Prediction of lung tumor palpability using high-resolution computed tomography
- PMID: 26542781
- DOI: 10.1177/0218492315615480
Prediction of lung tumor palpability using high-resolution computed tomography
Abstract
Background: Palpation is the most important means of locating lung tumors and resecting them with sufficient margins. This study aimed to predict the palpability of pulmonary lesions using high-resolution computed tomography.
Methods: Eighty-six pulmonary lesions were palpated in fresh resected lung specimens from July 2013 to March 2014. The following parameters were compared between 10 impalpable and 76 palpable lesions: maximum tumor size in pulmonary and bone window level settings, consolidation tumor size in pulmonary window level setting, and pleural-tumor distance. In 54 adenocarcinomas, the lepidic component and fibrosis foci rates were compared between the two groups.
Results: Tumor size in bone window level setting and the consolidation tumor size were significantly smaller in the impalpable group (both p < 0.001), and an operational cutoff of 5 mm was identified by receiver-operating characteristic analysis (sensitivity/specificity was 90.0%/94.7% and 90.0%/86.9%, respectively). Pulmonary lesions were impalpable with 87.5% probability when the tumor size in bone window level setting was ≤ 5 mm and the pleural-tumor distance was ≥ 5 mm, and with 85.7% probability when the consolidation tumor size was ≤ 5 mm and the pleural-tumor distance was ≥ 5 mm. Lepidic component and fibrosis foci rates of impalpable/palpable lesions were 96.0%/52.8% and 4.0%/24.7%, respectively (both p < 0.001).
Conclusions: Tumor size in bone window level setting or a consolidation tumor size ≤ 5 mm and pleural-tumor distance ≥ 5 mm are simple criteria that are potentially useful indicators for preoperative marking to locate small-sized lepidic-predominant adenocarcinomas with few fibrotic foci.
Keywords: Adenocarcinoma; Fibrosis; Lung neoplasms; Palpation; Thoracic surgery; Tomography; X-ray computed; bronchiolo-alveolar; video-assisted.
© The Author(s) 2015.
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