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Session: Multi-Scale Modeling in Imaging and Therapy [Return to Session]

Multi-Scale Modeling in Imaging and Therapy

A Badal1*, X Jia2*, S Abbasinejad Enger3*, A McNamara4*, (1) U.S. Food & Drug Administration (CDRH/OSEL), Silver Spring, MD, (2) The University of Texas Southwestern Medical Ctr, Garland, TX, (3) Medical Physics Unit, McGill University, Montreal, QC, Canada, Montreal, QC, CA, (4) Harvard/MGH, Boston, MA


TH-C-BRC-0 (Thursday, 7/14/2022) 10:00 AM - 11:00 AM [Eastern Time (GMT-4)]

Ballroom C

Radiation transport simulations can be used to study radiation dose distributions in practically any clinical applications of x-ray imaging, nuclear medicine, or radiation therapy. To simulate this large range of potential applications, a variety of geometry and physics modeling techniques have been developed over the years. These techniques can create digital twins of devices as large as particle accelerators or as small as brachytherapy seeds. They are also capable of modeling biological tissues from the whole body to the cellular level. In this session we will review Monte Carlo methods used to simulate radiation transport in distances that can vary by as much as nine orders of magnitude: from scatter radiation deposited meters away from a fluoroscopy source to radiolysis and DNA damage in the nanometer scale. We will also present mechanistic models that combine energy deposition distributions from Monte Carlo track structure simulations with DNA repair models to predict chromosome aberrations and cell survival. A mechanistic modeling approach can be substantially more powerful than a phenomenological model in providing insight into the underlying physical, chemical and biological mechanisms responsible for the tissue radiation response. The presented multi-scale modeling examples will introduce state-of-the-art modeling and simulation tools used in radiation microdosimetry and in silico imaging trials, and show how they enable new approaches to predict patient outcomes in brachytherapy and proton therapy.

Learning Objectives:
1. Review technical advances in simulation methods for dose estimation and virtual performance assessment in diagnostic imaging, nuclear medicine, and radiation therapy.
2. Understand the basic concepts of multi-scale microdosimetry modeling.
3. Learn how multi-scale mechanistic models can be used to understand the relative biological effectiveness between photons, protons or heavier ions, and predict and optimize radiotherapy treatment outcomes.


Microdosimetry, Radiation Transport, Monte Carlo


IM/TH- Radiation Transport: Monte Carlo simulation- charged particle transport and variance reduction

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