Evidence map›Paper›PMID 37705496›Full record

ArticleMagnetic resonance in medicine2024

Time-efficient, high-resolution 3T whole-brain relaxometry using 3D-QALAS with wave-CAIPI readouts.

Jaejin Cho, Borjan Gagoski, Tae Hyung Kim, Fuyixue Wang, Mary Kate Manhard, Douglas Dean, Steven Kecskemeti, Arvind Caprihan, Wei-Ching Lo, Daniel Nico Splitthoff and 6 more

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Group-Patch Joint Compression: Compressing Dynamic BMagnetic resonance in medicine · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Comparison of test-retest repeatability of DESPOT and 3D-QALAS for TQuantitative imaging in medicine and surgery · 2025
    Article
  7. Article
  8. Quantitative TImaging neuroscience (Cambridge, Mass.) · 2025
    Article
  9. Review
  10. Article
  11. 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

16 authors.

Jaejin ChoAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID 0000-0001-5672-6765
Borjan GagoskiDepartment of Radiology, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-3777-2621
Tae Hyung KimDepartment of Computer Engineering, Hongik University, Seoul, South Korea.ORCID 0000-0001-5881-7265
Fuyixue WangAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID 0000-0001-8975-2775
Mary Kate ManhardDepartment of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.ORCID 0000-0001-5374-9988
Douglas DeanWaisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0002-7057-1285
Steven KecskemetiWaisman Center, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID 0000-0003-3589-430X
Arvind CaprihanThe Mind Research Network, Albuquerque, New Mexico, USA.
Wei-Ching LoSiemens Medical Solutions USA, Inc., Charlestown, Massachusetts, USA.
Daniel Nico SplitthoffSiemens Healthcare GmbH, Erlangen, Germany.
Wei LiuSiemens Healthcare GmbH, Erlangen, Germany.
Daniel PolakSiemens Healthcare GmbH, Erlangen, Germany.ORCID 0000-0001-9781-1528
Stephen CauleyAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.
Kawin SetsompopDepartment of Electrical Engineering, Stanford University, Stanford, California, USA.
Patricia Ellen GrantDepartment of Radiology, Harvard Medical School, Boston, Massachusetts, USA.
Berkin BilgicAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.ORCID 0000-0002-9080-7865

Funding

CONNECTOME 2.0: DEVELOPING THE NEXT GENERATION HUMAN MRI SCANNER FOR BRIDGING STUDIES OF THE MICRO-, MESO- AND MACRO-CONNECTOMEU01EB026996 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BASSER, PETER J., HUANG, SUSIE YI · 2018 to 2022
$14.2M
MRI CORTICOGRAPHY: DEVELOPING NEXT GENERATION MICROSCALE HUMAN CORTEX MRI SCANNERU01EB025162 · NIBIB · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEINBERG, DAVID ALAN, LIU, CHUNLEI · 2017 to 2021
$13.4M
5/24 Healthy Brain and Child Development National ConsortiumU01DA055353 · NIDA · BOSTON CHILDREN'S HOSPITAL · PI Michelle A Bosquet Enlow, Patricia Ellen Grant · 2021 to 2026
$12.1M
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang · 2020 to 2026
$10.9M
Advanced Fetal ImagingR01EB017337 · NIBIB · BOSTON CHILDREN'S HOSPITAL · PI ADALSTEINSSON, ELFAR, GRANT, PATRICIA ELLEN · 2014 to 2018
$6.2M
Novel MRI Assessment of Placental Structure and Function Throughout PregnancyR01HD100009 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI ADALSTEINSSON, ELFAR, GRANT, PATRICIA ELLEN · 2019 to 2023
$3.6M
MRI technology for restoring brain image quality for pediatric patients with metallic orthodontic hardwareR01EB028797 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Berkin Bilgic, Jason P Stockmann · 2020 to 2026
$3.0M
Harmonizing data acquisition, reconstruction, and analysis for reproducible, cross-vendor, open source MRIR01EB032378 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI BILGIC, BERKIN, RATHI, YOGESH · 2022 to 2025
$2.7M
Rapid Fetal HASTE MR ImagingR03EB031175 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI BILGIC, BERKIN · 2021 to 2022
$188k
NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB017337NIBIB NIH HHS R01 EB028797NIBIB NIH HHS R01 EB032378NIBIB NIH HHS R03 EB031175NIBIB NIH HHS U01 EB025162NIBIB NIH HHS U01 EB026996NICHD NIH HHS R01 HD100009NIDA NIH HHS U01 DA055353NIH HHS P41EB030006NIH HHS R01EB017337NIH HHS R01EB028797NIH HHS R01EB032378NIH HHS R01HD100009NIH HHS R03EB031175NIH HHS U01DA055353-01NIH HHS U01EB025162NIH HHS U01EB026996
6 · The paper itself

Abstract

purposeVolumetric, high-resolution, quantitative mapping of brain-tissue relaxation properties is hindered by long acquisition times and SNR challenges. This study combines time-efficient wave-controlled aliasing in parallel imaging (wave-CAIPI) readouts with the 3D quantification using an interleaved Look-Locker acquisition sequence with a T

methodsWave-CAIPI readouts were embedded in the standard 3D-QALAS encoding scheme, enabling full-brain quantitative parameter maps (T

resultsWhen tested in both the ISMRM/NIST phantom and 10 healthy volunteers, the quantitative maps using the accelerated protocol showed excellent agreement against those obtained from conventional 3D-QALAS at R

conclusionThree-dimensional QALAS enhanced with wave-CAIPI readouts enables time-efficient, full-brain quantitative T

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingBrainBrain MappingHumansPhantoms, ImagingReproducibility of Results3D-QALAST1/T2/PD mappingtime-efficient quantitative mappingwave-CAIPI

Identifiers

PMID37705496
PMCPMC13439506

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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.