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Performance of FDG PET for detection of Alzheimer’s disease in two independent multicentre samples (NEST-DD and ADNI)


Haense, C., Herholz, K., Jagust, W. J., Heiss, W. D.


Dementia And Geriatric Cognitive Disorders, Volume: 28, No.: 3, Pages.: 259-266

Year of Publication



Aim: We investigated the performance of FDG PET using an automated procedure for discrimination between Alzheimer’s disease (AD) and controls, and studied the influence of demographic and technical factors.; Methods: FDG PET data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) [102 controls (76.0 +/- 4.9 years) and 89 AD patients (75.7 +/- 7.6 years, MMSE 23.5 +/- 2.1) and the Network for Standardisation of Dementia Diagnosis (NEST-DD) [36 controls (62.2 +/- 5.0 years) and 237 AD patients (70.8 +/- 8.3 years, MMSE 20.9 +/- 4.4). The procedure created t-maps of abnormal voxels. The sum of t-values in predefined areas that are typically affected by AD (AD t-sum) provided a measure of scan abnormality associated with a preset threshold for discrimination between patients and controls.; Results: AD patients had much higher AD t-sum scores compared to controls (p < 0.01), which were significantly related to dementia severity (ADNI: r = -0.62, p < 0.01; NEST-DD: r = -0.59, p < 0.01). Early-onset AD patients had significantly higher AD t-sum scores than late-onset AD patients (p < 0.01). Differences between databases were mainly due to different age distributions. The predefined AD t-sum threshold yielded a sensitivity and specificity of 83 and 78% in ADNI and 78 and 94% in NEST-DD, respectively.; Conclusion: The automated FDG PET analysis procedure provided good discrimination power, and was most accurate for early-onset AD.; Copyright 2009 S. Karger AG, Basel.

Bibtex Citation

@article{Haense_2009, doi = {10.1159/000241879}, url = {}, year = 2009, publisher = {S. Karger {AG}}, volume = {28}, number = {3}, pages = {259--266}, author = {C. Haense and K. Herholz and W.J. Jagust and W.D. Heiss}, title = {Performance of {FDG} {PET} for Detection of Alzheimer{&}rsquo$mathsemicolon$s Disease in Two Independent Multicentre Samples ({NEST}-{DD} and {ADNI})}, journal = {Dementia and Geriatric Cognitive Disorders} }


aged, aged, 80 and over, alzheimer disease, area under curve, data interpretation statistical, databases factual, diagnostic use, female, fluorodeoxyglucose f18, humans, male, middle aged, radionuclide imaging, radiopharmaceuticals, reproducibility of results

Countries of Study


Types of Dementia

Alzheimer’s Disease

Type of Interventions

Diagnostic Target Identification

Diagnostic Targets

Neuroimaging (e.g. MRI, PET, CAT etc.)