Evidence map›Paper›PMID 26230975›Full record

ArticleRadiology2016

Grading of Gliomas by Using Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MR Imaging and Diffusion Kurtosis MR Imaging.

Yan Bai, Yusong Lin, Jie Tian, Dapeng Shi, Jingliang Cheng, E Mark Haacke, Xiaohua Hong, Bo Ma, Jinyuan Zhou, Meiyun Wang

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In one paragraph

Article in Radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
112citing papers in PubMed, 5 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

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3 · Its place in the literature

Who cites it

112 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  11. Application of diffusion kurtosis imaging in differentiating T0-T1 from T2 rectal tumors.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
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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

10 authors.

Yan BaiFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Yusong LinFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Jie TianFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Dapeng ShiFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Jingliang ChengFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
E Mark HaackeFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Xiaohua HongFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Bo MaFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Jinyuan ZhouFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).
Meiyun WangFrom the Department of Radiology, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan 450003, China (Y.B., D.S., B.M., M.W.); Software Technology School of Zhengzhou University (Y.L.); Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); Division of MRI, First Affiliated Hospital of Zhengzhou University, Zhengzhou Henan, China (J.C.); Department of Radiology, Wayne State University, Detroit, Mich (E.M.H.); Magnetic Resonance Innovations, Detroit, Mich (E.M.H.); and Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Md (X.H., B.M., J.Z., M.W.).

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
Amide Proton Transfer (APT) MRI of Brain Tumors at 3T and 7TR01EB009731 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI ZHOU, JINYUAN · 2009 to 2016
$2.9M
Academic-Industrial Partnership to Develop Clinical Brain Cancer ImagingR01CA166171 · NCI · JOHNS HOPKINS UNIVERSITY · PI VAN ZIJL, PETER CM, ZHOU, JINYUAN · 2013 to 2017
$2.4M
NCI NIH HHS P30 CA006973NCI NIH HHS R01 CA166171NCI NIH HHS R01CA166171NIBIB NIH HHS R01 EB009731NIBIB NIH HHS R01EB009731
6 · The paper itself

Abstract

purposeTo quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas. MATERIALS AND

methodsThis study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusion-weighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations.

resultsADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P < .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P < .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P < .05).

conclusionWater molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.

Indexed as

AdultAgedAnisotropyBrain NeoplasmsContrast MediaDiffusion Magnetic Resonance ImagingFemaleGadolinium DTPAGliomaHumansImage Interpretation, Computer-AssistedMaleMiddle AgedNeoplasm GradingProspective StudiesSensitivity and SpecificityContrast MediaGadolinium DTPA

Identifiers

PMID26230975
PMCPMC4734159

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