Document Type

Conference Paper

Subject Area

CPS Medical

Date of this Version

3-14-2019

Publication Source

10th ACM/IEEE International Conference on CyberPhysical Systems (with CPS-IoT Week 2019) (ICCPS ’19), April 16–18, 2019, Montreal, QC, Canada. ACM, New York, NY, USA

DOI

10.1145/3302509.3311058

Abstract

Medical cyber-physical systems, such as the implantable cardioverter defibrillator (ICD), require evaluation of safety and efficacy in the context of a patient population in a clinical trial. Advances in computer modeling and simulation allow for generation of a simulated cohort or virtual cohort which mimics a patient population and can be used as a source of prior information. A major obstacle to acceptance of simulation results as a source of prior information is the lack of a framework for explicitly modeling sources of uncertainty in simulation results and quantifying the effect on trial outcomes.

In this work, we formulate the Computer-Aided Clinical Trial (CACT) within a Bayesian statistical framework allowing explicit modeling of assumptions and utilization of simulation results at all stages of a clinical trial. To quantify the robustness of the CACT outcome with respect to a simulation assumption, we define δ-robustness as the minimum perturbation of the base prior distribution resulting in a change of the CACT outcome and provide a method to estimate the δ-robustness.

We demonstrate the utility of the framework and how the results of δ-robustness evaluation can be utilized at various stages of a clinical trial through an application to the Rhythm ID Goes Head-to-head Trial (RIGHT), which was a comparative evaluation of the safety and efficacy of specific software algorithms across different implantable cardiac devices. Finally, we introduce a hardware interface that allows for direct interaction with the physical device in order to validate and confirm the results of a CACT for implantable cardiac devices.

Copyright/Permission Statement

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.

ICCPS ’19, April 16–18, 2019, Montreal, QC, Canada © 2019 Association for Computing Machinery.

ACM ISBN 978-1-4503-6285-6/19/04...$15.00 https://doi.org/10.1145/3302509.3311058

Keywords

Computer-aided, Clinical trials, Bayesian sensitivity analysis, Robustness, Medical devices, Implantable cardiac devices

Bib Tex

@article{jang_iccps2019, Address = {Montreal, QC, Canada}, Author = {Kuk Jin Jang and Yash Vardhan Pant and Bo Zhang and James Weimer and Rahul Mangharam}, Doi = {10.1145/3302509.3311058}, Keywords = {Computer-aided, Clinical trials, Bayesian sensitivity analysis, Robustness, Medical devices, Implantable cardiac devices}, Month = {April 16-18}, Organization = {ACM}, Publisher = {10th ACM/IEEE International Conference on CyberPhysical Systems (with CPS-IoT Week 2019) (ICCPS '19)}, Title = {Robustness Evaluation of Computer-aided Clinical Trials for Medical Devices}, Year = {2019}}

Share

COinS
 

Date Posted: 14 March 2019

This document has been peer reviewed.