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Division of Nuclear Medicine, Department of Internal Medicine, and Departments of Neurology and Radiology, University of Michigan, Ann Arbor, Michigan
Correspondence: For correspondence or reprints contact: Satoshi Minoshima, MD, PhD, Division of Nuclear Medicine, Department of Internal Medicine, The University of Michigan Medical Center, B1-G412 University Hospital, 1500 E. Medical Center Dr., Ann Arbor, MI 48109-0028.
ABSTRACT
To improve the diagnostic performance of PET as an aid in evaluating patients suspected of having Alzheimer's disease, we developed a fully automated method which generates comprehensive image presentations and objective diagnostic indices. Methods: Ruodne-18-fluorodeoxyglucose PET image sets were collected from 37 patients with probable Alzheimer's disease (including questionable and mildde mentia), 22 normal subjects and 5 patients with cerebrovascular disease. Following stereotectic anatomic standardization, metabolic activity on an individual's PET image set was extracted to a set of predefined surface pixels (three-dimensional stereotactic surface projection, 3D-SSP), which was used in the subsequent analysis. A normal database was created by averaging extracted data sets of the normal subjects. Patients' data sets were compared individually with the normal database by calculatinga Z-scoreona pixel-by pixel basis and were displayed in 3D-SSP views for visual inspections. Diagnostic indices were then generated based on averaged Z-scores for the association cortices. Results: Patterns and seventies of metabolic reduction in patients with probable Alzheimer's disease were seen in the standard 3D-SSP views of extracted raw data and statistical Z-scores. When dscriminating patients with probable Alzheimer's disease from normal subjects, diagnostic indices of the parietal assodation cortex and unilaterally averaged parietal-temporal-frontal cortex showed sensitivities of 95% and 97%, respectively, with a specificity of 100%. Neither index yielded false-positive results for cerebrovascular disease. Conclusion: 3D-SSP enables quantitative data extraction and reliable localization of metabolic abnormalities by means of stereotactic coordinates. The proposed method is a promising approach for interpreting functional brain PET scans.
Key Words: Alzheimer's disease • positron emission tomography • glucose metabolism • image interpretation • brain mapping
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