Efficacy of the Segment-Counting Method in Predicting Lung Function and Volume Following Stapler-Based Thoracoscopic...

Area of Science:

• Thoracic surgery
• Pulmonary function testing
• Medical imaging analysis

Background:

• Thoracoscopic segmentectomy is a minimally invasive lung cancer surgery.
• Accurate prediction of postoperative lung function is crucial for patient outcomes.
• Comparing segmentectomy with lobectomy requires reliable predictive tools.

Purpose of the Study:

• To evaluate the accuracy of a segment-counting method for predicting lung function and volume post-thoracoscopic segmentectomy.
• To compare the predictive accuracy of this method between segmentectomy and lobectomy.
• To identify factors influencing prediction accuracy in lung resections.

Main Methods:

• Retrospective review of 116 patients undergoing segmentectomy or lobectomy (2014-2018).
• Analysis of pre- and post-operative (1-year) thoracic CT and spirometry data.
• Comparison of predicted versus actual lung function and volume using the segment-counting method.

Main Results:

• Segment-counting method accurately predicted lung function and volume in the segmentectomy group.
• Predictions were significantly exceeded in the lobectomy group (P <0.01).
• Single segmentectomy showed a trend towards lower-than-predicted lung function (OR 3.29, P=0.04).

Conclusions:

• The segment-counting method is a valuable tool for predicting lung function after thoracoscopic segmentectomy.
• Lung function and volume are generally preserved or improved post-segmentectomy compared to predictions.
• The method demonstrates high accuracy with negligible prediction error for lung function.