Aditya Iyer
Pronouns: He/Him
Research Mentor(s): Krishnakumar Garikipati
Research Mentor School/College/Department: Mechanical Engineering, and Mathematics / Engineering
Program: UROP
Session: Session 4 (1:40pm – 2:30pm)
Authors: Aditya Iyer, Krishna Garikipati, Krishna Garikipati, Siddhartha Srivastava, Johannes Weickenmeier, Elizabeth Livingston
Abstract
The fetal human brain is in a constant state of morphological growth from week to week in its development phase. It is important to consider this growth as improper formations can lead to severe pathologies such as epilepsy or even seizures. Thus, understanding the growth metric for the fetal human brain, where these structures initially begin to form and grow, is essential to future remedies. In this study, a data-driven approach was taken to analyze the local volume changes within the brain. An inverse mathematical model is performed in order to obtain the growth deformation gradient tensor involved in brain growth based on the original MRI data received in Finite Element Mesh (FEM) form. This model utilizes adjoint solves to compute the gradient field that will be inverted. This computational process is done on a high-performance computing platform. The original data given details the brain meshes for weeks 25-31 of the development cycle. So far, computationally driven results have only been performed on week 26-27. In the near future, the results for the remaining weeks will be attained. All this computational data will then be used to derive the growth tensor driving local volume changes in the brain. With final analysis of this data, this information regarding the growth tensor can help researchers determine the evolution of brain growth over time.
