HIGH-RESOLUTION PULMONARY COMPUTED-TOMOGRAPHY SCANS QUANTIFIED BY ANALYSIS OF DENSITY DISTRIBUTION - APPLICATION TO ASBESTOSIS

A new method for quantitative evaluation for high resolution computed tomography (HRCT) of the lungs was developed by assessment of the dist ribution of radiological densities within the lung slices. To enable e ffective reduction of data and improve the sensitivity of detection of abnormalities, the density distributions were analysed by curve fitti ng through the gamma variate model. The output of two variables proved most representative: the most frequent density (Hoansfield units; HU) and width of distribution (HU). The method was applied to seven patie nts with early asbestosis (positive histological finding and Internati onal Labour Office (ILO) profusion score up to 0/1), 15 patients with advanced stage of asbestosis (positive histological finding and ILO sc ore above 1/2), and 13 normal controls. All patients with early asbest osis had isolated reduction of diffusing lung capacity to carbon monox ide (DLCO), whereas all patients with advanced asbestosis had reduced DLCO and restrictive disease; two of them also had an obstruction patt ern. The most frequent densities were significantly greater in the adv anced asbestosis group (-567 HU) when compared with both the early asb estosis group (-719 HU; p = 2 x 10(-6)), and controls (-799 HU; p = 0) , and they also discriminated significantly between the early asbestos is group and controls (p = 0.0002). Significantly stronger linear co'' elations were established between DLCO and the most frequent densities (r = 0.86) than between DLCO and HRCT score (r = 0.57) or ILO score ( r = 0.34). It is concluded that fitting the curve of the density distr ibution enables a more objective assessment of HRCT pulmonary scans, e specially in the early stage of asbestosis.