Alzheimer's disease detection using 11C-PiB with improved partial volume effect correction

Parnesh Raniga; Pierrick Bourgeat; Jurgen Fripp; Oscar Acosta; Sebastien Ourselin; Christopher Rowe; Victor L. Villemagne; Olivier Salvado

doi:10.1117/12.813501

27 February 2009 Alzheimer's disease detection using ¹¹C-PiB with improved partial volume effect correction

Parnesh Raniga, Pierrick Bourgeat, Jurgen Fripp, Oscar Acosta, Sebastien Ourselin, Christopher Rowe, Victor L. Villemagne, Olivier Salvado

Author Affiliations +

Proceedings Volume 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging; 72621O (2009) https://doi.org/10.1117/12.813501
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Despite the increasing use of ¹¹C-PiB in research into Alzheimer's disease (AD), there are few standardized analysis procedures that have been reported or published. This is especially true with regards to partial volume effects (PVE) and partial volume correction. Due to the nature of PET physics and acquisition, PET images exhibit relatively low spatial resolution compared to other modalities, resulting in bias of quantitative results. Although previous studies have applied PVE correction techniques on ¹¹C-PiB data, the results have not been quantitatively evaluated and compared against uncorrected data. The aim of this study is threefold. Firstly, a realistic synthetic phantom was created to quantify PVE. Secondly, MRI partial volume estimate segmentations were used to improve voxel-based PVE correction instead of using hard segmentations. Thirdly, quantification of PVE correction was evaluated on 34 subjects (AD=10, Normal Controls (NC)=24), including 12 PiB positive NC. Regional analysis was performed using the Anatomical Automatic Labeling (AAL) template, which was registered to each patient. Regions of interest were restricted to the gray matter (GM) defined by the MR segmentation. Average normalized intensity of the neocortex and selected regions were used to evaluate the discrimination power between AD and NC both with and without PVE correction. Receiver Operating Characteristic (ROC) curves were computed for the binary discrimination task. The phantom study revealed signal losses due to PVE between 10 to 40 % which were mostly recovered to within 5% after correction. Better classification was achieved after PVE correction, resulting in higher areas under ROC curves.

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Parnesh Raniga, Pierrick Bourgeat, Jurgen Fripp, Oscar Acosta, Sebastien Ourselin, Christopher Rowe, Victor L. Villemagne, and Olivier Salvado "Alzheimer's disease detection using ¹¹C-PiB with improved partial volume effect correction", Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72621O (27 February 2009); https://doi.org/10.1117/12.813501

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