Voxel-based analysis of 11C-PIB scans for diagnosing Alzheimer's disease

Abstract

The positron emission tomography (PET) radioligand N-methyl-11C-2-(4-methylaminophenyl)-6-hydroxybenzothiazole (also known as 11C-6-OH-BTA-1 or 11C-PIB) binds to amyloid-beta (Abeta), which accumulates pathologically in Alzheimer's disease (AD). Although 11C-PIB accumulation is greater in patients with AD than in healthy controls at a group level, the optimal method for discriminating between these 2 groups has, to our knowledge, not been established. We assessed the use of data-determined standardized voxels of interest (VOIs) to improve the classification capability of 11C-PIB scans on patients with AD.

Methods: A total of 16 controls and 14 AD age-matched patients were recruited. All subjects underwent a 11C-PIB scan and structural MRI. Binding potential (a measure of amyloid burden) was calculated for each voxel using the Logan graphical method with cerebellar gray matter as the reference region. Voxel maps were then partial-volume corrected and spatially normalized by MRI onto a standardized template. The subjects were divided into 2 cohorts. The first cohort (control, 12; AD, 9) was used for statistical parametric mapping analysis and delineation of data-based VOIs. These VOIs were tested in the second cohort (control, 4; AD, 5) of subjects.

Results: Statistical parametric mapping analysis revealed significant differences between control and AD groups. The VOI map determined from the first cohort resulted in complete separation between the control and the AD subjects in the second cohort (P < 0.02). Binding potential values based on this VOI were in the same range as other reported individual and mean cortical VOI results.

Conclusion: A standardized VOI template that is optimized for control or AD group discrimination provides excellent separation of control and AD subjects on the basis of 11C-PIB uptake. This VOI template can serve as a potential replacement for manual VOI delineation and can eventually be fully automated, facilitating potential use in a clinical setting. To facilitate independent analysis and validation with more and a broader variety of subjects, this VOI template and the software for processing will be made available through the Internet.

FIGURE 1

Maximum-intensity projections of SPM results comparing control (n = 12) and AD (n = 9) subjects for several t score values. SPM map at each t score threshold was used to calculate mean subject cortical BP_ND. Scatter plots of mean cortical BP_ND in control and AD groups are shown on bottom. Greater separation between groups with increasing t threshold is demonstrated. CTR = control.

FIGURE 2

Effect of SPM map t score threshold on control vs. AD separation (P value) and VOI volume. SPM map was derived from control (n = 12) and AD (n = 9) partial-volume–corrected BP_ND voxel images. Map was thresholded at various t scores and reapplied as VOIs to MRI space BP_ND voxel maps to calculate mean cortical BP_ND. P values were calculated by performing Student t test on control and AD groups mean cortical BP_ND for each t score threshold (A). Optimal t score for separation of groups is 10.61. (B) VOI volume vs. t score. Increasing t score decreases VOI volume. VOI volume (3,376 mm³, 422 voxels) at P value inflection point is shown (B). t score of 10.61 is represented by circle and horizontal black line.

FIGURE 3

Mean cortical BP_ND within VOI derived from SPM t map thresholded at t score of 10.61 (from Fig. 2). VOI was reapplied to first cohort of controls (n = 12) and patients with AD (n = 9) (A) and applied to second cohort of controls (n = 4) and patients with AD (n = 5) (B). CTR = control.

FIGURE 4

Workflow for calculating VOI binding, and potentially diagnosing subject, using our data-derived VOI and novel subjects' MRI and ¹¹C-PIB PET scans (A). (B) VOI is inverse-transformed (xfm) into MRI space using parameters from MRI to MNI normalization. MRI is then segmented into gray, white, and CSF images. PET data is modeled with Logan method to derive BP_ND voxel map. BP_ND map is inverse-transformed into MRI space using parameters from PET to MRI coregistration. (C) MRI VOI is masked to remove non–gray matter voxels. PVC is applied to BP_ND map. (D) Average BP_ND value within gray matter VOI voxels is calculated to extract final cortical BP_ND measure. Result (red dot) can be compared with control and AD group results derived with same process. CTR = control.