Parietal pleural invasion/adhesion of subpleural lung cancer: Quantitative 4-dimensional CT analysis using dynamic-ventilatory scanning. 2017
OBJECTIVE Using 4-dimensional dynamic-ventilatory scanning by a 320-row computed tomography (CT) scanner, we performed a quantitative assessment of parietal pleural invasion and adhesion by peripheral (subpleural) lung cancers. METHODS Sixteen patients with subpleural lung cancer underwent dynamic-ventilation CT during free breathing. Neither parietal pleural invasion nor adhesion was subsequently confirmed by surgery in 10 patients, whereas the other 6 patients were judged to have parietal pleural invasion or adhesion. Using research software, we tracked the movements of the cancer and of an adjacent structure such as the rib or aorta, and converted the data to 3-dimensional loci. The following quantitative indices were compared by the Mann-Whitney test: cross-correlation coefficient between time curves for the distances moved from the inspiratory frame by the cancer and the adjacent structure, the ratio of the total movement distances (cancer/adjacent structure), and the cosine similarities between the inspiratory and expiratory vectors (from the cancer to the adjacent structure) and between vectors of the cancer and of the adjacent structure (from inspiratory to expiratory frames). RESULTS Generally, the movements of the loci of the lung cancer and the adjacent structure were similar in patients with parietal pleural invasion/adhesion, while they were independent in patients without. There were significant differences in all the parameters between the two patient groups (cross-correlation coefficient and the movement distance ratio, P<0.01; cosine similarities, P<0.05). CONCLUSIONS These observations suggest that quantitative indices by dynamic-ventilation CT can be utilized as a novel imaging approach for the preoperative assessment of parietal pleural invasion/adhesion.