Evidence map›Paper›PMID 25260848›Full record

ArticleNeurobiology of aging2015

Empowering imaging biomarkers of Alzheimer's disease.

Boris A Gutman, Yalin Wang, Igor Yanovsky, Xue Hua, Arthur W Toga, Clifford R Jack, Michael W Weiner, Paul M Thompson, Alzheimer's Disease Neuroimaging Initiative

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurobiology of aging, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.5field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2015
    Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Boris A GutmanUSC Imaging Genetics Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Yalin WangSchool of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Igor YanovskyUCLA Joint Institute for Regional Earth System Science and Engineering, Los Angeles, CA, USA.
Xue HuaUSC Imaging Genetics Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Arthur W TogaInstitute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Clifford R JackMayo Clinic, Rochester, MN, USA.
Michael W WeinerDepartment of Radiology and Biomedical Imaging, UC San Francisco, San Francisco, CA, USA; Department of Medicine, UC San Francisco, San Francisco, CA, USA; Department of Psychiatry, UC San Francisco, San Francisco, CA, USA.
Paul M ThompsonUSC Imaging Genetics Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. Electronic address: pthomp@usc.edu.
Alzheimer's Disease Neuroimaging Initiative
University of Southern California · USArizona State University · USMayo Clinic in Arizona · USUniversity of California, San Francisco · US

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MONICA G. RIVERA-MINDT · 2016 to 2026
$226.7M
Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
UC Davis Alzheimer's Disease Core CenterP30AG010129 · NIA · UNIVERSITY OF CALIFORNIA DAVIS · PI RAJAN, KUMAR B. · 1991 to 2020
$28.3M
UCLA ALZHEIMERS DISEASE RESEARCH CENTERP50AG016570 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GRILL, JOSHUA · 1999 to 2014
$25.9M
TR&D3: Intrinsic Surface MappingP41EB015922 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI VAN HORN, JOHN DARRELL · 2012 to 2022
$14.1M
Training U54EB020403 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2018
$10.1M
Growth factors, neuroinflammation, exercise, and brain integrityRF1AG041915 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2014
$2.9M
Alzheimer's disease risk analyzed using population imaging genomicsR01AG040060 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2011 to 2016
$2.5M
Ultrasound-activated microbubbles for targeted siRNA delivery to tumorR01EB016516 · NIBIB · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI VILLANUEVA, FLORDELIZA S · 2012 to 2015
$2.3M
DIGITAL REPRESENTATION AND VISUALIZATION OF HUMAN BRAINR01LM005639 · NLM · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TOGA, ARTHUR W · 1995 to 2005
$1.8M
"MR Morphometrics and Cognitive Decline Rate in Large-Scale Aging Studies"K01AG030514 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI CARMICHAEL, OWEN T. · 2008 to 2012
$495k
MRI Biomarker Discovery for Preclinical Alzheimers Disease with Geometry MethodsR21AG043760 · NIA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI WANG, YALIN · 2013 to 2014
$409k
CIHRNCRR NIH HHS R21 RR019771NCRR NIH HHS RR019771NIA NIH HHS AG016570NIA NIH HHS K01 AG030514NIA NIH HHS P30 AG010129NIA NIH HHS P50 AG016570NIA NIH HHS R01 AG040060NIA NIH HHS R21 AG043760NIA NIH HHS RF1 AG041915NIA NIH HHS U01 AG024904NIA NIH HHS U19 AG024904NIBIB NIH HHS EB01651NIBIB NIH HHS P41 EB015922NIBIB NIH HHS R01 EB016516NIBIB NIH HHS U54 EB020403NLM NIH HHS LM05639NLM NIH HHS R01 LM005639
6 · The paper itself

Abstract

In a previous report, we proposed a method for combining multiple markers of atrophy caused by Alzheimer's disease into a single atrophy score that is more powerful than any one feature. We applied the method to expansion rates of the lateral ventricles, achieving the most powerful ventricular atrophy measure to date. Here, we expand our method's application to tensor-based morphometry measures. We also combine the volumetric tensor-based morphometry measures with previously computed ventricular surface measures into a combined atrophy score. We show that our atrophy scores are longitudinally unbiased with the intercept bias estimated at 2 orders of magnitude below the mean atrophy of control subjects at 1 year. Both approaches yield the most powerful biomarker of atrophy not only for ventricular measures but also for all published unbiased imaging measures to date. A 2-year trial using our measures requires only 31 (22, 43) Alzheimer's disease subjects or 56 (44, 64) subjects with mild cognitive impairment to detect 25% slowing in atrophy with 80% power and 95% confidence.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseAtrophyBiomarkersCerebral VentriclesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuroimagingBiomarkersADNIAlzheimer's diseaseBiomarkerDrug trialLateral ventriclesLinear discriminant analysisMachine learningMild cognitive impairmentShape analysisTensor-based morphometry

Identifiers

PMID25260848
PMCPMC4268333
OpenAlexW2064222308

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.