Evidence map›Paper›PMID 26233204›Full record

ArticleMedical physics2015

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model.

Chen Yang, Dong-Hoon Lee, Antonella Mangraviti, Lin Su, Kai Zhang, Yin Zhang, Bin Zhang, Wenxiao Li, Betty Tyler, John Wong and 4 more

Abstract read
In one paragraph

Article in Medical physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.2field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 16 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

14 authors at 3 institutions in 2 countries.

Chen YangDepartment of Ultrasound, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China.
Dong-Hoon LeeDivision of MR Research, Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
Antonella MangravitiDepartment of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
Lin SuDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Kai ZhangDivision of MR Research, Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
Yin ZhangDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Bin ZhangDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Wenxiao LiDivision of MR Research, Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
Betty TylerDepartment of Neurosurgery, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
John WongDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Ken Kang-Hsin WangDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Esteban VelardeDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Jinyuan ZhouDivision of MR Research, Department of Radiology, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21287.
Kai DingDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, School of Medicine, Baltimore, Maryland 21231.
Johns Hopkins University · USJohns Hopkins Medicine · USZhejiang Cancer Hospital · CN

Funding

Amide Proton Transfer (APT) MRI of Brain Tumors at 3T and 7TR01EB009731 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ZHOU, JINYUAN · 2009 to 2016
$2.9M
Academic-Industrial Partnership to Develop Clinical Brain Cancer ImagingR01CA166171 · NCI · JOHNS HOPKINS UNIVERSITY · PI VAN ZIJL, PETER CM, ZHOU, JINYUAN · 2013 to 2017
$2.4M
Molecular MRI of Radiation Necrosis in Preclinical ModelsR21EB015555 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ZHOU, JINYUAN · 2012 to 2013
$447k
NCI NIH HHS R01 CA166171NCI NIH HHS R01CA166171NIBIB NIH HHS R01 EB009731NIBIB NIH HHS R01EB009731NIBIB NIH HHS R21 EB015555NIBIB NIH HHS R21EB015555
6 · The paper itself

Abstract

purposeRadiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma.

methodsThirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performed to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging.

resultsArea under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T2, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = - 0.527, p < 0.05), time to peak (r = - 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = - 0.589, p < 0.01) and time to peak (r = - 0.543, p < 0.05).

conclusionsMRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.

Indexed as

Contrast MediaMicrobubblesAnimalsArea Under CurveBrainBrain NeoplasmsCell Line, TumorCerebrovascular CirculationEchoencephalographyGliomaHumansMagnetic Resonance ImagingMaleMolecular ImagingNeoplasm TransplantationRats, NudeContrast Media

Identifiers

PMID26233204
PMCPMC4514724
OpenAlexW1526121022

What OpenQuestion holds

Textmetadata
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.