Evidence map›Paper›PMID 38884083›Full record

ArticleFrontiers in oncology2024

MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma.

Stephanie J Blocker, Yvonne M Mowery, Jeffrey I Everitt, James Cook, Gary Price Cofer, Yi Qi, Alex M Bassil, Eric S Xu, David G Kirsch, Cristian T Badea and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Stephanie J BlockerDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.
Yvonne M MoweryDepartment of Radiation Oncology, Hillman Cancer Center, University of Pittsburgh Medical Center, Pittsburgh, PA, United States.
Jeffrey I EverittDepartment of Pathology, Duke University Medical Center, Duke University, Durham, NC, United States.
James CookDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.
Gary Price CoferDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.
Yi QiDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.
Alex M BassilDepartment of Radiation Oncology, Duke University Medical Center, Duke University, Durham, NC, United States.
Eric S XuDuke University Medical Center, Duke University, Durham, NC, United States.
David G KirschDepartments of Radiation Oncology and Medical Biophysics, Princess Margaret Cancer Centre, University Health Network (UHN), Toronto, ON, Canada.
Cristian T BadeaDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.
G Allan JohnsonDepartment of Radiology, Duke University Medical Center, Duke University, Durham, NC, United States.

Funding

Advancing Cancer Therapy through Ground Breaking Research in Radiation BiologyR35CA197616 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI David Guy Kirsch · 2016 to 2026
$10.7M
The Duke Preclinical Research Resources for Quantitative Imaging BiomarkersU24CA220245 · NCI · DUKE UNIVERSITY · PI BADEA, CRISTIAN T · 2017 to 2021
$2.8M
NCI NIH HHS R35 CA197616NCI NIH HHS U24 CA220245
6 · The paper itself

Abstract

Purpose: To identify significant relationships between quantitative cytometric tissue features and quantitative MR (qMRI) intratumorally in preclinical undifferentiated pleomorphic sarcomas (UPS). Materials and methods: In a prospective study of genetically engineered mouse models of UPS, we registered imaging libraries consisting of matched multi-contrast Results: Three features correlated with Conclusion: Registered multi-parametric imaging datasets can identify quantitative tissue features which contribute to UPS MR signal. T2* may provide quantitative information about nuclear morphology and pleomorphism, adding histological insights to radiological interpretation of UPS.

Indexed as

feature mappinghistologyimage registrationMRImulti-modalpreclinicalsarcoma

Identifiers

PMID38884083
PMCPMC11176416

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.