Nonlinear Brain Tumor Model Estimation with Long Short-Term Memory Neural Networks

Jiashu Guo, Zhengzhong Liang, Gregory Ditzler, Nidhal C. Bouaynaya, Elizabeth Scribner, Hassan M. Fathallah-Shaykh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Gliomas are malignant brain tumors that are associated with high neurological morbidity and poor outcomes. Patients diagnosed with low-grade gliomas are typically followed by a sequence of measurements of the tumor size. Here, we show the promise of Long Short-Term Memory Neural Networks (LSTMs) to address two important clinical questions in low-grade gliomas: 1) classification and prediction of future behavior; and 2) early detection of dedifferentiation to a higher grade or more aggressive growth. We use a system of partial differential equations (PDEs), from our earlier work, to generate simulated growth of low-grade gliomas with different clinical parameters. We design an LSTM network to solve the inverse problem of PDE parameter estimation. We find that accuracy increases as a function of the number of tumor measurements and perplexity can also be used to detect a change in tumor grade. These findings highlight the potential usefulness of LSTMs in solving inverse clinical problems.

Original languageEnglish (US)
Title of host publication2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509060146
DOIs
Publication statusPublished - Oct 10 2018
Event2018 International Joint Conference on Neural Networks, IJCNN 2018 - Rio de Janeiro, Brazil
Duration: Jul 8 2018Jul 13 2018

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2018-July

Other

Other2018 International Joint Conference on Neural Networks, IJCNN 2018
CountryBrazil
CityRio de Janeiro
Period7/8/187/13/18

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All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

Cite this

Guo, J., Liang, Z., Ditzler, G., Bouaynaya, N. C., Scribner, E., & Fathallah-Shaykh, H. M. (2018). Nonlinear Brain Tumor Model Estimation with Long Short-Term Memory Neural Networks. In 2018 International Joint Conference on Neural Networks, IJCNN 2018 - Proceedings [8489616] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2018-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2018.8489616