Table 1.
Study population (n = 40) characteristics.
Fig 1.
Visualization of the fully automatic lung parenchyma segmentation as obtained by in-house YACTA software.
Sagittal reconstruction image of a non-enhanced MDCT scan obtained from a patient suffering from idiopathic pulmonary fibrosis (IPF) not included in the current trial. YACTA software automatically segmented lung parenchyma and trachea-bronchial tree, emphasized as green and orange overlay respectively (window width: 1600 HU; level: -600 HU). Note that the segmentation algorithm fails to segment portions of the lung parenchyma in the sub-pleural space of the recessus, due to its similar density to the chest wall. (MDCT = multidetector computed tomography).
Table 2.
Visual scores obtained at multidetector computed tomography (MDCT).
Fig 2.
Median density changes at 1-year follow-up in the range of 10th-90th percentile of the MDCT attenuation histogram for patients suffering from idiopathic pulmonary fibrosis (IPF) treated and untreated with pirfenidone.
The largest difference with the lowest overlap between treated and untreated patients in longitudinal HU changes of the attenuation histogram was detected in the 40th and in the 80th percentiles. Black squares = median increase of each 5th percentile step included in the 10th-90th range of the lung density histogram for patients treated with pirfenidone; black triangles and circles = interquartile range of the increase in each 5th percentile step included in the 10th-90th range of the lung density histogram for patients treated with pirfenidone; grey squares = median increase of each 5th percentile step included in the 10th-90th range of the lung density histogram for patients not treated with pirfenidone; grey triangles and circles = interquartile range of the increase in each 5th percentile step included in the 10th-90th range of the lung density histogram for patients not treated with pirfenidone. (Δ HU/y = changes in Hounsfield units per year; MDCT = multidetector computed tomography).
Fig 3.
Distribution of the density changes at 1-year in the selected percentiles from the MDCT attenuation histogram of patients suffering from idiopathic pulmonary fibrosis (IPF) treated and untreated with pirfenidone.
Box and Whisker plots represent the 40th percentile (a) and the 80th percentile distributions (b) of lung density histogram as observed in patients treated with pirfenidone and in patients not treated with pirfenidone. The central line represents the median, the yellow box encompasses the 25th-75th percentiles, whiskers show the 10th-90th percentile, and the empty circles represent individual outliers. (HU/y = Hounsfield units per year; Δ 40th percentile = changes at 1-year in the 40th percentile of the attenuation histogram; Δ 80th percentile = changes at 1-year in the 80th percentile of the attenuation histogram; MDCT = multidetector computed tomography).
Table 3.
Correlation analysis between selected percentiles of multidetector computed tomography (MDCT) attenuation histogram and visual scores (VSs).
Fig 4.
Correlations between changes at 1-year in selected percentiles of MDCT attenuation histogram and visual scores.
Dot plots with linear regression curves for changes in overall extent of parenchymal abnormalities plotted against density variation in the 40th percentile of the MDCT attenuation histogram (r = 0.69, p < 0.001) (a), for the changes in ground-glass opacity extent plotted against density variation in the 40th percentile of the MDCT attenuation histogram (r = 0.66, p < 0.001) (b), and for changes in reticulations extent plotted against density variation in 80th percentile of the MDCT attenuation histogram (r = 0.56, p < 0.001) (c). (%/y = percent per year; HU/y = Hounsfield units per year; MDCT = multidetector computed tomography).
Fig 5.
Variation of disease extent at follow-up MDCT in a 53 years-old man suffering from idiopathic pulmonary fibrosis (IPF) not treated with pirfenidone.
Axial MDCT image at level 5 (1 cm above the right hemi-diaphragm as described in the text) of the initial examination shows mild reticular opacities and minimal honeycombing (arrowheads) in a sub-pleural distribution (a). The 80th percentile of the initial MDCT attenuation histogram corresponded to -730 HU (b). Follow-up MDCT scan at the same axial level after 17 months shows a predominant increase of reticulations (visual score = +22%) and unmodified honeycombing extent (arrowhead) (c). An increase of 86 HU in the density of the 80th percentile was seen between initial and follow-up MDCT attenuation histograms (d). (Prob. = probability; HU = Hounsfield units; MDCT = multidetector computed tomography).
Table 4.
Correlation analysis of pulmonary function tests (PFTs) with visual scores (VSs) and selected percentiles obtained from multidetector computed tomography (MDCT) attenuation histogram.