Evidence map›Paper›PMID 31765494›Full record

ArticleMagnetic resonance in medicine2020

Magnetic resonance imaging of mean cell size in human breast tumors.

Junzhong Xu, Xiaoyu Jiang, Hua Li, Lori R Arlinghaus, Eliot T McKinley, Sean P Devan, Benjamin M Hardy, Jingping Xie, Hakmook Kang, A Bapsi Chakravarthy and 1 more

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing 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

77 citing papers in PubMed.

  1. Trial
  2. Article
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  4. Diffusion MRI of the Body: Beyond PGSE-EPI.Journal of magnetic resonance imaging : JMRI · 2026
    Review
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  15. Observational
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  18. Time-dependent diffusion MRI as in vivo histology: microstructural biomarkers for breast cancer diagnosis and prognostic stratification.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    Article
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

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

11 authors.

Junzhong XuInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0001-7895-4232
Xiaoyu JiangInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.ORCID 0000-0002-0369-6301
Hua LiInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Lori R ArlinghausInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Eliot T McKinleyDepartment of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
Sean P DevanInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Benjamin M HardyInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Jingping XieInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.
Hakmook KangDepartment of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.
A Bapsi ChakravarthyDepartment of Radiation Oncology, Vanderbilt University Medical Center, Nashville, Tennessee.
John C GoreInstitute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding

Tumor Immunology and Microenvironment Research ProgramP30CA068485 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI STACIE B DUSETZINA · 1995 to 2026
$172.8M
Vanderbilt Institute for Clinical and Translational Research (VICTR) -Identifying correlates of functional immunity in SARS-CoV-2 convalescent plasmaUL1TR002243 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI Paul A. Harris, Wesley H Self · 2017 to 2026
$130.7M
The Vanderbilt Institute for Clinical and Translational Research (VICTR)UL1TR000445 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI BERNARD, GORDON RAPHAEL · 2012 to 2016
$41.4M
Quantitative MRI for Predicting Response of Breast Cancer to Neoadjuvant TherapyU01CA142565 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI KARCZMAR, GREGORY S., NANDA, RITA · 2010 to 2019
$4.5M
MRI Diffusion in Tumors Using Oscillating GradientsR01CA109106 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI XU, JUNZHONG · 2006 to 2022
$4.0M
Replacement and Upgrade of a 3T MR Scanner for ResearchS10OD021771 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2016 to 2016
$2.0M
Comprehensive Evaluation of OGSE DWI for Assessing Tumor Treatment ResponseR01CA173593 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GORE, JOHN C · 2013 to 2017
$1.3M
Assessment of Tumor Early Response to Treatment by Diffusion MRIK25CA168936 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI XU, JUNZHONG · 2013 to 2017
$728k
Early assessment of radiation response in brain tumors using quantitative temporal diffusion spectroscopyF32CA216942 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI JIANG, XIAOYU · 2017 to 2018
$77k
NCATS NIH HHS UL1 TR000445NCATS NIH HHS UL1 TR002243NCI NIH HHS F32 CA216942NCI NIH HHS K25 CA168936NCI NIH HHS P30 CA068485NCI NIH HHS R01 CA109106NCI NIH HHS R01 CA173593NCI NIH HHS U01 CA142565NIH HHS S10 OD021771
6 · The paper itself

Abstract

purposeCell size is a fundamental characteristic of all tissues, and changes in cell size in cancer reflect tumor status and response to treatments, such as apoptosis and cell-cycle arrest. Unfortunately, cell size can currently be obtained only by pathological evaluation of tumor tissue samples obtained invasively. Previous imaging approaches are limited to preclinical MRI scanners or require relatively long acquisition times that are impractical for clinical imaging. There is a need to develop cell-size imaging for clinical applications.

methodsWe propose a clinically feasible IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) approach that can characterize mean cell sizes in solid tumors. We report the use of a combination of pulse sequences, using different gradient waveforms implemented on clinical MRI scanners and analytical equations based on these waveforms to analyze diffusion-weighted MRI signals and derive specific microstructural parameters such as cell size. We also describe comprehensive validations of this approach using computer simulations, cell experiments in vitro, and animal experiments in vivo and demonstrate applications in preoperative breast cancer patients.

resultsWith fast acquisitions (~7 minutes), IMPULSED can provide high-resolution (1.3 mm in-plane) mapping of mean cell size of human tumors in vivo on clinical 3T MRI scanners. All validations suggest that IMPULSED provides accurate and reliable measurements of mean cell size.

conclusionThe proposed IMPULSED method can assess cell-size variations in tumors of breast cancer patients, which may have the potential to assess early response to neoadjuvant therapy.

Indexed as

Breast NeoplasmsMagnetic Resonance ImagingAnimalsCell SizeDiffusion Magnetic Resonance ImagingHumansSensitivity and Specificitycell sizedensitydiameterdiffusionIMPULSEDMRIOGSEoscillating gradient

Identifiers

PMID31765494
PMCPMC7047520

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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.