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Quantitative computed tomography for the prediction of pulmonary function after lung cancer surgery: a simple method using simulation software

^a Department of Surgery and Clinical Science, Division of Chest Surgery, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi 755-8505, Japan
^b Department of Radiopathology and Science, Division of Radiology, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami-Kogushi, Ube, Yamaguchi 755-8505, Japan

Received 7 January 2008; received in revised form 7 January 2008; accepted 5 April 2008.

^_* Corresponding author. Tel.: +81 836 22 2259; fax: +81 836 22 2423. (Email: kaueda{at}c-able.ne.jp).

Objective: The prediction of pulmonary functional reserve is mandatory in therapeutic decision-making for patients with resectable lung cancer, especially those with underlying lung disease. Volumetric analysis in combination with densitometric analysis of the affected lung lobe or segment with quantitative computed tomography (CT) helps to identify residual pulmonary function, although the utility of this modality needs investigation. Methods: The subjects of this prospective study were 30 patients with resectable lung cancer. A three-dimensional CT lung model was created with voxels representing normal lung attenuation (–600 to –910 Hounsfield units). Residual pulmonary function was predicted by drawing a boundary line between the lung to be preserved and that to be resected, directly on the lung model. The predicted values were correlated with the postoperative measured values. Results: The predicted and measured values corresponded well (r = 0.89, p < 0.001). Although the predicted values corresponded with values predicted by simple calculation using a segment-counting method (r = 0.98), there were two outliers whose pulmonary functional reserves were predicted more accurately by CT than by segment counting. The measured pulmonary functional reserves were significantly higher than the predicted values in patients with extensive emphysematous areas (<–910 Hounsfield units), but not in patients with chronic obstructive pulmonary disease. Conclusion: Quantitative CT yielded accurate prediction of functional reserve after lung cancer surgery and helped to identify patients whose functional reserves are likely to be underestimated. Hence, this modality should be utilized for patients with marginal pulmonary function.

Key Words: Quantitative CT • Lung cancer • Pulmonary resection • Pulmonary function