Evidence map›Paper›PMID 38446357›Full record

ArticleNeuroinformatics2024

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline.

Lanya T Cai, Joseph Moon, Paul B Camacho, Aaron T Anderson, Won Jong Chwa, Bradley P Sutton, Amy J Markowitz, Eva M Palacios, Alexis Rodriguez, Geoffrey T Manley and 5 more

Abstract read
PubMed Publisher
In one paragraph

Article in Neuroinformatics, 2024. 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

15 authors.

Lanya T Cai *Department of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., San Francisco, CA, 94107, USA.
Joseph Moon *Lawrence Livermore National Laboratory, 7000 East Ave, Livermore, CA, 94550, USA.
Paul B CamachoBeckman Institute, University of Illinois at Urbana-Champaign, 405 N Mathews Ave, Urbana, IL, 61801, USA.
Aaron T AndersonBeckman Institute, University of Illinois at Urbana-Champaign, 405 N Mathews Ave, Urbana, IL, 61801, USA.
Won Jong ChwaDepartment of Radiology, Washington University in St. Louis, 510 S Kingshighway Blvd, St. Louis, MO, 63110, USA.
Bradley P SuttonBioengineering Department, University of Illinois at Urbana-Champaign, 506 S Mathews Ave, Urbana, IL, 61801, USA.
Amy J MarkowitzDepartment of Neurosurgery, University of California, San Francisco, 400 Parnassus Ave, San Francisco, CA, 94143, USA.
Eva M PalaciosDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., San Francisco, CA, 94107, USA.
Alexis RodriguezArgonne National Laboratory, 9700 S Cass Ave, Lemont, IL, 60439, USA.
Geoffrey T ManleyDepartment of Neurosurgery, University of California, San Francisco, 400 Parnassus Ave, San Francisco, CA, 94143, USA.
Shivsundaram ShankarLawrence Livermore National Laboratory, 7000 East Ave, Livermore, CA, 94550, USA.
Peer-Timo BremerLawrence Livermore National Laboratory, 7000 East Ave, Livermore, CA, 94550, USA.
Pratik MukherjeeDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, 185 Berry St., San Francisco, CA, 94107, USA. pratik.mukherjee@ucsf.edu.
Ravi K MadduriArgonne National Laboratory, 9700 S Cass Ave, Lemont, IL, 60439, USA. madduri@anl.gov.
TRACK-TBI Investigators

Funding

NIH/NINDS/NIBIB/NICHD/NIDCD U01 NS086090-01U.S. Department of Defense W81XWH-14-2-0176U.S. Department of Energy B628729U.S. Department of Energy DE-AC02-06CH11357U.S. Department of Energy KJ040301
6 · The paper itself

Abstract

Large-scale diffusion MRI tractography remains a significant challenge. Users must orchestrate a complex sequence of instructions that requires many software packages with complex dependencies and high computational costs. We developed MaPPeRTrac, an edge-centric tractography pipeline that simplifies and accelerates this process in a wide range of high-performance computing (HPC) environments. It fully automates either probabilistic or deterministic tractography, starting from a subject's magnetic resonance imaging (MRI) data, including structural and diffusion MRI images, to the edge density image (EDI) of their structural connectomes. Dependencies are containerized with Singularity (now called Apptainer) and decoupled from code to enable rapid prototyping and modification. Data derivatives are organized with the Brain Imaging Data Structure (BIDS) to ensure that they are findable, accessible, interoperable, and reusable following FAIR principles. The pipeline takes full advantage of HPC resources using the Parsl parallel programming framework, resulting in the creation of connectome datasets of unprecedented size. MaPPeRTrac is publicly available and tested on commercial and scientific hardware, so it can accelerate brain connectome research for a broader user community. MaPPeRTrac is available at: https://github.com/LLNL/mappertrac .

Indexed as

ConnectomeMagnetic Resonance ImagingBrainDiffusion Magnetic Resonance ImagingConnectomesEdge density imagingFAIRHigh performance computingTractography

Identifiers

PMID38446357

What OpenQuestion holds

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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.