Prashanthi Vemuri1, Matthew L Senjem2, Jeffrey L Gunter2, Emily S Lundt3, Nirubol Tosakulwong3, Stephen D Weigand3, Bret J Borowski4, Matt A Bernstein4, Samantha M Zuk4, Val J Lowe4, David S Knopman5, Ronald C Petersen5, Nick C Fox6, Paul M Thompson7, Michael W Weiner8, Clifford R Jack4. 1. Departments of Radiology, MN, USA. Electronic address: vemuri.prashanthi@mayo.edu. 2. Departments of Radiology, MN, USA; Information Technology, MN, USA. 3. Health Sciences Research, MN, USA. 4. Departments of Radiology, MN, USA. 5. Neurology Mayo Clinic Rochester, MN, USA. 6. Dementia Research Center, UCL Institute of Neurology, London, UK. 7. Imaging genetics Center, Institute for Neuroimaging and Informatics, Department of Neurology, University of Southern California, Los Angeles, CA, USA; Department of Psychiatry, University of Southern California, Los Angeles, CA, USA; Department of Radiology, University of Southern California, Los Angeles, CA, USA; Department of Pediatrics, University of Southern California, Los Angeles, CA, USA; Department of Engineering, University of Southern California, Los Angeles, CA, USA; Department of Opthalmology , University of Southern California, Los Angeles, CA, USA. 8. University of California at San Francisco, Department of Veterans Affairs Medical Center, San Francisco, CA, USA; Center for Imaging of Neurodegenerative Diseases, Department of Veterans Affairs Medical Center, San Francisco, CA, USA.
Abstract
OBJECTIVE: Our primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer's disease (AD). METHODS: We identified cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD subjects from all available Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects with usable pairs of accelerated and unaccelerated scans. There were a total of 696 subjects with baseline and 3 month scans, 628 subjects with baseline and 6 month scans and 464 subjects with baseline and 12 month scans available. We employed the Symmetric Diffeomorphic Image Normalization method (SyN) for normalization of the serial scans to obtain tensor based morphometry (TBM) maps which indicate the structural changes between pairs of scans. We computed a TBM-SyN summary score of annualized structural changes over 31 regions of interest (ROIs) that are characteristically affected in AD. TBM-SyN scores were computed using accelerated and unaccelerated scan pairs and compared in terms of agreement, group-wise discrimination, and sample size estimates for a hypothetical therapeutic trial. RESULTS: We observed a number of systematic differences between TBM-SyN scores computed from accelerated and unaccelerated pairs of scans. TBM-SyN scores computed from accelerated scans tended to have overall higher estimated values than those from unaccelerated scans. However, the performance of accelerated scans was comparable to unaccelerated scans in terms of discrimination between clinical groups and sample sizes required in each clinical group for a therapeutic trial. We also found that the quality of both accelerated vs. unaccelerated scans were similar. CONCLUSIONS: Accelerated scanning protocols reduce scan time considerably. Their group-wise discrimination and sample size estimates were comparable to those obtained with unaccelerated scans. The two protocols did not produce interchangeable TBM-SyN estimates, so it is arguably important to use either accelerated pairs of scans or unaccelerated pairs of scans throughout the study duration.
OBJECTIVE: Our primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer's disease (AD). METHODS: We identified cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD subjects from all available Alzheimer's Disease Neuroimaging Initiative (ADNI) subjects with usable pairs of accelerated and unaccelerated scans. There were a total of 696 subjects with baseline and 3 month scans, 628 subjects with baseline and 6 month scans and 464 subjects with baseline and 12 month scans available. We employed the Symmetric Diffeomorphic Image Normalization method (SyN) for normalization of the serial scans to obtain tensor based morphometry (TBM) maps which indicate the structural changes between pairs of scans. We computed a TBM-SyN summary score of annualized structural changes over 31 regions of interest (ROIs) that are characteristically affected in AD. TBM-SyN scores were computed using accelerated and unaccelerated scan pairs and compared in terms of agreement, group-wise discrimination, and sample size estimates for a hypothetical therapeutic trial. RESULTS: We observed a number of systematic differences between TBM-SyN scores computed from accelerated and unaccelerated pairs of scans. TBM-SyN scores computed from accelerated scans tended to have overall higher estimated values than those from unaccelerated scans. However, the performance of accelerated scans was comparable to unaccelerated scans in terms of discrimination between clinical groups and sample sizes required in each clinical group for a therapeutic trial. We also found that the quality of both accelerated vs. unaccelerated scans were similar. CONCLUSIONS: Accelerated scanning protocols reduce scan time considerably. Their group-wise discrimination and sample size estimates were comparable to those obtained with unaccelerated scans. The two protocols did not produce interchangeable TBM-SyN estimates, so it is arguably important to use either accelerated pairs of scans or unaccelerated pairs of scans throughout the study duration.
Authors: Mark A Griswold; Peter M Jakob; Robin M Heidemann; Mathias Nittka; Vladimir Jellus; Jianmin Wang; Berthold Kiefer; Axel Haase Journal: Magn Reson Med Date: 2002-06 Impact factor: 4.668
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Authors: Irene Sintini; Jonathan Graff-Radford; Matthew L Senjem; Christopher G Schwarz; Mary M Machulda; Peter R Martin; David T Jones; Bradley F Boeve; David S Knopman; Kejal Kantarci; Ronald C Petersen; Clifford R Jack; Val J Lowe; Keith A Josephs; Jennifer L Whitwell Journal: Brain Date: 2020-07-01 Impact factor: 13.501
Authors: P M Cogswell; M C Murphy; M L Senjem; H Botha; J L Gunter; B D Elder; J Graff-Radford; D T Jones; J K Cutsforth-Gregory; C G Schwarz; F B Meyer; J Huston; C R Jack Journal: AJNR Am J Neuroradiol Date: 2021-10-21 Impact factor: 3.825
Authors: David S Knopman; Clifford R Jack; Emily S Lundt; Stephen D Weigand; Prashanthi Vemuri; Val J Lowe; Kejal Kantarci; Jeffrey L Gunter; Matthew L Senjem; Michelle M Mielke; Mary M Machulda; Rosebud O Roberts; Bradley F Boeve; David T Jones; Ronald C Petersen Journal: Neurobiol Aging Date: 2016-06-16 Impact factor: 4.673
Authors: David T Jones; Jonathan Graff-Radford; Val J Lowe; Heather J Wiste; Jeffrey L Gunter; Matthew L Senjem; Hugo Botha; Kejal Kantarci; Bradley F Boeve; David S Knopman; Ronald C Petersen; Clifford R Jack Journal: Cortex Date: 2017-10-03 Impact factor: 4.027
Authors: Emily N Manning; Kelvin K Leung; Jennifer M Nicholas; Ian B Malone; M Jorge Cardoso; Jonathan M Schott; Nick C Fox; Josephine Barnes Journal: Neuroinformatics Date: 2017-04
Authors: Christopher G Schwarz; Walter K Kremers; Heather J Wiste; Jeffrey L Gunter; Prashanthi Vemuri; Anthony J Spychalla; Kejal Kantarci; Aaron P Schultz; Reisa A Sperling; David S Knopman; Ronald C Petersen; Clifford R Jack Journal: Neuroimage Date: 2021-02-11 Impact factor: 7.400
Authors: Qin Chen; Scott A Przybelski; Matthew L Senjem; Christopher G Schwarz; Timothy G Lesnick; Hugo Botha; David S Knopman; Jonathan Graff-Radford; Rodolfo Savica; David T Jones; Julie A Fields; Manoj K Jain; Neill R Graff-Radford; Tanis J Ferman; Walter K Kremers; Clifford R Jack; Ronald C Petersen; Bradley F Boeve; Val J Lowe; Kejal Kantarci Journal: Mov Disord Date: 2022-03-08 Impact factor: 9.698