Evidence map›Paper›PMID 38196746›Full record

ArticleArXiv2023

High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting.

Congyu Liao, Xiaozhi Cao, Siddharth Srinivasan Iyer, Sophie Schauman, Zihan Zhou, Xiaoqian Yan, Quan Chen, Zhitao Li, Nan Wang, Ting Gong and 7 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026
    Review
  2. AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026
    Review
  3. AI-based augmentation of oncology clinical trials.Nature reviews. Clinical oncology · 2026
    Review
  4. Review
  5. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 8 institutions in 3 countries.

Congyu LiaoDepartment of Radiology, Stanford University, Stanford, CA, USA.
Xiaozhi CaoDepartment of Radiology, Stanford University, Stanford, CA, USA.
Siddharth Srinivasan IyerDepartment of Radiology, Stanford University, Stanford, CA, USA.
Sophie SchaumanDepartment of Radiology, Stanford University, Stanford, CA, USA.
Zihan ZhouDepartment of Radiology, Stanford University, Stanford, CA, USA.
Xiaoqian YanDepartment of Psychology, Stanford University, Stanford, CA, USA.
Quan ChenDepartment of Radiology, Stanford University, Stanford, CA, USA.
Zhitao LiDepartment of Radiology, Stanford University, Stanford, CA, USA.
Nan WangDepartment of Radiology, Stanford University, Stanford, CA, USA.
Ting GongAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
Zhe WuTechna Institute, University Health Network, Toronto, ON, Canada.
Hongjian HeCenter for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
Jianhui ZhongCenter for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
Yang YangDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
Adam KerrDepartment of Electrical Engineering, Stanford University, Stanford, CA, USA.
Kalanit Grill-SpectorDepartment of Psychology, Stanford University, Stanford, CA, USA.
Kawin SetsompopDepartment of Radiology, Stanford University, Stanford, CA, USA.
Stanford University · USFudan University · CNMassachusetts General Hospital · USMassachusetts Institute of Technology · USUniversity Health Network · CAUniversity of California, San Francisco · USUniversity of Rochester · USZhejiang University · CN

Funding

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
Training and Dissemination CoreP41EB030006 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Susie Yi Huang, BRUCE R ROSEN · 2020 to 2026
$10.9M
Next generation in-vivo diffusion imaging at submillimeter resolutionR01MH116173 · NIMH · STANFORD UNIVERSITY · PI Yogesh Rathi, Kawin Setsompop · 2018 to 2026
$6.2M
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution: Administrative SupplementR01EB019437 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI POLIMENI, JONATHAN RIZZO, SETSOMPOP, KAWIN · 2015 to 2024
$5.5M
NIBIB NIH HHS P41 EB030006NIBIB NIH HHS R01 EB019437NIBIB NIH HHS U01 EB025162NIMH NIH HHS R01 MH116173
6 · The paper itself

Abstract

Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T Methods: We developed 3D ViSTa-MRF, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T Results: The in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in-vivo results of 1mm- and 0.66mm-iso datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30x slower with lower SNR. Furthermore, we applied the proposed method to enable 5-minute whole-brain 1mm-iso assessment of MWF and T Conclusions: In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T

Indexed as

high resolutionmyelin-water fractionquantitative MRI

Identifiers

PMID38196746
PMCPMC10775347
OpenAlexW4390136576

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.