Literature DB >> 10714659

Using serial registered brain magnetic resonance imaging to measure disease progression in Alzheimer disease: power calculations and estimates of sample size to detect treatment effects.

N C Fox1, S Cousens, R Scahill, R J Harvey, M N Rossor.   

Abstract

OBJECTIVE: To evaluate the rate of brain atrophy calculated from serial magnetic resonance imaging (MRI) registration as a surrogate marker of disease progression for use in clinical trials in Alzheimer disease (AD).
METHODS: Eighteen patients with mild to moderate AD and 18 age-matched normal controls underwent 2 MRI brain scans separated by a 12-month interval. Each individual's later scan was registered to their first scan, and the volume of cerebral tissue loss calculated directly from the registered and subtracted MRI scan pairs. The mean and SD of the rate of brain volume changes were used to estimate the sample sizes that would be needed in a clinical trial with a drug anticipated to modify disease progression by varying degrees. Comparable sample size estimates were performed with data for other methods of monitoring rates of brain atrophy, extracted from published papers.
RESULTS: The mean (SD) rate of brain atrophy for the patients with AD was 2.37% (1.11%) per year, while in the control group it was 0.41% (0.47%) per year. Based on these figures, to have 90% power to detect a drug effect equivalent to a 20% reduction in the rate of atrophy, 207 patients would be needed in each treatment arm. This assumes a 1-year placebo-controlled trial with a 10% patient dropout rate, and that 10% of scan pairs are unusable.
CONCLUSION: Registration of serial MRI volume images provides a powerful method of quantification of brain atrophy that can be used to monitor progression of AD in clinical trials.

Entities:  

Mesh:

Year:  2000        PMID: 10714659     DOI: 10.1001/archneur.57.3.339

Source DB:  PubMed          Journal:  Arch Neurol        ISSN: 0003-9942


  119 in total

1.  Functional brain imaging to identify affected subjects genetically at risk for Alzheimer's disease.

Authors:  S I Rapoport
Journal:  Proc Natl Acad Sci U S A       Date:  2000-05-23       Impact factor: 11.205

Review 2.  Alliance for aging research AD biomarkers work group: structural MRI.

Authors:  Clifford R Jack
Journal:  Neurobiol Aging       Date:  2011-12       Impact factor: 4.673

3.  Basal ganglia atrophy in prodromal Huntington's disease is detectable over one year using automated segmentation.

Authors:  D S Adnan Majid; Adam R Aron; Wesley Thompson; Sarah Sheldon; Samar Hamza; Diederick Stoffers; Dominic Holland; Jody Goldstein; Jody Corey-Bloom; Anders M Dale
Journal:  Mov Disord       Date:  2011-09-19       Impact factor: 10.338

4.  Characterizing Alzheimer's disease using a hypometabolic convergence index.

Authors:  Kewei Chen; Napatkamon Ayutyanont; Jessica B S Langbaum; Adam S Fleisher; Cole Reschke; Wendy Lee; Xiaofen Liu; Dan Bandy; Gene E Alexander; Paul M Thompson; Leslie Shaw; John Q Trojanowski; Clifford R Jack; Susan M Landau; Norman L Foster; Danielle J Harvey; Michael W Weiner; Robert A Koeppe; William J Jagust; Eric M Reiman
Journal:  Neuroimage       Date:  2011-01-27       Impact factor: 6.556

5.  MRI as a biomarker of disease progression in a therapeutic trial of milameline for AD.

Authors:  C R Jack; M Slomkowski; S Gracon; T M Hoover; J P Felmlee; K Stewart; Y Xu; M Shiung; P C O'Brien; R Cha; D Knopman; R C Petersen
Journal:  Neurology       Date:  2003-01-28       Impact factor: 9.910

6.  [Functional magnetic resonance imaging and dementia].

Authors:  F L Giesel; A Hempel; P Schönknecht; T Wüstenberg; M A Weber; J Schröder; M Essig
Journal:  Radiologe       Date:  2003-06-24       Impact factor: 0.635

7.  Estimating sample sizes for predementia Alzheimer's trials based on the Alzheimer's Disease Neuroimaging Initiative.

Authors:  Joshua D Grill; Lijie Di; Po H Lu; Cathy Lee; John Ringman; Liana G Apostolova; Nicole Chow; Omid Kohannim; Jeffrey L Cummings; Paul M Thompson; David Elashoff
Journal:  Neurobiol Aging       Date:  2012-04-13       Impact factor: 4.673

8.  Longitudinal changes in cortical thickness associated with normal aging.

Authors:  Madhav Thambisetty; Jing Wan; Aaron Carass; Yang An; Jerry L Prince; Susan M Resnick
Journal:  Neuroimage       Date:  2010-05-02       Impact factor: 6.556

Review 9.  Biomarkers for Alzheimer's disease: academic, industry and regulatory perspectives.

Authors:  Harald Hampel; Richard Frank; Karl Broich; Stefan J Teipel; Russell G Katz; John Hardy; Karl Herholz; Arun L W Bokde; Frank Jessen; Yvonne C Hoessler; Wendy R Sanhai; Henrik Zetterberg; Janet Woodcock; Kaj Blennow
Journal:  Nat Rev Drug Discov       Date:  2010-07       Impact factor: 84.694

10.  MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths.

Authors:  Jorge Jovicich; Silvester Czanner; Xiao Han; David Salat; Andre van der Kouwe; Brian Quinn; Jenni Pacheco; Marilyn Albert; Ronald Killiany; Deborah Blacker; Paul Maguire; Diana Rosas; Nikos Makris; Randy Gollub; Anders Dale; Bradford C Dickerson; Bruce Fischl
Journal:  Neuroimage       Date:  2009-02-20       Impact factor: 6.556

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