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Computer-aided Diagnosis of Isocitrate Dehydrogenase Genotypes in Glioblastomas from Radiomic Patterns by Lo, Chung-Ming; Weng, Rui-Cian; Cheng, Sho-Jen; Wang, Hung-Jung; Hsieh, Kevin Li-Chun is a Medicine article available to read on EtoBox.

What is Computer-aided Diagnosis of Isocitrate Dehydrogenase Genotypes in Glioblastomas from Radiomic Patterns about?

## Abstract World Health Organization tumor classifications of the central nervous system differentiate glioblastoma multiforme (GBM) into wild-type (WT) and mutant isocitrate dehydrogenase (__IDH__) genotypes. This study proposes a noninvasive computer-aided diagnosis to interpret the status of __IDH__ in glioblastomas from transformed magnetic resonance imaging patterns. The collected image database was composed of 32 WT and 7 mutant __IDH__ cases. For each image, a ranklet transformation which changed the original pixel values into relative coefficients was 1st applied to reduce the effects of different scanning parameters and machines on the underlying patterns. Extracting various textural features from the transformed ranklet images and combining them in a logistic regression classifier allowed an __IDH__ prediction. We achieved an accuracy of 90%, a sensitivity of 57%, and a specificity of 97%. Four of the selected textural features in the classifier (homogeneity, difference entropy, information measure of correlation, and inverse difference normalized) were significant (__P__ < .05), and the other 2 were close to being significant (__P__ = .06). The proposed computer-aided d

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Author
Lo, Chung-Ming; Weng, Rui-Cian; Cheng, Sho-Jen; Wang, Hung-Jung; Hsieh, Kevin Li-Chun
Publisher
Lippincott Williams and Wilkins; Elsevier ; Ovid Technologies (Wolters Kluwer) - Lippincott Williams & Wilkins; Elsevier BV; Lippincott Williams & Wilkins Ltd.; Medicine Publishing Company Ltd; Williams & Wilkins; Ovid Technologies (Wolters Kluwer Health) (ISSN 1357-3039)
Published
2020
Language
EN
Field
Medicine (Health Sciences)

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