BLUE RIBBON POSTER RADIOPHARMACEUTICALS: Advanced Microscale Mouse Bone Marrow Dosimetry Using Nanoct Data
Abstract
Purpose
In the rapidly developing field of radiopharmaceuticals, the skeleton poses a uniquely daunting challenge to any effort to safely employ these powerful tools. The skeleton’s wide distribution throughout the body as well as its variability make dose difficult to estimate with current models such as the Mouse Whole Body (MOBY) phantom. Structures like red marrow and bone endosteum play leading roles in radiogenic risk of leukemia and bone cancer. The current method for estimating dose to this vital structure assumes homogeneity of trabecular bone. This is not accurate for short range particles like alphas and betas. Improved dosimetry methods in preclinical models are needed to better understand how to mitigate the risks involved in the use of radiopharmaceuticals. In order improve our understanding, our team has constructed microscale models of mouse bones directly from anatomical data obtained via a nanoCT.
Methods
5 strain CD-1 mice, ages ranging from 4 weeks to 20 months were sacrificed and 32 selected bones from each individual were harvested. These bones were then scanned with a GE v|tome|x m 240 NanoCT and their internal structures were assessed. From a combination of scan results and literature values, 3D tetrahedral meshes were constructed to represent these observations. These meshes were then distributed throughout the MOBY phantom’s bone trabeculae and doses were simulated using the Particle and Heavy Ion Transport System (PHITS) Monte Carlo code.
Results
Image-based trabecular bone and bone marrow were generated with resolution down to 10 µm at maximum. Dosimetry information with these new structures was also obtained.
Conclusion
Microscale models of the mouse skeleton were generated directly from anatomical information, allowing for a more anatomically rigorous model of the mouse bone, and dosimetry results were generated. More work is required to determine if the more anatomically rigorous model is also more accurate.