Computational hybrid anthropometric paediatric phantom library for internal radiation dosimetry

Area of Science:

• Medical physics
• Computational modeling
• Anthropometry

Background:

• Hybrid computational phantoms integrate voxel-based and equation-based methods for enhanced realism.
• Existing models often lack detailed statistical distributions of pediatric body morphometry.

Purpose of the Study:

• To develop a methodology and C++ code for generating hybrid computational phantoms representing statistical distributions of pediatric body morphometry.
• To create a library of 1100 female and male pediatric phantoms across various ages and body mass indices.

Main Methods:

• Modified existing pediatric phantoms (Virtual Population Series) to match anthropometric data from NCHS and NHANES databases.
• Selected anchor phantoms for ages newborn to 15 years and remodelled them.
• Evaluated phantoms qualitatively (3D visualization) and quantitatively (organ mass analysis).

Main Results:

• Generated 1100 hybrid computational phantoms representing diverse pediatric populations.
• Phantom organ masses correlate with height and body mass, consistent with trends observed in autopsy and reference data.
• Internal organ masses (heart, kidney, liver, lung, spleen) show age-dependent trends comparable to published data.

Conclusions:

• The newly generated hybrid computational phantoms are representative of the pediatric population across various ages, genders, and body types.
• This phantom library facilitates comprehensive radiation dosimetry calculations and risk assessments for diverse pediatric groups.
• The methodology provides a robust approach for creating realistic anthropomorphic models for scientific research.