The Interplay of Patient and Imaging Variabilities on Quantitative Imaging Outcomes through Virtual Imaging Trials

Abstract

Computed tomography (CT) is an essential diagnostic tool, continually evolving with rapid technological advancements. Among these, photon-counting CT has emerged as a groundbreaking innovation, offering unprecedented spatial and material discrimination. However, these advancements come at the cost of technological diversification, making it challenging to compare image sets and quality across different systems. This variability stems from differences in implementation, varied technologies across practices, and the coexistence of systems with differing levels of technological sophistication. Furthermore, incidental and biological variabilities such as intra-patient changes between imaging sessions and motion-related variations from lung and cardiac activity often match or exceed the spatial resolution of modern CT systems. These factors significantly impact the precision and quantitative capabilities of CT imaging. To fully realize the benefits of photon-counting CT in patient care, it is critical to ensure that its enhanced discrimination capabilities are not compromised by these variabilities.Successful clinical implementation of photon-counting CT requires comprehensive assessment and application-driven optimization to effectively distinguish meaningful changes in a patient’s condition. However, given the vast number of influencing parameters, conducting these evaluations through human trials is neither ethically nor practically feasible. Instead, virtual imaging trials (VITs), which utilize computational models of both the human body and imaging systems, offer a rapid and cost-effective alternative for assessing emerging imaging technologies. In this work, we leverage VITs to systematically investigate individual sources of variability in CT lung imaging. Built upon decades of research and development, our extensive suite of computational tools enables sophisticated modeling of human anatomy and CT imaging processes. The goal of this project is to meaningfully forward the technological advances of modern CT to benefit individual patients, making their presumed advantages effectually advantageous, and providing reliable quantitative biomarkers for patient care.