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C. Berg
Moderator of
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ED09 - Advances in Lung Cancer Screening (ID 277)
- Event: WCLC 2016
- Type: Education Session
- Track: Radiology/Staging/Screening
- Presentations: 4
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ED09.01 - Radiological Advances in Lung Cancer Screening (ID 6473)
14:30 - 14:50 | Author(s): M. Prokop
- Abstract
- Presentation
Abstract not provided
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ED09.02 - Risk Prediction Modelling in Lung Cancer Screening Programs (ID 6474)
14:50 - 15:10 | Author(s): M. Tammemägi
- Abstract
- Presentation
Abstract not provided
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ED09.03 - Overdiagnosis in Lung Cancer Screening (ID 6475)
15:10 - 15:30 | Author(s): C.A. Powell
- Abstract
Abstract not provided
Information from this presentation has been removed upon request of the author.
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ED09.04 - Cost Effectiveness of CT Screening (ID 6477)
15:30 - 15:45 | Author(s): B. Pyenson
- Abstract
- Presentation
Abstract not provided
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MA01 - Improvement and Implementation of Lung Cancer Screening (ID 368)
- Event: WCLC 2016
- Type: Mini Oral Session
- Track: Radiology/Staging/Screening
- Presentations: 12
- Moderators:M. Studnicka, C. Berg
- Coordinates: 12/05/2016, 11:00 - 12:30, Lehar 1-2
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MA01.01 - Detection of Lung Cancer and EGFR Mutations by Electronic Nose System (ID 4867)
11:00 - 11:06 | Author(s): D. Shlomi, M. Abud-Hawa, O. Liran, J. Bar, N. Gai Mor, M. Ilouze, A. Onn, A. Ben-Nun, H. Haick, N. Peled
- Abstract
- Presentation
Background:
Early detection of LC has been well established as a significant key point for patient survival and prognosis. New sensitive nanoarray sensors for exhaled Volatile Organic Compounds (VOCs) were developed and coupled with powerful statistical programs; diseases such as LC could be suspected.
Methods:
Breath samples were taken from patients who were evaluated for pulmonary nodules, LC patients before treatment and other control patients. 'Breath-prints' were recognized by nanomaterial based sensor array/Artificial Olfactory System (NaNose®) and Pattern recognition methods were used.
Results:
A total of 139 patients participated in this study, 30 patients with benign nodules, 89 LC patients (16 early and 73 advanced disease) and 20 controls. We revealed significant discrimination between all groups with accuracy of 75.6% to 90.9%. Discrimination of LC from benign nodules had 79% accuracy, while benign nodules could be discriminated from early LC lesions with positive and negative predicted values (PPV and NPV) of 87.7 and 87.5% respectively, and accuracy of 87%. Also, we could discriminate LC patients who harbor EGFR mutations (19) from wild-type (34) with an accuracy of 83%, a sensitivity of 79% and a specificity of 85%. Figure 1
Conclusion:
Breath analysis could discriminate LC patients from benign pulmonary nodules and between EGFR positive and negative mutations. In future, a portable, non-expensive, simple and user-friendly device may support evaluation of pulmonary nodules.
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MA01.02 - Non-Invasive LuCED® Test for Endobronchial Dysplasia, Enabling Chemoprevention Therapy with Drugs Such as Iloprost (ID 3866)
11:06 - 11:12 | Author(s): M. Meyer, R. Katdare, C. Presley, D. Wilbur, D. Steinhauer, J. Liang, J. Zulueta, R.L. Keith, Y.E. Miller, W.A. Franklin, G. Yang, J. Hayenga, A. Nelson
- Abstract
- Presentation
Background:
The LuCED test for early stage lung cancer detects rare abnormal cells that are exfoliated from tumors into sputum and promotes cancer case detection with >92% sensitivity and >95% specificity. Additionally, the LuCED test detects endobronchial lung dysplasia to triage patients with pre-cancer to chemoprevention therapy involving drugs such as Iloprost that show potential for reversing dysplasia. This test is complementary to lung cancer screening methods such as LDCT that do not detect dysplasia. We discuss the performance of the LuCED test for the non-invasive detection of endobronchial dysplasia.
Methods:
We analyzed 23,188 normal, 690 cancer, and 65 moderate/severe dysplasia cells from patient sputum. Each individual cell was imaged in 3D using the Cell-CT. Cells were analyzed to measure 594 3D structural biomarkers. Classifiers were developed with cytopathology as the gold standard to predict stages of carcinogenesis, from normal to dysplasia and cancer. The classifier output was binned into two diagnostic indications: 1) cancer vs. all other cell types; and 2) moderate/severe dysplasia vs. all other cell types.
Results:
Areas under ROC curves for the two diagnostic bins were both = 0.993. Thresholds were chosen to yield case specificity >95%. Using these thresholds, cell classification sensitivity of 75% was measured for cancer and dysplasia detection. Since abnormal sputum typically contains at least three abnormal cells the cancer case detection sensitivity is at least {100% x [1 – (1 - 0.75)[3]]} = 98%.Figure 1 Figure 1 shows ROC curves plus examples of cells imaged in 3D by the Cell-CT.
Conclusion:
This study demonstrates the feasibility of using the LuCED test to detect endobronchial dysplasia in the lung, achieving an estimated 98% case sensitivity and 95% case specificity. Future efforts will include testing on independent sets. Importantly, the non-invasive detection of dysplasia by LuCED testing may enable chemoprevention of lung cancer using drugs such as Iloprost.
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MA01.03 - The Non-Invasive LuCED® Test for Detection of Early Stage Lung Cancer (ID 3867)
11:12 - 11:18 | Author(s): M. Meyer, T. Bell, D. Sussman, D. Wilbur, C. Presley, J. Hayenga, F. Lakers, J. Reyna, M. Davies, J.K. Field, G. Yang, C. Lancaster, J. Zulueta, A. Nelson
- Abstract
- Presentation
Background:
LDCT screening for lung cancer often triggers follow-up scans for indeterminate nodules. The non-invasive LuCED test for detection of early stage lung cancer may resolve nodule findings and reduce LDCT false positives. In LuCED, patient sputum is analyzed by the Cell-CT® which computes 3D images of single cells allowing measurement of 3D structural biomarkers to identify potential abnormal cells. Final case disposition is determined through cytology review of these cells. Example images of abnormal cells identified by LuCED are shown in the figure. Figure 1
Methods:
Sputum samples from 127 patients were processed by LuCED: 65 patients had biopsy-confirmed lung cancer; and 62 patients were normal controls. Sensitivity was computed as the percentage of cancer cases where abnormal cells were found by LuCED. Generally, abnormal cells found in a case otherwise understood to be normal could constitute a diagnostic overcall and counted as a false positive. However, a finding of abundant (>5) abnormal cells in cases understood to be normal indicates discovery of a possible occult cancer or dysplastic lesion. Accordingly, these cases were not included in specificity calculations.
Results:
For cancer cases, the histology included adenocarcinoma (29 cases), squamous cancer (24), small cell lung cancer (5) and undifferentiated cancer (7); representing stages 1 (14), 2 (11), 3 (25), 4 (14), and unknown (1). Abnormal cells were found in 61 of 65 cancer cases for sensitivity of 93.8%. For stage 1 and 2 cancer, sensitivity was 88%. Ten cells exhibiting changes consistent with atypical adenomatous hyperplasia were found in one case. After removal, there remained two false positive cases, leading to specificity of 96.7% (N = 61).
Conclusion:
The LuCED test demonstrates accurate detection of early stage lung cancer with the potential of detecting pre-cancerous conditions of the lung. Results suggest that suspicious nodules may be efficiently reconciled by LuCED when used adjunctively with LDCT.
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MA01.04 - Discussant for MA01.01, MA01.02, MA01.03 (ID 7071)
11:18 - 11:30 | Author(s): J. Votruba
- Abstract
- Presentation
Abstract not provided
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MA01.05 - Predictive Performances of NELSON Screening Program Based on Clinical, Metrological and Population Statistics (ID 4688)
12:24 - 12:30 | Author(s): H. Beaumont, N. Faye, A. Iannessi, D. Wormanns
- Abstract
- Presentation
Background:
The balance of benefits and harms of screening programs depends on multiple factors such as the scenario of patient selection, the triage algorithm and the imaging methods. Because of the multifactorial nature of the outcome of screening programs, it is important to evaluate the performance of its components. We modeled the triage algorithm of the NELSON program for lung cancer screening in different scenarios in order to assess the robustness of the chosen approach. We are looking to develop a model that allows for testing the imaging protocol performance using various high-risk screening populations. Our Objective is to work out a simulator adaptive to multiple screening scenarios. In a first step, we tested a simulation of the NELSON triage algorithm by using published statistics as input data: the distribution of nodule size, the precision of nodule volume measurements and the distribution of nodules growth.
Methods:
We modeled the baseline round of NELSON triage algorithm. We simulated 10,000,000 ground truth (GT) data where the axial diameter of nodules followed a chi2 (df=1) distribution between 3 mm and 20 mm. For each of the GT nodule, we modeled also a chi2 (df=1) distribution of volume doubling time between 90 and 1000 days. We included into the model a Gaussian distribution of the time between visits (average: 105 days, standard deviation: 5 days). We modeled volume measurement of the nodules by adding a Gaussian random error as documented by the Quantitative Imaging Biomarker Alliance (QIBA) screening profile. We performed a by-nodule comparison between nodule classification by the triage algorithm and the corresponding GT in the first round. At each step of the triage algorithm, we evaluated Sensitivity (Se), Specificity (Sp), Positive Predictive Value (PPV) and Negative Predictive Value (NPV).
Results:
Sensitivity of the triage algorithm for classifying nodules into size categories was for 96,6% for NODCAT2, 86.9% for NODCAT3 and 90.7% for NODCAT4. Classification of GROWCAT C yielded Se=66.2% / Sp=21.2%. We found an overall performance of the NELSON triage algorithm of Se/Sp 94.0%/80.3%.PPV was 11.3%, and NPV was 99.8%
Conclusion:
Mathematical modeling gives valuable insights into the performance of different components of triage algorithms in lung cancer screening. We found a markedly different test performance for size versus growth assessment of the NELSON triage algorithm. Future work will extent the model to non-solid nodules and multiple rounds of screening. Moreover, it may have the potential to optimize triage algorithms in the design of screening programs.
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- Abstract
- Presentation
Background:
It is uncertain how long persistent and stable ground-glass nodules (GGNs) should be followed although a minimum of 3 years is suggested. Here, we aimed to evaluate the proportion of GGNs showing subsequent growth after initial 3 years among GGNs that had been stable during the initial 3 years, and to determine clinical and radiologic factors associated with subsequent growth.
Methods:
We retrospectively analyzed patients who underwent further computed tomography after the initial 3-year follow-up period showing a persistent and stable GGN (at least 5-year follow-up from initial CT).
Results:
Between May 2003 and June 2015, 453 GGNs (438 pure GGNs and 15 part-solid GGNs) were found in 218 patients. Of the 218 patients, 14 patients had 15 GGNs showing subsequent growth after the initial 3 years during the median follow-up period of 6.4 years. For the person-based analysis, frequency of subsequent growth of GGNs that had been stable during initial 3 years was 6.7% (14/218). For the nodule-based analysis, the frequency was 3.3% (15/453). In a multivariate analysis, age ≥ 65 years (odds ratio [OR], 5.51; p = 0.012), history of lung cancer (OR, 6.44; p = 0.006), initial size ≥ 8 mm (OR, 5.74; p = 0.008), presence of a solid component (OR, 16.58; p = 0.009), and an air bronchogram (OR, 5.83; p = 0.015) were independent risk factors for subsequent GGN growth.Between May 2003 and June 2015, 453 GGNs (438 pure GGNs and 15 part-solid GGNs) were found in 218 patients. Of the 218 patients, 14 patients had 15 GGNs showing subsequent growth after the initial 3 years during the median follow-up period of 6.4 years. For the person-based analysis, frequency of subsequent growth of GGNs that had been stable during initial 3 years was 6.7% (14/218). For the nodule-based analysis, the frequency was 3.3% (15/453). In a multivariate analysis, age ≥ 65 years (odds ratio [OR], 5.51; p = 0.012), history of lung cancer (OR, 6.44; p = 0.006), initial size ≥ 8 mm (OR, 5.74; p = 0.008), presence of a solid component (OR, 16.58; p = 0.009), and an air bronchogram (OR, 5.83; p = 0.015) were independent risk factors for subsequent GGN growth.
Conclusion:
For the individuals with GGNs having risk factors described above, the longer follow-up period is required to confirm subsequent GGN growth.
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MA01.07 - Influence of Nodule Morphology on Inter-Reader Variability of Volume and Diameter Measurements in CT Lung Cancer Screening (ID 4750)
11:36 - 11:42 | Author(s): M.A. Heuvelmans, D. Han, R. Vliegenthart, G. De Jonge, J.E. Walter, P. Van Ooijen, H.J. De Koning, M. Oudkerk
- Abstract
- Presentation
Background:
The high number of false positive screen results is a major disadvantage of lung cancer screening by low-dose chest computed tomography (CT). Measurement strategy influences the false-positive rate, and nodule morphology may influence measurement of nodule size. Comparison between inter-reader variation for semi-automatic volume measurements and manual diameter measurements are scarce. Therefore, we aimed to evaluate the influence of nodule morphology on inter-reader variability and assessment of growth for semi-automatic volume measurements and manual diameter measurements, in intermediate-sized solid nodules found in CT lung cancer screening.
Methods:
Twenty-five nodules of each morphological category: smooth, lobulated, spiculated and irregular, were randomly selected from 93 participants of the Dutch-Belgian randomized lung cancer screening trial (NELSON). Semi-automatic volume measurements were performed using Syngo LungCARE[®] software. Two chest radiologists independently measured maximum and mean diameters manually. The impact of nodule morphology on inter-reader variability was evaluated based on the systematic error and 95% limits of agreement (LoA). Inter-reader variability was compared to volume change cutoff at 3-month follow-up based on NELSON for nodule growth and Lung-RADS diameter cutoff.
Results:
For manual diameter measurements, a significant systematic deviation was found between readers in smooth, lobulated, and spiculated nodules. The deviation was up to 1.5 mm based on maximum diameter measurements, and 1.2 mm based on mean diameter measurements. For semi-automatic volume measurements, no statistically significant systematic deviation was found. For lobulated, spiculated, and irregular nodules, the 95%-LoA for mean diameter measurements was up to 66% larger than the 1.5 mm cutoff for nodule growth. For volume measurements, the 95%-LoA exceeded the 25% growth cutoff for spiculated and irregular nodules, but only by up to 12%.
Conclusion:
Nodule morphology has a greater effect on size assessment based on manual diameter measurements than based on volume measurements. The larger inter-reader variability for manual diameter measurement may cause misclassification of spiculated nodules when assessing growth in 24% of cases. Therefore, semi-automatic volume measurement is recommended for nodule size and growth determination in CT lung cancer screening.
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MA01.08 - Discussant for MA01.05, MA01.06, MA01.07 (ID 7016)
11:42 - 11:54 | Author(s): R.S. Santos
- Abstract
- Presentation
Abstract not provided
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MA01.09 - Mortality, Survival and Incidence Rates in the ITALUNG Randomised Lung Cancer Screening Trial (ITALY) (ID 4249)
11:54 - 12:00 | Author(s): E. Paci, D. Puliti, A. Lopes Pegna, L. Carrozzi, G. Picozzi, F. Falaschi, F. Pistelli, F. Aquilini, M. Zappa, F.M. Carozzi, M. Mascalchi
- Abstract
Background:
Low Dose Computed Tomography (LDCT) screening for lung cancer (LC) is still not recommended in Europe.
Methods:
71.232 invitation letters were sent to subjects registered with local General Practitioners, aged 5569 years. (Fig.1) From eligible respondents, we randomised 3206 eligible subjects, smokers and ex- smokers (< 10 years), to the active arm receiving 4 annual LDCT (n=1613) and to control arm receiving usual care (n=1593). Each LDCT was read by 2 radiologists and size of Non Calcific Nodules measured manually. Study design and performance data were already published. All subjects, enrolled from 2004-2009,were followed up for lung cancer incidence and mortality (average: 8.3 and 9.3 years, respectively); characteristics of enrolled subjects are presented in Table1. Figure 1Figure 2
Results:
Reductions of 17% (RR=0.83; 95%: 0.67-1.03) for overall and 30% (RR=0.70; 95%CI: 0.47-1.03) for LC-specific mortality were estimated. 67 lung cancers were diagnosed in the active, compared with 72 in the control group (RR=0.92; 95%CI: 0.66–1.28). A greater proportion of Stage I (36% vs 6%, (p<0.0001) was observed in the active group.
Conclusion:
LDCT screening could reduce LC-specific and overall mortality. The number of Lung cancer diagnosed in the two groups did not suggest over-diagnosis, after 8.5 years of follow-up time.
Information from this presentation has been removed upon request of the author.
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MA01.10 - Performance of ACR Lung-RADS in the 1st Brazilian Lung Cancer Screening Trial (BRELT1) (ID 6156)
12:00 - 12:06 | Author(s): R.S. Santos, J.P. Franceschini, M.C. Ghefter, R.C. Chate, A.L.C. Trajano, R. Saad Junior
- Abstract
- Presentation
Background:
In BRELT1 we found a significant number of low dose CT (LDCT) considered positive (nodules > 4mm). The aim of this study was to assess the effect of applying ACR Lung-RADS and Pre-Test Probability of Malignancy (PTPM) in suspicious nodules > 8mm founded in a clinical CT lung screening program.
Methods:
Clinical LDCT (baseline and follow up) containing nodules > 8mm were retroactively reclassified using the new ACR Lung-RADS™ structured reporting system and PTPM. The model used in this study to predict the probability of malignancy was designed by Swensen et al and included patient’s age, current or former smoker, diameter of the nodule, speculation and location. All LDCT had initially been interpreted by radiologists accredited in CT lung screening reporting following the National Comprehensive Cancer Network’s Clinical Practice Guidelines in Oncology: Lung Cancer Screening (version 1.2012), which considered as positive the same criteria from the National Lung Screening Trial.
Results:
In BRELT1 were recruited 790 current or former smokers, with a heavy smoking history. A total of 552 nodules were found in 312 positive LDCT at baseline (39%). LDCT follow up was performed in 89.1% of this population. From them 74 patients presented solid or semi solid nodules > 8mm in the highest diameter. According to ACR Lung-RADS™ 39 baseline LDCT were classified as 4A (52.7%), 6 as 4B (8.1%), 17 as 4X (22.9%) and 10 as 2 (13.5%). Follow-up LDCT showed reduction in the category in more than 80% of cases. Using the PTPM, 44 cases were considered at moderate risk (between 6 and 60%) and 30 cases of high risk for malignancy (over 60%). None was considered low risk (5% or less). Among 26 patients who underwent biopsy in BRELT1, we found 12 cases of lung cancer, of which 90% were stage IA or IB.
Conclusion:
The application of ACR Lung-RADS and PTPM associated with careful multidisciplinary assessment can help in the decision process. The follow-up of patients with positive nodules requires careful analysis of the main factors related to malignancy.
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MA01.11 - Implementation of LDCT Lung Cancer Screening into Practice. Results of Regional Early Detection Program (ID 5568)
12:06 - 12:12 | Author(s): M. Bryl, B. Nikisch, W. Dyszkiewicz, C. Piwkowski, M. Kasprzyk, W. Kasprzak, A. Barinow-Wojewodzki
- Abstract
- Presentation
Background:
Lung cancer is the leading cause of cancer deaths both in men and women in either Wielkopolska and the whole Poland. Wielkopolska is one of Polish regions (voivodships) with about 3,4 mln inhabitants and incidence of lung cancer aprox. 1900 new cases every year. Screening by low dose computer tomography (LDCT) showed reduction of lung cancer mortality in NLST trial. Regional authorities covered this program from local budget beside Polish health system.
Methods:
Since october 2009 program of early detection of lung cancer started in 5 centers of Wielkopolska region. Till the end of 2015 N=17222 subjects were screened. The entry criteria were: age between 55 and 70 years and smoking ≥ 20 packyears. Every person has the LDCT performed. Results were first clasified as normal or abnormal. Abnormalities were divided into 6 categories: <5mm single, <5 mm multiple, 5-15 mm single, 5-15 mm multiple, >15 mm single, >15 mm multiple. Patient received also recomendation for further actions. Results presented are based on annual reports for regional authorities.
Results:
More than 85% of the images were clasified as abnormal. Nodes of any kind were found in about 47% of entire population. More than 3000 patient received recomendation for further diagnostic evaluation. Finally 108 patients underwent surgery (37 lobectomies, 41 wedge resections, 30 thoracotomies/thoracoscopies). There were 92 cases of lung cancer confirmed (11 SCLC, 78 NSCLC, 3 carcinoids) and 1 case of mesothelioma.
Conclusion:
Lung cancer screening program identifies magnitude of lung changes. Many patients requires further diagnostic procedures. Most of them are fibrotic, post inflammatory changes. It is possible to diagnose lung cancer in early presymptomatic stage but numbers are low and risk models or biomarkers should be implemented to better define patients / nodules at risk.
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MA01.12 - Discussant for MA01.09, MA01.10, MA01.11 (ID 7043)
12:12 - 12:24 | Author(s): D.F. Yankelevitz
- Abstract
- Presentation
Abstract not provided
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Author of
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MTE04 - Screening for Lung Cancer (Ticketed Session) (ID 298)
- Event: WCLC 2016
- Type: Meet the Expert Session (Ticketed Session)
- Track: Radiology/Staging/Screening
- Presentations: 1
- Moderators:
- Coordinates: 12/05/2016, 07:30 - 08:30, Schubert 5
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MTE04.01 - Screening for Lung Cancer (ID 6544)
07:30 - 08:00 | Author(s): C. Berg
- Abstract
- Presentation
Abstract not provided
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