An automated, normative-based fluorodeoxyglucose positron emission tomography image-analysis procedure to aid Alzheimer disease diagnosis using statistical parametric mapping and interactive image display

Kewei Chen, Xiaolin Ge, Li Yao, Dan Bandy, Gene E. Alexander, Anita Prouty, Christine Burns, Xiaojie Zhao, Xiaotong Wen, Ronald Korn, Michael Lawson, Eric M. Reiman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Having approved fluorodeoxyglucose positron emission tomography (FDG PET) for the diagnosis of Alzheimer's disease (AD) in some patients, the Centers for Medicare and Medicaid Services suggested the need to develop and test analysis techniques to optimize diagnostic accuracy. We developed an automated computer package comparing an individual's FDG PET image to those of a group of normal volunteers. The normal control group includes FDG-PET images from 82 cognitively normal subjects, 61.89±5.67 years of age, who were characterized demographically, clinically, neuropsychologically, and by their apolipoprotein E genotype (known to be associated with a differential risk for AD). In addition, AD-affected brain regions functionally defined as based on a previous study (Alexander, et al, Am J Psychiatr, 2002) were also incorporated. Our computer package permits the user to optionally select control subjects, matching the individual patient for gender, age, and educational level. It is fully streamlined to require minimal user intervention. With one mouse click, the program runs automatically, normalizing the individual patient image, setting up a design matrix for comparing the single subject to a group of normal controls, performing the statistics, calculating the glucose reduction overlap index of the patient with the AD-affected brain regions, and displaying the findings in reference to the AD regions. In conclusion, the package automatically contrasts a single patient to a normal subject database using sound statistical procedures. With further validation, this computer package could be a valuable tool to assist physicians in decision making and communicating findings with patients and patient families.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2006
Subtitle of host publicationImage Processing
DOIs
StatePublished - Jun 22 2006
EventMedical Imaging 2006: Image Processing - San Diego, CA, United States
Duration: Feb 13 2006Feb 16 2006

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6144 III
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2006: Image Processing
CountryUnited States
CitySan Diego, CA
Period2/13/062/16/06

Keywords

  • Alzheimer disease (AD)
  • Clinical computing system
  • Clinical diagnosis
  • Computer-aided diagnosis
  • Fluorodeoxyglucose (FDG)
  • Normal database
  • Positron Emission Tomography (PET)
  • Statistical general linear model
  • Voxel-based image-analysis

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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    Chen, K., Ge, X., Yao, L., Bandy, D., Alexander, G. E., Prouty, A., Burns, C., Zhao, X., Wen, X., Korn, R., Lawson, M., & Reiman, E. M. (2006). An automated, normative-based fluorodeoxyglucose positron emission tomography image-analysis procedure to aid Alzheimer disease diagnosis using statistical parametric mapping and interactive image display. In Medical Imaging 2006: Image Processing [614453] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6144 III). https://doi.org/10.1117/12.651069