External respiratory motion: shape analysis and custom realistic respiratory trace generation.

Area of Science:

• Medical physics
• Radiotherapy research
• Software development

Background:

• Accurate simulation of patient respiratory motion is crucial for developing and testing new radiotherapy technologies.
• Existing models may not fully capture the complex dynamics of abdominal wall motion during respiration.

Purpose of the Study:

• To develop a realistic respiratory trace generating (RTG) tool for use in phantom and simulation studies.
• To create a software that accurately models patient respiratory motion for research purposes.

Main Methods:

• Analyzed abdominal wall motion data from 125 lung, liver, and abdominal patients using a real-time position management system.
• Employed Akaike's information criterion (AIC) to compare various models for optimal respiratory motion representation.
• Developed a four-parameter sigmoid fit as the superior model for patient respiratory traces.

Main Results:

• A four-parameter sigmoid fit accurately modeled over 98% of patient inhale and exhale traces.
• The sigmoid fit outperformed sinusoidal models (sin(2)(x) and sin(x)) for patient respiratory traces.
• Developed the RTG software with population and user-defined modes for customizable respiratory data generation.

Conclusions:

• The developed RTG tool provides a method for generating custom respiratory data.
• This tool facilitates the initial implementation and testing of novel radiotherapy technologies.