The Alzheimer’s disease metabolic brain pattern in mild cognitive impairment

We investigated the expression of the Alzheimer’s disease-related metabolic brain pattern (ADRP) in 18F-FDG-PET scans of 44 controls, 27 patients with mild cognitive impairment (MCI) who did not convert to Alzheimer’s disease (AD) after five or more years of clinical follow-up, 95 MCI patients who did develop AD dementia on clinical follow-up, and 55 patients with mild-to-moderate AD. The ADRP showed good sensitivity (84%) and specificity (86%) for MCI-converters when compared to controls, but limited specificity when compared to MCI non-converters (66%). Assessment of 18F-FDG-PET scans on a case-by-case basis using the ADRP may be useful for quantifying disease progression.

[1]  D. Perani,et al.  Cross-validation of biomarkers for the early differential diagnosis and prognosis of dementia in a clinical setting , 2015, European Journal of Nuclear Medicine and Molecular Imaging.

[2]  Chris C. Tang,et al.  Differential diagnosis of parkinsonism: a metabolic imaging study using pattern analysis , 2010, The Lancet Neurology.

[3]  Nick C Fox,et al.  Advancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria , 2014, The Lancet Neurology.

[4]  A. Alavi,et al.  The [18F]Fluorodeoxyglucose Method for the Measurement of Local Cerebral Glucose Utilization in Mane , 1979, Circulation research.

[5]  Chris C. Tang,et al.  Abnormalities in Metabolic Network Activity Precede the Onset of Motor Symptoms in Parkinson's Disease , 2010, The Journal of Neuroscience.

[6]  K. Ritchie Mild cognitive impairment: an epidemiological perspective , 2004, Dialogues in clinical neuroscience.

[7]  F. Woon,et al.  Does mild cognitive impairment always lead to dementia? A review , 2016, Journal of the Neurological Sciences.

[8]  David Eidelberg,et al.  Scaled subprofile modeling of resting state imaging data in Parkinson's disease: Methodological issues , 2011, NeuroImage.

[9]  Alessandro Giuliani,et al.  Predicting the transition from normal aging to Alzheimer's disease: A statistical mechanistic evaluation of FDG-PET data , 2016, NeuroImage.

[10]  J. Roerdink,et al.  The Alzheimer's disease-related glucose metabolic brain pattern. , 2014, Current Alzheimer research.

[11]  oNe mediciNe,et al.  A Cochrane review on brain [18F]FDG PET in dementia: limitations and future perspectives , 2015, European Journal of Nuclear Medicine and Molecular Imaging.

[12]  V. Dhawan,et al.  Changes in network activity with the progression of Parkinson's disease. , 2007, Brain : a journal of neurology.

[13]  Alessandro Giuliani,et al.  Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data , 2017, The Journal of Nuclear Medicine.

[14]  B. D. de Jong,et al.  Metabolic Imaging in Parkinson Disease , 2017, The Journal of Nuclear Medicine.

[15]  David Eidelberg,et al.  Automated Differential Diagnosis of Early Parkinsonism Using Metabolic Brain Networks: A Validation Study , 2016, The Journal of Nuclear Medicine.

[16]  V. Dhawan,et al.  Abnormal metabolic network activity in REM sleep behavior disorder , 2014, Neurology.

[17]  Chris C. Tang,et al.  Distinct brain networks underlie cognitive dysfunction in Parkinson and Alzheimer diseases , 2016, Neurology.

[18]  Yaakov Stern,et al.  Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease , 2008, NeuroImage.

[19]  D. Perani,et al.  Education and occupation as proxies for reserve in aMCI converters and AD , 2008, Neurology.

[20]  Eric Guedj,et al.  Metabolic Networks Underlying Cognitive Reserve in Prodromal Alzheimer Disease: A European Alzheimer Disease Consortium Project , 2013, The Journal of Nuclear Medicine.