Purpose: To prospectively compare pulmonary function tests and helical computed tomographic (CT) indexes for quantifying pulmonary emphysema with macroscopic and microscopic morphometry.
Materials and Methods: The investigation was approved by the local ethics committee, and written informed consent was obtained from patients. Multi–detector row CT of the thorax was performed with simultaneous acquisition of four 1-mm sections in 80 patients (57 men, 23 women; age range, 38–79 years) referred for surgical resection of lung cancer. From the raw data, 1.25-mm-thick sections were reconstructed at 10-mm intervals. Relative areas of lung with attenuation coefficients lower than nine thresholds and eight percentiles of the distribution of attenuation coefficients were calculated. Relative areas and percentiles were compared with areas found macroscopically to have emphysema and with two microscopic indexes assessed on resected specimens. Pulmonary function tests were measured 24–48 hours before surgery. Spearman correlation coefficients were calculated between each set of CT data obtained with the nine tested thresholds and eight percentiles with macroscopic and microscopic measurements.
Results: For relative lung areas, the strongest correlation with macroscopy was observed with a threshold of −970 HU (r = 0.543, P < .001) and that with microscopy was observed at −960 and −970 HU, depending on the index considered (r = 0.592, P < .001 and r = −0.546, P < .001, respectively). For percentiles, 1st percentile showed the strongest correlation with both macroscopy (r = −0.463, P < .001) and microscopy (r = −0.573, P < .001; and r = 0.523, P < .001 for each microscopic measurement). Forced expiratory volume in 1 second and vital capacity ratio, diffusing capacity of lung for carbon monoxide, and each of the three CT indexes were complementary to predict microscopic indexes.
Conclusion: Relative lung areas with attenuation coefficients lower than −960 or −970 HU and 1st percentile are valid indexes to quantify pulmonary emphysema on multi–detector row CT scans.
© RSNA, 2006
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