Search

Screening with low-dose helical computed tomography (CT) has been shown to significantly reduce lung cancer mortality but the optimal target population and time interval to subsequent screening are yet to be defined. We developed two models to stratify individual smokers according to risk of developing lung cancer. We first used the number of lung cancers detected at baseline screening CT in the 5,203 asymptomatic participants of the COSMOS trial to recalibrate the Bach model, which we propose using to select smokers for screening. Next, we incorporated lung nodule characteristics and presence of emphysema identified at baseline CT into the Bach model and proposed the resulting multivariable model to predict lung cancer risk in screened smokers after baseline CT. Age and smoking exposure were the main determinants of lung cancer risk. The recalibrated Bach model accurately predicted lung cancers detected during the first year of screening. Presence of nonsolid nodules (RR = 10.1, 95% CI = 5.57–18.5), nodule size more than 8 mm (RR = 9.89, 95% CI = 5.84–16.8), and emphysema (RR = 2.36, 95% CI = 1.59–3.49) at baseline CT were all significant predictors of subsequent lung cancers. Incorporation of these variables into the Bach model increased the predictive value of the multivariable model (c-index = 0.759, internal validation). The recalibrated Bach model seems suitable for selecting the higher risk population for recruitment for large-scale CT screening. The Bach model incorporating CT findings at baseline screening could help defining the time interval to subsequent screening in individual participants. Further studies are necessary to validate these models. Cancer Prev Res; 4(11); 1778–89. ©2011 AACR.

PDF file - 452K

Background A project to assess the existing literature and to benchmark the quality of past guidelines and recommendations on lung cancer screening projects was developed with a particular focus on the assessment of the methodology used in producing them. Methods Each guideline was assessed in the different items and domains with the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument and scored on a seven-point scale. Results Eight guidelines matched the inclusion criteria and were assessed. A multinational collaboration produced three out of five guidelines. The multivariable analysis shows that improved scores of stakeholders' involvement were related to internationally developed guidelines. Improved methodological quality was related to the involvement of scientific societies due to the better rigor of development and editorial independence. Countries with higher expenditure on healthcare produced significantly better guidelines. Conclusions Assessed by the AGREE II criteria, the methodological quality of previous guidelines was relatively low. Nevertheless, the National Comprehensive Cancer Network Guidelines should be recommended as a model for the development of best methodological quality guidelines.

Purpose Low-dose CT screening allows early lung cancer detection, but is affected by frequent false positive results, inter/intra observer variation and uncertain diagnoses of lung nodules. Radiomics-based models have recently been introduced to overcome these issues, but limitations in demonstrating their generalizability on independent datasets are slowing their introduction to clinic. The aim of this study is to evaluate two radiomics-based models to classify malignant pulmonary nodules in low-dose CT screening, and to externally validate them on an independent cohort. The effect of a radiomics features harmonization technique is also investigated to evaluate its impact on the classification of lung nodules from a multicenter data. Methods Pulmonary nodules from two independent cohorts were considered in this study; the first cohort (110 subjects, 113 nodules) was used to train prediction models, and the second cohort (72 nodules) to externally validate them. Literature-based radiomics features were extracted and, after feature selection, used as predictive variables in models for malignancy identification. An in-house prediction model based on artificial neural network (ANN) was implemented and evaluated, along with an alternative model from the literature, based on a support vector machine (SVM) classifier coupled with a least absolute shrinkage and selection operator (LASSO). External validation was performed on the second cohort to evaluate models' generalization ability. Additionally, the impact of the Combat harmonization method was investigated to compensate for multicenter datasets variabilities. A new training of the models based on harmonized features was performed on the first cohort, then tested separately on the harmonized and non-harmonized features of the second cohort. Results Preliminary results showed a good accuracy of the investigated models in distinguishing benign from malignant pulmonary nodules with both sets of radiomics features (i.e., non-harmonized and harmonized). The performance of the models, quantified in terms of Area Under the Curve (AUC), was > 0.89 in the training set and > 0.82 in the external validation set for all the investigated scenarios, outperforming the clinical standard (AUC of 0.76). Slightly higher performance was observed for the SVM-LASSO model than the ANN in the external dataset, although they did not result significantly different. For both harmonized and non-harmonized features, no statistical difference was found between Receiver operating characteristic (ROC) curves related to training and test set for both models. Conclusions Although no significant improvements were observed when applying the Combat harmonization method, both in-house and literature-based models were able to classify lung nodules with good generalization to an independent dataset, thus showing their potential as tools for clinical decision-making in lung cancer screening.

In the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, pathologists can be exposed to infection handling surgical specimens. Guidelines related to safety procedures in the laboratory have been released. However, there is a lack of studies performed on biopsy and surgical resection specimens. Here we report the detection of SARS-CoV-2 in formalin-fixed paraffin-embedded samples from surgical resection of tongue squamous cell carcinoma of a patient who developed COVID-19 postsurgery. RNA of SARS-CoV-2 strain was detected in the tumour and the normal submandibular gland samples using real-time PCR-based assay. No viral RNA was found in metastatic and reactive lymph nodes. We demonstrated that SARS-CoV-2 RNA can be detected in routine histopathological samples even before COVID-19 disease development. These findings may give important information on the possible sites of infection or virus reservoir, and highlight the necessity of proper handling and fixation before sample processing.

Smoking is the main risk factor for lung cancer (LC), which is the leading cause of cancer-related death worldwide. Independent randomized controlled trials, governmental and inter-governmental task forces, and meta-analyses established that LC screening (LCS) with chest low dose computed tomography (LDCT) decreases the mortality of LC in smokers and former smokers, compared to no-screening, especially in women. Accordingly, several Italian initiatives are offering LCS by LDCT and smoking cessation to about 10,000 high-risk subjects, supported by Private or Public Health Institutions, envisaging a possible population-based screening program. Because LDCT is the backbone of LCS, Italian radiologists with LCS expertise are presenting this position paper that encompasses recommendations for LDCT scan protocol and its reading. Moreover, fundamentals for classification of lung nodules and other findings at LDCT test are detailed along with international guidelines, from the European Society of Thoracic Imaging, the British Thoracic Society, and the American College of Radiology, for their reporting and management in LCS. The Italian College of Thoracic Radiologists produced this document to provide the basics for radiologists who plan to set up or to be involved in LCS, thus fostering homogenous evidence-based approach to the LDCT test over the Italian territory and warrant comparison and analyses throughout National and International practices.

Integrating the information coming from biological samples with digital data, such as medical images, has gained prominence with the advent of precision medicine. Research in this field faces an ever-increasing amount of data to manage and, as a consequence, the need to structure these data in a functional and standardized fashion to promote and facilitate cooperation among institutions. Inspired by the Minimum Information About BIobank data Sharing (MIABIS), we propose an extended data model which aims to standardize data collections where both biological and digital samples are involved. In the proposed model, strong emphasis is given to the cause-effect relationships among factors as these are frequently encountered in clinical workflows. To test the data model in a realistic context, we consider the Continuous Observation of SMOking Subjects (COSMOS) dataset as case study, consisting of 10 consecutive years of lung cancer screening and follow-up on more than 5000 subjects. The structure of the COSMOS database, implemented to facilitate the process of data retrieval, is therefore presented along with a description of data that we hope to share in a public repository for lung cancer screening research.

Simple Summary Radiomics aims to extract high-dimensional features from clinical images and associate them to clinical outcomes. These associations may be further investigated with machine learning models; however, guidelines on the most suitable method to support clinical decisions are still missing. To improve the reliability and the accuracy of radiomic features in the prediction of a binary variable in a lung cancer setting, we compared several machine learning classifiers and feature selection methods on simulated data. These account for important characteristics that may vary in real clinical datasets: sample size, outcome balancing and association strength between radiomic features and outcome variables. We were able to suggest the most suitable classifiers for each studied case and to evaluate the impact of method choices. Our work highlights the importance of these choices in radiomic analyses and provides guidelines on how to select the best models for the data at hand. Abstract Radiomics uses high-dimensional sets of imaging features to predict biological characteristics of tumors and clinical outcomes. The choice of the algorithm used to analyze radiomic features and perform predictions has a high impact on the results, thus the identification of adequate machine learning methods for radiomic applications is crucial. In this study we aim to identify suitable approaches of analysis for radiomic-based binary predictions, according to sample size, outcome balancing and the features–outcome association strength. Simulated data were obtained reproducing the correlation structure among 168 radiomic features extracted from Computed Tomography images of 270 Non-Small-Cell Lung Cancer (NSCLC) patients and the associated to lymph node status. Performances of six classifiers combined with six feature selection (FS) methods were assessed on the simulated data using AUC (Area Under the Receiver Operating Characteristics Curves), sensitivity, and specificity. For all the FS methods and regardless of the association strength, the tree-based classifiers Random Forest and Extreme Gradient Boosting obtained good performances (AUC ≥ 0.73), showing the best trade-off between sensitivity and specificity. On small samples, performances were generally lower than in large–medium samples and with larger variations. FS methods generally did not improve performances. Thus, in radiomic studies, we suggest evaluating the choice of FS and classifiers, considering specific sample size, balancing, and association strength.

The aim of this study is to present the results of the Italian survey on the management of pulmonary nodules incidentally identified at computed tomography (CT). An online electronic survey, consisting of 23 multiple-choice questions, was created using the SurveyMonkey web-based tool. The questionnaire was developed by the Board of the Italian College of Chest Radiology of the Italian Society of Medical and Interventional Radiology (SIRM) and by an experienced group of Italian Academic Chest Radiologists. The link to the online electronic survey was submitted by email to all the SIRM members. A total of 767 radiologists, corresponding to 7.5% of all the SIRM members, participated in the online survey. The majority of participants (92%) routinely describe the attenuation of pulmonary nodules in the report, and 84.1% recommend the further follow-up, with 92.7% of respondents taking CT nodule morphological features into consideration. The 57.7% of participants adhere to the Fleischner Society guidelines for the management of incidental pulmonary nodules. However, 56.6% and 75.6% of respondents have a more cautious approach than that recommended by the guidelines and tend to use a shorter follow-up for both solid and ground-glass nodules, respectively. Finally, 94.5% of participants favor congresses and refresher courses dedicated to insights on lung nodule diagnosis and management. This survey demonstrates that the management of pulmonary nodules incidentally detected on CT is still complex and controversial. The majority of SIRM members express a need for an update on this topic.

Simple Summary Tyrosine kinase inhibitors (TKIs) are the treatment of choice for BCR-ABL1-positive chronic myeloid leukemia (CML). Dasatinib is a second generation TKI frequently associated with pleural effusion in up to 33% of patients. Here, we describe two cases of HHV8-negative large B cell effusion-based lymphoma (EBL) confined to the pleura, incidentally, diagnosed in patients presenting with dasatinib-related pleural effusion. One patient is alive and is in remission at 17 months from diagnosis, while unfortunately the other patient died of progressive disease and novel coronavirus disease 2019 (COVID-19)-related pneumonia 16 months from diagnosis. These cases of large B cell EBL in patients receiving dasatinib raise concern about a possible association and we strongly recommend cytological investigation in patients with persistent/relapsing pleural effusion under dasatinib to improve the knowledge about this entity. Abstract Tyrosine kinase inhibitors (TKIs) are the treatment of choice for BCR-ABL1-positive chronic myeloid leukemia (CML). Although TKIs have substantially improved prognosis of CML patients, their use is not free of adverse effects. Dasatinib is a second generation TKI frequently associated with pleural effusion in up to 33% of patients. This results in symptoms as dyspnea, cough and chest pain that may require therapy discontinuation. In the present report, we describe two exceptional cases of HHV8-negative large B-cell effusion-based lymphoma (EBL) confined to the pleura, incidentally, diagnosed in patients presenting with dasatinib-related pleural effusion. One patient (case 1) is alive and is in remission at 17 months from large B-cell EBL diagnosis while unfortunately the other patient (case 2) died of progressive disease and COVID-19 pneumonia 16 months from large B-cell EBL diagnosis. These cases raise concern about a possible association between large B-cell EBL and dasatinib, and the different clinical outcome of the two cases poses a challenge in treatment decision. For this reason, we strongly recommend cytological investigation in patients with persistent/relapsing pleural effusion under dasatinib, primarily to validate its possible association with lymphoma development and to improve the knowledge about this entity.

Background: the aim of this paper is to quantify multidisciplinary team meeting (MDT) impact on the decisional clinical pathway of thoracic cancer patients, assessing the modification rate of the initial out-patient evaluation. Methods: the impact of MDT was classified as follows: confirmation: same conclusions as out-patient hypothesis, modification: change of out-patient hypothesis, implementation: definition of a clear clinical track/conclusion for patients that did not receive any clinical hypothesis, further exams required: the findings that emerged in the MDT meeting require further exams. Results: one thousand consecutive patients evaluated at MDT meetings were enrolled. Clinical settings of patients were: early stage lung cancer (17.4%), locally advanced lung cancer (27.4%), stage IV lung cancer (9.8%), mesothelioma (1%), metastases to the lung from other primary tumors (4%), histologically proven or suspected recurrence from previous lung cancer (15%), solitary pulmonary nodule (19.2%), mediastinal tumors (3.4%), other settings (2.8%). Conclusions: MDT meetings impact patient management in oncologic thoracic surgery by modifying the out-patient clinical hypothesis in 10.6% of cases, the clinical settings with the highest decisional modification rates are &ldquo, solitary pulmonary nodule&rdquo, and &ldquo, proven or suspected recurrence&rdquo, with modification rates of 14.6% and 13.3%, respectively.

Purpose Chest imaging modalities play a key role for the management of patient with coronavirus disease (COVID-19). Unfortunately, there is no consensus on the optimal chest imaging approach in the evaluation of patients with COVID-19 pneumonia, and radiology departments tend to use different approaches. Thus, the main objective of this survey was to assess how chest imaging modalities have been used during the different phases of the first COVID-19 wave in Italy, and which diagnostic technique and reporting system would have been preferred based on the experience gained during the pandemic. Material and Methods The questionnaire of the survey consisted of 26 questions. The link to participate in the survey was sent to all members of the Italian Society of Medical and Interventional Radiology (SIRM). Results The survey gathered responses from 716 SIRM members. The most notable result was that the most used and preferred chest imaging modality to assess/exclude/monitor COVID-19 pneumonia during the different phases of the first COVID-19 wave was computed tomography (51.8% to 77.1% of participants). Additionally, while the narrative report was the most used reporting system (55.6% of respondents), one-third of participants would have preferred to utilize structured reporting systems. Conclusion This survey shows that the participants’ responses did not properly align with the imaging guidelines for managing COVID-19 that have been made by several scientific, including SIRM. Therefore, there is a need for continuing education to keep radiologists up to date and aware of the advantages and limitations of the chest imaging modalities and reporting systems.

Reconstruction of work history of subjects exposed to occupational carcinogens might be extremely challenging and provide unreliable results. This study, carried out in Italy from February to November 2014, aimed to explore the validity of an innovative approach to reconstruct the occupational history of workers who have previously been exposed to asbestos combining the administration of structured questionnaire with the use of administrative data. Subjects recruited in this study were enrolled in the cohorts of COSMOS 1 and 2 studies. Participants indicating an exposure to asbestos were contacted and a structured questionnaire was administered to them to verify the validity of the self-reported asbestos exposure. Subsequently, work histories of respondents were investigated using administrative information. The record linkage with social security archives allowed the reassembling of the complete work history of 487 participants. In detail, administrative files allow the retrieval of 98 % of workers declaring not to be exposed, versus 77 % using the questionnaire. Furthermore, the percentage of retrieved cases is not relevant for high risk sectors but it is almost double for industries with probable presence of asbestos. The combined and integrated use of structured questionnaire with administrative data proved effective in accurately identifying subjects who actually had an asbestos exposure. This innovative strategy, being cost-effective and easily adaptable to other carcinogens, could be particularly useful in selecting subjects to recruit in specific screening and control programs for the early diagnosis of occupational cancers.

Purpose With the future goal of defining a large dataset based on low-dose CT with labelled pulmonary lesions for lung cancer screening (LCS) research, the aim of this work is to propose and evaluate into a clinical context a tool for semi-automatic segmentation able to facilitate the process of labels collection from a LCS study (COSMOS, Continuous Observation of SMOking Subjects). Methods Considering a preliminary set of manual annotations, a segmentation model based on a 2D-Unet was trained from scratch. Contour quality of the final 2D-Unet was assessed on an internal test set of manual annotations and on a subset of the public available LIDC dataset used as external test set. The tool for semi-automatic segmentation was then designed integrating the tested model into a Graphical User Interface. According to the opinion of two clinical users, the percentage of lesions properly contoured through the tool was quantified (Acceptance Rate, AR). The variability between segmentations derived by the two readers was estimated as mean percentage of difference (MPD) between the two sets of volumes and comparing the likelihood of malignancy derived from Volume Doubling Time (VDT). Results Performance in test sets were found similar (DICE ~ 0.75(0.15)). Accordingly, a good mean AR (80.1%) resulted from the two readers. Variability in terms of MPD was equal to 23.6% while 2.7% was the VDTs percentage of disagreement. Conclusions A semi-automatic segmentation tool was developed and its applicability evaluated into a clinical context demonstrating the efficacy of the tool in facilitating the collection of labelled data.

Lung cancer screening by helical low-dose computed tomography detects nonsolid nodules that may be lung adenocarcinoma precursors. Aspirin’s anti-inflammatory properties make it an attractive target for prevention of multiple cancers, including lung cancer. Therefore, we conducted a phase IIb trial (NCT02169271) to study the efficacy of low-dose aspirin to reduce the size of subsolid lung nodules (SSNs). A total of 98 current or former smokers (67.3% current) undergoing annual low-dose computed tomography screening with persistent SSNs were randomly assigned to receive aspirin 100 mg/day or placebo for 1 year. There was no difference in change in the sum of the longest diameters of target nodules in the placebo and aspirin arm after 12 months of treatment (-0.12 mm [SD = 1.55 mm] and +0.30 mm [SD= 2.54 mm], respectively; 2-sided P = .33 primary endpoint). There were no changes observed in subgroup analyses by individual characteristics or nodule type. One year of low-dose aspirin did not show any effect on lung SSNs. SSNs regression may not be the proper target for aspirin, and/or longer duration may be needed to see SSNs modifications.

A novel coronavirus causing severe acute respiratory syndrome (SARS), named SARS-CoV-2, was identified at the end of 2019. The spread of coronavirus disease 2019 (COVID-19) has progressively expanded from China, involving several countries throughout the world, leading to the classification of the disease as a pandemic by the World Health Organization (WHO). According to published reports, COVID-19 severity and mortality are higher in elderly patients and those with active comorbidities. In particular, lung cancer patients were reported to be at high risk of pulmonary complications related to SARS-CoV2 infection. Therefore, the management of cancer care during the COVID-19 pandemic is a crucial issue, to which national and international oncology organizations have replied with recommendations concerning patients receiving anticancer treatments, delaying follow-up visits and limiting caregiver admission to the hospitals. In this historical moment, medical oncologists are required to consider the possibility to delay active treatment administration based on a case-by-case risk/benefit evaluation. Potential risks associated with COVID-19 infection should be considered, considering tumor histology and natural course, disease setting, clinical conditions, and disease burden, together with the expected benefit, toxicities (e.g., myelosuppression or interstitial lung disease), and response obtained from the planned or ongoing treatment. In this study, we report the results of proactive measures including social media, telemedicine, and telephone triage for screening patients with lung cancer during the COVID-19 outbreak in the European Institute of Oncology (Milan, Italy). Proactive management and containment measures, applied in a structured and daily way, has significantly aided the identification of advance patients with suspected symptoms related to COVID-19, limiting their admission to our cancer center; we have thus been more able to protect other patients from possible contamination and at the same time guarantee to the suspected patients the immediate treatment and evaluation in referral hospitals for COVID-19.

Excisional biopsy of non-palpable rib tumors still represents a challenge for thoracic surgeons: in fact primary or metastatic tumors originating from a rib can be difficult to localize topographically at the time of excisional biopsy, thus potentially resulting in inappropriately placed skin incisions, incomplete tumor excision or even in wrong rib or segment resection (1).

Lung cancer screening (LCS) with low-dose computed tomography (LDCT) was demonstrated in the National Lung Screening Trial (NLST) to reduce mortality from the disease. European mortality data has recently become available from the Nelson randomised controlled trial, which confirmed lung cancer mortality reductions by 26% in men and 39–61% in women. Recent studies in Europe and the USA also showed positive results in screening workers exposed to asbestos. All European experts attending the “Initiative for European Lung Screening (IELS)”—a large international group of physicians and other experts concerned with lung cancer—agreed that LDCT-LCS should be implemented in Europe. However, the economic impact of LDCT-LCS and guidelines for its effective and safe implementation still need to be formulated. To this purpose, the IELS was asked to prepare recommendations to implement LCS and examine outstanding issues. A subgroup carried out a comprehensive literature review on LDCT-LCS and presented findings at a meeting held in Milan in November 2018. The present recommendations reflect that consensus was reached.

Squamous cell carcinoma and adenocarcinoma are the most common types of lung cancer. The knowledge of the preferential pathways of diffusion, with particular regard to the assessment of local invasion and lymph node involvement, is challenging but mandatory for an accurate staging. This is more important than ever in the era of precision medicine, which is characterized by promising and personalized treatments for lung cancer.

Malignant pleural mesothelioma usually arises from the pleural surface and progressively encases the lungs. Pulmonary involvement generally occurs at an advanced stage, while intraparenchymal nodules, in the absence of pleural lesions, constitute a less frequent presentation. We describe the case of a patient with multiple bilateral pulmonary nodules, mediastinal lymphadenopathies and left pleural effusion in the absence of pleural lesions, simulating advanced stage lung cancer. Thoracoscopic inspection did not detect any lesions. Pathological examination on one pulmonary nodule revealed malignant pleural mesothelioma. Despite its rarity, intraparenchymal malignant pleural mesothelioma should always be taken into account, when lung nodules are present, to prevent misdiagnosis and avoid delayed treatment. ispartof: ADVANCES IN RESPIRATORY MEDICINE vol:87 issue:6 pages:265-267 ispartof: location:Switzerland status: published

Objectives Smoking is the main risk factor for lung cancer, but environmental and occupational exposure to carcinogens also increase lung cancer risk. We assessed whether extending low-dose computed tomography (LDCT) screening to persons with occupational exposure to asbestos may be an effective way reducing lung cancer mortality. Materials and methods We conducted a nested case-control study within the COSMOS screening program, assessing past asbestos exposure with a questionnaire. LDCT scans of asbestos-exposed participants were reviewed to assess the presence of pulmonary, interstitial and pleural alterations in comparison to matched unexposed controls. We also performed an exhaustive review, with meta-analysis, of the literature on LDCT screening in asbestos-exposed persons. Results Exposure to asbestos, initially self-reported by 9.8% of COSMOS participants, was confirmed in 216 of 544 assessable cases, corresponding to 2.6% of the screened population. LDCT of asbestos-exposed persons had significantly more pleural plaques, diaphragmatic pleural thickening and pleural calcifications, but similar frequency of parenchymal and interstitial alterations to unexposed persons. From 16 papers, including this study, overall lung cancer detection rates at baseline were 0.81% (95% CI 0.50–1.19) in asbestos-exposed persons, 0.94% (95% CI 0.47–1.53) in asbestos-exposed smokers (12 studies), and 0.11% (95% CI 0.00-0.43) in asbestos-exposed non-smokers (9 studies). Conclusion Persons occupationally exposed to asbestos should be monitored to gather more information about risks. Although LDCT screening is effective in the early detection lung cancer in asbestos-exposed smokers, our data suggest that screening of asbestos-exposed persons with no additional risk factors for cancer does is not viable due to the low detection rate.

The typical presentation of early stage lung cancers on low-dose CT screening are non-calcified pulmonary nodules. However, there is a wide spectrum of unusual focal abnormalities that can be early presentations of lung cancer. These abnormalities include, for example, cancers associated with ‘cystic airspaces’ or scar-like cancers. The detection of lung cancer with low-dose CT can be affected by the absence of intravenous contrast medium. As a consequence, endobronchial and central lesions can be difficult to recognize, raising the potential for missed cancers. Focal lesions arising within pre-existing lung disease, such as lung fibrosis or apical scars, can also be early lung cancer manifestations and deserve particular consideration as recognition of these lesions may be hindered by the underlying disease. Furthermore, the unpredictable growth rate of lung cancer, which ranges from indolent to aggressive cancers, necessitates attention to the wide spectrum of progression in lung cancer appearance on serial low-dose CT scans. In this pictorial review we discuss the spectrum of early lung cancer presentation in low-dose CT screening, highlighting typical as well as unusual radiological features and the varied growth rates of early lung cancer. Teaching Points • There is a wide spectrum of early presentations of lung cancer on LDCT. • Low radiation dose and the absence of contrast medium injection can affect lung cancer detection. • Lung cancer growth shows various behaviours, ranging from indolent to aggressive cancers. • Familiarity with LDCT technique can improve CT screening effectiveness and avoid missed diagnosis.

Results from retrospective studies indicate that selecting individuals for low-dose CT lung cancer screening on the basis of a highly predictive risk model is superior to using criteria similar to those used in the National Lung Screening Trial (NLST; age, pack-year, and smoking quit-time). We designed the Pan-Canadian Early Detection of Lung Cancer (PanCan) study to assess the efficacy of a risk prediction model to select candidates for lung cancer screening, with the aim of determining whether this approach could better detect patients with early, potentially curable, lung cancer.We did this single-arm, prospective study in eight centres across Canada. We recruited participants aged 50-75 years, who had smoked at some point in their life (ever-smokers), and who did not have a self-reported history of lung cancer. Participants had at least a 2% 6-year risk of lung cancer as estimated by the PanCan model, a precursor to the validated PLCOm2012 model. Risk variables in the model were age, smoking duration, pack-years, family history of lung cancer, education level, body-mass index, chest x-ray in the past 3 years, and history of chronic obstructive pulmonary disease. Individuals were screened with low-dose CT at baseline (T0), and at 1 (T1) and 4 (T4) years post-baseline. The primary outcome of the study was incidence of lung cancer. This study is registered with ClinicalTrials.gov, number NCT00751660.7059 queries came into the study coordinating centre and were screened for PanCan risk. 15 were duplicates, so 7044 participants were considered for enrolment. Between Sept 24, 2008, and Dec 17, 2010, we recruited and enrolled 2537 eligible ever-smokers. After a median follow-up of 5·5 years (IQR 3·2-6·1), 172 lung cancers were diagnosed in 164 individuals (cumulative incidence 0·065 [95% CI 0·055-0·075], incidence rate 138·1 per 10 000 person-years [117·8-160·9]). There were ten interval lung cancers (6% of lung cancers and 6% of individuals with cancer): one diagnosed between T0 and T1, and nine between T1 and T4. Cumulative incidence was significantly higher than that observed in NLST (4·0%; p0·0001). Compared with 593 (57%) of 1040 lung cancers observed in NLST, 133 (77%) of 172 lung cancers in the PanCan Study were early stage (I or II; p0·0001).The PanCan model was effective in identifying individuals who were subsequently diagnosed with early, potentially curable, lung cancer. The incidence of cancers detected and the proportion of early stage cancers in the screened population was higher than observed in previous studies. This approach should be considered for adoption in lung cancer screening programmes.Terry Fox Research Institute and Canadian Partnership Against Cancer.

OBJECTIVE We sought to characterise circulating and tissue tumour biomarkers of patients who developed early-stage non-small cell lung cancer (NSCLC) during long-term follow-up of a chemoprevention trial (NCT00321893). MATERIALS AND METHODS Blood and sputum samples were collected from 202 high-risk asymptomatic individuals with CT-detected stable lung nodules. Real-time PCR was performed on plasma to quantify free circulating DNA. Baseline serum was investigated with a previously validated test based on 13 circulating miRNAs (miR-Test). Promoter methylation status of p16, RASSF1a and RARβ2 and telomerase activity were assessed in sputum samples. DNA was extracted from each tumour developed during follow-up and subjected to a mutation survey using the LungCarta panel on the Sequenom MassARRAY platform. RESULTS During follow-up (9 years) six individuals underwent surgery for stage I NSCLC with a median time of disease onset of 20.5 months. MiR-Test scores were positive (range: 0.14-7.24) in four out of six baseline pre-disease onset sera. No association was identified between free circulating DNA or sputum biomarkers and disease onset. All tumours harboured at least one somatic mutation in well-known cancer genes, including KRAS (n = 4), BRAF (n = 1), and TP53 (n = 3). CONCLUSION Circulating miRNA tests may represent valuable tools to detect clinically-silent tumours. Early-stage lung adenocarcinomas harbour recurrent genetic events similar to those described in advanced-stage NSCLCs.

Background To assess whether intake of selected foods and food groups and adherence to a Mediterranean diet are associated with lung cancer risk in heavy smokers. Patients and methods In the context of a lung cancer screening programme, we invited asymptomatic volunteers, aged 50 years or more, current smokers or recent quitters, who had smoked at least 20 pack-years, to undergo annual low-dose computed tomography. We assessed participants' diet at baseline using a self-administered food frequency questionnaire and calculated their average daily food intake using an ad hoc computer program and determined their alternate Mediterranean diet (aMED) score. We used Cox proportional hazards regression to assess the association between selected food items, beverages and the aMED score and lung cancer risk. Results During a mean screening period of 5.7 years, 178 of 4336 participants were diagnosed with lung cancer. At multivariable analysis, red meat consumption was associated with an increased risk of lung cancer [hazard ratio (HR) Q4 versus Q1, 1.73; 95% confidence interval (CI) 1.15–2.61; P-value for trend 0.002], while tea consumption (HR for one or more cup/day versus none, 0.56; 95% CI 0.31–0.99; P-value for trend 0.04) and adherence to a Mediterranean diet (HR for aMED≥8 versus ≤1, 0.10; 95% CI 0.01–0.77) were significantly associated with reduced lung cancer risk. Conclusions Among heavy smokers, high red meat consumption and low adherence to a Mediterranean diet are associated with increased risk of lung cancer.

The National Lung Cancer Screening Trial has recently demonstrated that screening of high-risk populations with the use of low-dose computed tomography (LDCT) reduces lung cancer mortality[1]. Based on this encouraging result, the National Comprehensive Cancer Network guidelines recommended LDCT for selected patients at high risk of lung cancer[2]. This suggests that an increasing number of CT screening examinations will be performed. The LDCT technique is relatively simple but some CT parameters are important and should be accurately defined in order to achieve good diagnostic quality and minimize the delivered dose. In addition, LDCT examinations are not as easy to read as they may initially appear; different approaches and tools are available for nodule detection and measurement. Moreover, the management of positive results can be a complex process and can differ significantly from routine clinical practice. Therefore this paper deals with the LDCT technique, reading methods and interpretation in lung cancer screening, particularly for those radiologists who have little experience of the technique.

We have read with interest the editorial of Mascalchi and colleagues, on our study “ Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis ” (1).

To evaluate the feasibility and performance of ultrasound-guided transcutaneous tru-cut biopsy (USGTCB) in selected patients (with stenosis of airways or difficult intubation or contraindication to general anaesthesia) with untreated or previously treated suspicious laryngo-hypopharyngeal masses.Biopsies were performed with a free-hand technique by a single radiologist. Thirty-six USGTCBs were scheduled in 34 patients (24 males, 10 females; age range 47-95 years). Two USGTCBs were not performed, as lesions were not detectable: therefore, 16 USGTCBs were performed for an untreated mass suspicious for malignancy and 18 were performed for a mass suspicious for recurrence after radiotherapy alone, or associated with endoscopic laser surgery or chemotherapy.USGTCB diagnosed 25 squamous cell carcinomas (73.5%) and nine benign lesions (26.5%); no false positives and two false negatives were reported, both in patients previously treated with radiotherapy. The sensitivity, specificity, positive and negative predictive value of the technique was 92.5%, 100%, 100% and 77.7% respectively, with no major complications.Although biopsy under microlaryngoscopy remains the "gold-standard" technique, USGTCB is feasible, carries the advantages of avoiding general anaesthesia, is suitable for outpatients and is cost-effective. If applied to selected patients, it could be considered for the histological diagnosis of both primary and recurrent laryngo-hypopharyngeal masses.

We have little knowledge about the evolution of emphysema, and relatively little is understood about its evolution in relation to smoking habits. This study aims to assess the evolution of emphysema in asymptomatic current and former smokers over 2 years and to investigate the association with subjects’ characteristics. The study was approved by our Ethics Committee and all participants provided written informed consent. We measured emphysema by automatic low-dose computed tomography densitometry in 254 current and 282 former smokers enrolled in a lung-cancer screening. The measures were repeated after 2 years. The association between subjects’ characteristics, smoking habits and emphysema were assessed by chi-squared and Wilcoxon tests. Univariate and multivariate odds ratios (OR) with 95% confidence intervals (CI) were calculated for the risk of emphysema worsening according to subjects’ characteristics. We assessed the trend of increasing risk of emphysema progression by smoking habits using the Mantel-Haenszel chi-squared test. The median percentage increase in emphysema over a 2-year period was significantly higher in current than in former smokers (OR 1.8; 95% CI 1.3–2.6; p

The objectives of our study were to evaluate the in vivo reproducibility of automated volume calculations of small lung nodules with both low-dose and standard-dose CT and to assess whether repeatability within each technique varies according to the diameter, site, or morphology of the nodule or to percentage of emphysema.Sixty-six subjects with 83 solid pulmonary nodules between 5 and 10 mm in diameter were enrolled in this prospective study. Four consecutive MDCT data sets, two low dose and two standard dose, were obtained for each nodule on separate breath-holds during the same session. The volume of each nodule was calculated by automated software. Repeatability was evaluated by Bland-Altman's approach and the coefficient of repeatability. Associations of the percentage of volume variation between two measurements with nodule diameter, emphysema percentage, nodule site, and nodule morphology were assessed by Spearman's correlation coefficient and the Kruskal-Wallis test. A p value of0.05 was considered statistically significant.The range of variation of the volumes of pulmonary nodules between two subsequent measurements was -38% +/- 60% for low-dose CT and -27% +/- 40% for standard-dose CT. No significant statistical association was found between variation in volume measurements and nodule site, nodule diameter, nodule morphology, or emphysema percentage by semiautomated calculation of lung density.Automated volume calculations of small pulmonary nodules can significantly differ between two subsequent breath-holds with both low-dose and standard-dose CT techniques; in clinical practice we recommend that a volume variation of greater than 30% for nodules between 5 and 10 mm should be confirmed by follow-up CT to be sure that a nodule is actually growing.

BACKGROUND The identification of circulating microRNAs (miRNAs) in the blood has been recently exploited for the development of minimally invasive tests for the early detection of cancer. Nevertheless, the clinical transferability of such tests is uncertain due to still-insufficient standardization and optimization of methods to detect circulating miRNAs in the clinical setting. METHODS We performed a series of tests to optimize the quantification of serum miRNAs that compose the miR-Test, a signature for lung cancer early detection, and systematically analyzed variables that could affect the performance of the test. We took advantage of a large-scale (>1000 samples) validation study of the miR-Test that we recently published, to evaluate, in clinical samples, the effects of analytical and preanalytical variables on the quantification of circulating miRNAs and the clinical output of the signature (risk score). RESULTS We developed a streamlined and standardized pipeline for the processing of clinical serum samples that allows the isolation and analysis of circulating miRNAs by quantitative reverse-transcription PCR, with a throughput compatible with screening trials. The major source of analytical variation came from RNA isolation from serum, which could be corrected by use of external (spike-in) or endogenous miRNAs as a reference for normalization. We also introduced standard operating procedures and QC steps to check for unspecific fluctuations that arise from the lack of standardized criteria in the collection or handling of the samples (preanalytical factors). CONCLUSIONS We propose our methodology as a reference for the development of clinical-grade blood tests on the basis of miRNA detection.

Lung cancer is the leading cause of cancer death worldwide. Low-dose computed tomography screening (LDCT) was recently shown to anticipate the time of diagnosis, thus reducing lung cancer mortality. However, concerns persist about the feasibility and costs of large-scale LDCT programs. Such concerns may be addressed by clearly defining the target "high-risk" population that needs to be screened by LDCT. We recently identified a serum microRNA signature (the miR-Test) that could identify the optimal target population. Here, we performed a large-scale validation study of the miR-Test in high-risk individuals (n = 1115) enrolled in the Continuous Observation of Smoking Subjects (COSMOS) lung cancer screening program. The overall accuracy, sensitivity, and specificity of the miR-Test are 74.9% (95% confidence interval [CI] = 72.2% to 77.6%), 77.8% (95% CI = 64.2% to 91.4%), and 74.8% (95% CI = 72.1% to 77.5%), respectively; the area under the curve is 0.85 (95% CI = 0.78 to 0.92). These results argue that the miR-Test might represent a useful tool for lung cancer screening in high-risk individuals.

Low-dose computed tomography (CT) screening for lung cancer can reduce lung cancer mortality, but overdiagnosis, false positives and invasive procedures for benign nodules are worrying. We evaluated the utility of positron emission tomography (PET)-CT in characterising indeterminate screening-detected lung nodules. 383 nodules, examined by PET-CT over the first 6 years of the COSMOS (Continuous Observation of Smoking Subjects) study to diagnose primary lung cancer, were reviewed and compared with pathological findings (surgically-treated patients) or follow-up (negative CT for ⩾2 years, considered negative); 196 nodules were malignant. The sensitivity, specificity and accuracy of PET-CT for differentially diagnosing malignant nodules were, respectively, 64%, 89% and 76% overall, and 82%, 92% and 88% for baseline-detected nodules. Performance was lower for nodules found at repeat annual scans, with sensitivity ranging from 22% for nonsolid to 79% for solid nodules (p=0.0001). Sensitivity (87%) and specificity (73%) were high for nodules ⩾15 mm, better (sensitivity 98%) for solid nodules ⩾15 mm. PET-CT was highly sensitive for the differential diagnosis of indeterminate nodules detected at baseline, nodules ⩾15 mm and solid nodules. Sensitivity was low for sub-solid nodules and nodules discovered after baseline for which other methods, e.g. volume doubling time, should be used. PET-CT is good at differentially diagnosing large, solid and baseline-detected lung nodules in the screening setting

To assess the association between CT features and EGFR, ALK, KRAS mutations in non-small cell lung cancer.Patients undergoing chest CT and testing for the above gene mutations were included. Qualitative evaluation of CTs included: lobe; lesion diameter; shape; margins; ground-glass opacity; density; cavitation; air bronchogram; pleural thickening; intratumoral necrosis; nodules in tumour lobe; nodules in non-tumour lobes; pleural retraction; location; calcifications; emphysema; fibrosis; pleural contact; pleural effusion. Statistical analysis was performed to assess association of features with each gene mutation. ROC curves for gene mutations were drawn; the corresponding area under the curve was calculated. P-values0.05 were considered significant.Of 285 patients, 60/280 (21.43 %) were positive for EGFR mutation; 31/270 (11.48 %) for ALK rearrangement; 64/240 (26.67 %) for KRAS mutation. EGFR mutation was associated with air bronchogram, pleural retraction, females, non-smokers, small lesion size, and absence of fibrosis. ALK rearrangements were associated with age and pleural effusion. KRAS mutation was associated with round shape, nodules in non-tumour lobes, and smoking.This study disclosed associations between CT features and alterations of EGFR (air bronchogram, pleural retraction, small lesion size, absence of fibrosis), ALK (pleural effusion) and KRAS (round lesion shape, nodules in non-tumour lobes).Air bronchogram, pleural retraction, small size relate to EGFR mutation in NSCLC. Pleural effusion and younger age relate to ALK mutation. Round lesion shape, nodules in non-tumour lobes relate to KRAS mutation.

ObjectiveTo estimate the cumulative radiation exposure and lifetime attributable risk of cancer incidence associated with lung cancer screening using annual low dose computed tomography (CT).DesignSecondary analysis of data from a lung cancer screening trial and risk-benefit analysis.Setting10 year, non-randomised, single centre, low dose CT, lung cancer screening trial (COSMOS study) which took place in Milan, Italy in 2004-15 (enrolment in 2004-05). Secondary analysis took place in 2015-16.ParticipantsHigh risk asymptomatic smokers aged 50 and older, who were current or former smokers (≥20 pack years), and had no history of cancer in the previous five years.Main outcome measuresCumulative radiation exposure from low dose CT and positron emission tomography (PET) CT scans, calculated by dosimetry software; and lifetime attributable risk of cancer incidence, calculated from the Biological Effects of Ionizing Radiation VII (BEIR VII) report.ResultsOver 10 years, 5203 participants (3439 men, 1764 women) underwent 42 228 low dose CT and 635 PET CT scans. The median cumulative effective dose at the 10th year of screening was 9.3 mSv for men and 13.0 mSv for women. According to participants' age and sex, the lifetime attributable risk of lung cancer and major cancers after 10 years of CT screening ranged from 5.5 to 1.4 per 10 000 people screened, and from 8.1 to 2.6 per 10 000 people screened, respectively. In women aged 50-54, the lifetime attributable risk of lung cancer and major cancers was about fourfold and threefold higher than for men aged 65 and older, respectively. The numbers of lung cancer and major cancer cases induced by 10 years of screening in our cohort were 1.5 and 2.4, respectively, which corresponded to an additional risk of induced major cancers of 0.05% (2.4/5203). 259 lung cancers were diagnosed in 10 years of screening; one radiation induced major cancer would be expected for every 108 (259/2.4) lung cancers detected through screening.ConclusionRadiation exposure and cancer risk from low dose CT screening for lung cancer, even if non-negligible, can be considered acceptable in light of the substantial mortality reduction associated with screening.

To test whether the inflammatory potential of diet, as measured using the dietary inflammatory index (DII), is associated with risk of lung cancer or other respiratory conditions and to compare results obtained with those based on the aMED score, an established dietary index that measures adherence to the traditional Mediterranean diet.In 4336 heavy smokers enrolled in a prospective, non-randomized lung cancer screening program, we measured participants' diets at baseline using a self-administered food frequency questionnaire from which dietary scores were calculated. Cox proportional hazards and logistic regression models were used to assess association between the dietary indices and lung cancer diagnosed during annual screening, and other respiratory outcomes that were recorded at baseline, respectively.In multivariable analysis, adjusted for baseline lung cancer risk (estimated from age, sex, smoking history, and asbestos exposure) and total energy, both DII and aMED scores were associated with dyspnoea (p trend = 0.046 and 0.02, respectively) and radiological evidence of emphysema (p trend = 0.0002 and 0.02). After mutual adjustment of the two dietary scores, only the association between DII and radiological evidence of emphysema (Q4 vs. Q1, OR 1.30, 95 % CI 1.01-1.67, p trend = 0.012) remained statistically significant. At univariate analysis, both DII and aMED were associated with lung cancer risk, but in fully adjusted multivariate analysis, only the association with aMED remained statistically significant (p trend = 0.04).Among heavy smokers, a pro-inflammatory diet, as indicated by increasing DII score, is associated with dyspnoea and radiological evidence of emphysema. A traditional Mediterranean diet, which is associated with a lower DII, may lower lung cancer risk.

The authors sought to evaluate the effect of model-based iterative reconstruction (MBIR) on the sensitivity of ground-glass nodule (GGN) detection at different dose levels.Fifty-four artificial GGN were randomly divided into three sets, each positioned in an anthropomorphic phantom. The three sets were evaluated on standard-dose (SD, 350 mA), low-dose (LD, 35 mA) and ultra-low-dose (ULD, 10 mA) CT scans (100 kV, 64 × 0.625 mm, 0.5 s), and each scan was reconstructed twice with filtered back projection (FBP) and MBIR. Three radiologists independently evaluated the scans for GGN presence and size. SD + FBP was considered the reference standard. A region of interest (ROI) was used to calculate signal-to-noise ratio (SNR) and contrast-to-noise ratio normalised to dose (CNRD). McNemar's test, Bland-Altman analysis and t test were used for statistical assessment (p 0.05).The mean diameter of the 54 GGNs was 9.2 mm (range 3.7-17.3 mm). For the three readers, no statistically significant differences were observed in the sensitivity of GGN detection between LD + MBIR, ULD + MBIR and SD + FBP (p 0.05). Bland-Altman analysis showed a good reader agreement (±1.5 mm) for GGN size between SD + FBP and ULD + MBIR. For low dose and ultra-low dose, the SNR and CNRD were significantly higher with MBIR (p 0.0001). The effective dose was 97.1 % lower with ultra-low dose (0.15 mSv) than standard dose (5.15 mSv).The detection of GGN with MBIR at low-dose and ultra-low-dose CT does not differ significantly from standard-dose CT with FBP in an anthropomorphic phantom.

Computed Tomographic (CT) screening for lung cancer remains controversial, although the National Lung Screening Trial (NLST) found that low dose CT (LDCT) reduced lung cancer mortality by about 20% [1], the high rate of indeterminate and false positive lung nodules was worrying. The diagnostic work-up of CT nodules considers size (diameter or volume), characteristics (density, morphology, homogeneity) and volume doubling time (VDT), but several studies have investigated the ability of positron emission tomography (PET) to characterize nodules, although its role in diagnostic algorithms for screening-detected nodules has not been defined. The first PET study with [18F]fluorodeoxyglucose to characterize indeterminate nodules outside screening was published in 2001 [2]. In a previous study on PET-CT at baseline screening, we found an overall sensitivity of 88% for diagnosing malignancy, while for solid nodules >10 mm, sensitivity was 100%, suggesting PET-CT as an alternative to invasive procedures in the screening setting [3]. When assessing the ability of PET-CT to diagnose indeterminate nodules detected during the subsequent years of the screening and analyzing 383 PET-CT examinations performed over 6 study years of screening, the sensitivity, specificity and accuracy of visually evaluated PET-CT, in distinguishing benign from malignant nodules, were 64%, 89% and 76% respectively. PET performance varied with nodule diameter (accuracy increased from 70% for nodules

Introduction: Low-dose computed tomography (LD-CT) screening can reduce lung cancer mortality; however, it is essential to improve nodule management protocols. We analyze the performance of the diagnostic protocol of the Continuous Observation of SMOking Subjects single-center screening study, after long-term follow-up. Methods: Between 2004 and 2005, 5203 asymptomatic high-risk individuals (≥20 pack-years, aged 50 years or older) were enrolled to undergo annual LD-CT for 5 years. Nodules 5 mm or smaller underwent repeat LD-CT a year later. Nodules larger than 5.0 mm and 8.0 mm or smaller received LD-CT 3 to 6 months later. Nodules larger than 8.0 mm or growing underwent CT-positron emission tomography. True positives were any stage prevalent lung cancer, progressing nodules diagnosed at stage 1, localized multifocal cancer, or new nodules diagnosed at any stage. False negatives were progressing nodules diagnosed at stage >1. False positives were benign nodules resected surgically. Results: Compliance was 79% over 5 years; 175 primary lung cancers were detected (0.76% per year), 136 (77.7%) were N0M0 and three were interval cancers. Eleven second primary lung cancers were diagnosed. Resectability was 87.4%; postoperative mortality 0.6%. Recall was 6.4% overall, 10.1% at baseline. False negatives were 14 of 175 (8%). Protocol sensitivity was 158 of 175 (90%); specificity 4994 of 5028 (99.4%); positive predictive value was 158 of 187 (84.5%); and negative predictive value was 4994 of 5016 (99.7%). Twenty-nine of 204 (14.2%) benign lesions were diagnosed surgically. Five-year overall and cancer-specific survival were 78% (95% confidence interval, 72–84) and 82% (95% confidence interval, 76%–88%) respectively. Conclusions: The performance of the CT protocol was satisfactory with an acceptable number of benign lesions biopsied surgically, low recall rate, and good oncological outcomes. However, interval and advanced cancers, and misdiagnoses, need to be reduced, perhaps by risk modeling and use of serum markers.

Introduction It is unclear how long low-dose computed tomographic (LDCT) screening should continue in populations at high risk of lung cancer. We assessed outcomes and the predictive ability of the COSMOS prediction model in volunteers screened for 10 years. Materials and methods Smokers and former smokers (>20 pack-years), >50 years, were enrolled over one year (2000–2001), receiving annual LDCT for 10 years. The frequency of screening-detected lung cancers was compared with COSMOS and Bach risk model estimates. Results Among 1035 recruited volunteers (71% men, mean age 58 years) compliance was 65% at study end. Seventy-one (6.95%) lung cancers were diagnosed, 12 at baseline. Disease stage was: IA in 48 (66.6%); IB in 6; IIA in 5; IIB in 2; IIIA in 5; IIIB in 1; IV in 5; and limited small cell cancer in 3. Five- and ten-year survival were 64% and 57%, respectively, 84% and 65% for stage I. Ten (12.1%) received surgery for a benign lesion. The number of lung cancers detected during the first two screening rounds was close to that predicted by the COSMOS model, while the Bach model accurately predicted frequency from the third year on. Conclusions Neither cancer frequency nor proportion at stage I decreased over 10 years, indicating that screening should not be discontinued. Most cancers were early stage, and overall survival was high. Only a limited number of invasive procedures for benign disease were performed. The Bach model – designed to predict symptomatic cancers – accurately predicted cancer frequency from the third year, suggesting that overdiagnosis is a minor problem in lung cancer screening. The COSMOS model – designed to estimate screening-detected lung cancers – accurately predicted cancer frequency at baseline and second screening round.