Biomedical Engineering Letters

, Volume 4, Issue 1, pp 73–79

Parametric response mapping of longitudinal PET scans and their use in detecting changes in Alzheimer’s diseases

Original Article

DOI: 10.1007/s13534-014-0120-8

Cite this article as:
Lee, S., Park, H. & the ADNI Biomed. Eng. Lett. (2014) 4: 73. doi:10.1007/s13534-014-0120-8

Abstract

Purpose

The purpose of this study is to determine the effectiveness of an image analysis method called parametric response mapping (PRM) in predicting changes related to progression of Alzheimer’s disease (AD).

Methods

Forty patients were obtained from the ADNI database. Each patient underwent longitudinal 18F Fludeoxyglucose (FDG) positron emission tomography (PET) imaging. The patients were divided into four groups, the NC group (n = 10) with stable normal control (NC) patients, the NC-to-MCI group (n = 10) with converting patients from NC to mild cognitive impairment (MCI), the MCI group (n = 10) with stable MCI patients, and the MCI-to-AD group (n = 10) with converting patients from MCI to AD. The PRM approach was applied to longitudinal PET scans using the following procedures; 1) Longitudinal scans were co-registered, 2) intensities were normalized using the cerebral mask, 3) an expert drew regions of interest (ROIs) for tumor volumes, and 4) voxels were classified into unchanged, increased, and decreased categories.

Results

PRM analysis results were analyzed with linear regression and the slopes of regression lines corresponding to different groups were compared. The PRM analysis was able to distinguish between the NC and NC-to-MCI group with p-value 0.05, while it was not able to distinguish between the MCI and the MCI-to-AD group with p-value 0.54.

Conclusions

An image analysis method, PRM approach, was able to distinguish between stable NC patients and converting patients from NC to MCI.

Keywords

Alzheimer’s disease Positron emission tomography Parametric response mapping Longitudinal analysis Early detection of AD 

Copyright information

© Korean Society of Medical and Biological Engineering and Springer 2014

Authors and Affiliations

  1. 1.School of Electronic and Electrical EngineeringSungkyunkwan UniversitySuwonKorea

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