Evidence map›Paper›PMID 32528270›Full record

ArticleFrontiers in neuroinformatics2020

Beware (Surprisingly Common) Left-Right Flips in Your MRI Data: An Efficient and Robust Method to Check MRI Dataset Consistency Using AFNI.

Daniel R Glen, Paul A Taylor, Bradley R Buchsbaum, Robert W Cox, Richard C Reynolds

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  6. Processing, evaluating, and understanding FMRI data with afni_proc.py.Imaging neuroscience (Cambridge, Mass.) · 2024
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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

5 authors.

Daniel R GlenScientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States.
Paul A TaylorScientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States.
Bradley R BuchsbaumRotman Research Institute at Baycrest, Toronto, ON, Canada.
Robert W CoxScientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States.
Richard C ReynoldsScientific and Statistical Computing Core, NIMH/NIH/DHHS, Bethesda, MD, United States.

Funding

Scientific and Statistical Computing CoreZICMH002888 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI TAYLOR, PAUL · 2009 to 2025
$30.9M
BRAIN project (Cox)ZIAMH002974 · NIMH · NATIONAL INSTITUTE OF MENTAL HEALTH · PI COX, ROBERT · 2019 to 2020
$417k
Intramural NIH HHS ZIC MH002888
6 · The paper itself

Abstract

Knowing the difference between left and right is generally assumed throughout the brain MRI research community. However, we note widespread occurrences of left-right orientation errors in MRI open database repositories where volumes have contained systematic left-right flips between subject EPIs and anatomicals, due to having incorrect or missing file header information. Here we present a simple method in AFNI for determining the consistency of left and right within a pair of acquired volumes for a particular subject; the presence of EPI-anatomical inconsistency, for example, is a sign that dataset header information likely requires correction. The method contains both a quantitative evaluation as well as a visualizable verification. We test the functionality using publicly available datasets. Left-right flipping is not immediately obvious in most cases, so we also present visualization methods for looking at this problem (and other potential problems), using examples from both FMRI and DTI datasets.

Indexed as

asymmetryDICOMDTIEPI (echo planar imaging)fMRINiftisymmetryT1-weighted brain image

Identifiers

PMID32528270
PMCPMC7263312

What OpenQuestion holds

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LicenceCC BY
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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.