Model-based registration for pneumothorax deformation analysis using intraoperative cone-beam CT images

Area of Science:

• Medical imaging
• Computational anatomy
• Surgical navigation

Background:

• Lung deformation during surgery, caused by pneumothorax, complicates accurate tumor localization.
• Intraoperative cone-beam CT (CBCT) provides a means to estimate lung deformation during surgical procedures.

Purpose of the Study:

• To develop and evaluate a deformable mesh registration framework for analyzing lung deformation from paired CBCT images.
• To improve the accuracy of estimating partial organ shape deformations, including large rotations and displacements.

Main Methods:

• Utilized deformable mesh registration techniques on paired CBCT images from inflated and deflated lung states.
• Developed a novel framework specifically designed for partial organ deformations with significant rotation and displacement.
• Applied registration using surgically placed markers (surgical clips) on the lung surface.

Main Results:

• The proposed deformable mesh registration methods demonstrated reduced point-to-point correspondence errors.
• Registration using surgical clips in eight cases resulted in an average error of 3.9 mm.
• Analysis revealed that both tissue rotation and contraction significantly influenced lung displacement.

Conclusions:

• The developed deformable mesh registration framework enhances the accuracy of estimating lung tumor location during surgery.
• The findings highlight the importance of accounting for tissue rotation and contraction in lung deformation analysis.
• This method offers improved precision for surgical navigation and tumor tracking in thoracic procedures.