New strategies for automated differential diagnosis of degenerative brain disorders.
New strategies are considered for automated, single-subject differential diagnosis of independent degenerative brain disorders characterized by similar clinical symptoms using functional imaging. The methodology of these strategies is described and its application in parkinsonian movement disorders is illustrated for PET data. Using an automated diagnostic Topographic Profile Rating (TPR) technique based on the Scaled Subprofile Model (SSM-PCA), single-subject score values for different conditions are compared with reference values to predict diagnosis. The discriminatory parameters of reference score sets associated with significant SSM principal components referred to as group invariant subprofiles (GIS networks) are examined. It is shown that the extraction of exclusive sub-networks that stem from contrasting image features between conditions can be an effective tool for optimization that does not require expert knowledge.
Spetsieris
Phoebe G
PG
Center for Neurosciences, Feinstein Institute for Medical Research, North Shore - LIJ Health System, Manhasset, NY 11030, USA. pspetsie@nshs.edu
Ma
Yilong
Y
Eckert
Thomas
T
Dhawan
Vijay
V
Eidelberg
David
D
D000465:Algorithms; D001185:Artificial Intelligence; D003937:Diagnosis, Differential; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D019636:Neurodegenerative Diseases / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity