Clinical impact of high-attenuation and XXXX on computed tomography in fibrotic @entity16058 .

@entity1 @entity82 @entity5409 @entity16058 @entity1223 @entity2416 @entity358 @entity401 @entity1319
BACKGROUND: Quantitative computed tomography (CT) analysis has been proposed as a means of objectively assessing fibrotic @entity401 ( @entity401 ) including @entity2416 ( @entity2416 ). We investigated whether percentages of high-attenuation areas (HAA%) and @entity5409 (CA%) quantified from CT images were useful as indices of @entity401 . METHODS: CT images of 74 @entity1 with fibrotic @entity16058 ( @entity2416 , 36; non-specific @entity401 , 9; unclassifiable @entity16058 , 29) were analyzed via in-house computer software, which automatically calculated HAA%, CA%, @entity358 ( @entity358 ), standard deviation of lung density (SD-LD), kurtosis, and @entity1319 from CT attenuation histograms. These indices were compared in each instance with physiologic measures, visual @entity82 score, clinical diagnosis, radiologic CT pattern, and prognosis. RESULTS: HAA% correlated significantly with physiologic measures and visual @entity82 score to a moderate extent (%forced vital capacity, rs   =   -0.59; % @entity1223 diffusion capacity, rs   =   -0.43; @entity82 score, rs   =   0.23). Densitometric parameters ( @entity358 , SD-LD, kurtosis, and @entity1319 ) correlated significantly with physiologic measures and @entity82 score ( rs    =   0.28-0.59). CA% showed no association with pulmonary functions but differed significantly between @entity2416 and other @entity401 ( @entity401 ) (1.50        2.41% vs. 0.41        0.80%; P   <   0.01) and between the definite @entity2416 ( @entity2416 ) pattern and other patterns (1.48        2.38% vs. 0.55        1.19%; P   <   0.01). On univariate analysis, HAA%, @entity358 , SD-LD, kurtosis, @entity1319 , @entity82 score, and definite @entity2416 pattern all correlated with survival, with kurtosis alone identified as a significant predictor of mortality on multivariate analysis (hazard ratio   =   0.67; 95% CI, 0.44-0.96; P   =   0.03). CONCLUSION: CA% and HAA% are novel quantitative CT indices with differing properties in @entity401 evaluations. HAA% largely reflects physiologic impairments, whereas CA% corresponds with diagnosis and HRCT pattern. Of the CT indices examined, kurtosis constituted the strongest predictor of mortality.
