BMC pulmonary medicine · 2018
Automated computed tomographic scoring of lung disease in adults with primary ciliary dyskinesia.
СтатьяНазвание и аннотация: Перевод в очереди
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Hoang-Thi Trieu-Nghi, Revel Marie-Pierre, Burgel Pierre-Régis, Bassinet Laurence, Honoré Isabelle, Hua-Huy Thong, Martin Charlotte, Maitre Bernard, Chassagnon Guillaume
Аннотация
BACKGROUND: The present study aimed to develop an automated computed tomography (CT) score based on the CT quantification of high-attenuating lung structures, in order to provide a quantitative assessment of lung structural abnormalities in patients with Primary Ciliary Dyskinesia (PCD).
METHODS: Adult (≥18 years) PCD patients who underwent both chest CT and spirometry within a 6-month period were retrospectively included. Commercially available lung segmentation software was used to isolate the lungs from the mediastinum and chest wall and obtain histograms of lung density. CT-density scores were calculated using fixed and adapted thresholds based on various combinations of histogram characteristics, such as mean lung density (MLD), skewness, and standard deviation (SD). Additionally, visual scoring using the Bhalla score was performed by 2 independent radiologists. Correlations between CT scores, forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were evaluated.
RESULTS: Sixty-two adult patients with PCD were included. Of all histogram characteristics, those showing good positive or negative correlations to both FEV1 and FVC were SD (R = - 0.63 and - 0.67; p < 0.001) and Skewness (R = 0.67 and 0.67; p < 0.001). Among all evaluated thresholds, the CT-density score based on MLD + 1SD provided the best negative correlation with both FEV1 (R = - 0.68; p < 0.001) and FVC (R = - 0.71; p < 0.001), close to the correlations of the visual score (R = - 0.60; p < 0.001 for FEV1 and R = - 0.62; p < 0.001, for FVC).
CONCLUSIONS: Automated CT scoring of lung structural abnormalities lung in primary ciliary dyskinesia is feasible and may prove useful for evaluation of disease severity in the clinic and in clinical trials.
METHODS: Adult (≥18 years) PCD patients who underwent both chest CT and spirometry within a 6-month period were retrospectively included. Commercially available lung segmentation software was used to isolate the lungs from the mediastinum and chest wall and obtain histograms of lung density. CT-density scores were calculated using fixed and adapted thresholds based on various combinations of histogram characteristics, such as mean lung density (MLD), skewness, and standard deviation (SD). Additionally, visual scoring using the Bhalla score was performed by 2 independent radiologists. Correlations between CT scores, forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) were evaluated.
RESULTS: Sixty-two adult patients with PCD were included. Of all histogram characteristics, those showing good positive or negative correlations to both FEV1 and FVC were SD (R = - 0.63 and - 0.67; p < 0.001) and Skewness (R = 0.67 and 0.67; p < 0.001). Among all evaluated thresholds, the CT-density score based on MLD + 1SD provided the best negative correlation with both FEV1 (R = - 0.68; p < 0.001) and FVC (R = - 0.71; p < 0.001), close to the correlations of the visual score (R = - 0.60; p < 0.001 for FEV1 and R = - 0.62; p < 0.001, for FVC).
CONCLUSIONS: Automated CT scoring of lung structural abnormalities lung in primary ciliary dyskinesia is feasible and may prove useful for evaluation of disease severity in the clinic and in clinical trials.