BACKGROUND: The New National Institute on Aging-Alzheimer's Association diagnostic guidelines for Alzheimer's disease (AD) incorporate biomarkers in the diagnostic criteria and suggest division of biomarkers into two categories: Aβ accumulation and neuronal degeneration or injury. OBJECTIVE: It was the aim of this study to compute hippocampus volume from MRI and a neocortical standard uptake value ratio (SUVR) from [(18)F]flutemetamol PET and investigate the performance of these biomarkers when used individually and when combined. METHODS: Fully automated methods for hippocampus segmentation and for computation of neocortical SUVR were applied to MR and scans with the investigational imaging agent [(18)F]flutemetamol in a cohort comprising 27 AD patients, 25 healthy volunteers (HVs) and 20 subjects with amnestic mild cognitive impairment (MCI). Clinical follow-up was performed 2 years after the initial assessment. RESULTS: Hippocampus volumes showed extensive overlap between AD and HV cases while PET SUVRs showed clear group clustering. When both measures were combined, there was a relatively compact cluster of HV scans and a less compact AD cluster. MCI cases had a bimodal distribution of SUVRs. [(18)F]Flutemetamol-positive MCI subjects showed a large variability in hippocampus volumes, indicating that these subjects were in different stages of neurodegeneration. Some [(18)F]flutemetamol-negative MCI scans had hippocampus volumes that were well below the HV range. Clinical follow-up showed that 8 of 9 MCI to AD converters came from the [(18)F]flutemetamol-positive group. CONCLUSION: Combining [(18)F]flutemetamol PET with structural MRI provides additional information for categorizing disease and potentially predicting shorter time to progression from MCI to AD, but this has to be validated in larger longitudinal studies.
BACKGROUND: The New National Institute on Aging-Alzheimer's Association diagnostic guidelines for Alzheimer's disease (AD) incorporate biomarkers in the diagnostic criteria and suggest division of biomarkers into two categories: Aβ accumulation and neuronal degeneration or injury. OBJECTIVE: It was the aim of this study to compute hippocampus volume from MRI and a neocortical standard uptake value ratio (SUVR) from [(18)F]flutemetamol PET and investigate the performance of these biomarkers when used individually and when combined. METHODS: Fully automated methods for hippocampus segmentation and for computation of neocortical SUVR were applied to MR and scans with the investigational imaging agent [(18)F]flutemetamol in a cohort comprising 27 AD patients, 25 healthy volunteers (HVs) and 20 subjects with amnestic mild cognitive impairment (MCI). Clinical follow-up was performed 2 years after the initial assessment. RESULTS: Hippocampus volumes showed extensive overlap between AD and HV cases while PET SUVRs showed clear group clustering. When both measures were combined, there was a relatively compact cluster of HV scans and a less compact AD cluster. MCI cases had a bimodal distribution of SUVRs. [(18)F]Flutemetamol-positive MCI subjects showed a large variability in hippocampus volumes, indicating that these subjects were in different stages of neurodegeneration. Some [(18)F]flutemetamol-negative MCI scans had hippocampus volumes that were well below the HV range. Clinical follow-up showed that 8 of 9 MCI to AD converters came from the [(18)F]flutemetamol-positive group. CONCLUSION: Combining [(18)F]flutemetamol PET with structural MRI provides additional information for categorizing disease and potentially predicting shorter time to progression from MCI to AD, but this has to be validated in larger longitudinal studies.
Authors: Wai Lam Yip; Sverre Arne Sande; David Grace; Dirk Jan in't Veld; Per Christian Sontum; Tina Solvang; Knut Dyrstad Journal: Pharm Res Date: 2014-10-31 Impact factor: 4.200
Authors: Dustin B Hammers; Taylor J Atkinson; Bonnie C A Dalley; Kayla R Suhrie; Kevin P Horn; Kelli M Rasmussen; Britney E Beardmore; Lance D Burrell; Kevin Duff; John M Hoffman Journal: Am J Alzheimers Dis Other Demen Date: 2017-04-12 Impact factor: 2.035
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Authors: Kevin Duff; Norman L Foster; Kathryn Dennett; Dustin B Hammers; Lauren V Zollinger; Paul E Christian; Regan I Butterfield; Britney E Beardmore; Angela Y Wang; Kathryn A Morton; John M Hoffman Journal: Arch Clin Neuropsychol Date: 2013-06-30 Impact factor: 2.813
Authors: Chuan Huang; Jerome L Ackerman; Yoann Petibon; Thomas J Brady; Georges El Fakhri; Jinsong Ouyang Journal: Med Phys Date: 2014-04 Impact factor: 4.071
Authors: Thomas Polak; Martin J Herrmann; Laura D Müller; Julia B M Zeller; Andrea Katzorke; Matthias Fischer; Fabian Spielmann; Erik Weinmann; Leif Hommers; Martin Lauer; Andreas J Fallgatter; Jürgen Deckert Journal: J Neural Transm (Vienna) Date: 2017-09-01 Impact factor: 3.575
Authors: Kari Antila; Jyrki Lötjönen; Lennart Thurfjell; Jarmo Laine; Marcello Massimini; Daniel Rueckert; Roman A Zubarev; Matej Orešič; Mark van Gils; Jussi Mattila; Anja Hviid Simonsen; Gunhild Waldemar; Hilkka Soininen Journal: Interface Focus Date: 2013-04-06 Impact factor: 3.906