%0 Journal Article %J J Alzheimers Dis %D 2016 %T Optimization of Statistical Single Subject Analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer's Disease Conversion. %A Lange, Catharina %A Suppa, Per %A Frings, Lars %A Brenner, Winfried %A Spies, Lothar %A Buchert, Ralph %K Aged %K Alzheimer Disease %K Area Under Curve %K Brain %K Cognitive Dysfunction %K Disease Progression %K Female %K Fluorodeoxyglucose F18 %K Follow-Up Studies %K Glucose %K Humans %K Image Interpretation, Computer-Assisted %K Male %K Positron-Emission Tomography %K Prognosis %K Radiopharmaceuticals %K ROC Curve %X

BACKGROUND: Positron emission tomography (PET) with the glucose analog F-18-fluorodeoxyglucose (FDG) is widely used in the diagnosis of neurodegenerative diseases. Guidelines recommend voxel-based statistical testing to support visual evaluation of the PET images. However, the performance of voxel-based testing strongly depends on each single preprocessing step involved.

OBJECTIVE: To optimize the processing pipeline of voxel-based testing for the prognosis of dementia in subjects with amnestic mild cognitive impairment (MCI).

METHODS: The study included 108 ADNI MCI subjects grouped as 'stable MCI' (n = 77) or 'MCI-to-AD converter' according to their diagnostic trajectory over 3 years. Thirty-two ADNI normals served as controls. Voxel-based testing was performed with the statistical parametric mapping software (SPM8) starting with default settings. The following modifications were added step-by-step: (i) motion correction, (ii) custom-made FDG template, (iii) different reference regions for intensity scaling, and (iv) smoothing was varied between 8 and 18 mm. The t-sum score for hypometabolism within a predefined AD mask was compared between the different settings using receiver operating characteristic (ROC) analysis with respect to differentiation between 'stable MCI' and 'MCI-to-AD converter'. The area (AUC) under the ROC curve was used as performance measure.

RESULTS: The default setting provided an AUC of 0.728. The modifications of the processing pipeline improved the AUC up to 0.832 (p = 0.046). Improvement of the AUC was confirmed in an independent validation sample of 241 ADNI MCI subjects (p = 0.048).

CONCLUSION: The prognostic value of voxel-based single subject analysis of brain FDG PET in MCI subjects can be improved considerably by optimizing the processing pipeline.

%B J Alzheimers Dis %V 49 %P 945-59 %8 2016 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/26577523?dopt=Abstract %R 10.3233/JAD-150814