated / Q000379:methods; D019275:Radiopharmaceuticals / Q000493:pharmacokinetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*; D014326:Tropanes / Q000493:pharmacokinetics*
chemical_list: D050483:Dopamine Plasma Membrane Transport Proteins; D019275:Radiopharmaceuticals; D014326:Tropanes; C087552:2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane