Evidence map›Paper›PMID 32319527›Full record

ArticleNeuro-oncology2020

Recurrent tumor and treatment-induced effects have different MR signatures in contrast enhancing and non-enhancing lesions of high-grade gliomas.

Julia Cluceru, Sarah J Nelson, Qiuting Wen, Joanna J Phillips, Anny Shai, Annette M Molinaro, Paula Alcaide-Leon, Marram P Olson, Devika Nair, Marisa LaFontaine and 6 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuro-oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 32% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

16 authors at 1 institution in 1 country.

Julia CluceruDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Sarah J NelsonDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Qiuting WenDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Joanna J PhillipsDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Anny ShaiDepartment of Neurological Surgery, University of California San Francisco, San Francisco, California.
Annette M MolinaroDepartment of Neurological Surgery, University of California San Francisco, San Francisco, California.
Paula Alcaide-LeonDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Marram P OlsonDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Devika NairDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Marisa LaFontaineDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Pranathi ChunduruDepartment of Neurological Surgery, University of California San Francisco, San Francisco, California.
Javier E Villanueva-MeyerDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Soonmee ChaDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
Susan M ChangDepartment of Neurological Surgery, University of California San Francisco, San Francisco, California.
Mitchel S BergerDepartment of Neurological Surgery, University of California San Francisco, San Francisco, California.
Janine M LupoDepartment of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
University of California, San Francisco · US

Funding

Project 4: Multi-modality Metabolic Imaging for Monitoring Molecular Sub-types of GliomaP01CA118816 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Pavithra Viswanath · 2007 to 2026
$44.7M
Training Program in Translational Brain Tumor ResearchT32CA151022 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Joseph F Costello · 2010 to 2026
$6.6M
NCI NIH HHS P01 CA118816NCI NIH HHS T32 CA151022
6 · The paper itself

Abstract

backgroundDifferentiating treatment-induced injury from recurrent high-grade glioma is an ongoing challenge in neuro-oncology, in part due to lesion heterogeneity. This study aimed to determine whether different MR features were relevant for distinguishing recurrent tumor from the effects of treatment in contrast-enhancing lesions (CEL) and non-enhancing lesions (NEL).

methodsThis prospective study analyzed 291 tissue samples (222 recurrent tumor, 69 treatment-effect) with known coordinates on imaging from 139 patients who underwent preoperative 3T MRI and surgery for a suspected recurrence. 8 MR parameter values were tested from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location for association with histopathological outcome using generalized estimating equation models for CEL and NEL tissue samples. Individual cutoff values were evaluated using receiver operating characteristic curve analysis with 5-fold cross-validation.

resultsIn tissue samples obtained from CEL, elevated relative cerebral blood volume (rCBV) was associated with the presence of recurrent tumor pathology (P < 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were associated with the presence of recurrent tumor pathology in NEL tissue samples (P < 0.008). A mean CNI cutoff value of 2.7 had the highest performance, resulting in mean sensitivity and specificity of 0.61 and 0.81 for distinguishing treatment-effect from recurrent tumor within the NEL.

conclusionAlthough our results support prior work that underscores the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion, we found that metabolic parameters may be better at differentiating recurrent tumor from treatment-related changes in the NEL of high-grade gliomas.

Indexed as

Brain NeoplasmsGliomaHumansMagnetic Resonance ImagingMagnetic Resonance SpectroscopyProspective Studiesdiffusion-weighted imagingDSC perfusion imagingglioblastomahigh-grade gliomaimage-guided tissue acquisitionMRIMRSIspectroscopic imagingtreatment effect

Identifiers

PMID32319527
PMCPMC7566399
OpenAlexW2984880354

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.