Towards the Performance Characterization of a Robotic Multimodal Diagnostic Imaging System

Authors

George Papaioannou, New Bedford Research & Robotics
Christos Mitrogiannis, New Bedford Research & Robotics
Mark Schweitzer, Wayne State University
Nikolaos Michailidis, Aristotle University of Thessaloniki
Maria Pappa, Aristotle University of Thessaloniki
Pegah Khosravi, CUNY New York City College of TechnologyFollow
Apostolos Karantanas, University Hospital, Heraklion, Greece
Sean Starling, Meat and Livestock Australia
Christian Ruberg, Meat and Livestock Australia

Document Type

Article

Publication Date

5-7-2025

Abstract

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal process, with limited field of view and considerable dose. High dynamic accuracy is also necessary to diagnose tissue’s dynamic behavior beyond its static structural morphology. This study presents several performance characterization experiments from a new robotic multimodal imaging system using specially designed calibration methods at different system configurations. Additional musculoskeletal imaging and imaging from a pediatric brain stroke patient without anesthesia are presented for comparisons. The findings suggest that the system’s large dynamically controlled gantry enables scanning at full patient movement and with important improvements in scan times, accuracy, radiation dose, and the ability to image brain structures without anesthesia. This could position the system as a potential transformative tool in the pediatric interventional imaging landscape.

Comments

This article was originally published in Journal of Imaging, available at https://doi.org/10.3390/jimaging11050147

This work is distributed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).