Capturing breathing variability using surface tracking-assisted time-resolved multi-cycle 4D lung MRI.

Area of Science:

• Medical Imaging
• Radiotherapy
• Pulmonology

Background:

• Accurate 4D lung imaging is crucial for MR-guided radiotherapy.
• Respiration-induced anatomical variations present challenges for lung imaging.
• Existing methods may not fully capture cycle-to-cycle breathing variability.

Purpose of the Study:

• To develop time-resolved multi-cycle MRI (TRMC-MRI) for 4D lung imaging.
• To capture respiration-induced cycle-to-cycle variations in internal lung anatomy.
• To assist in MR-guided lung radiotherapy through improved motion insights.

Main Methods:

• Golden-angle 3D stack-of-stars gradient echo data acquired for 2 minutes.
• Concurrent tracking of thoracoabdominal motion using MR-compatible sensors.
• Reconstruction of dynamic lung volumes using principal component scores and parallel imaging with TV regularization.

Main Results:

• Demonstrated significant cycle-to-cycle breathing variability (period: 8%-23%, amplitude: 7%-36%).
• Generated dynamic lung volumes at 60.6 ms intervals over 23.2 average breathing cycles.
• Captured considerable breathing variations in time-resolved multi-cycle motion.

Conclusions:

• Surface tracking-assisted TRMC-MRI effectively captures breathing variations in 4D lung imaging.
• This framework provides critical information for lung radiotherapy planning and real-time treatment.
• TRMC-MRI enhances motion modeling, prediction, and training for lung radiotherapy.