Anatomy-wise lung ventilation imaging for precise functional lung avoidance radiation therapy.

Area of Science:

• Medical Imaging
• Radiation Oncology
• Pulmonary Function Assessment

Background:

• Lung cancer treatment planning requires accurate assessment of lung parenchyma function.
• Tumor-induced airway blockage complicates functional lung segmentation.
• Existing methods may not adequately differentiate between recoverable and unrecoverable lung function in blocked segments.

Purpose of the Study:

• To propose a novel method for generating anatomy-wise lung ventilation images (VIaw).
• To enable functional assessment of lung parenchyma and tumor-blocked segments for radiation therapy planning.
• To define functional lung volumes (HFV, LFV, rLFV) to guide treatment optimization.

Main Methods:

• A super-voxel-based method was used to generate initial ventilation images (VIsvd).
• Anatomy-wise ventilation images (VIaw) were created by setting blocked segments' function to zero in VIsvd.
• Three intensity-modulated photon plans (aPlan, fPlan, rfPlan) were designed based on different functional lung guidance strategies.

Main Results:

• High overlap (0.90 ± 0.07) was found between low functional volume (LFV) and tumor-blocked segments.
• A moderate-to-strong correlation (Spearman's ρ = 0.72 ± 0.05) was observed between VIaw and reference ventilation images.
• The recoverable functional lung (rLFV) received significantly lower doses in the rfPlan compared to aPlan and fPlan.

Conclusions:

• The VIaw method provides a reliable tool for functional lung assessment, correlating well with reference images.
• VIaw effectively identifies recoverable low functional volume (rLFV) in tumor-obstructed segments.
• This approach supports radiation treatment planning to better preserve overall lung function.