Evidence map›Paper›PMID 34294864›Full record

ArticleScientific reports2021

Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging.

Hamed Akbari, Anahita Fathi Kazerooni, Jeffrey B Ware, Elizabeth Mamourian, Hannah Anderson, Samantha Guiry, Chiharu Sako, Catalina Raymond, Jingwen Yao, Steven Brem and 6 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 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

16 authors at 3 institutions in 1 country.

Hamed Akbari *Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Anahita Fathi Kazerooni *Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Jeffrey B WareDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Elizabeth MamourianDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Hannah AndersonDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Samantha GuiryDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Chiharu SakoDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Catalina RaymondUCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Jingwen YaoUCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Steven BremDepartment of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Donald M O'RourkeDepartment of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Arati S DesaiDivision of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Stephen J BagleyDivision of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Benjamin M EllingsonUCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
Christos DavatzikosDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
Ali NabavizadehDepartment of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA. Ali.Nabavizadeh@pennmedicine.upenn.edu.
University of Pennsylvania · USHospital of the University of Pennsylvania · USUniversity of California, Los Angeles · US

Funding

UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert M Prins · 2017 to 2026
$25.2M
Statistical atlases of brain tumor MRI:do imaging phenotypes predict progression?R01NS042645 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI DAVATZIKOS, CHRISTOS · 2002 to 2024
$8.7M
Cancer imaging phenomics software suite: application to brain and breast cancerU24CA189523 · NCI · UNIVERSITY OF PENNSYLVANIA · PI DAVATZIKOS, CHRISTOS, KONTOS, DESPINA · 2015 to 2019
$3.2M
Metabolic MRI for quantifying aerobic glycolysis and immune function in gliomasR21CA223757 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ELLINGSON, BENJAMIN M. · 2018 to 2019
$366k
Role of Nix in pancreatic ductal adenocarcinomaF30CA200240 · NCI · STATE UNIVERSITY NEW YORK STONY BROOK · PI ALAGESAN, BRINDA · 2016 to 2019
$148k
EPA EP-C-15-003NCI NIH HHS F30 CA200240NCI NIH HHS P50 CA211015NCI NIH HHS R21 CA223757NCI NIH HHS U24 CA189523NINDS NIH HHS R01 NS042645
6 · The paper itself

Abstract

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTR

Indexed as

Hydrogen-Ion ConcentrationTumor MicroenvironmentAgedAnimalsData Interpretation, StatisticalDisease Models, AnimalFemaleGlioblastomaHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiceMiddle AgedNeoplasm GradingNeoplasm Staging

Identifiers

PMID34294864
PMCPMC8298590
OpenAlexW3186543935

What OpenQuestion holds

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LicenceCC BY
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.