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Purpose: To improve outcomes for lung cancer through low-dose computed tomography (LDCT) early lung cancer detection. The International Association for the Study of Lung Cancer is developing the Early Lung Imaging Confederation (ELIC) to serve as an open-source, international, universally accessible environment to analyze large collections of quality-controlled LDCT images and associated biomedical data for research and routine screening care., Methods: ELIC is an international confederation that allows access to efficiently analyze large numbers of high-quality computed tomography (CT) images with associated de-identified clinical information without moving primary imaging/clinical or imaging data from its local or regional site of origin. Rather, ELIC uses a cloud-based infrastructure to distribute analysis tools to the local site of the stored imaging and clinical data, thereby allowing for research and quality studies to proceed in a vendor-neutral, collaborative environment. ELIC's hub-and-spoke architecture will be deployed to permit analysis of CT images and associated data in a secure environment, without any requirement to reveal the data itself (ie, privacy protecting). Identifiable data remain under local control, so the resulting environment complies with national regulations and mitigates against privacy or data disclosure risk., Results: The goal of pilot experiments is to connect image collections of LDCT scans that can be accurately analyzed in a fashion to support a global network using methodologies that can be readily scaled to accrued databases of sufficient size to develop and validate robust quantitative imaging tools., Conclusion: This initiative can rapidly accelerate improvements to the multidisciplinary management of early, curable lung cancer and other major thoracic diseases (eg, coronary artery disease and chronic obstructive pulmonary disease) visualized on a screening LDCT scan. The addition of a facile, quantitative CT scanner image quality conformance process is a unique step toward improving the reliability of clinical decision support with CT screening worldwide.

Purpose: To test ultra-low-dose computed tomography (ULDCT) scanning protocols for the detection of pulmonary nodules (PN)., Methods: A chest phantom containing 19 solid and 11 subsolid PNs was scanned on a third-generation dual-source computed tomography (CT) scanner. Five ULDCT scans (Sn100kVp and 120, 70, 50, 30, and 20 reference mAs, using tube current modulation), reconstructed with iterative reconstruction (IR) algorithm at strength levels 2, 3, 4, and 5, were compared with standard CT (120kVp, 150 reference mAs, using tube current modulation). PNs were subjectively assessed according to a 4-point scale: 0, nondetectable nodule; 1, detectable nodule, very unlikely to be correctly measured; 2, detectable nodule, likely to be correctly measured; 3, PN quality equal to standard of reference. PN scores were analysed according to the Lung Imaging Reporting and Data System (Lung-RADS), simulating detection of nodules at baseline and incidence screening round., Results: For the baseline round, there were 17 Lung-RADS 2, 4 Lung-RADS 3, 8 Lung-RADS 4A, and 1 Lung-RADS 4B PNs. They were detectable in any ULDCT protocol, with the exception of 1 nondetectable part-solid nodule in 1 scanning protocol (120 reference mAs; IR strength: 3). For the incidence round, there were 4 Lung-RADS 2, 14 Lung-RADS 3, 2 Lung-RADS 4A, and 10 Lung-RADS 4B PNs. Ten were nondetectable in at least one ULDCT dataset; however, they were at least detectable in ULDCT with 70 reference mAs (IR strength: 4 and 5)., Conclusions: ULDCT scanning protocols allowing the detection of PNs can be proposed for the purpose of lung cancer screening.

Smokers have higher levels of C-Reactive Protein (CRP) compared to never smokers. The role of smoking cessation on CRP is still under debate. Using data from two screening studies conducted in Italy in 2000-2010 on 3050 heavy smokers (including 777 ex-smokers), we estimated multivariate odds ratios (OR) for high CRP (i.e. ≥2 mg/L) according to smoking status. Moreover, in a longitudinal analysis based on 975 current smokers, with a second measurement of CRP after an average study period of 3.4 years, we estimated the changes in CRP according to smoking cessation. Prevalence of high CRP at baseline was 35.8% among ex-smokers and 41.1% among current smokers (significant OR for ex- vs. current smokers: 0.79). After four years since smoking cessation, CRP levels significantly decreased with increasing years of cessation (significant OR for ex-smokers since more than 8 years: 0.55). In the longitudinal analysis, no significant reduction in CRP was found for time since smoking cessation (ORs: 1.21, 1.04, and 0.91 for ex-smokers since 1 year, 2-3 years, and ≥4 years, respectively). In the largest prospective study available so far, we found that smoking cessation has a favourable effect on CRP, but this benefit is not evident in the short-term.

Objectives: The aim of this study was to compare computer-aided diagnosis (CAD) and visual reading for the detection of subsolid nodules (SSNs) in volumetrl measuremic low-dose computed tomography (LDCT) for lung cancer screening., Materials and Methods: Prospective visual detection (VD) and manuaent of SSN were performed in the 2303 baseline volumetric LDCTs of the Multicenter Italian Lung Detection trial. Baseline and 2- and 4-year LDCTs underwent retrospective CAD analysis, subsequently reviewed by 2 experienced thoracic radiologists. The reference standard was defined by the cumulative number of SSNs detected by any reading method between VD and CAD. The number of false-positive CAD marks per scan (FP/scan) was calculated. The positive predictive value of CAD was quantified per nodule (PPV) and per screenee (PPV). The sensitivity and negative predictive value were compared between CAD and VD. The longitudinal 3-time-point sensitivity of CAD was calculated in the subgroup of persistent SSNs seen by VD (ratio between the prevalent SSNs detected by CAD through 3 time points and the total number of persistent prevalent SSNs detected by VD) to test the sensitivity of iterated CAD analysis during a screening program. Semiautomatic characteristics (diameter, volume, and mass; both for whole nodule and solid component) were compared between SSN detected CAD-only or VD-only to investigate whether either reading method could suffer from specific sensitivity weakness related to SSN features. Semiautomatic and manual diameters were compared using Spearman ρ correlation and Bland-Altman plot., Results: Computer-aided diagnosis and VD detected a total of 194 SSNs in 6.7% (155/2,303) of screenees at baseline LDCT. The CAD showed mean FP/scan of 0.26 (604/2,303); PPV 22.5% (175/779) for any SSN, with 54.4% (37/68) for PSN and 19.4% for NSN (138/711; P < 0.001); PPV 25.6% (137/536). The sensitivity of CAD was superior to that of VD (88.4% and 34.2%, P < 0.001), as well as negative predictive value (99.2% and 95.5%, P < 0.001). The longitudinal 3-time-point sensitivity of CAD was 87.5% (42/48). There was no influence of semiautomatic characteristics on the performance of either reading method. The diameter of the solid component in PSN was larger by CAD compared with manual measurement. At baseline, CAD detected 3 of 4 SSNs, which were first overlooked by VD and subsequently evolved to lung cancer., Conclusions: Computer-aided diagnosis and VD as concurrent reading methods showed complementary performance, with CAD having a higher sensitivity, especially for PSN, but requiring visual confirmation to reduce false-positive calls. Computer-aided diagnosis and VD should be jointly used for LDCT reading to reduce false-negatives of either lone method. The semiautomatic measurement of solid core showed systematic shift toward a larger diameter, potentially resulting in an up-shift within Lung CT Screening Reporting and Data System classification.

Subsolid pulmonary nodules are commonly encountered in lung cancer screening and clinical routine. Compared to other nodule types, subsolid nodules are associated with a higher malignancy probability for which the size and mass of the nodule and solid core are important indicators. However, reliably measuring these characteristics on computed tomography (CT) can be hampered by the presence of vessels encompassed by the nodule, since vessels have similar CT attenuation as solid cores. This can affect treatment decisions and patient management. We present a method based on voxel classification to automatically identify vessels and solid cores in given subsolid nodules on CT. Three experts validated our method on 170 screen-detected subsolid nodules from the Multicentric Italian Lung Disease trial. The agreement between the proposed method and the observers was substantial for vessel detection and moderate for solid core detection, which was similar to the inter-observer agreement. We found a relatively high variability in the inter-observer agreement and low method-observer agreements for delineating the borders of vessels and solid cores, illustrating the difficulty of this task. However, 92.4% of the proposed vessel and 80.6% of the proposed solid core segmentations were labeled as usable in clinical practice by the majority of experts.

Lung cancer screening with low-dose CT can save lives. This European Union (EU) position statement presents the available evidence and the major issues that need to be addressed to ensure the successful implementation of low-dose CT lung cancer screening in Europe. This statement identified specific actions required by the European lung cancer screening community to adopt before the implementation of low-dose CT lung cancer screening. This position statement recommends the following actions: a risk stratification approach should be used for future lung cancer low-dose CT programmes; that individuals who enter screening programmes should be provided with information on the benefits and harms of screening, and smoking cessation should be offered to all current smokers; that management of detected solid nodules should use semi-automatically measured volume and volume-doubling time; that national quality assurance boards should be set up to oversee technical standards; that a lung nodule management pathway should be established and incorporated into clinical practice with a tailored screening approach; that non-calcified baseline lung nodules greater than 300 mm 3 , and new lung nodules greater than 200 mm 3 , should be managed in multidisciplinary teams according to this EU position statement recommendations to ensure that patients receive the most appropriate treatment; and planning for implementation of low-dose CT screening should start throughout Europe as soon as possible. European countries need to set a timeline for implementing lung cancer screening., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly relies on nodule size and nodule type. In this paper, we present a deep learning system based on multi-stream multi-scale convolutional networks, which automatically classifies all nodule types relevant for nodule workup. The system processes raw CT data containing a nodule without the need for any additional information such as nodule segmentation or nodule size and learns a representation of 3D data by analyzing an arbitrary number of 2D views of a given nodule. The deep learning system was trained with data from the Italian MILD screening trial and validated on an independent set of data from the Danish DLCST screening trial. We analyze the advantage of processing nodules at multiple scales with a multi-stream convolutional network architecture, and we show that the proposed deep learning system achieves performance at classifying nodule type that surpasses the one of classical machine learning approaches and is within the inter-observer variability among four experienced human observers.

Purpose: In this study, we tested the association between COPD and interstitial lung abnormality (ILA), notably in relation to the presence of computed tomography (CT) signs of lung fibrosis., Patients and Methods: COPD cases were selected from participants undergoing lung cancer screening (Multicentric Italian Lung Detection trial) for airflow obstruction (n=311/2,303, 13.5%) and 146 consecutive patients with clinical COPD. In all, 457 COPD cases were selected and classified according to the stages of Global Initiative for Chronic Obstructive Lung Disease. A nested matching (case:control = 1:2) according to age, sex, and smoking history was operated between each COPD case and two control subjects from Multicentric Italian Lung Detection trial without airflow obstruction. Low-dose CT scans of COPD cases and controls were reviewed for the presence of ILA, which were classified into definite or indeterminate according to the presence of signs of lung fibrosis., Results: The frequency of definite ILA was similar between COPD cases and controls (P=0.2), independent of the presence of signs of lung fibrosis (P=0.07). Combined definite and indeterminate ILA was homogeneously distributed across Global Initiative for Chronic Obstructive Lung Disease stages (P=0.6). Definite ILA was directly associated with current smoker status (odds ratio [OR] 4.05, 95% confidence interval [CI]: 2.2-7.4) and increasing pack-years (OR 1.01, 95% CI: 1-1.02). Subjects with any fibrotic ILA were more likely to be older (OR 1.17, 95% CI: 1.10-1.25) and male (OR 8.58, 95% CI: 1.58-68.9)., Conclusion: There was no association between COPD and definite ILA. However, low-dose CT signs of lung fibrosis were also observed in COPD, and their clinical relevance is yet to be determined.

Introduction: The National Lung Screening Trial has achieved a 7% reduction in total mortality with low-dose computed tomography (LDCT) screening as compared with in the chest radiography arm. Other randomized trials are under way, comparing LDCT screening with no intervention. None of these studies was designed to investigate the impact of smoking habits on screening outcome. In the present study, we tested the effect of stopping smoking on the overall mortality of participants undergoing repeated LDCT screening for many years., Methods: Between 2000 and 2010, 3381 smokers aged 50 years or older were enrolled in two LDCT screening programs. On the basis of the last follow-up information, subjects were divided into two groups: current smokers throughout the screening period and former smokers., Results: With a median follow-up time of 9.7 years and a total of 32,857 person-years (PYs) of follow-up, a total of 151 deaths were observed in the group of 1797 current smokers (17,846 PYs) versus 109 among 1584 former smokers (15,011 PYs), corresponding to mortality rates of 8.46 and 7.26 for every 1000 PYs, respectively. Compared with current smokers, former smokers had an adjusted mortality hazard ratio of 0.61 (95% confidence interval: 0.44-0.83), with a 39% reduction in mortality. A similar reduction in mortality was observed in the subset of 712 late quitters, with a hazard ratio of 0.65 (95% confidence interval: 0.44-0.96)., Conclusions: Stopping smoking significantly reduces the overall mortality of smokers enrolled in LDCT screening programs. The beneficial effect of stopping smoking on total mortality appears to be threefold to fivefold greater than the one achieved by earlier detection in the National Lung Screening Trial., (Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Introduction: Small cell lung cancer (SCLC) constitutes a distinct component of symptomatic or advanced-stage lung cancers in clinical practice and in lung cancer screening trials. The purpose of this study was to describe the outcome of SCLC in lung cancer screening trials and compare the frequency of SCLC in our cohort with that in the major lung cancer screening trials., Methods: Subjects with a diagnosis of SCLC were selected from two lung cancer screening trials by low-dose computed tomography (LDCT), and their demographic characteristics, clinical parameters, tumor stage at diagnosis, therapy, and survival times were recorded. Survival curves were estimated using the Kaplan-Meier method., Results: Ten cases of SCLC were reported in 45,141 person-years (22 in 100,000 person-years), representing the 6% of all lung cancer cases. Cumulative tobacco consumption was 82 pack-years compared with 39 and 46 pack-years for the overall study population and subjects with non-SCLC, respectively. Most of the neoplasms were in an advanced stage (seven in stage IV and one each in stages IIIb, IIIa, and Ia). Two subjects were treated with lobectomy for curative purposes and died of diffuse metastasis within 2 years of diagnosis. The median overall survival time in the LDCT arms was 20.6 months, with no survivors remaining at 3 years., Conclusions: Subjects in whom SCLC develops are a subgroup of smokers with extremely high cumulative tobacco consumption. Consequently, the frequency of SCLC in our population was lower than in other screening populations, with higher cumulative tobacco consumption. Screening for lung cancer by LDCT does not improve survival of SCLC, with no survivors remaining at 3 years after diagnosis., (Copyright © 2015 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

Liquid biopsies can detect biomarkers carrying information on the development and progression of cancer. We demonstrated that a 24 plasma-based microRNA signature classifier (MSC) was capable of increasing the specificity of low dose computed tomography (LDCT) in a lung cancer screening trial. In the present study, we tested the prognostic performance of MSC, and its ability to monitor disease status recurrence in LDCT screening-detected lung cancers.Between 2000 and 2010, 3411 heavy smokers enrolled in two screening programmes, underwent annual or biennial LDCT. During the first five years of screening, 84 lung cancer patients were classified according to one of the three MSC levels of risk: high, intermediate or low. Kaplan-Meier survival analysis was performed according to MSC and clinico-pathological information. Follow-up MSC analysis was performed on longitudinal plasma samples (n = 100) collected from 31 patients before and after surgical resection.Five-year survival was 88.9% for low risk, 79.5% for intermediate risk and 40.1% for high risk MSC (p = 0.001). The prognostic power of MSC persisted after adjusting for tumor stage (p = 0.02) and when the analysis was restricted to LDCT-detected cases after exclusion of interval cancers (p < 0.001). The MSC risk level decreased after surgery in 76% of the 25 high-intermediate subjects who remained disease free, whereas in relapsing patients an increase of the MSC risk level was observed at the time of detection of second primary tumor or metastatic progression.These results encourage exploiting the MSC test for lung cancer monitoring in LDCT screening for lung cancer.

Background: Although screening programmes of smokers have detected resectable early lung cancers more frequently than expected, their efficacy in reducing mortality remains debatable. To elucidate the biological features of computed tomography (CT) screening detected lung cancer, we examined the mRNA signatures on tumours according to the year of detection, stage and survival., Methods: Gene expression profiles were analysed on 28 patients (INT-IEO training cohort) and 24 patients of Multicentre Italian Lung Detection (MILD validation cohort). The gene signatures generated from the training set were validated on the MILD set and a public deposited DNA microarray data set (GSE11969). Expression of selected genes and proteins was validated by real-time RT-PCR and immunohistochemistry. Enriched core pathway and pathway networks were explored by GeneSpring GX10., Findings: A 239-gene signature was identified according to the year of tumour detection in the training INT-IEO set and correlated with the patients' outcomes. These signatures divided the MILD patients into two distinct survival groups independently of tumour stage, size, histopathological type and screening year. The signatures can also predict survival in the clinically detected cancers (GSE11969). Pathway analyses revealed tumours detected in later years enrichment of the PI3K/PTEN/AKT pathway, with up-regulation of PDPK1, ITGB1 and down-regulation of FOXO1A. Analysis of normal lung tissue from INT-IEO cohort produced signatures distinguishing patients with early from late detected tumours., Interpretation: The distinct pattern of "indolent" and "aggressive" tumour exists in CT-screening detected lung cancer according to the gene expression profiles. The early development of an aggressive phenotype may account for the lack of mortality reduction by screening observed in some cohorts.

The selection of populations to be screened for lung cancer must be further optimized before translation to large population. A 3-step refinement should be integrated into forthcoming lung cancer trials, namely, calculation of risk based on (1) demographics, (2) biological factors, and (3) radiologic inputs. Biological sampling should be implemented up-front to reduce the use of low-dose computed tomography scanning in patients with lower risk of aggressive disease and, notably, to improve detection of aggressive disease that is overlooked by current screening strategies., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Purpose: Recent screening trial results indicate that low-dose computed tomography (LDCT) reduces lung cancer mortality in high-risk patients. However, high false-positive rates, costs, and potential harms highlight the need for complementary biomarkers. The diagnostic performance of a noninvasive plasma microRNA signature classifier (MSC) was retrospectively evaluated in samples prospectively collected from smokers within the randomized Multicenter Italian Lung Detection (MILD) trial., Patients and Methods: Plasma samples from 939 participants, including 69 patients with lung cancer and 870 disease-free individuals (n = 652, LDCT arm; n = 287, observation arm) were analyzed by using a quantitative reverse transcriptase polymerase chain reaction-based assay for MSC. Diagnostic performance of MSC was evaluated in a blinded validation study that used prespecified risk groups., Results: The diagnostic performance of MSC for lung cancer detection was 87% for sensitivity and 81% for specificity across both arms, and 88% and 80%, respectively, in the LDCT arm. For all patients, MSC had a negative predictive value of 99% and 99.86% for detection and death as a result of disease, respectively. LDCT had sensitivity of 79% and specificity of 81% with a false-positive rate of 19.4%. Diagnostic performance of MSC was confirmed by time dependency analysis. Combination of both MSC and LDCT resulted in a five-fold reduction of LDCT false-positive rate to 3.7%. MSC risk groups were significantly associated with survival (χ1(2) = 49.53; P < .001)., Conclusion: This large validation study indicates that MSC has predictive, diagnostic, and prognostic value and could reduce the false-positive rate of LDCT, thus improving the efficacy of lung cancer screening.

Purpose: We aimed to evaluate the validity of lung lobe weight assessment via computed tomography (CT) by comparing CT-derived and ex vivo measurements., Materials and Methods: Unenhanced CT scanning was performed in 30 consecutive patients before lobectomy for lung cancer. The CT images were analyzed using research software after allowing for lobar weight quantitation. The lobar weight estimated by CT was then compared with that measured after surgery using a precision scale (ex vivo measurement). Comparisons as well as assessment of intra- and interoperator variability were conducted using the Bland-Altman method and the coefficient of repeatability (CR). Correlations were examined using Pearson's correlation analysis., Results: Comparison analyses were feasible for 28 cases. The ex vivo lobe weight was 186.2±57.3 g, whereas the weights measured by the two operators by CT were 190.0±55 and 182.4±58.2 g, respectively. As compared with ex vivo weights, the CR was 36.4 for operator 1 and 50.4 for operator 2; the mean differences were 3.8 and -3.8 for operators 1 and 2, respectively. The intraoperator and interoperator CR were 20.9 and 36.6, respectively. The mean differences for the intra- and interoperator analysis were -1.5 and -7.5, respectively. The correlation was very high between CT-based and ex vivo measurements (r=0.95 and r=0.90 for operators 1 and 2, respectively; P < 0.001)., Conclusion: Estimation of lung lobe weight by semi-automated CT analysis is sufficiently reproducible and in agreement with ex vivo measurements.

Objectives: To investigate the relationship between emphysema phenotype, mean lung density (MLD), lung function and lung cancer by using an automated multiple feature analysis tool on thin-section computed tomography (CT) data., Methods: Both emphysema phenotype and MLD evaluated by automated quantitative CT analysis were compared between outpatients and screening participants with lung cancer (n=119) and controls (n=989). Emphysema phenotype was defined by assessing features such as extent, distribution on core/peel of the lung and hole size. Adjusted multiple logistic regression models were used to evaluate independent associations of CT densitometric measurements and pulmonary function test (PFT) with lung cancer risk., Results: No emphysema feature was associated with lung cancer. Lung cancer risk increased with decreasing values of forced expiratory volume in 1s (FEV1) independently of MLD (OR 5.37, 95% CI: 2.63-10.97 for FEV1<60% vs. FEV1≥90%), and with increasing MLD independently of FEV1 (OR 3.00, 95% CI: 1.60-5.63 for MLD>-823 vs. MLD<-857 Hounsfield units)., Conclusion: Emphysema per se was not associated with lung cancer whereas decreased FEV1 was confirmed as being a strong and independent risk factor. The cross-sectional association between increased MLD and lung cancer requires future validations., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Background: Factors determining the shape of the human rib cage are not completely understood. We aimed to quantify the contribution of anthropometric and COPD-related changes to rib cage variability in adult cigarette smokers., Methods: Rib cage diameters and areas (calculated from the inner surface of the rib cage) in 816 smokers with or without COPD, were evaluated at three anatomical levels using computed tomography (CT). CTs were analyzed with software, which allows quantification of total emphysema (emphysema%). The relationship between rib cage measurements and anthropometric factors, lung function indices, and %emphysema were tested using linear regression models., Results: A model that included gender, age, BMI, emphysema%, forced expiratory volume in one second (FEV1)%, and forced vital capacity (FVC)% fit best with the rib cage measurements (R(2) = 64% for the rib cage area variation at the lower anatomical level). Gender had the biggest impact on rib cage diameter and area (105.3 cm(2); 95% CI: 111.7 to 98.8 for male lower area). Emphysema% was responsible for an increase in size of upper and middle CT areas (up to 5.4 cm(2); 95% CI: 3.0 to 7.8 for an emphysema increase of 5%). Lower rib cage areas decreased as FVC% decreased (5.1 cm(2); 95% CI: 2.5 to 7.6 for 10 percentage points of FVC variation)., Conclusions: This study demonstrates that simple CT measurements can predict rib cage morphometric variability and also highlight relationships between rib cage morphometry and emphysema.

Introduction: The purpose of this study was to evaluate the natural evolution of ground-glass nodules (GGNs) in the Multicentric Italian Lung Detection (MILD) trial, which adopted a nonsurgical approach to this subset of lesions., Methods: From September 2005 to August 2007, 56 consecutive MILD participants with 76 GGNs were identified from 1866 individuals who underwent baseline low-dose computed tomography. The features of GGNs were assessed and compared with the corresponding repeat low-dose computed tomographies after a mean time of 50.26 ± 7.3 months. The GGNs were classified as pure (pGGN) or part-solid (psGGN) GGNs. The average of the maximum and the minimum diameters for both pGGNs and psGGNs and the maximum diameter of the solid portion of psGGNs were manually measured. At follow-up, GGNs were classified as follows: resolved, decreased, stable, or progressed (according to three defined growth patterns)., Results: A total of 15 of 48 pGGNs (31.3%) resolved, 4 of 48 (8.3%) decreased in size, 21 of 48 (43.8%) remained stable, and 8 of 48 (16.7%) progressed. Among the psGGNs with a solid component smaller than 5 mm, 3 of 26 (11.5%) resolved, 11 of 26 (42.3%) remained stable, and 12 of 26 (46.2%) progressed. One of the two psGGNs with a solid component larger than 5 mm remained stable, and the other decreased in size. Four lung cancers were detected among the GGN subjects, but only one arose from a psGGN, and was resected in stage Ia., Conclusions: The progression rate of the GGNs toward clinically relevant disease was extremely low in the MILD trial and supports an active surveillance attitude.

Rationale and Objectives: To define a statistically based variation of individual whole-lung densitometry above which a real increase of pulmonary extent can be suspected in lung cancer screening trials., Materials and Methods: Baseline and 3-month follow-up low-dose computed tomography (LDCT) examinations of 131 smokers or former smokers recruited in the ITALUNG (32 subjects) and MILD (99 subjects) trials were compared using for each data set two different image processing tools for whole-lung densitometry. Both trials were approved by institutional review boards, and written informed consent was obtained from all participants. Assuming that no change of emphysema extent can occur in a 3-month interval, the Bland and Altman method was used to assess the agreement between baseline and follow-up LDCT examinations for lung volume, 15th percentile (Perc15) of lung density and Perc15 corrected for lung volume by application of a linear detrend on log-transformed data., Results: Similar results were obtained in each data set using two different image processing tools. In the ITALUNG cohort the 95% limits of agreement (LoA) interval of volume corrected Perc15 was -9.7 to 10.7% using image processing method 1 and -10.3 to 11.5% using image processing method 2. In the MILD cohort, the 95% LoA interval of volume corrected Perc15 was -14.7 to 17.3% with both image processing methods., Conclusion: In the two considered lung cancer screening settings a range of 9.7-14.7% decrease of volume corrected Perc15 represents a statistically defined threshold to suspect a real increase of emphysema extent in serial LDCT examinations., (Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.)

The efficacy of computed tomography (CT) screening for early lung cancer detection in heavy smokers is currently being tested by a number of randomized trials. Critical issues remain the frequency of unnecessary treatments and impact on mortality, indicating the need for biomarkers of aggressive disease. We explored microRNA (miRNA) expression profiles of lung tumors, normal lung tissues and plasma samples from cases with variable prognosis identified in a completed spiral-CT screening trial with extensive follow-up. miRNA expression patterns significantly distinguished: (i) tumors from normal lung tissues, (ii) tumor histology and growth rate, (iii) clinical outcome, and (iv) year of lung cancer CT detection. Interestingly, miRNA profiles in normal lung tissues also displayed remarkable associations with clinical features, suggesting the influence of a permissive microenvironment for tumor development. miRNA expression analyses in plasma samples collected 1-2 y before the onset of disease, at the time of CT detection and in disease-free smokers enrolled in the screening trial, resulted in the generation of miRNA signatures with strong predictive, diagnostic, and prognostic potential (area under the ROC curve ≥ 0.85). These signatures were validated in an independent cohort from a second randomized spiral-CT trial. These results indicate a role for miRNAs in lung tissues and plasma as molecular predictors of lung cancer development and aggressiveness and have theoretical and clinical implication for lung cancer management.

Background: Fluorodeoxyglucose-positron emission tomography (FDG-PET) has proven its value in the diagnosis of undetermined pulmonary lesions, lung cancer staging, and assessment of prognosis. Purpose of this study is to clarify whether standardized uptake value (SUV) can predict clinical outcome of computed tomography (CT) screening detected lung cancer., Methods: We tested the predictive value of FDG-PET using SUV on long-term survival of 34 lung cancer patients, detected from 1035 heavy smokers > or = 50 years monitored by annual low-dose CT for 5 years, with a median follow-up of 75 months from diagnosis., Findings: PET scan was performed in 34 (89%) of 38 lung cancer patients diagnosed during the 5 years of screening and was positive in 32 (94%). Complete resection was achieved in 30 cases (88%), 20 (59%) were pathologic stage I and 23 (68%) were adenocarcinoma. Median SUV was 5.0 overall, being significantly lower in stage I (2.5 vs. 10.1, p = 0.001) and in adenocarcinoma (2.5 vs. 13.0, p = 0.001). The 5-year survival of lung cancer patients was 100% for SUV levels < or = 2.5, 60% for SUV more than 2.5 and less than 8, and only 20% for SUV > or = 8 (p = 0.001)., Conclusions: FDG-PET using SUV can predict long-term survival of screening detected lung cancer, in a noninvasive manner. Metabolic assessment of biologic behavior might improve the clinical management of CT-detected lung cancer and reduce the risk of unnecessary treatments for indolent disease.

Purpose: To assess in vivo volumetric repeatability of an automated software algorithm in pulmonary nodules detected during a lung cancer screening trial., Materials and Methods: This study was approved by an institutional review board. Written informed consent was obtained from all participants. Data were collected from the Multicentric Italian Lung Detection project, a randomized controlled lung cancer screening trial. The first 1236 consecutive baseline computed tomographic (CT) studies performed at the Istituto Nazionale Tumori of Milan were evaluated. Among the enrolled participants, those who underwent repeat low-dose CT after 3 months and had at least one indeterminate nodule with a volume of more than 60 mm(3) (diameter of 4.8 mm or greater) were considered. Nonsolid, part-solid, and pleural-based nodules were excluded from this study. A descriptive analysis was performed by calculating means and standard deviations of nodule volumes at three assessment times (at baseline and 3 and 12 months later). The volume measurement repeatability was determined by using the approach described by Bland and Altman., Results: One hundred one subjects (70 men, 31 women; mean age, 58 years) with 233 eligible nodules (mean volume, 98.3 mm(3); range, 5-869 mm(3)) were identified. The 95% confidence interval for difference in measured volumes was in the range of +/-27%. About 70% of measurements had a relative difference in nodule volume of less than 10%. No malignant lesions were registered during the follow-up of these subjects., Conclusion: Semiautomatic volumetry is sufficiently accurate and repeatable and may be useful in assisting with lung nodule management in a lung cancer screening program.

Context: Current and former smokers are currently being screened for lung cancer with computed tomography (CT), although there are limited data on the effect screening has on lung cancer outcomes. Randomized controlled trials assessing CT screening are currently under way., Objective: To assess whether screening may increase the frequency of lung cancer diagnosis and lung cancer resection or may reduce the risk of a diagnosis of advanced lung cancer or death from lung cancer., Design, Setting, and Participants: Longitudinal analysis of 3246 asymptomatic current or former smokers screened for lung cancer beginning in 1998 either at 1 of 2 academic medical centers in the United States or an academic medical center in Italy with follow-up for a median of 3.9 years., Intervention: Annual CT scans with comprehensive evaluation and treatment of detected nodules., Main Outcome Measures: Comparison of predicted with observed number of new lung cancer cases, lung cancer resections, advanced lung cancer cases, and deaths from lung cancer., Results: There were 144 individuals diagnosed with lung cancer compared with 44.5 expected cases (relative risk [RR], 3.2; 95% confidence interval [CI], 2.7-3.8; P<.001). There were 109 individuals who had a lung resection compared with 10.9 expected cases (RR, 10.0; 95% CI, 8.2-11.9; P<.001). There was no evidence of a decline in the number of diagnoses of advanced lung cancers (42 individuals compared with 33.4 expected cases) or deaths from lung cancer (38 deaths due to lung cancer observed and 38.8 expected; RR, 1.0; 95% CI, 0.7-1.3; P = .90)., Conclusions: Screening for lung cancer with low-dose CT may increase the rate of lung cancer diagnosis and treatment, but may not meaningfully reduce the risk of advanced lung cancer or death from lung cancer. Until more conclusive data are available, asymptomatic individuals should not be screened outside of clinical research studies that have a reasonable likelihood of further clarifying the potential benefits and risks.