Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study.

scientific article published on 17 April 2018

Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study. is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.1038/S41598-018-24438-4
P932PMC publication ID5904150
P698PubMed publication ID29666413

P50authorSebastian BrandnerQ58333540
Sotirios BisdasQ61478650
Vasileios K. KatsarosQ77708346
P2093author name stringJianguo Zhang
George Stranjalis
Steffi Thust
Christos Boskos
Haocheng Shen
P2860cites workCombination of diffusion tensor imaging and conventional MRI correlates with isocitrate dehydrogenase 1/2 mutations but not 1p/19q genotyping in oligodendroglial tumours.Q52148950
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Cerebral gliomas: diffusional kurtosis imaging analysis of microstructural differencesQ33525427
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Integrating diffusion kurtosis imaging, dynamic susceptibility-weighted contrast-enhanced MRI, and short echo time chemical shift imaging for grading gliomasQ33753445
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A method of comparing the areas under receiver operating characteristic curves derived from the same casesQ34272510
Precise ex vivo histological validation of heightened cellularity and diffusion-restricted necrosis in regions of dark apparent diffusion coefficient in 7 cases of high-grade gliomaQ34511741
Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practiceQ35676598
Magnetic resonance image features identify glioblastoma phenotypic subtypes with distinct molecular pathway activitiesQ36336679
Texture Feature Ratios from Relative CBV Maps of Perfusion MRI Are Associated with Patient Survival in Glioblastoma.Q36463578
Diffusion kurtosis imaging can efficiently assess the glioma grade and cellular proliferationQ36561792
Magnetic Resonance of 2-Hydroxyglutarate in IDH1 -Mutated Low-Grade GliomasQ37168287
Differentiation of Low- and High-Grade Gliomas Using High b-Value Diffusion Imaging with a Non-Gaussian Diffusion ModelQ37246734
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Diagnostic, prognostic and predictive relevance of molecular markers in gliomasQ38461565
T2-FLAIR Mismatch, an Imaging Biomarker for IDH and 1p/19q Status in Lower Grade Gliomas: A TCGA/TCIA Project.Q38656588
The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summaryQ38829244
Extracted magnetic resonance texture features discriminate between phenotypes and are associated with overall survival in glioblastoma multiforme patientsQ39934478
Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas.Q42683729
ADC texture--an imaging biomarker for high-grade glioma?Q43546624
Comparison of multiple parameters obtained on 3T pulsed arterial spin-labeling, diffusion tensor imaging, and MRS and the Ki-67 labeling index in evaluating glioma gradingQ46768779
In vivo molecular profiling of human glioma using diffusion kurtosis imagingQ47943878
Mean Diffusional Kurtosis in Patients with Glioma: Initial Results with a Fast Imaging Method in a Clinical SettingQ48175910
Optimal experimental design for diffusion kurtosis imaging.Q48285322
Prediction of IDH1-Mutation and 1p/19q-Codeletion Status Using Preoperative MR Imaging Phenotypes in Lower Grade Gliomas.Q48331864
ATRX and IDH1-R132H immunohistochemistry with subsequent copy number analysis and IDH sequencing as a basis for an "integrated" diagnostic approach for adult astrocytoma, oligodendroglioma and glioblastomaQ48446221
Histogram analysis of diffusion kurtosis imaging estimates for in vivo assessment of 2016 WHO glioma grades: A cross-sectional observational studyQ49506485
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue1
P407language of work or nameEnglishQ1860
P921main subjectsupport vector machineQ282453
P304page(s)6108
P577publication date2018-04-17
P1433published inScientific ReportsQ2261792
P1476titleTexture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study
P478volume8

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cites work (P2860)
Q97646064A New Method Based on CEEMD Combined With Iterative Feature Reduction for Aided Diagnosis of Epileptic EEG
Q97418633Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status
Q60954430Role of diffusional kurtosis imaging in grading of brain gliomas: a protocol for systematic review and meta-analysis

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