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DTSTART;TZID=America/New_York:20201119T133000
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UID:submissions.supercomputing.org_SC20_sess293_drs105@linklings.com
SUMMARY:Establishing a Massively Parallel, Patient-Specific Model of Cardi
 ovascular Disease
DESCRIPTION:Doctoral Showcase\n\nEstablishing a Massively Parallel, Patien
 t-Specific Model of Cardiovascular Disease\n\nVardhan, Randles\n\nRecent y
 ears have witnessed a dramatic increase in computational fluid dynamic (CF
 D) simulations for diagnosing cardiovascular diseases, which continue to d
 ominate healthcare costs and are projected to be over one trillion dollars
  by 2035. Current frameworks, however, face three key technical challenges
 : simulations are memory intensive with high time-to-solutions; the need f
 or validation against in vivo measurements; and methods for clinicians to 
 intuitively interact with the simulation results are lacking. In this thes
 is, we overcome these challenges by first establishing a novel, memory-lig
 ht algorithmic representation that both reduces the memory requirements by
  74% and maintains excellent parallel scalability. Second, we validate our
  CFD framework through a multicenter, clinical study comparing invasive pr
 essure measurements to calculated values for 200 patients. Third, we asses
 s how physicians interact with large-scale CFD simulation data and present
  a virtual reality platform to enhance treatment planning. We expect this 
 work to lay the critical groundwork for translating the use of massively p
 arallel simulation-driven diagnostics and treatment planning to the clinic
 . Our long-term goal is to enable the use of personalized simulations to i
 mprove clinical diagnosis and outcome for patients suffering from cardiova
 scular diseases.\n\nRegistration Category: Tech Program Reg Pass
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