Detection of Chromosomal Arms 1p/19q Codeletion in Low Graded Glioma using Probability Distribution of MRI Volume Heterogeneity

• Main Authors: Bhattacharya, Debanjali, Sinha, Neelam, Saini, Jitender
• Format: Conference Proceeding
• Language: English
• Subjects: 1p/19q co-deletion; characteristic function; Fish; Low grade glioma; Magnetic resonance imaging; moment generating function; Probability distribution; Random variables; Support vector machines; Tumors; Variance of cross correlation
• ISSN: 2159-3450
• DOI: 10.1109/TENCON.2019.8929255

Glioma is a type of brain tumor that leaves the subject with very low survival rate. However the evidence showed that co-deletion of chromosome arms 1p/19q in low-grade glioma (LGG) revealed good response to therapy in LGG and is associated with longer survival rate. Therefore, predicting 1p/19q status is essential for effective treatment planning of LGG. There are several studies related with predicting deletion of chromosomal arms 1p/19q using multimodal medical images. Our study aims to classify 1p/19q co-deleted LGG status based on 3D volumetric probability distribution of glioma. Dataset are collected from TCIA public access. Study subjects included preoperative postcontrast-T1-W (T1C) and T2-W MRIs who had biopsy-proven 1p/19q status. A total of 159 grade-II and grade III LGG (57 non-deleted and 102 co-deleted) with 3 MRI slices in each subject were utilized in our study. The proposed method utilized statistical moments to obtain moment generating function (MGF) and characteristic function (CF). The optimal range of argument values were derived from MGF and CF for which the probability distribution of two classes were easily distinguishable. KS statistical test verified that the data of two classes have different distributions. Due to imbalanced dataset RUSboost classification was performed that yields better classification performance with MGF features compared to CF features. The average classification performance on the unseen test set with T1-W and T2-W MGF features were 93.22% (precision), 84.6% (recall), and 87.1% (accuracy) for grade-II and 90% (precision), 86% (recall), and 84% (accuracy) for grade-III.