Evidence map›Paper›PMID 31402410›Full record

ArticleNeurosurgical review2020

Magnetic resonance imaging texture analyses in lower-grade gliomas with a commercially available software: correlation of apparent diffusion coefficient and T2 skewness with 1p/19q codeletion.

Tokunori Kanazawa, Yasuhiro Minami, Hidenori Takahashi, Hirokazu Fujiwara, Masahiro Toda, Masahiro Jinzaki, Kazunari Yoshida, Hikaru Sasaki

Abstract read
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In one paragraph

Article in Neurosurgical review, 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
–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

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

  1. Pooled it
  2. Review
  3. Deep learning in precision medicine and focus on glioma.Bioengineering & translational medicine · 2023
    Review
  4. Article
  5. Article
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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.

Tokunori KanazawaDepartment of Neurosurgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Yasuhiro MinamiDepartment of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Hidenori TakahashiDepartment of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Hirokazu FujiwaraDepartment of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Masahiro TodaDepartment of Neurosurgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Masahiro JinzakiDepartment of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Kazunari YoshidaDepartment of Neurosurgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
Hikaru SasakiDepartment of Neurosurgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan. hsasaki@keio.jp.ORCID http://orcid.org/0000-0001-7380-1931

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preoperative prediction of molecular information of lower-grade gliomas (LrGGs) helps to determine the overall treatment strategy as well as the initial surgical strategy. This study aimed to detect magnetic resonance imaging (MRI) texture parameters to predict the molecular signature of LrGGs using a commercially available software and routine MR images. Forty-three patients treated at Keio University Hospital who had World Health Organization grade II or III gliomas were included. All patients having preoperative T1- and T2-weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted (DW) images were also included. Texture analyses of T2, FLAIR, and apparent diffusion coefficient (ADC) histograms were performed using a commercially available software. Texture parameters including kurtosis, skewness, and entropy were investigated to determine any correlation with the presence or absence of isocitrate dehydrogenase (IDH) mutations, 1p/19q codeletion, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. ADC skewness and T2 skewness were significantly associated with 1p/19q codeletion status. ADC skewness of ≥ 0.25 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 65.2%, respectively (AUC = 0.728). T2 skewness of ≥ - 0.11 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 91.3%, respectively, (AUC = 0.866). None of the texture parameters were associated with IDH mutation and MGMT promoter methylation. MRI texture analysis using a commercially available software demonstrated that T2 skewness could predict 1p/19q codeletion with high sensitivity and specificity, suggesting a clinical utility.

Indexed as

AdultAgedBrain NeoplasmsDiffusion Magnetic Resonance ImagingDNA Modification MethylasesDNA Repair EnzymesFemaleGene DeletionGliomaHumansImage Processing, Computer-AssistedIsocitrate DehydrogenaseMagnetic Resonance ImagingMaleMiddle AgedMutationDNA Modification MethylasesDNA Repair EnzymesIsocitrate DehydrogenaseMGMT protein, humanTumor Suppressor Proteins1p/19q codeletionADCGliomaT2Texture analysis

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Registered trials

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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.