Artificial neural networks that use single-photon emission tomography to identify patients with probable Alzheimer's disease

1994 ◽  
Vol 21 (12) ◽  
pp. 1303-1311 ◽  
Author(s):  
M. R. W. Dawson ◽  
A. Dobbs ◽  
H. R. Hooper ◽  
A. J. B. McEwan ◽  
J. Triscott ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Single Photon ◽  
Photon Emission ◽  
Single Photon Emission Tomography ◽  
Emission Tomography ◽  
Single Photon Emission ◽  
Artificial Neural ◽  
Photon Emission Tomography

Early prediction of donepezil cognitive response in Alzheimer’s disease by brain perfusion single photon emission tomography

2019 ◽  
Vol 13 (6) ◽  
pp. 1665-1673
Author(s):  
Supatporn Tepmongkol ◽  
Solaphat Hemrungrojn ◽  
Patrick Dupont ◽  
Chavit Tunvirachaisakul ◽  
Daruj Aniwattanapong ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Single Photon ◽  
Photon Emission ◽  
Brain Perfusion ◽  
Single Photon Emission Tomography ◽  
Emission Tomography ◽  
Early Prediction ◽  
Single Photon Emission ◽  
Cognitive Response ◽  
Photon Emission Tomography

Combined Magnetic Resonance Imaging and Single-Photon Emission Tomography Scanning in the Discrimination of Alzheimer's Disease From Age-Matched Controls

2001 ◽  
Vol 13 (2) ◽  
pp. 149-161 ◽  
Author(s):  
John T. O'Brien ◽  
David Ames ◽  
Patricia Desmond ◽  
Meir Lichtenstein ◽  
David Binns ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Alzheimer’S Disease ◽  
Magnetic Resonance ◽  
Single Photon ◽  
Photon Emission ◽  
Single Photon Emission Tomography ◽  
Emission Tomography ◽  
Resonance Imaging ◽  
Single Photon Emission ◽  
Photon Emission Tomography

Objective: To compare the utility of temporal lobe magnetic resonance imaging (MRI) and single-photon emission tomography (SPET) scanning in discriminating between subjects with Alzheimer's disease (AD) and age-matched controls. Methods: Thirty subjects with NINCDS-ADRDA AD (23 probable AD, 5 possible AD, 2 definite AD) and 22 age- and sex-matched controls underwent T1-weighted coronal MRI scanning (0.3 T) and technetium 99m-HMPAOSPET scanning. MRI scans were analyzed using a digitizer system with volumes of hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, and whole cerebral cortex calculated. From SPET scans, regional cerebral blood flow (rCBF) was assessed in anterior and posterior frontal, parietal, occipital, and mesial temporal cortex using a region of interest analysis with the cerebellum as a reference area. Results: Using MRI, the areas that best separated groups were left hippocampal and left amygdala volume, resulting in correct classification (patient vs. control) in 79% of cases (sensitivity 77%, specificity 82%). Exactly the same proportion of subjects were correctly classified by SPET, with the most discriminating rCBF changes being left parietal and right posterio frontal. Combining information from both scans improved the proportion of correctly classified subjects in a discriminant function to 90% (sensitivity 93%, specificity 86%, only 2AD and 3 controls misclassified). All AD subjects had abnormalities on MRI and/or SPET (sensitivity for combined examinations 100%), while abnormalities on both MRI and SPET had a positive predictive value of 100% for dementia (including the detection of one control subject who later had dementia). Significant correlations between MRI and SPET measures were seen in control subjects but not in patients. Conclusion: Both 0.3 T MRI and single rotating gamma camera SPET were equally useful in separating AD subjects from age-matched controls, although the combination of both significantly enhanced discrimination. In particular, all AD subjects had abnormalities on either MRI or SPET and both techniques may have an important role in assisting with clinical diagnosis, though replication in other centers and examination of differentiation of AD from other causes of dementia need to be examined.

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