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Development of anatomically variable digital Wistar rat phantoms for small animal imaging research
Hannah E Segars1, Rohan Nadkarni2, Cristian T Badea2
1Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA.
Medical Physics
|August 14, 2025
Summary
New digital Wistar rat phantoms offer anatomically variable models for preclinical imaging. These computational tools aid in optimizing imaging systems and protocols, reducing animal use in research.
Area of Science:
- Medical imaging
- Biomedical engineering
- Computational modeling
Background:
- Digital phantoms are crucial for evaluating small animal imaging systems and refining protocols.
- Wistar rats are a key model organism in preclinical imaging research due to their biological relevance.
Purpose of the Study:
- To develop anatomically variable digital Wistar rat phantoms for small animal imaging research.
- To create a versatile resource for optimizing imaging parameters and reducing animal use.
Main Methods:
- Constructed 10 computational Wistar rat phantoms (male/female) using high-resolution micro-CT and MRI data.
- Segmented 35 distinct anatomical tissues and fitted them with smooth polygon mesh surfaces.
- Performed photon-counting CT (PCCT) simulations to evaluate image quality and material decomposition.
Main Results:
- Computational phantoms accurately represent inter-subject anatomical variation in Wistar rats.
- Iterative reconstruction methods significantly improved image quality and material decomposition accuracy in PCCT simulations.
- Demonstrated substantial reduction in root mean square error for water, iodine, and calcium maps.
Conclusions:
- Anatomically variable digital Wistar rat phantoms are valuable for evaluating imaging systems and optimizing protocols.
- These phantoms facilitate the validation of reconstruction algorithms for diverse anatomies.
- The study highlights the potential for advancing virtual preclinical imaging trials with these models.
