New ratios for the detection and classification of CJD in multisequence MRI of the brain

Med Image Comput Comput Assist Interv. 2005;8(Pt 2):492-9. doi: 10.1007/11566489_61.

Abstract

We present a method for the analysis of deep grey brain nuclei for accurate detection of human spongiform encephalopathy in multisequence MRI of the brain. We employ T1, T2 and FLAIR-T2 MR sequences for the detection of intensity deviations in the internal nuclei. The MR data are registered to a probabilistic atlas and normalised in intensity prior to the segmentation of hyperintensities using a foveal model. Anatomical data from a segmented atlas are employed to refine the registration and remove false positives. The results are robust over the patient data and in accordance to the clinical ground truth. Our method further allows the quantification of intensity distributions in basal ganglia. sCJD patient FLAIR images are classified with a more significant hypersignal in caudate nuclei (10/10) and putamen (6/10) than in thalami. Defining normalised MRI measures of the intensity relations between the internal grey nuclei of patients, we robustly differentiate sCJD and variant CJD (vCJD) patients, as an attempt towards the automatic detection and classification of human spongiform encephalopathies.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Algorithms
  • Artificial Intelligence
  • Brain / pathology*
  • Brain Mapping / methods*
  • Cluster Analysis
  • Creutzfeldt-Jakob Syndrome / classification*
  • Creutzfeldt-Jakob Syndrome / diagnosis*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods
  • Magnetic Resonance Imaging / methods*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Severity of Illness Index
  • Subtraction Technique