Evidence map›Paper›PMID 37418036›Full record

ArticleJournal of medical systems2023

Continuous Automated Analysis Workflow for MRS Studies.

Helge Jörn Zöllner, Christopher W Davies-Jenkins, Erik G Lee, Timothy J Hendrickson, William T Clarke, Richard A E Edden, Jessica L Wisnowski, Aaron T Gudmundson, Georg Oeltzschner

Abstract read
In one paragraph

Article in Journal of medical systems, 2023. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Helge Jörn ZöllnerRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA. hzoelln2@jhmi.edu.
Christopher W Davies-JenkinsRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Erik G LeeMasonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
Timothy J HendricksonMasonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
William T ClarkeWellcome Centre for Integrative Neuroimaging, Department of Clinical Neurosciences, FMRIB, University of Oxford, Oxford, Nuffield, UK.
Richard A E EddenRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Jessica L WisnowskiDepartment of Radiology, Keck School of Medicine, Children's Hospital Los Angeles, University of Southern California, Los Angeles, USA.
Aaron T GudmundsonRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Georg OeltzschnerRussell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.

Funding

TRD 4: Platforms for multi-modal and multi-scale imaging dataP41EB031771 · NIBIB · HUGO W. MOSER RES INST KENNEDY KRIEGER · PI Peter CM Van Zijl · 2021 to 2026
$9.9M
2/24 Healthy Brain and Child Development National ConsortiumU01DA055362 · NIDA · CHILDREN'S HOSPITAL OF LOS ANGELES · PI PAT LEVITT, Beth A Smith · 2021 to 2026
$9.6M
Universal GABA-edited MRS at 3TR01EB016089 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI Richard Anthony Edward Edden · 2013 to 2026
$5.4M
Simultaneous Hadamard Editing of GABA and GlutathioneR01EB023963 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI EDDEN, RICHARD ANTHONY EDWARD · 2017 to 2024
$3.8M
Towards a comprehensive neurometabolic profile in patients with mild cognitive impairment.R00AG062230 · NIA · JOHNS HOPKINS UNIVERSITY · PI OELTZSCHNER, GEORG · 2021 to 2023
$735k
Validating MRS lipids as biomarkers of brain injury in neonates with hypoxic-ischemic encephalopathyK23HD099309 · NICHD · CHILDREN'S HOSPITAL OF LOS ANGELES · PI WISNOWSKI, JESSICA L · 2019 to 2023
$693k
General Linear Modeling For Magnetic Resonance SpectroscopyR21EB033516 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI OELTZSCHNER, GEORG · 2022 to 2024
$670k
Towards a comprehensive neurometabolic profile in patients with mild cognitive impairment.K99AG062230 · NIA · JOHNS HOPKINS UNIVERSITY · PI OELTZSCHNER, GEORG · 2019 to 2020
$171k
NIA NIH HHS K99 AG062230NIA NIH HHS R00 AG062230NIBIB NIH HHS P41 EB031771NIBIB NIH HHS R01 EB016089NIBIB NIH HHS R01 EB023963NIBIB NIH HHS R21 EB033516NICHD NIH HHS K23 HD099309NIDA NIH HHS U01 DA055362Wellcome TrustWellcome Trust [225924/Z/22/Z]
6 · The paper itself

Abstract

Magnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review.The proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps.The automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory.Continuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies and offers considerable economic advantages.

Indexed as

SoftwareHumansMagnetic Resonance SpectroscopyProbabilityWorkflowBIDSLinear-combination modelingMagnetic resonance spectroscopyNIfTI-MRSOspreyReproducibility

Identifiers

PMID37418036
PMCPMC10947169

What OpenQuestion holds

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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.