Predicting different pathological grades with contrast-enhanced MR imaging in oligodendrogliomas

Medical image processing and its quantitative analysis plays a vital role in several clinical scenarios, such as diagnosis as well as treatment. The results of this study show that there are 478 mRNAs differentially expressed in low grade as compared to anaplastic oligodendroglial tumor (2 Fold greater, p < 0.05) group. These genes participated in Gene Ontology and KEGG pathways such as cell migration, cell motility, and cytokine-cytokine receptor interaction. Oligodendroglial classification models derived from advanced imaging will improve the accuracy of tumor grading, provide prognostic information, and have potential to influence treatment decisions. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Alexandria University.

Automated summary

Medical image processing and quantitative analysis are crucial in clinical scenarios for diagnosis and treatment. Studying differentially expressed genes can improve accuracy in tumor grading and guide treatment decisions.