Age-Dependent Skeletal Tissue Models for the UF/MSK Newborn, Infant, and Toddler Phantom Series
Abstract
Purpose
To develop a slice-specific CT organ dose library using Monte Carlo radiation transport simulations on a set of newborn, infant, and toddler (NIT) computational phantoms containing newly developed age-specific skeletal tissue models. This dose library forms the basis for fast calculation of patient-dependent cumulative organ doses for a range of clinical protocols.
Methods
The NIT phantom set was created from the ICRP-156 reference phantoms using North American population survey data that include standing height, weight, and head circumference. Phantoms were arranged by age from 0 to 2 years at 2-month increments, and grouped at 10th, 50th, and 90th percentile height, weight, and head circumference. In the present study, the skeletal tissue models of the phantoms were updated through interpolation to reflect material compositions that account for age-dependent fractions of skeletal tissues, including red bone marrow and endosteum. Monte Carlo simulations were then performed using a validated user-based CT source term in the Particle and Heavy Ion Transport code System (PHITS) on a set of phantoms to generate slice-specific dosimetry datasets for several combinations of technique factors including kVp, collimated beam width, and bowtie filter size. Finally, total organ absorbed doses were calculated for common clinical CT studies by summing slice-specific doses over the scan range.
Results
Organ dose values were generated for the NIT phantom set with skeletal tissue models incorporating updated material compositions across several combinations of technique factors to replicate a range of clinical protocols and were subsequently normalized using physical free-in-air kerma measurements.
Conclusion
Organ dose values of this study can be further adjusted based on scan pitch and the vendor-specific impact of tube current modulation (TCM). Slice-specific dose values will provide accurate patient-dependent total organ dose estimates for a given scan protocol and will be incorporated into a freely available Excel-based dosimetry platform.