Evidence map›Paper›PMID 32879995›Full record

ArticleNeuroradiology2021

Differentiation of recurrent diffuse glioma from treatment-induced change using amide proton transfer imaging: incremental value to diffusion and perfusion parameters.

Yae Won Park, Sung Soo Ahn, Eui Hyun Kim, Seok-Gu Kang, Jong Hee Chang, Se Hoon Kim, Jinyuan Zhou, Seung-Koo Lee

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Neuroradiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
3.1field-weighted citation impact, top 6% 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 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 2 institutions in 2 countries.

Yae Won ParkDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
Sung Soo AhnDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea. sungsoo@yuhs.ac.ORCID http://orcid.org/0000-0002-0503-5558
Eui Hyun KimDepartment of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea.
Seok-Gu KangDepartment of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea.
Jong Hee ChangDepartment of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea.
Se Hoon KimDepartment of Pathology, Yonsei University College of Medicine, Seoul, Korea.
Jinyuan ZhouDivision of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Seung-Koo LeeDepartment of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
Yonsei University · KRJohns Hopkins University · US

Funding

Korea Basic Science Institute 2014R1A1A1002716Korea Basic Science Institute 2017R1D1A1B03030440Korea Basic Science Institute 2020R1I1A1A0107164811Korean Society for Neuro-Oncology na
6 · The paper itself

Abstract

purposeTo evaluate the incremental value of amide proton transfer (APT) imaging to diffusion tensor imaging (DTI), dynamic susceptibility contrast (DSC) imaging, and dynamic contrast-enhanced (DCE) imaging in differentiating recurrent diffuse gliomas (World Health Organization grade II-IV) from treatment-induced change after concurrent chemoradiotherapy or radiotherapy.

methodsThis study included 36 patients (25 patients with recurrent gliomas and 11 with treatment-induced changes) with post-treatment gliomas. The mean values of apparent diffusion coefficient (ADC), fractional anisotropy (FA), normalized cerebral blood volume (nCBV), normalized cerebral blood flow, volume transfer constant, rate transfer coefficient, extravascular extracellular volume fraction, plasma volume fraction, and APT asymmetry index were assessed. Independent quantitative parameters were investigated to predict recurrent glioma using multivariable logistic regression. The incremental value of APT signal to other parameters was assessed by the increase of the area under the curve, net reclassification index, and integrated discrimination improvement.

resultsUnivariable analysis showed that lower ADC (p = 0.018), higher FA (p = 0.031), higher nCBV (p = 0.021), and higher APT signal (p = 0.009) were associated with recurrent gliomas. In multivariable logistic regression, the diagnostic performance of the model with ADC, FA, and nCBV significantly increased when APT signal was added, with areas under the curve of 0.87 and 0.92, respectively (net reclassification index of 0.77 and integrated discrimination improvement of 0.13).

conclusionAPT imaging may be a useful imaging biomarker that adds value to DTI, DCE, and DSC parameters for distinguishing between recurrent gliomas and treatment-induced changes.

Indexed as

Brain NeoplasmsGliomaAmidesDiffusion Tensor ImagingHumansMagnetic Resonance ImagingNeoplasm GradingNeoplasm Recurrence, LocalPerfusionProtonsAmidesProtonsAmidesChemoradiotherapyGliomaMagnetic resonance imaging

Identifiers

PMID32879995
OpenAlexW3082087280

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.