Loading...
Thumbnail Image
Publication

Nanoswimmer-oriented Direct Targeting Strategy Inspired by Momentum-based Gradient Optimization

Abstract
This paper considers the advantage of knowledgeaided direct targeting strategy (DTS) over systemic targeting for tumor homing in complex human vasculature. Tumor location in the body can be estimated by closely observing the tumortriggered bio-physical gradients in its vicinity, helping drugloaded magnetic nanoswimmers to accumulate at the disease location. These nanoswimmers are assembled by magnetic nanoparticles (MNPs), which act as contrast agents increasing the diagnostic capability of different medical imaging techniques. We propose a novel DTS inspired by the iterative gradient descent (GD) with momentum optimization for tumor targeting amplification. We show by computational experiments that the MNPs accumulate at the disease location at a faster rate and the probability of tumor detection is higher for the proposed knowledge-aided DTS as compared to the knowledgeless systemic targeting. We believe that our work for tumor targeting amplification based on such nanosystem will open new horizons in the field of diagnosing tumor at its early stage.
Type
Conference Contribution
Type of thesis
Series
Citation
Ali, M., Cree, M. J., Sharifi, N., & Chen, Y. (2019). Nanoswimmer-oriented Direct Targeting Strategy Inspired by Momentum-based Gradient Optimization. In Proceedings of 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 741–744). Washington, DC, USA: IEEE. https://doi.org/10.1109/embc.2019.8857802
Date
2019
Publisher
IEEE
Degree
Supervisors
Rights
This is an author’s accepted version of a paper published in the Proceedings: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). ©2019 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.