Evidence map›Paper›PMID 31666092›Full record

ArticleRadiation oncology (London, England)2019

Evaluation of acute esophageal radiation-induced damage using magnetic resonance imaging: a feasibility study in mice.

Pouya Jelvehgaran, Jeffrey D Steinberg, Artem Khmelinskii, Gerben Borst, Ji-Ying Song, Niels de Wit, Daniel M de Bruin, Marcel van Herk

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Radiation oncology (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 24% of its field
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

7 citing papers in PubMed, 13 citations in OpenAlex.

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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

8 authors at 4 institutions in 2 countries.

Pouya JelvehgaranDepartment of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands. p.jelvehgaran@amc.uva.nl.ORCID http://orcid.org/0000-0003-0721-0572
Jeffrey D SteinbergMouse Clinic for Cancer and Aging (MCCA) Imaging Unit, The Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.
Artem KhmelinskiiDepartment of Radiation Oncology, The Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.
Gerben BorstDepartment of Radiation Oncology, The Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.
Ji-Ying SongDepartment of Experimental Animal Pathology, The Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.
Niels de WitMouse Clinic for Cancer and Aging (MCCA) Imaging Unit, The Netherlands Cancer Institute (NKI), Amsterdam, the Netherlands.
Daniel M de BruinDepartment of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands.
Marcel van HerkDepartment of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands.
The Netherlands Cancer Institute · NLAmsterdam University Medical Centers · NLInstitute for Atomic and Molecular Physics · NLManchester Academic Health Science Centre · GB

Funding

Elekta (SE) NoneNine Point Medical None
6 · The paper itself

Abstract

backgroundThoracic and head and neck cancer radiation therapy (RT) can cause damage to nearby healthy organs such as the esophagus, causing acute radiation-induced esophageal damage (ARIED). A non-invasive method to detect and monitor ARIED can facilitate optimizing RT to avoid ARIED while improving local tumor control. Current clinical guidelines are limited to scoring the esophageal damage based on the symptoms of patients. Magnetic resonance imaging (MRI) is a non-invasive imaging modality that may potentially visualize radiation-induced organ damage. We investigated the feasibility of using T2-weighted MRI to detect and monitor ARIED using a two-phased study in mice.

methodsThe first phase aimed to establish the optimal dose level at which ARIED is inducible and to determine the time points where ARIED is detectable. Twenty four mice received a single dose delivery of 20 and 40 Gy at proximal and distal spots of 10.0 mm (in diameter) on the esophagus. Mice underwent MRI and histopathology analysis with esophageal resection at two, three, and 4 weeks post-irradiation, or earlier in case mice had to be euthanized due to humane endpoints. In the second phase, 32 mice received a 40 Gy single dose and were studied at two, three, and 7 days post-irradiation. We detected ARIED as a change in signal intensity of the MRI images. We measured the width of the hyperintense area around the esophagus in all mice that underwent MRI prior to and after irradiation. We conducted a blind qualitative comparison between MRI findings and histopathology as the gold standard. RESULTS/

conclusionsA dose of 40 Gy was needed to induce substantial ARIED. MRI detected ARIED as high signal intensity, visible from 2 days post-irradiation. Quantitative MRI analysis showed that the hyperintense area around the esophagus with severe ARIED was 1.41 mm wider than with no damage and MRI-only mice. The overall sensitivity and specificity were 56 and 43% respectively to detect any form of ARIED. However, in this study MRI correctly detected 100% of severe ARIED cases. Our two-phased preclinical study showed that MRI has the potential to detect ARIED as a change in signal intensity and width of enhancement around the esophagus.

Indexed as

Acute DiseaseAnimalsCone-Beam Computed TomographyEsophagusFeasibility StudiesMagnetic Resonance ImagingMiceQualitative ResearchRadiation InjuriesEsophagusMRIRadiation-induced damageRadiation therapy

Identifiers

PMID31666092
PMCPMC6822441
OpenAlexW2984875330

What OpenQuestion holds

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LicenceCC BY
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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.