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Abstract #4310

Identification of NF2 loss in meningiomas using 1H-MRS at 3T

Banu Sacli-Bilmez1, Abdullah Baş2, Kübra Tan3, Ayça Erşen Danyeli4,5, Özge Can6, M.Necmettin Pamir5,7, Alp Dinçer5,8, Koray Özduman5,7, and Esin Ozturk-Isik1
1Institute of Biomedical Engineering, Bogazici University, İstanbul, Turkey, 2Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey, 3Health Institutes of Turkey, İstanbul, Turkey, 4Department of Medical Pathology, Acıbadem Mehmet Ali Aydınlar University, İstanbul, Turkey, 5Center for Neuroradiological Applications and Reseach, Acıbadem Mehmet Ali Aydınlar University, İstanbul, Turkey, 6Department of Medical Engineering, Acıbadem Mehmet Ali Aydınlar University, İstanbul, Turkey, 7Department of Neurosurgery, Acıbadem Mehmet Ali Aydınlar University, İstanbul, Turkey, 8Department of Radiology, Acıbadem Mehmet Ali Aydınlar University, İstanbul, Turkey

Synopsis

Loss of neurofibromatosis 2 (NF2-L) is a well-known genetic alteration of meningiomas and causes meningiomas to evolve into more aggressive and infiltrating form. This study aims to investigate single-voxel proton magnetic resonance spectroscopy (1H-MRS) correlations of NF2-L in meningiomas and to develop machine learning and deep learning models to identify NF2-L in meningiomas. NF2-L meningiomas had significantly higher Ins, Lac, and Ins+Glyc, and lower tNAA than tumors with no copy number loss. While a subspace discriminant model achieved a classification accuracy of 77.25%, a 1D-CNN model obtained a classifcation accuracy of 88.9% for identifying NF2-L meningiomas.

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