Evidence map›Paper›PMID 31233953›Full record

ArticleNeuroImage. Clinical2019

Non-linear registration improves statistical power to detect hippocampal atrophy in aging and dementia.

F Bartel, M Visser, M de Ruiter, J Belderbos, F Barkhof, H Vrenken, J C de Munck, M van Herk, Alzheimer's Disease Neuroimaging Initiative

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. 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 2 countries.

F BartelDepartment of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands. Electronic address: f.bartel@vumc.nl.
M VisserDepartment of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
M de RuiterDivision of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
J BelderbosDepartment of Radiotherapy, Netherlands Cancer Institute, Amsterdam, the Netherlands.
F BarkhofDepartment of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands; UCL institutes of Neurology and healthcare engineering, London, United Kingdom.
H VrenkenDepartment of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
J C de MunckDepartment of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands.
M van HerkManchester Cancer Research Centre, Division of Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom.
Alzheimer's Disease Neuroimaging Initiative
Amsterdam UMC Location Vrije Universiteit Amsterdam · NLThe Netherlands Cancer Institute · NLManchester Academic Health Science Centre · GBUniversity College London · GB

Funding

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 DECARLI, CHARLES · 1991 to 2020
$28.3M
"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
NIA NIH HHS K01 AG030514NIA NIH HHS P30 AG010129NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

objectiveTo compare the performance of different methods for determining hippocampal atrophy rates using longitudinal MRI scans in aging and Alzheimer's disease (AD).

backgroundQuantifying hippocampal atrophy caused by neurodegenerative diseases is important to follow the course of the disease. In dementia, the efficacy of new therapies can be partially assessed by measuring their effect on hippocampal atrophy. In radiotherapy, the quantification of radiation-induced hippocampal volume loss is of interest to quantify radiation damage. We evaluated plausibility, reproducibility and sensitivity of eight commonly used methods to determine hippocampal atrophy rates using test-retest scans. MATERIALS AND

methodsManual, FSL-FIRST, FreeSurfer, multi-atlas segmentation (MALF) and non-linear registration methods (Elastix, NiftyReg, ANTs and MIRTK) were used to determine hippocampal atrophy rates on longitudinal T1-weighted MRI from the ADNI database. Appropriate parameters for the non-linear registration methods were determined using a small training dataset (N = 16) in which two-year hippocampal atrophy was measured using test-retest scans of 8 subjects with low and 8 subjects with high atrophy rates. On a larger dataset of 20 controls, 40 mild cognitive impairment (MCI) and 20  AD patients, one-year hippocampal atrophy rates were measured. A repeated measures ANOVA analysis was performed to determine differences between controls, MCI and AD patients. For each method we calculated effect sizes and the required sample sizes to detect one-year volume change between controls and MCI (N

resultsExcept for MALF, all methods detected a significant group difference between CTRL and AD, but none could find a significant difference between the CTRL and MCI. FreeSurfer and MIRTK required the lowest sample sizes (FreeSurfer: N DISCUSSION AND

conclusionNon-linear registration methods were most consistent in determining hippocampal atrophy and because of their better reproducibility, methods, such as ANTs, Elastix and NiftyReg, are preferred for determining hippocampal atrophy rates on longitudinal MRI. Since performances of non-linear registration methods are well comparable, the preferred method would mostly depend on computational efficiency.

Indexed as

AgedAged, 80 and overAgingAlzheimer DiseaseAtrophyCognitive DysfunctionDatabases, FactualFemaleHippocampusHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleNeuroimagingADAutomatic segmentationHippocampal atrophyLongitudinal MRIMCINon-linear registration

Identifiers

PMID31233953
PMCPMC6595082
OpenAlexW2949425208

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.