CT colonography: size reduction of submerged colorectal polyps due to electronic cleansing and CT-window settings.

OBJECTIVES: To assess whether electronic cleansing (EC) of tagged residue and different computed tomography (CT) windows influence the size of colorectal polyps in CT colonography (CTC). METHODS: A database of 894 colonoscopy-validated CTC datasets of a low-prevalence cohort was retrospectively reviewed to identify patients with polyps ≥6 mm that were entirely submerged in tagged residue. Ten radiologists independently measured the largest diameter of each polyp, two-dimensionally, before and after EC in colon, bone, and soft-tissue-windows, in randomised order. Differences in size and polyp count before and after EC were calculated for size categories ≥6 mm and ≥10 mm. Statistical testing involved 95% confidence interval, intraclass correlation and mixed-model ANOVA. RESULTS: Thirty-seven patients with 48 polyps were included. Mean polyp size before EC was 9.8 mm in colon, 9.9 mm in bone and 8.2 mm in soft-tissue windows. After EC, the mean polyp size decreased significantly to 9.4 mm in colon, 9.1 mm in bone and 7.1 mm in soft-tissue windows. Compared to unsubtracted colon windows, EC, performed in colon, bone and soft-tissue windows, led to a shift of 6 (12,5%), 10 (20.8%) and 25 (52.1%) polyps ≥6 mm into the next smaller size category, thus affecting patient risk stratification. CONCLUSIONS: EC and narrow CT windows significantly reduce the size of polyps submerged in tagged residue. Polyp measurements should be performed in unsubtracted colon windows. KEY POINTS: • EC significantly reduces the size of polyps submerged in tagged residue. • Abdominal CT-window settings significantly underestimate 2D sizes of submerged polyps. • Size reduction in EC is significantly greater in narrow than wide windows. • Underestimation of polyp size due to EC may lead to inadequate treatment. • Polyp measurements should be performed in unsubtracted images using a colon window.

Longitudinal alignment of disease progression in fibrosing interstitial lung disease.

Generating disease progression models from longitudinal medical imaging data is a challenging task due to the varying and often unknown state and speed of disease progression at the time of data acquisition, the limited number of scans and varying scanning intervals. We propose a method for temporally aligning imaging data from multiple patients driven by disease appearance. It aligns follow- up series of different patients in time, and creates a cross-sectional spatio-temporal disease pattern distribution model. Similarities in the disease distribution guide an optimization process, regularized by temporal rigidity and disease volume terms. We demonstrate the benefit of longitudinal alignment by classifying instances of different fibrosing interstitial lung diseases. Classification results (AUC) of Usual Interstitial Pneumonia (UIP) versus non-UIP improve from AUC = 0.71 to 0.78 following alignment, classification of UIP vs. Extrinsic Allergic Alveolitis (EAA) improves from 0.78 to 0.88.

Gravitational gradients in expiratory computed tomography examinations of patients with small airways disease: effect of body position on extent of air trapping.

PURPOSE: First, to test the hypothesis that air trapping in diseased patients follows a gravitational gradient and is more extensive in dependent than in nondependent lung regions. Second, to test the hypothesis that the dependent lung regions on combined supine and prone expiratory computed tomography (CT) examinations will show more air trapping than would a supine expiratory CT examination alone. MATERIALS AND METHODS: For this ethics committee-approved study, supine and prone multidetector-row CT (4×1 mm collimation, 0.5 s rotation time, 140 kVp, and effective 80 mAs) was performed at full end-expiration on 47 lung transplant recipients (mean age 41±12 y; 18 without bronchiolitis, 18 with potential bronchiolitis, and 11 with bronchiolitis). The extent of air trapping was visually quantified in the supine and prone positions, and in dependent and nondependent lung regions. Individual air trapping scores from these regions were thus available and could be combined for later analysis. Differences in the extent of air trapping between the positions and regions were tested with a Wilcoxon signed-rank test. RESULTS: Air trapping was significantly more extensive in the combined dependent lung regions than in the combined nondependent lung regions (15.00% vs. 5.77%; P<0.001). Air trapping was also significantly more extensive in the combined dependent regions than in the supine body position (15.00% vs. 7.50%; P<0.001). No statistically significant difference in the extent of air trapping was found between the supine and the prone positions (7.50% vs. 12.14%; P=0.735). CONCLUSIONS: In patients with suspected or overt small airways disease, air trapping follows a gravitational gradient. A change from the supine to the prone position can make air trapping visible in formerly nondependent lung regions. The combined readings from supine and prone CT examinations in dependent lung regions show more air trapping than a standard supine CT examination alone.