Evidence map›Paper›PMID 35366813›Full record

ArticleBMC medical imaging2022

Comparison of test-retest reliability of BOLD and pCASL fMRI in a two-center study.

James W Ibinson, Andrea G Gillman, Vince Schmidthorst, Conrad Li, Vitaly Napadow, Marco L Loggia, Ajay D Wasan

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

James W Ibinson *Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Andrea G Gillman *Department of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Vince SchmidthorstDepartment of Radiology, University of Pittsburgh, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Conrad LiDepartment of Bioengineering, Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA.
Vitaly NapadowA. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Marco L LoggiaA. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
Ajay D WasanDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA. wasanad@upmc.edu.
University of Pittsburgh · USAthinoula A. Martinos Center for Biomedical Imaging · USMassachusetts General Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe establishment of test-retest reliability and reproducibility (TRR) is an important part of validating any research tool, including functional magnetic resonance imaging (fMRI). The primary objective of this study is to investigate the reliability of pseudo-Continuous Arterial Spin Labeling (pCASL) and Blood Oxygen Level Dependent (BOLD) fMRI data acquired across two different scanners in a sample of healthy adults. While single site/single scanner studies have shown acceptable repeatability, TRR of both in a practical multisite study occurring in two facilities spread out across the country with weeks to months between scans is critically needed.

methodsTen subjects were imaged with similar 3 T MRI scanners at the University of Pittsburgh and Massachusetts General Hospital. Finger-tapping and Resting-state data were acquired for both techniques. Analysis of the resting state data for functional connectivity was performed with the Functional Connectivity Toolbox, while analysis of the finger tapping data was accomplished with FSL. pCASL Blood flow data was generated using AST Toolbox. Activated areas and networks were identified via pre-defined atlases and dual-regression techniques. Analysis for TRR was conducted by comparing pCASL and BOLD images in terms of Intraclass correlation coefficients, Dice Similarity Coefficients, and repeated measures ANOVA.

resultsBoth BOLD and pCASL scans showed strong activation and correlation between the two locations for the finger tapping tasks. Functional connectivity analyses identified elements of the default mode network in all resting scans at both locations. Multivariate repeated measures ANOVA showed significant variability between subjects, but no significant variability for location. Global CBF was very similar between the two scanning locations, and repeated measures ANOVA showed no significant differences between the two scanning locations.

conclusionsThe results of this study show that when similar scanner hardware and software is coupled with identical data analysis protocols, consistent and reproducible functional brain images can be acquired across sites. The variability seen in the activation maps is greater for pCASL versus BOLD images, as expected, however groups maps are remarkably similar despite the low number of subjects. This demonstrates that multi-site fMRI studies of task-based and resting state brain activity is feasible.

Indexed as

Cerebrovascular CirculationMagnetic Resonance ImagingAdultHumansReproducibility of ResultsRestSpin LabelsSpin LabelsBlood oxygen level dependentFinger tappingFunctional magnetic resonance imagingPseudo-continuous arterial spin labelingResting state functional connectivityTest–retest reliability

Identifiers

PMID35366813
PMCPMC8977011
OpenAlexW4223989668

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Registered trials

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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.