Show simple item record

Enhanced Patient-Specific Brain Biomechanical Modeling: Structure and Disease

dc.creatorNarasimhan, Saramati
dc.date.accessioned2020-08-22T17:08:51Z
dc.date.available2021-06-19
dc.date.issued2019-06-19
dc.identifier.urihttps://etd.library.vanderbilt.edu/etd-06192019-081428
dc.identifier.urihttp://hdl.handle.net/1803/12638
dc.description.abstractBetween 2011 and 2015, approximately 121,277 malignant brain and other central nervous system tumors were diagnosed in the United States with a five year survival rate of 35.0%. Two clinical challenges that directly influence this survival rate are accurate diagnosis and complete resection of the tumor. This research hypothesizes that enhancing anatomical models of intracranial biomechanics with the addition of effects from space-occupying lesions will improve the predictive fidelity of biomechanical models for use in neurosurgical and interventional applications. Modeling of normal brain structures was enhanced using novel anatomical constraints and material property reconstructions, resulting in the accurate capturing of intracranial pressure compartmentalization. Investigating the effects of space-occupying lesions, a biophysical model-based framework for intracranial tumors was developed to estimate biophysical tumor growth properties using standard-of-care imaging and was capable of noninvasive discrimination of tumor recurrence from radiation-induced necrosis. Accounting for both normal brain structure and the influence of a growing tumor, a model-based atlas of tumor cavity collapse was conceived that predicted intra-operative brain shifts from tumor resection. Accounting for both patient-specific structure and disease, the models in this work improve the fidelity of biomechanical modeling for neurosurgical and interventional applications.
dc.format.mimetypeapplication/pdf
dc.subjectRadiation
dc.subjectBrain Shift
dc.subjectFinite Element Modeling
dc.subjectBiomechanics
dc.subjectNeurosurgery
dc.titleEnhanced Patient-Specific Brain Biomechanical Modeling: Structure and Disease
dc.typedissertation
dc.contributor.committeeMemberReid C. Thompson
dc.contributor.committeeMemberJared A. Weis
dc.contributor.committeeMemberBenoit Dawant
dc.contributor.committeeMemberBrett C. Byram
dc.type.materialtext
thesis.degree.namePHD
thesis.degree.leveldissertation
thesis.degree.disciplineBiomedical Engineering
thesis.degree.grantorVanderbilt University
local.embargo.terms2021-06-19
local.embargo.lift2021-06-19
dc.contributor.committeeChairMichael I. Miga


Files in this item

Icon

This item appears in the following Collection(s)

Show simple item record