Characterization of free breathing patterns with 5D lung motion model

Area of Science:

• Medical imaging and radiation oncology.
• Computational modeling of biological systems.

Background:

• Accurate lung motion modeling is crucial for effective radiation therapy in lung cancer patients.
• Breathing motion introduces significant variability in tumor targeting during treatment.

Purpose of the Study:

• To determine the parameters of a quiet respiration breathing motion model for lung cancer and non-lung cancer patients.
• To characterize lung motion patterns and interpatient variability using a novel 3D model.

Main Methods:

• Utilized 4D computed tomography (4DCT) datasets from 49 patients with simultaneous spirometry.
• Employed a cross-correlation registration technique to track lung tissue motion.
• Applied a lung motion model incorporating tidal volume (v) and airflow (f) parameters (alpha and beta) to quantify motion and hysteresis.

Main Results:

• The motion parameter alpha (tidal volume dependent) was predominantly highest in the inferior and posterior lungs for most patients.
• The hysteresis motion parameter beta showed greater interpatient variability, with the largest values often observed in the lateral lungs.
• Similar alpha parameter maps were observed across the majority of patients, indicating consistent volume-dependent motion.

Conclusions:

• This study presents the first report of 3D breathing motion model parameters for a large patient cohort.
• The developed model shows potential for non-invasive prediction of lung motion.
• Interpatient variability in motion parameters, particularly hysteresis, highlights the need for customized radiation therapy motion models.