Abstract #2130

Attention Deep-Shallow Network (ADSN): A Deep Learning Model for IDH and TERTp Mutation Detection in Gliomas using 1H-MRS

Abdullah Bas¹, Banu Sacli-Bilmez¹, Ayca Ersen Danyeli^2,3, Ozge Can^2,4, Koray Ozduman^2,5, Alp Dincer^2,6, and Esin Ozturk-Isik^1,2

¹Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, ²Brain Tumor Research Group, Acibadem University, Istanbul, Turkey, ³Department of Medical Pathology, Acibadem University, Istanbul, Turkey, ⁴Department of Biomedical Engineering, Acibadem University, Istanbul, Turkey, ⁵Department of Neurosurgery, Acibadem University, Istanbul, Turkey, ⁶Department of Radiology, Acıbadem University, Istanbul, Turkey

Synopsis

Keywords: Tumors, Machine Learning/Artificial Intelligence, Deep LearningIsocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp) mutations affect the clinical behavior and survival rate of diffuse gliomas. According to the latest WHO 2021 brain tumor classification, IDH mutation is an important factor for grouping adult-type diffuse gliomas. The preoperative detection of these mutations is very critical for treatment planning. In this study, we propose enhanced 1D-CNN models by adding an attention mechanism as a prior network to focus on relevant spectral frequencies of 1H-MRS to identify IDH-mutant (IDH-mut), TERTp-mutant (TERTp-mut), and IDH-wt, TERTp-mut (TERTp-only) gliomas using three binary models

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