MRI Radiomics for IDH Genotype Prediction in Glioblastoma Diagnosis
It addresses the problem of predicting IDH genotype in glioblastoma diagnosis for medical professionals, but it is incremental as it reviews existing developments rather than presenting new findings.
This paper reviews the use of MRI radiomic features to predict the IDH mutation status, an important biomarker for glioblastoma and grade IV astrocytoma diagnosis, highlighting the potential for faster and more accurate oncological diagnosis through standardized feature extraction.
Radiomics is a relatively new field which utilises automatically identified features from radiological scans. It has found a widespread application, particularly in oncology because many of the important oncological biomarkers are not visible to the naked eye. The recent advent of big data, including in medical imaging, and the development of new ML techniques brought the possibility of faster and more accurate oncological diagnosis. Furthermore, standardised mathematical feature extraction based on radiomics helps to eliminate possible radiologist bias. This paper reviews the recent development in the oncological use of MRI radiomic features. It focuses on the identification of the isocitrate dehydrogenase (IDH) mutation status, which is an important biomarker for the diagnosis of glioblastoma and grade IV astrocytoma.