Computed Tomography Screening For Lung Cancer Research Articles

Serum lipid profile discriminates patients with early lung cancer from healthy controls

ObjectivesThe role of a low-dose computed tomography lung cancer screening remains a matter of controversy due to its low specificity and high costs. Screening complementation with blood-based biomarkers may allow a more efficient pre-selection of candidates for imaging tests or discrimination between benign and malignant chest abnormalities detected by low-dose computed tomography (LD-CT). We searched for a molecular signature based on a serum lipid profile distinguishing individuals with early lung cancer from healthy participants of the lung cancer screening program. Materials and methodsBlood samples were collected from 100 patients with early stage lung cancer (including 31 screen-detected cases) and from a matched group of 300 healthy participants of the lung cancer screening program. MALDI-ToF mass spectrometry was used to analyze the molecular profile of lipid-containing organic extract of serum samples in the 320–1000Da range. ResultsSeveral components of the serum lipidome were detected, with abundances discriminating patients with early lung cancer from high-risk smokers. An effective cancer classifier was built with an area under the curve of 0.88. Corresponding negative predictive value was 98% and a positive predictive value was 42% when the classifier was tuned for maximum negative predictive value. Furthermore, the downregulation of a few lysophosphatidylcholines (LPC18:2, LPC18:1 and LPC18:0) in samples from cancer patients was confirmed using a complementary LC–MS approach (a reasonable cancer discrimination was possible based on LPC18:2 alone with 25% total weighted error of classification). ConclusionsLipid-based serum signature showed potential usefulness in discriminating early lung cancer patients from healthy individuals.

Progress in preoperative localization for small pulmonary nodules

Video-assisted thoracic surgery (VATS) is associated with reduced postoperative pain, shorter hospital stay, and fewer perioperative complications than thoracotomy, and its application in surgery for both primary lung cancer and metastatic lung tumors is increasing. Lung cancer screening with annual low-dose computed tomography (CT) has reduced morality from lung cancer, as compared with chest radiography (1), while 24.2% of screened cases were positive in the low-dose CT group. The current guidelines recommend surgical biopsy if a lung nodule is ≥8 mm in size and the probability of malignancy is high (2). Furthermore, VATS wedge resection is recommended to obtain diagnosis for an indeterminate nodule. The increased use of CT screening for lung cancer will increase the number of cases where VATS is necessary for small pulmonary nodules.

Model concept of the health economic evaluation of low-dose CT lung cancer screening in Hungary

Lung cancer is a rapidly progressing, often life-threatening disease that constitutes a huge societal burden. Because of the scarce resources of the Hungarian health care system, the cost-effectiveness of introducing low-dose computed tomography screening is a relevant health policy matter. The aim of this study is to design a model concept for assessing the cost-effectiveness of low-dose computed tomography lung cancer screening in Hungary, and to define the required steps for performing the analysis. A targeted literature review was conducted to identify and synthesize the evidence on efficacy and effectiveness of screening, and results were evaluated based on adaptability to Hungarian settings. We also summarized the available Hungarian scientific evidence and reconstructed the potential patient pathways. In accordance with these findings, we recommend to perform the full health-economic evaluation of low-dose computed tomography lung cancer screening using a complex model structure that consists of several sub-models and is capable to follow the population at risk on life-time horizon. The proposed cost-effectiveness model will be suitable to provide data for further analyses that support decision-making on introducing low-dose computed tomography lung cancer screening as public health program. Orv Hetil. 2017; 158(25): 963-975.

Abstract IA18: Development and validation of risk models to select ever-smokers for CT lung-cancer screening

Abstract The US Preventive Services Task Force (USPSTF) recommends computed-tomography (CT) lung-cancer screening for ever-smokers ages 55-80 years who smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung-cancer risk calculations may be more effective and efficient than current USPSTF recommendations. We compare of modeled outcomes from risk-based CT lung-screening strategies versus USPSTF recommendations. We developed empirical risk models for lung-cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age, education, sex, race, smoking intensity/duration/quit-years, Body Mass Index, family history of lung-cancer, and self-reported emphysema. Models were validated in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the US. Models applied to US ever-smokers ages 50-80 (NHIS 2010-2012) to estimate outcomes of risk-based selection for annual CT lung-screening for 3 years, assuming screening for all ever-smokers yields the percent changes in lung-cancer detection and death observed in the NLST. Lung-cancer incidence and death risk models were well-calibrated in PLCO and NLST. The lung-cancer death model calibrated and discriminated well for US ever-smokers ages 50-80 (NHIS 1997-2001: Estimated/Observed=0.94, 95%CI=0.84-1.05; AUC=0.78, 95%CI=0.76-0.80). Under USPSTF recommendations, the models estimated 9.0 million US ever-smokers would qualify for lung-cancer screening and 46,488 (95%CI=43,924-49,053) lung-cancer deaths were estimated as screen-avertable over 5 years (estimated NNS=194, 95%CI=187-201). In contrast, risk-based selection screened the same number of ever-smokers (9.0 million) at highest 5-year lung-cancer risk (≥1.9%), was estimated to avert 20% more deaths (55,717; 95%CI=53,033-58,400) and was estimated to reduce the estimated NNS by 17% (NNS=162, 95%CI=157-166). Among a cohort of US ever-smokers age 50-80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lung-cancer deaths prevented over 5 years along with a lower NNS to prevent 1 lung-cancer death. Citation Format: Hormuzd A. Katki, Stephanie A. Kovalchik, Christine D. Berg, Li C. Cheung, Anil K. Chaturvedi. Development and validation of risk models to select ever-smokers for CT lung-cancer screening. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA18.

Abstract IA17: Risk prediction modeling in lung cancer: How can we improve?

Abstract IA17: Risk prediction modeling in lung cancer: How can we improve?

Relative predictive value of lung cancer screening CT versus myocardial perfusion attenuation correction CT in the evaluation of coronary calcium.

Coronary artery calcium scores (CACS) from lung cancer screening computed tomography (LCSCT) or myocardial perfusion attenuation correction computed tomography (ACCT) are not routinely performed or reported. CACS from LCSCT and ACCT have not been directly compared in the same patient population. We identified 66 patients who underwent both LCSCT (non-gated) and ECG-gated cardiac CT (CCT) within a 2-year span. Of this population, 40 subjects had also undergone ACCT. Using the Agatston method, CACS for 264 individual vessels from the LCSCT population and for 160 vessels from ACCT population were calculated and evaluated for agreement with ECG-gated CCT as the gold standard. Secondary analysis included a comparison of individual vessel contribution to variations in agreement and a comparison of total CACS from CCT, LCSCT, and ACCT for respective MACE prediction. CACS from LCSCT demonstrated a strong Pearson correlation, r = 0.9017 (0.876–0.9223), with good agreement when compared to CACS from CCT. CACS from ACCT demonstrated a significantly (P < 0.00001) weaker correlation, r = 0.5593 (0.4401–0.6592). On an individual vessel basis, CACS from all major vessels (LM, LAD, LCX, and RCA) contributed to the weaker correlation. For total vessel CACS, LCSCT demonstrated comparable area under the curve (AUC) for the receiver operating characteristic (ROC) curve (LCSCT AUC = 0.8133 and CCT AUC = 0.8302, P = 0.691) for prediction of MACE. Although ACCT demonstrated a similar AUC (ACCT AUC = 0.7969, P = 0.662) for MACE prediction the cutoff value for elevated risk was extremely low. In conclusion, LCSCT outperformed ACCT at calcium scoring by providing better agreement and comparable risk assessment to CCT despite the absence of ECG-gating. It is therefore reasonable to use LCSCT images to derive and report Agatston-based CACS for cardiovascular risk assessment, whereas the use of ACCT images to report Agatston-based CACS is not currently practical.

Cost-effectiveness of implementing computed tomography screening for lung cancer in Taiwan

BackgroundA screening program for lung cancer requires more empirical evidence. Based on the experience of the National Lung Screening Trial (NLST), we developed a method to adjust lead-time bias and quality-of-life changes for estimating the cost-effectiveness of implementing computed tomography (CT) screening in Taiwan. MethodsThe target population was high-risk (≥30 pack-years) smokers between 55 and 75 years of age. From a nation-wide, 13-year follow-up cohort, we estimated quality-adjusted life expectancy (QALE), loss-of-QALE, and lifetime healthcare expenditures per case of lung cancer stratified by pathology and stage. Cumulative stage distributions for CT-screening and no-screening were assumed equal to those for CT-screening and radiography-screening in the NLST to estimate the savings of loss-of-QALE and additional costs of lifetime healthcare expenditures after CT screening. Costs attributable to screen-negative subjects, false-positive cases and radiation-induced lung cancer were included to obtain the incremental cost-effectiveness ratio from the public payer’s perspective. ResultsThe incremental costs were US$22,755 per person. After dividing this by savings of loss-of-QALE (1.16 quality-adjusted life year (QALY)), the incremental cost-effectiveness ratio was US$19,683 per QALY. This ratio would fall to US$10,947 per QALY if the stage distribution for CT-screening was the same as that of screen-detected cancers in the NELSON trial. ConclusionsLow-dose CT screening for lung cancer among high-risk smokers would be cost-effective in Taiwan. As only about 5% of our women are smokers, future research is necessary to identify the high-risk groups among non-smokers and increase the coverage.

Quantification of growth patterns of screen-detected lung cancers: The NELSON study

ObjectivesAlthough exponential growth is assumed for lung cancer, this has never been quantified in vivo. Aim of this study was to evaluate and quantify growth patterns of lung cancers detected in the Dutch-Belgian low-dose computed tomography (CT) lung cancer screening trial (NELSON), in order to elucidate the development and progression of early lung cancer. Materials and methodsSolid lung nodules found at ≥3 CT examinations before lung cancer diagnosis were included. Lung cancer volume (V) growth curves were fitted with a single exponential, expressed as V=V1 exp(t/τ), with t time from baseline (days), V1 estimated baseline volume (mm3), and τ estimated time constant. The R2 coefficient of determination was used to evaluate goodness of fit. Overall volume-doubling time for the individual lung cancer is given by τ*log(2). ResultsForty-seven lung cancers in 46 participants were included. Forty participants were male (87.0%); mean age was 61.7 years (standard deviation, 6.2 years). Median nodule size at baseline was 99.5mm3 (IQR: 46.8–261.8mm3). Nodules were followed for a median of 770 days (inter-quartile range: 383–1102 days) before lung cancer diagnosis. One cancer (2.1%) was diagnosed after six CT examinations, six cancers (12.8%) were diagnosed after five CTs, 14 (29.8%) after four CTs, and 26 cancers (55.3%) after three CTs. Lung cancer growth could be described by an exponential function with excellent goodness of fit (R2 0.98). Median overall volume-doubling time was 348 days (inter-quartile range: 222–492 days). ConclusionThis study based on CT lung cancer screening provides in vivo evidence that growth of cancerous small-to-intermediate sized lung nodules detected at low-dose CT lung cancer screening can be described by an exponential function such as volume-doubling time.

The role of screening expectations in modifying short–term psychological responses to low-dose computed tomography lung cancer screening among high-risk individuals

ObjectiveThis study aimed to examine the relationship between pre-screening expectations and psychological responses to low-dose computerised tomography (LDCT) screening among high-risk individuals in the United Kingdom Lung Cancer Screening (UKLS) pilot trial. MethodsPrior to screening, high-risk individuals randomised into the intervention arm of the UKLS were asked about their expected screening test result. Their actual LDCT scan result was compared with their baseline screening expectation to determine the level of congruence. Levels of concern about and perceived accuracy of the result were assessed in a questionnaire two weeks following receipt of their test result. ResultsThe sample included 1589 participants. Regardless of their expected results, patients who required follow-up investigations after their initial LDCT scan were the most concerned about their result (p<0.001). Participants who expected to require follow-up, but did not need it, perceived the test to be least accurate (p=0.006). ConclusionsLung cancer screening participants who require follow-up or who have unexpected negative results can be identified for supportive interventions.Practical Implications: These findings can be used to ensure that any future LDCT lung cancer screening programme is tailored to identify and support those high-risk individuals who may benefit from additional help.

Exposure to low dose computed tomography for lung cancer screening and risk of cancer: secondary analysis of trial data and risk-benefit analysis

Objective To estimate the cumulative radiation exposure and lifetime attributable risk of cancer incidence associated with lung cancer screening using annual low dose computed tomography (CT).Design Secondary analysis of data...

Performance and Cost-Effectiveness of Computed Tomography Lung Cancer Screening Scenarios in a Population-Based Setting: A Microsimulation Modeling Analysis in Ontario, Canada.

BackgroundThe National Lung Screening Trial (NLST) results indicate that computed tomography (CT) lung cancer screening for current and former smokers with three annual screens can be cost-effective in a trial setting. However, the cost-effectiveness in a population-based setting with >3 screening rounds is uncertain. Therefore, the objective of this study was to estimate the cost-effectiveness of lung cancer screening in a population-based setting in Ontario, Canada, and evaluate the effects of screening eligibility criteria.Methods and FindingsThis study used microsimulation modeling informed by various data sources, including the Ontario Health Insurance Plan (OHIP), Ontario Cancer Registry, smoking behavior surveys, and the NLST. Persons, born between 1940 and 1969, were examined from a third-party health care payer perspective across a lifetime horizon. Starting in 2015, 576 CT screening scenarios were examined, varying by age to start and end screening, smoking eligibility criteria, and screening interval. Among the examined outcome measures were lung cancer deaths averted, life-years gained, percentage ever screened, costs (in 2015 Canadian dollars), and overdiagnosis. The results of the base-case analysis indicated that annual screening was more cost-effective than biennial screening. Scenarios with eligibility criteria that required as few as 20 pack-years were dominated by scenarios that required higher numbers of accumulated pack-years. In general, scenarios that applied stringent smoking eligibility criteria (i.e., requiring higher levels of accumulated smoking exposure) were more cost-effective than scenarios with less stringent smoking eligibility criteria, with modest differences in life-years gained. Annual screening between ages 55–75 for persons who smoked ≥40 pack-years and who currently smoke or quit ≤10 y ago yielded an incremental cost-effectiveness ratio of $41,136 Canadian dollars ($33,825 in May 1, 2015, United States dollars) per life-year gained (compared to annual screening between ages 60–75 for persons who smoked ≥40 pack-years and who currently smoke or quit ≤10 y ago), which was considered optimal at a cost-effectiveness threshold of $50,000 Canadian dollars ($41,114 May 1, 2015, US dollars). If 50% lower or higher attributable costs were assumed, the incremental cost-effectiveness ratio of this scenario was estimated to be $38,240 ($31,444 May 1, 2015, US dollars) or $48,525 ($39,901 May 1, 2015, US dollars), respectively. If 50% lower or higher costs for CT examinations were assumed, the incremental cost-effectiveness ratio of this scenario was estimated to be $28,630 ($23,542 May 1, 2015, US dollars) or $73,507 ($60,443 May 1, 2015, US dollars), respectively.This scenario would screen 9.56% (499,261 individuals) of the total population (ever- and never-smokers) at least once, which would require 4,788,523 CT examinations, and reduce lung cancer mortality in the total population by 9.05% (preventing 13,108 lung cancer deaths), while 12.53% of screen-detected cancers would be overdiagnosed (4,282 overdiagnosed cases). Sensitivity analyses indicated that the overall results were most sensitive to variations in CT examination costs. Quality of life was not incorporated in the analyses, and assumptions for follow-up procedures were based on data from the NLST, which may not be generalizable to a population-based setting.ConclusionsLung cancer screening with stringent smoking eligibility criteria can be cost-effective in a population-based setting.

Preface on "pulmonary nodules special issue for lung cancer".

The incidence of small pulmonary nodules (SPNs) is increasing as a result of the widespread use of multislice spiral computed tomography (CT) and the low-dose helical CT screening for lung cancer (1). A pulmonary nodule is definite as a well or poorly-circumscribed, approximately spherical, radiographic opacity less than or equal to 30mm in diameter that is completely surrounded by aerated lung and is not associated with atelectasis, hilar enlargement, or pleural effusion, which can be divided into solid and sub-solid nodules, with the latter group further subdivided between pure ground-glass opacity (GGO) and part-solid nodules (2).

OA01.02 A Lung Cancer Surgical Mortality Risk-Prediction Algorithm to Inform Lung Cancer Screening Shared Decision-Making

Low-dose computed tomography lung cancer screening has been demonstrated to increase detection of cases at an early-stage and reduce lung cancer mortality (vs. x-ray or no screening). However, screening benefits are greatly reduced in persons who are poor candidates for curative intent surgery in the event of screen-detected early-stage disease. To date, no practical tools have been developed to assess potential suitability for surgical treatment at the time of screening shared decision-making. The objective of this study was to use readily available socio-demographic and medical history variables to develop a prediction model that estimates the risk of 30-day mortality following surgical treatment for early-stage non-small cell lung cancer (NSCLC). We used logistic regression to develop a risk-prediction model for 30-day mortality following surgical treatment for Stage I/II NSCLC in patients age 65 to 79 using SEER-Medicare linked databases (2007-2012). Additionally, all patients had at least 1 year of Medicare enrollment prior to NSCLC diagnosis and received initial surgical treatment within 6 months of diagnosis. We developed the model with a training sample of 1,571 surgical cases and conducted internal validation exercises with a sample 4,632 independent surgical cases. Models included age, sex, race, country of birth, urban-rural status, and comorbidities in the year prior to NSCLC diagnosis. The Hosmer-Lemeshow test (by decile) and area under the receiver-operating characteristic curve (AUC) were assessed as measures of model calibration and discrimination, respectively. Within the full sample of 6,203 cases, 201 deaths were identified within 30 days of surgical treatment (3.2% of sample). In the training and internal validation sets, the AUC was 0.831 and 0.734, respectively. The observed risk of 30-day mortality was 9.3-fold greater in the highest decile of predicted risk (8.3%) vs. the lowest decile (0.7%), and the Hosmer-Lemeshow test indicated satisfactory model fit (p=0.92). The model had similar performance in women, men, whites, and non-whites; and also had similar calibration and discrimination for 60- and 90-day mortality. Our risk-prediction model has good ability to identify patients at increased risk of mortality following surgical treatment for early-stage NSCLC, and pending additional development and validation, can potentially be applied in clinic to inform lung cancer screening shared decision-making with minimal time or resource impacts.

SC24.02 Radiological Techniques for the Evaluation of Pulmonary Nodules

Radiologic Techniques for the Evaluation of Pulmonary Nodules The incidental detection of pulmonary nodules has increased with improved CT technology and thin section imaging techniques.1,2 Adding to this increased detection of nodules is the heightened interest in the purposeful search for nodules such as in oncology patients and lung cancer screening programs. The management of CT detected nodules is a subject of much debate and dependent upon the clinical setting. For instance, in a lung cancer screening setting, there has been a large volume of investigation of solid, semi-solid and ground glass nodules that is the foundation of management recommendations such as LungRads.3 In patients with a known malignancy, there is minimal literature on management recommendations and thus more influenced by pulmonary metastatic potential of the malignancy and clinician experience.4 Finally incidentally detected nodule management is greatly influenced by cancer risk factors and nodule texture; for these situations, the Fleischner criteria have been the most widely used and accepted management guidelines.5 The radiologic evaluation of nodules most often utilizes conventional imaging techniques of chest radiographs, computed tomography (CT), PET/CT. Occasionally MRI and ultrasound may be employed. Most recent changes involve risk stratification, computer software applications to enhance nodule analysis such as nodule enhancement patterns, volumetric computations, and texture analysis.6-8 Future directions include incorporation of genomics into imaging as well as radiomic analysis and machine learning.9,10 This presentation will review the highlights of the radiologic methods for evaluating pulmonary nodules with a focus on current guidelines and future directions. 1. Frank L, Quint LE. Chest CT incidentalomas: thyroid lesions, enlarged mediastinal lymph nodes, and lung nodules. Cancer imaging : the official publication of the International Cancer Imaging Society 2012;12:41-8. 2. Jacobs PC, Mali WP, Grobbee DE, van der Graaf Y. Prevalence of incidental findings in computed tomographic screening of the chest: a systematic review. Journal of computer assisted tomography 2008;32:214-21. 3. Lung CT Screening Reporting and Data Systen (Lung-RADS). 2014. (Accessed March 27, 2015, at www.acr.org/Quality-Safety/Resources/LungRADS) 4. Munden RF, Erasmus JJ, Wahba H, Fineberg NS. Follow-up of small (4 mm or less) incidentally detected nodules by computed tomography in oncology patients: a retrospective review. J Thorac Oncol 2010;5:1958-62. 5. McMahon PM, Meza R, Plevritis SK, et al. Comparing benefits from many possible computed tomography lung cancer screening programs: extrapolating from the National Lung Screening Trial using comparative modeling. PloS one 2014;9:e99978. 6. McWilliams A, Tammemagi MC, Mayo JR, et al. Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med 2013;369:910-9. 7. Revel MP, Merlin A, Peyrard S, et al. Software volumetric evaluation of doubling times for differentiating benign versus malignant pulmonary nodules. AJR Am J Roentgenol 2006;187:135-42. 8. Talwar A, Gleeson FV, Rahman NM, Pickup L, Gooding M, Kadir T. A Review Of The Use Of Computer Aided Texture Analysis For Pulmonary Nodules Classification. American journal of respiratory and critical care medicine 2015;191. 9. El-Zein RA, Lopez MS, D'Amelio AM, Jr., et al. The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2014;23:2462-70. 10. Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology 2016;278:563-77. Radiomics, Incidental, nodules, CT

P1.01-036 Lung Cancer Screening Program Is Cost Effective in French Setting: A Model Based Study

The National Lung Screening Trial (NLST) showed that screening with low-dose computed tomography (CT) as compared with chest radiography reduced lung cancer-mortality. There is no data's on the feasibility and cost-effectiveness of CT lung cancer screening program in the French setting. We estimated mean life-years gained, costs and incremental cost-effectiveness ratio (ICER) for screening with low-dose CT compare to no screening. Estimations of life-years gained were based on the efficacy of NLST trail applied to the general French population using the same inclusion criteria's that NLST trail (age of 55 to 74 years with a minimum of 30 pack-years of smoking and no more than 15 years since quitting) adjusted to sex, age and smoking status. Costs were limited to direct costs from the payers perspective. We also performed sensitivity analysis based on several assumptions of program efficacy. The target population was 5 551 141 subjects. Compared with no screening, screening with low-dose CT, over a period of 2 years, will have an additional cost of 941 978 €, will provide 52.4 additional year of life with a corresponding ICER of 17 969 € per year gained. Sensitivity analysis showed that this result is sensitive to program efficacy (number, stage and survival of lung cancer diagnosed by the program) and to subjects compliance rate to the program. Cost effectiveness of CT lung cancer screening program in a French population using the same main inclusion criteria and outcomes of NLST trial appears as acceptable from the French health system

P1.03-042 Nodule Size is Poorly Represented by Nodule Diameter in Low-Dose CT Lung Cancer Screening

In lung cancer screening, at least one pulmonary nodule is found in over 50% of participants, of which 99% is benign. As lung cancer probability in low-dose computed tomography (CT) lung cancer screening usually is based on nodule size and growth rate, accurate nodule size determination is of major importance to decrease false positive screen results. Previous studies showed that nodule size measurements based on semi-automated volume are preferred over diameter measurements. Aim of this study was to determine the correlation between nodule diameter and nodule size of nodules found in low-dose CT lung cancer screening, and to directly compare it with semi-automated volume measurements. We investigated baseline data of 2,240 solid nodules of intermediate size (volume 50-500mm3) in 1,500 lung cancer screening participants. Nodule volume, x, y, and z diameter and minimum / maximum diameter in any direction were generated by semi-automated software (LungCARE, Siemens). Range in maximum axial and mean nodule diameter per nodule volume category (50-100mm3, 100-200mm3, 200-300mm3, 300-400mm3, 400-500mm3) was determined. Semi-automated nodule volume represented nodule size. Intra-nodule diameter variation was defined as maximum minus minimum nodule diameter. Median participant age was 59 years, 14.1% were women. Median nodule volume was 82.4 mm3 (interquartile range [IQR], 62.9–125.4 mm3). Median nodule diameter was 6.1 mm (IQR, 5.4–7.2 mm) for mean diameter, and 6.6 mm (IQR, 5.9–7.7 mm) for maximum axial diameter. Range in mean nodule diameter per volume category varied from 8.55 mm (3.0 – 11.5 mm) for nodules with volume of 50-100 mm3 to 6.1 mm (7.2 – 13.3 mm) for nodules with volume of 200-300 mm3; range in maximum axial diameter varied from 11.2 mm (7.3 – 18.5 mm) for nodules with volume of 200-300 mm3, to 7.0 mm (9.1 – 16.1 mm) for nodules with volume of 400-500 mm3. Intra-nodule diameters varied by a median of 2.8 mm (IQR, 2.2-3.7 mm). Intra-nodule diameter variation for smaller intermediate-sized nodules (50-200 mm3) was 2.8 mm (IQR 2.2-3.5 mm), and was smaller than intra-nodule diameter variation for larger intermediate-sized nodules (200-500 mm3; median 3.6 mm [IQR 2.5-5.1 mm], P<0.01). Nodule size is poorly represented by diameter, as a nodule has an infinite number of diameters, but only one volume. Therefore, use of nodule diameter measurements may lead to misclassification of lung cancer probability. Median intra-nodule diameter variation was found to be higher as the 1.5mm LungRADS cutoff for nodule growth.

MA03.06 Cost Effectiveness of Chest Scan Screeing for Lung Cancer in Abestos Occupational Exposure Subjects: A Model Based Study

The National Lung Screening trial (NLST) showed that screening with low-dose computed tomography (CT) compared with chest radiography reduced lung-cancer mortality. There is very few data's on subjects with occupational asbestos exposure. We examined the cost-effectiveness of CT lung cancer screening in a French cohort of asbestos post professional exposure subjects (APEXS cohort). We estimated mean lif-years, costs and incremental cost-effectiveness ration (ICER) for screening with low-dose CT compare to no screening in this population of asbestos exposed subjects. Estimations of life-years gained were based on the efficacy of NLST trial applied to APEXS cohort, adjusted to sex and age. Costs were limited to direct costs, from the payer perspective. We also performed sensitivity analysis based on several assumptions of screening program efficacy. Compared with no screening, screening with low-dose CT, over a period of 2 years, will cost, for 1000 subjects of APEXS cohort 312 645 €, will provide 9.4 additional life-years. The corresponding ICER was 33 102 € per life-gained. Sensitivity analysis showed that this result is sensitive to screening program efficacy (number, stage, and survival diagnosed by the program). ICER of low-dose CT lung cancer program in a cohort of asbestos post occupational exposure population appears as acceptable from the French health system.

Incidental renal tumours on low-dose CT lung cancer screening exams.

Introduction Renal cancer incidence has increased markedly in the United States in recent decades, largely due to incidentally detected tumours from computed tomography imaging. Here, we analyze the potential for low-dose computed tomography lung cancer screening to detect renal cancer. Methods The National Lung Screening Trial randomized subjects to three annual screens with either low-dose computed tomography or chest X-ray. Eligibility criteria included 30 + pack-years, current smoking or quit within 15 years, and age 55-74. Subjects were followed for seven years. Low-dose computed tomography screening forms collected information on lung cancer and non-lung cancer abnormalities, including abnormalities below the diaphragm. A reader study was performed on a sample of National Lung Screening Trial low-dose computed tomography images assessing presence of abnormalities below the diaphragms and abnormalities suspicious for renal cancer. Results There were 26,722 and 26,732 subjects enrolled in the low-dose computed tomography and chest X-ray arms, respectively, and there were 104 and 85 renal cancer cases diagnosed, respectively (relative risk = 1.22, 95% CI: 0.9-1.5). From 75,126 low-dose computed tomography screens, there were 46 renal cancer diagnoses within one year. Abnormalities below the diaphragm rates were 39.1% in screens with renal cancer versus 4.1% in screens without (P < 0.001). Cases with abnormalities below the diaphragms had shorter median time to diagnosis than those without (71 vs. 160 days, P = 0.004). In the reader study, 64% of renal cancer cases versus 13% of non-cases had abnormalities below the diaphragms; 55% of cases and 0.8% of non-cases had a finding suspicious for renal cancer (P < 0.001). Conclusion Low-dose computed tomography screens can potentially detect renal cancers. The benefits to harms tradeoff of incidental detection of renal tumours on low-dose computed tomography is unknown.

Prediction of anatomical lung volume using planimetric measurements on chest radiographs.

The anatomical lung volume is conventionally measured by computed tomography (CT). However, chest radiographs could be considered as an alternative method with low cost and low radiation. To predict the anatomical lung volume using planimetric measurements of chest radiographs. In total, 119 participants (M:F ratio = 66:53; age, 53.7 ± 9.6 years) who underwent chest CT for lung cancer screening were enrolled. The lung volume on CT was measured as a reference for the anatomical lung volume. To eliminate the bias from the degree of inspiration, virtual chest radiographs (posterior-anterior view and lateral view) were generated from the CT images using the thick multiplanar technique, and the lung area (cm(2)) was measured in the right (P), left (Q), and lateral (R) lungs according to the planimetric method. A regression equation predicting the anatomical lung volume from the planimetric measurements was generated. The correlation between the measured and estimated lung volumes was evaluated. The percentage error rate (%) was calculated and the equation was validated internally and externally. The equation predicting the anatomical lung volume (mL) was 9.6*S-1367, where the summed lung area (S) was defined as (P + Q + R). The measured and estimated lung volumes were highly correlated (R = 0.941, P < 0.001). The absolute error rate was 5.7 ± 4.9%. The root mean square error of the equation was 290.2. The root mean square errors on internal and external validation were 300.4 and 267.0. The anatomical lung volume may be feasibly and accurately predicted from planimetric measurements of chest radiographs.

Predicting Malignant Nodules from Screening CT Scans

ObjectivesThe aim of this study was to determine whether quantitative analyses (“radiomics”) of low-dose computed tomography lung cancer screening images at baseline can predict subsequent emergence of cancer. MethodsPublic data from the National Lung Screening Trial (ACRIN 6684) were assembled into two cohorts of 104 and 92 patients with screen-detected lung cancer and then matched with cohorts of 208 and 196 screening subjects with benign pulmonary nodules. Image features were extracted from each nodule and used to predict the subsequent emergence of cancer. ResultsThe best models used 23 stable features in a random forests classifier and could predict nodules that would become cancerous 1 and 2 years hence with accuracies of 80% (area under the curve 0.83) and 79% (area under the curve 0.75), respectively. Radiomics outperformed the Lung Imaging Reporting and Data System and volume-only approaches. The performance of the McWilliams risk assessment model was commensurate. ConclusionsThe radiomics of lung cancer screening computed tomography scans at baseline can be used to assess risk for development of cancer.