Histological heterogeneity of glomerular segmental lesions in focal segmental glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) involves considerable histological heterogeneity in terms of location and quality of the glomerular segmental lesions. The present study investigated the heterogeneity of segmental lesions in each variant of FSGS, determined by the Columbia classification, and its clinical relevance. All glomerular segmental lesions of 80 cases of primary FSGS were evaluated histologically based on location [tip (TIP), perihilar (PH), or not otherwise specified (NOS)], and quality (cellular or fibrous). Among the 1,299 glomeruli of the 80 biopsy specimens, 210 glomeruli (16.2%) had segmental lesions, comprising 57 (27%) cellular TIP, 4 (2%) fibrous TIP, 42 (20%) cellular NOS, 86 (41%) fibrous NOS, and 21 (10%) fibrous PH lesions. Each case was also classified into one of the five histological variants of the Columbia classification: collapsing (COL), TIP, cellular (CEL), PH, or NOS. Overlap of segmental lesions in different location categories was seen in the COL, TIP, and PH variants, and heterogeneity of quality was apparent in the COL and CEL variants. Histological findings of the CEL variant (endocapillary hypercellularity) were observed in nine of the 13 COL variants. Both location and quality correlated with disease duration, degree of proteinuria, and histological severity of global glomerular sclerosis and tubulo-interstitial lesions. These results demonstrated the histological heterogeneity of glomerular segmental lesions in all variants of the Columbia classification, except NOS. However, the fidelity of location and dominance of histological features were generally conserved in the TIP and PH variants. The COL and CEL variants warrant further investigation because of their overlapping histological findings and apparent histological heterogeneity in the glomerular segmental lesions

Limitations of airway dimension measurement on images obtained using multi-detector row computed tomography.

[Objectives](a) To assess the effects of computed tomography (CT) scanners, scanning conditions, airway size, and phantom composition on airway dimension measurement and (b) to investigate the limitations of accurate quantitative assessment of small airways using CT images. [Methods]An airway phantom, which was constructed using various types of material and with various tube sizes, was scanned using four CT scanner types under different conditions to calculate airway dimensions, luminal area (Ai), and the wall area percentage (WA%). To investigate the limitations of accurate airway dimension measurement, we then developed a second airway phantom with a thinner tube wall, and compared the clinical CT images of healthy subjects with the phantom images scanned using the same CT scanner. The study using clinical CT images was approved by the local ethics committee, and written informed consent was obtained from all subjects. Data were statistically analyzed using one-way ANOVA. [Results]Errors noted in airway dimension measurement were greater in the tube of small inner radius made of material with a high CT density and on images reconstructed by body algorithm (p<0.001), and there was some variation in error among CT scanners under different fields of view. Airway wall thickness had the maximum effect on the accuracy of measurements with all CT scanners under all scanning conditions, and the magnitude of errors for WA% and Ai varied depending on wall thickness when airways of <1.0-mm wall thickness were measured. [Conclusions]The parameters of airway dimensions measured were affected by airway size, reconstruction algorithm, composition of the airway phantom, and CT scanner types. In dimension measurement of small airways with wall thickness of <1.0 mm, the accuracy of measurement according to quantitative CT parameters can decrease as the walls become thinner

The mean values of CT density (HU) in the phantom materials mimicking lung parenchyma and the mean values of maximum CT density in the tube walls.

<p>Average of measured values (SD).</p

Schema describing the method of airway dimension measurement.

<p>A: Using sequential CT slices which included a section of the target tube, the center (solid) line of the tube was calculated by linking the center points of sections on each slice. B: Images were constructed perpendicular to the center line.</p

Effects of scanning conditions on errors of airway dimension measurement.

<p>A: Effects of field of view (FOV) and slice thickness on errors for wall area percentage (WA%) in acrylic resin tubes surrounded by acrylic foam that were scanned using Aquilion 64 (120 mAs and lung algorithm FC56). B: Effects of the reconstruction algorithm on the errors of WA% in acrylic resin tubes surrounded by acrylic foam that were scanned using Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV). FC13: body algorithm, FC51: lung algorithm, FC56: lung algorithm (FC51) with beam-hardening correction. *: failure to measure. The error of airway dimensions was defined as follows: Error (%) = (CT measurement − actual value)/actual value×100.</p

Effects of wall thickness on airway dimension measurement.

<p>Average of measured values (SD).</p><p>Measured values of Ai, WA%, and wall thickness (WT) for various wall thickness using airway phantom B (actual luminal area: 7.07 mm²) scanned by Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV, and lung reconstruction algorithm FC56).</p

The four CT scanners used in assessments and their respective scanning data.

<p>kVp, kilovolts peak; FOV, field of view; AEC, automatic exposure control (actual range in this study: 25–30 mAs).</p

Effects of CT scanner and FOV on errors of airway dimension measurement.

<p>Comparison of errors WA% and luminal area (Ai) in acrylic resin tubes embedded in acrylic foam among four CT scanners under varying FOV (A: 200 mm, B: 350 mm). The images were reconstructed by the lung algorithm. The definition of error is shown in the legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076381#pone-0076381-g003" target="_blank">Figure 3</a>.</p

Effects of phantom composition on errors of airway dimension measurement.

<p>Percentage error of wall area (WA%) and luminal area (Ai) for the phantom scanned using Aquilion 64 (120 mAs, 0.5-mm slice thickness, 350-mm FOV, lung reconstruction algorithm FC56). A: Comparison of errors of WA% and Ai for acrylic resin tubes among materials simulating lung parenchyma, phenol resin (0.32 g/cm³), acrylic foam (0.10 g/cm³), and air. B: Comparison of errors for WA% and Ai among tube materials, fluorocarbon polymers (2.1 g/cm³), acrylic resin (1.2 g/cm³), and polyethylene (0.9 g/cm³) embedded in acrylic foam.</p

Examples of airways measured at different generations.

<p>The representative images of right posterior basal bronchi (3^rd generation) and more distal bronchi of a healthy control on Aquilion 64 (Auto Exposure Control, 0.5-mm slice thickness, 350-mm FOV, lung reconstruction algorithm FC56). At the 6^th to 7^th generation, the thickness of the bronchus wall had equal or less than pixels size.</p