Longitudinal airway remodeling in active and past smokers in a lung cancer screening population.

OBJECTIVES: To longitudinally investigate smoking cessation-related changes of quantitative computed tomography (QCT)-based airway metrics in a group of heavy smokers. METHODS: CT scans were acquired in a lung cancer screening population over 4 years at 12-month intervals in 284 long-term ex-smokers (ES), 405 continuously active smokers (CS), and 31 subjects who quitted smoking within 2 years after baseline CT (recent quitters, RQ). Total diameter (TD), lumen area (LA), and wall percentage (WP) of 1st-8th generation airways were computed using airway analysis software. Inter-group comparison was performed using Mann-Whitney U test or Student's t test (two groups), and ANOVA or ANOVA on ranks with Dunn's multiple comparison test (more than two groups), while Fisher's exact test or chi-squared test was used for categorical data. Multiple linear regression was used for multivariable analysis. RESULTS: At any time, TD and LA were significantly higher in ES than CS, for example, in 5th-8th generation airways at baseline with 6.24 mm vs. 5.93 mm (p < 0.001) and 15.23 mm2 vs. 13.51 mm2 (p < 0.001), respectively. RQ showed higher TD (6.15 mm vs. 5.93 mm, n.s.) and significantly higher LA (14.77 mm2 vs. 13.51 mm2, p < 0.001) than CS after 3 years, and after 4 years. In multivariate analyses, smoking status independently predicted TD, LA, and WP at baseline, at 3 years and 4 years (p < 0.01-0.001), with stronger impact than pack years. CONCLUSIONS: Bronchial dimensions depend on the smoking status. Smoking-induced airway remodeling can be partially reversible after smoking cessation even in long-term heavy smokers. Therefore, QCT-based airway metrics in clinical trials should consider the current smoking status besides pack years. KEY POINTS: • Airway lumen and diameter are decreased in active smokers compared to ex-smokers, and there is a trend towards increased airway wall thickness in active smokers. • Smoking-related airway changes improve within 2 years after smoking cessation. • Smoking status is an independent predictor of airway dimensions.

Effect of smoking cessation on quantitative computed tomography in smokers at risk in a lung cancer screening population.

OBJECTIVE: To longitudinally evaluate effects of smoking cessation on quantitative CT in a lung cancer screening cohort of heavy smokers over 4 years. METHODS: After 4 years, low-dose chest CT was available for 314 long-term ex-smokers (ES), 404 continuous smokers (CS) and 39 recent quitters (RQ) who quitted smoking within 2 years after baseline CT. CT acquired at baseline and after 3 and 4 years was subjected to well-evaluated densitometry software, computing mean lung density (MLD) and 15th percentile of the lung density histogram (15TH). RESULTS: At baseline, active smokers showed significantly higher MLD and 15TH (-822±35 and -936±25 HU, respectively) compared to ES (-831±31 and -947±22 HU, p<0.01-0.001). After 3 years, CS again had significantly higher MLD and 15TH (-801±29 and -896±23 HU) than ES (-808±27 and -906±20 HU, p<0.01-0.001) but also RQ (-813±20 and -909±15 HU, p<0.05-0.001). Quantitative CT parameters did not change significantly after 4 years. Importantly, smoking status independently predicted MLD at baseline and year 3 (p<0.001) in multivariate analysis. CONCLUSION: On quantitative CT, lung density is higher in active smokers than ex-smokers, and sustainably decreases after smoking cessation, reflecting smoking-induced inflammation. Interpretations of quantitative CT data within clinical trials should consider smoking status. KEY POINTS: • Lung density is higher in active smokers than ex-smokers. • Lung density sustainably decreases after smoking cessation. • Impact of smoking cessation on lung density is independent of potentially confounding factors. • Smoke-induced pulmonary inflammation and particle deposition influence lung density on CT.

New bone post-processing tools in forensic imaging: a multi-reader feasibility study to evaluate detection time and diagnostic accuracy in rib fracture assessment.

PURPOSE: The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. MATERIALS AND METHODS: Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. RESULTS: Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. CONCLUSION: Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.

Lung nodule detection in a high-risk population: comparison of magnetic resonance imaging and low-dose computed tomography.

OBJECTIVE: To investigate the potential of MRI for lung nodule detection in a high-risk population in comparison to low-dose CT. METHODS: 49 participants (31 men, 18 women, 51-71 years) of the German Lung Cancer Screening and Intervention Trial (LUSI) with a cancer-suspicious lung lesion in CT were examined with non-contrast-enhanced MRI of the lung at 1.5 T. Data were pseudonymized and presented at random order together with 30 datasets (23 in men, 7 in women, 18-64 years) from healthy volunteers. Two radiologists read the data for the presence of nodules. Sensitivity and specificity were calculated. Gold standard was either histology or long-term follow-up. Contrast-to-Noise-Ratio (CNR) was measured for all detected lesions in all MRI sequences. RESULTS: Average maximum diameter of the lesions was 15 mm. Overall sensitivity and specificity of MRI were 48% (26/54) and 88% (29/33) compared to low-dose CT. Sensitivity of MRI was significantly higher for malignant nodules (78% (12.5/16)) than for benign ones (36% (13.5/38); P=0.007). There was no statistically significant difference in sensitivity between nodules (benign and malignant) larger or smaller than 10 mm (P=0.7). Inter observer agreement was 84% (κ=0.65). Lesion-to-background CNR of T2-weighted single-shot turbo-spin-echo was significantly higher for malignant nodules (89±27) than for benign ones (56±23; P=0.002). CONCLUSION: The sensitivity of MRI for detection of malignant pulmonary nodules in a high-risk population is 78%. Due to its inherent soft tissue contrast, MRI is more sensitive to malignant nodules than to benign ones. MRI may therefore represent a useful test for early detection of lung cancer.