Evidence map›Paper›PMID 39377927›Full record

ArticleNeuroradiology2024

Diffusion MRI is superior to quantitative T2-FLAIR mismatch in predicting molecular subtypes of human non-enhancing gliomas.

Nicholas S Cho, Francesco Sanvito, Viên Lam Le, Sonoko Oshima, Ashley Teraishi, Jingwen Yao, Donatello Telesca, Catalina Raymond, Whitney B Pope, Phioanh L Nghiemphu and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuroradiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. A review of MRI signal changes of cerebellar disorders in adults.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
  3. Article
  4. Automated Diffusion Analysis for Noninvasive Prediction ofAJNR. American journal of neuroradiology · 2025
    Article
  5. 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

14 authors.

Nicholas S ChoDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.ORCID http://orcid.org/0000-0002-8686-0575
Francesco SanvitoDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Viên Lam LeDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Sonoko OshimaDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Ashley TeraishiDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Jingwen YaoDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Donatello TelescaDepartment of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
Catalina RaymondDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Whitney B PopeDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Phioanh L NghiemphuUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Albert LaiUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Noriko SalamonDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Timothy F CloughesyUCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Benjamin M EllingsonDepartment of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA. bellingson@mednet.ucla.edu.ORCID http://orcid.org/0000-0002-2764-6640

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Robert Damoiseaux · 1985 to 2026
$134.5M
UCLA-Caltech Medical Scientist Training ProgramT32GM008042 · NIGMS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI AJIJOLA, OLUJIMI A, DAWSON, DAVID WAYNE · 1985 to 2023
$29.9M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Yvonne Yu-Hsuan Chen · 2017 to 2026
$25.2M
Role of decorin and diffusion MRI in anti-VEGF efficacy for recurrent glioblastomaR01CA270027 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TIMOTHY CLOUGHESY, Benjamin M. Ellingson · 2022 to 2026
$3.0M
Quantitative molecular MR-PET imaging of glycolysis in glioblastomaR01CA279984 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Benjamin M. Ellingson, David A. Nathanson · 2023 to 2026
$2.4M
Molecular MR-PET to characterize malignant transformation and identify therapeutic vulnerabilities in human IDH-mutant gliomasF30CA284809 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI CHO, NICHOLAS S. · 2023 to 2025
$136k
NCI NIH HHS F30 CA284809NCI NIH HHS F30CA284809NCI NIH HHS P30 CA016042NCI NIH HHS P50 CA211015NCI NIH HHS P50CA211015NCI NIH HHS R01 CA270027NCI NIH HHS R01CA270027NCI NIH HHS R01 CA279984NCI NIH HHS R01CA279984NIGMS NIH HHS T32 GM008042NIH HHS T32GM008042U.S. Department of Defense CA220732
6 · The paper itself

Abstract

purposeThis study compared the classification performance of normalized apparent diffusion coefficient (nADC) with percentage T2-FLAIR mismatch-volume (%T2FM-volume) for differentiating between IDH-mutant astrocytoma (IDHm-A) and other glioma molecular subtypes.

methodsA total of 105 non-enhancing gliomas were studied. T2-FLAIR digital subtraction maps were used to identify T2FM and T2-FLAIR non-mismatch (T2FNM) subregions within tumor volumes of interest (VOIs). Median nADC from the whole tumor, T2FM, and T2NFM subregions and %T2FM-volume were obtained. IDHm-A classification analyses using receiver-operating characteristic curves and multiple logistic regression were performed in addition to exploratory survival analyses.

resultsT2FM subregions had significantly higher nADC than T2FNM subregions within IDHm-A with ≥ 25% T2FM-volume (P < 0.0001). IDHm-A with ≥ 25% T2FM-volume demonstrated significantly higher whole tumor nADC compared to IDHm-A with < 25% T2FM-volume (P < 0.0001), and both IDHm-A subgroups demonstrated significantly higher nADC compared to IDH-mutant oligodendroglioma and IDH-wild-type gliomas (P < 0.05). For classification of IDHm-A vs. other gliomas, the area under curve (AUC) of nADC was significantly greater compared to the AUC of %T2FM-volume (P = 0.01, nADC AUC = 0.848, %T2FM-volume AUC = 0.714) along with greater sensitivity. In exploratory survival analyses within IDHm-A, %T2FM-volume was not associated with overall survival (P = 0.2), but there were non-significant trends for nADC (P = 0.07) and tumor volume (P = 0.051).

conclusionT2-FLAIR subtraction maps are useful for characterizing IDHm-A imaging characteristics. nADC outperforms %T2FM-volume for classifying IDHm-A amongst non-enhancing gliomas with preserved high specificity and increased sensitivity, which may be related to inherent diffusivity differences regardless of T2FM. In line with previous findings on visual T2FM-sign, quantitative %T2FM-volume may not be prognostic.

Indexed as

Brain NeoplasmsDiffusion Magnetic Resonance ImagingGliomaAdultAgedFemaleHumansImage Interpretation, Computer-AssistedIsocitrate DehydrogenaseMaleMiddle AgedMutationPredictive Value of TestsRetrospective StudiesSensitivity and SpecificityTumor BurdenIsocitrate DehydrogenaseDiffusion MRIDigital subtractionIDH-mutant gliomaMRIT2-FLAIR mismatch sign

Identifiers

PMID39377927
PMCPMC11611930

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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.