Moderator of

• 18881

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  ES 02 - Diagnostic and Interventional Radiology in Lung Cancer: Update 2017 (ID 511)

  • Event: WCLC 2017
  • Type: Educational Session
  • Track: Radiology/Staging/Screening
  • Presentations: 5
  • Moderators:David F Yankelevitz, Shuji Sakai
  • Coordinates: 10/16/2017, 11:00 - 12:30, Room 315

  • 22854

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    ES 02.01 - The Dutch-Belgian Lung Cancer Screening Trial (NELSON) (ID 7587)

    11:00 - 11:15  |  Presenting Author(s): Harry J De Koning
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Background Lung cancer is the most important tobacco-related health problem worldwide, accounting for an estimated 1.3 million deaths each year, representing 28% of all deaths from cancer. Lung cancer screening aims to reduce lung cancer-related mortality with relatively limited harm through early detection and treatment. The US National Lung Screening Trial showed that individuals randomly assigned to screening with low-dose CT scans had 20% lower lung cancer mortality than did those screened with conventional chest radiography. On the basis of a review of the literature and a modelling study, the US Preventive Services Task Force (USPSTF) recommends annual screening for lung cancer for high-risk individuals. However, the balance between benefits and harms of lung cancer screening is still greatly debated. Some investigators suggest the ratio between benefits and harms could be improved through various means. Nevertheless, many questions remain with regard to the implementation of lung cancer screening. Whether nationally implemented programmes can provide similar levels of quality as achieved in these trials remains unclear. The NELSON trial is Europe’s largest running lung cancer screening trial. The main purposes of this trial are; (1) to see if screening for lung cancer by multi-slice low-dose CT in high risk subjects will lead to a 25% decrease in lung cancer mortality or more; (2) to estimate the impact of lung cancer screening on health related quality of life and smoking cessation; (3) to estimate cost-effectiveness of lung cancer screening. The NELSON trial was set up in 2003 in which subjects with high risk for lung cancer were selected from the general population. After informed consent, 15,792 participants were randomised (1:1) to the screen arm (n=7,900) or the control arm (n=7,892). Screen arm participants received CT-screening at baseline, after 1 year, after 2 years and after 2,5 years. Control arm participants received usual care (no screening). In the NELSON trial a unique nodule management protocol was used. According to the size and volume doubling time of the nodules, initially three screen results were possible: negative (an invitation for the next round), indeterminate (an invitation for a follow-up scan) or positive (referred to the pulmonologist because of suspected lung cancer). Those with an indeterminate scan result received a follow-up scan in order to classify the final result as positive or negative. All scans were accomplished at the end of 2012. The lung cancer detection rate across the four rounds were, respectively: 0.9%, 0.8%, 1.1% and 0.8%. The cumulative lung cancer detection rate is 3.2% which is comparable with the Danish Lung Cancer Screening Trial (DLCST). Relative to the National Lung Screening Trial (NLST), more lung cancers were found in the NELSON: 3.2% vs. 2.4%. However, the NLST had less screening rounds and a different nodule management protocol and a different study population. False-positive rate after a positive screen result of the NELSON is 59.4%. The overall false-positive (over four rounds) is 1.2% in the NELSON study, which is lower compared to other lung cancer screening studies. A 2-year interval did not lead to significantly more advanced stage lung cancers compared with a 1-year interval (p=0.09). However, a 2.5-year interval led to a stage shift in screening-detected cancers that was significantly less favourable than after a 1-year screening interval (e.g. more stage IIIb/IV cancers). It also led to significantly higher proportions of squamous-cell carcinoma, boncho-alveolar carcinoma, and small-cell carcinoma (p<0.001). Compared with a 2-year screening interval, there was a similar tendency towards unfavourable change in stage distribution for a 2.5-year screening interval although this did not reach statistical significance. Also, the interval cancer rate was 1.47(28/19) times higher in the 2.5-year interval compared with the 2-year interval. Moreover, in the last six months before the final fourth screening round the interval rate was 1.3(16/12) times higher than in the first 24 months after the third round, suggesting that a 2.5-year interval may be too long. On average, 69.4% of the screening-detected lung cancers across the four screening rounds in the NELSON trial were diagnosed in stage I and 9.8% in stage IIIb/IV. This cumulative stage distribution of the screening-detected lung cancers in the NELSON trial appears to be favourable compared to those of the DLCST and the NLST (68.1% and 61.6% of cancers at stage I, and 15.9% and 20.0% at stage IIIb/IV, respectively).However, this finding should be interpreted with caution because 1) the NLST used the 6th edition of the TNM staging system, while the NELSON trial used the 7th edition, 2) the NLST and DLCST applied different eligibility criteria than the NELSON trial, and 3) the proportion of over-diagnosed lung cancers in the screening group is yet unknown. The lung cancers found in the NELSON control group have yet to be investigated.
    
    

    Information from this presentation has been removed upon request of the author.

    Information from this presentation has been removed upon request of the author.

  • 22855

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    ES 02.02 - The Fleischner Guideline / Lung-RADs (ID 7588)

    11:15 - 11:30  |  Presenting Author(s): Matthew Eric Callister
    • Abstract
    • Presentation
    • Slides

    Abstract:
    The Fleischner Society guidelines (most recently revised in 2017) [1,2] are the most referenced guidelines for management of pulmonary nodules detected incidentally on CT images. In 2014, the American College of Radiology produced the Lung-RADS assessment categories specifically to guide management of nodules detected by Low Dose CT screening for lung cancer [3]. Nodule management guidelines have also been published by the American College of Chest Physicians (ACCP) in 2013 [4] and the British Thoracic Society (BTS) in 2015 [5]. Whilst the Fleisher guidelines and Lung-RADS predominantly offer specific recommendations for interpretation of CT images and guidance for surveillance imaging, the ACCP and BTS guidelines in addition offer more proscriptive recommendations for ongoing investigation or treatment of larger nodules with PET-CT, biopsy techniques, and surgical/non-surgical treatment. There is much common ground between the four proposals. Most of the high quality evidence for nodule management comes from screening studies that only included patients at high risk of lung cancer, and there is an acknowledged paucity of evidence for guiding nodule management in patients with a lower background risk of cancer. There is agreement about the need to minimise radiation dose for CT surveillance for nodules, and an acknowledgement of the low likelihood of malignancy in small nodules detected through any route. All guidelines recognise that sub-solid nodules require a different management algorithm which incorporates a less interventional approach (acknowledging the more indolent nature of the tumours that these may represent) but by implication the need for longer follow-up before nodules can be deemed benign or harmless. Differences between the recommendations are summarised in Table 1. The size below which nodules can be ignored differs slightly between the guidelines. Lung-RADS recommends no intervention for nodules <6mm (or <4mm for new nodules) on the assumption that the patient continues with annual LDCT screening. Determining a threshold for discharge of small nodules detected out a screening program is of potentially greater significance, as a patient with a small malignant nodule discharged in this context is likely to have a poor outcome if that nodule subsequently presents as a symptomatic lung cancer. The Fleischner Society guidelines select a threshold of 1% lung cancer risk (roughly equating to 6mm diameter) below which surveillance is not routinely recommended (although is an option if the patient is high risk). The BTS guidelines base their discharge threshold of 80mm­[3] (5mm) on data from the NELSON screening trial which demonstrated this to be the threshold below which the presence of a nodule did not appear to increase the likelihood of subsequently diagnosed lung cancer above that seen in screening participants with no nodules [6]. More recent data from NELSON has suggested a different size threshold for nodules newly appearing during the screening process. New incident nodules above 27mm[3] appeared to confer an increased risk of cancer [7], and this is reflected in the Lung-RADS category 3 which suggests a 6 month surveillance scan for new incident nodules ≥4mm. When an incidentally detected nodule can be shown to be new compared to recent CT imaging, a lower threshold for ongoing surveillance is probably merited, although not currently recommended in the three relevant guidelines. The use of composite risk-prediction scores in guiding nodule management differs between the various guidelines. The Fleischner guidelines highlight the various risk factors to be considered when deciding management but do not recommend use of a risk prediction score. The ACCP guidelines recommend either qualitative assessment of the probability of malignancy, or quantitative assessment using a validated model (referencing the Mayo model [8]). The BTS guideline recommend use of the Pancan lung cancer risk calculator [9] to decide which nodules should be evaluated with PET-CT on the basis of a validation study in a UK population [10]. Subsequent studies from Australia and Denmark have also demonstrated the utility of the Pancan model in screening studies. The guidelines also differ in the extent to which they promote use of semi-automated volumetry. No reference to volumetry is made in Lung-RADS assessment categories. Both the Fleischner and BTS guidelines acknowledge the better reproducibility of volumetry over diameter measurements and the superior sensitivity in detecting growth. Both however highlight the need to use identical software versions if comparing nodule volumes between scans due to clearly demonstrated variability between different software programs/versions. The Fleischner guidelines comment that robust validated volumetry is not currently widely used hence continuing to base recommendations predominantly on caliper long and short-axis diameter measurements, whereas the BTS guidelines have strongly recommended volumetry in an attempt to drive uptake of this technology. The definition of what constitutes nodule growth also differs between the guidelines. Lung-RADS and the Fleischner guidelines define growth as an increase is diameter of >1.5mm and ≥2mm respectively, reflecting possible inaccuracy in smaller increments in size according to caliper measurements. The threshold of 25% change in volume recommended in the BTS guideline is based on the nodule management stategy used in both NELSON and UKLS. By way of comparison, nodule growth from 7mm to 9mm represents a 113% increase in volume (from 180mm[3] to 381mm[3]). All four guidelines/assessment categories have been published within the last 5 years, and there have been few validation studies published to date. Lung-RADS was compared to the National Comprehensive Care Network guidelines for lung cancer screening and was shown to increase the positive predictive value without increasing false-negative results. Prospective comparisons between these guidelines/approaches are needed to guide future practice.

    	Fleischner [1,2]	Lung-RADS [3]	BTS [4]	ACCP [5]
    Remit	Incidentally detected nodules	Screen-detected nodules	Incidentally and screen-detected nodules	Incidentally and screen-detected nodules
    Assessment of size	Average of long & short axis diameter	Average diameter	Semi-automated volumetry	As per Fleischner guidelines
    Threshold for discharge	<6mm - optional follow-up below this size if high risk	<6mm (revert to annual screen)	<80mm[3]	<5mm - optional follow-up below this size if high risk
    Selection of further investigation for larger nodules	>8mm consider PET, PET-CT or biopsy	≥8mm PET-CT, biopsy or assess with Brock/Pancan score	≥8mm Brock/ Pancan score to guide PET-CT/other tests	≥8mm clinical judge-ment or validated model (e.g. Mayo)
    Assessment of growth	Increase in size of ≥2mm	Increase in size of >1.5mm	Increase in volume of >25%	Not specified
    Pure Ground Glass Nodules	Surveillance only for 5 years duration	Revert to annual screen (unless >20mm)	Risk assess, but surveillance pref-erred (for 4 years)	CT surveillance for 3 years

    Table 1: Summary of significant differences between nodule management strategies recommended by various guidelines/assessment categories Fleischner [1,2] Lung-RADS [3] BTS [4] ACCP [5] Remit Incidentally detected nodules Screen-detected nodules Incidentally and screen-detected nodules Incidentally and screen-detected nodules Assessment of size Average of long & short axis diameter Average diameter Semi-automated volumetry where possible As per Fleischner guidelines Threshold for discharge <6mm - optional follow-up below this size if high risk <6mm (revert to annual screen) <80mm3 <5mm - optional follow-up below this size if high risk Selection of further investigation for larger nodules >8mm - consider PET, PET-CT or biopsy ≥8mm - PET-CT, biopsy or assess with Brock/ Pancan score ≥8mm - Brock/ Pancan score to guide PET-CT/other tests ≥8mm - clinical judgement or validated model (e.g. Mayo) Assessment of growth Increase in size of ≥2mm Increase in size of >1.5mm Increase in volume of >25% Not specified Pure Ground Glass Nodules Surveillance only for 5 years duration Revert to annual screen (unless >20mm) Risk assess, but surveillance preferred (for 4 years) CT surveillance for 3 years References [1] MacMahon H, Naidich DP, Goo JM, et al. Guidelines for Management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 2017;284:228-243 [2] Bankier AA, MacMahon H, Goo JM, et al. Recommendations for measuring pulmonary nodules at CT: a statement from the Fleischner Society. Radiology 2017, epub ahead of print. [3] American College of Radiology. Lung CT Screening Reporting and Data System (Lung-RADS). Available at : https://www.acr.org/Quality-Safety/Resources/LungRADS . Release date April 28, 2014, Accessed August 1, 2017. [4] Gould MK, Donington J, Lynch WR, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143:e93s-e120S. [5] Callister ME, Baldwin DR, Akram AR, et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 2015;70:ii1-ii54 [6] Horeweg N, van Rosmalen J, Heuvelmans MA, et al. Lung cancer probability in patients with CT-detected pulmonary nodules: a pre-specified analysis of data from the NELSON trial of low-dose CT screening. Lancet Oncol. 2014;15:1332–41. [7] Walter JE, Heuvelmans MA, de Jong PA, et al. Occurrence and lung cancer probability of new solid nodules at incidence screening with low-dose CT: analysis of data from the randomised, controlled NELSON trial. Lancet Oncol. 2016;17:907-16. [8] Swensen SJ, Silverstein MD, Ilstrup DM, et al. The probability of malignancy in solitary pulmonary nodules. Application to small radiologically indeterminate nodules. Arch Intern Med 1997;157:849–55. [9] 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. [10] Al-Ameri AMP, Malhotra P, Thygesen H, et al. Risk of malignancy in pulmonary nodules: a validation study of four prediction models. Lung Cancer 2015;89:27-30
    
    

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  • 22856

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    ES 02.03 - Radiologic Implications of the WHO Classification for Lung Cancer (ID 8026)

    11:30 - 11:45  |  Presenting Author(s): Kavita Garg
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Marked heterogeneity exists in clinical, radiologic, molecular, and pathologic features among adenocarcinoma cases. Therefore, a new Classification of Lung Adenocarcinoma was proposed by the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society in 2011 (1). The 2011 classification addressed three important weaknesses in the previous classification. First, it eliminated the term bronchioloalveolar carcinoma (BAC). Second, it added new terminologies of carcinoma-in-situ (CIS), and minimally invasive adenocarcinoma (MIA) to recognize that minimal invasion (< 5mm) had nearly similar clinical outcome as noninvasive nodules. Third, it replaced the terminology of mixed subtype of adenocarcinoma. In this revised classification, invasive lung ADCs were divided into the five subtypes; lepidic, acinar, solid, papillary, and micropapillary patterns primarily based on histologic features. The term predominant is appended to all categories of invasive ADC, as most of these tumors consist of mixtures of the subtypes (1). The widespread availability of MDCT and abundance of new information obtained especially from low-dose CT lung cancer screening programs, have increased our understanding of the types and management of small peripheral lung nodules encountered in daily clinical practice, in particular, the importance and prevalence of subsolid pulmonary nodules (atypical adenomatous hyperplasia (AAH), ground glass nodules (GGN) and part-solid nodules). Thin-section CT has emerged as a new biomarker for lung adenocarcinoma subtypes. The approval of CT as a screening tool for lung cancer was based primarily on National Lung Screening Trial (NLST) results. The NLST recently found that Low Dose Helical Computed Tomography (LDCT) reduces lung cancer specific mortality by 20% relative to chest x-ray screening in a cohort at high risk of lung cancer (2). However, significant concerns remain regarding its high false positive rate, overdiagnosis, cost effectiveness and concerns related to radiation burden from repeat CT screens. There is a trade-of between early detection of lung cancer vs unnecessary work-up of indeterminate nodules resulting in many side effects including anxiety, radiation exposure from CT follow-up to assess for growth, cost and morbidity and mortality related to biopsy or resection of a benign nodule. It is expected that false positive rate would decrease by 50% using more accurate phenotyping of a nodule using the lung CT reporting and data system (Lung-RADS) appropriately (3). One of the major changes proposed in Lung-RADS is the size threshold for positive screen, from 4 mm in NLST to 6 mm for solid nodules and 20 mm for nonsolid nodules. Tissue sampling would be used primarily for larger than 15 mm solid nodules or PET positive nodules with larger than 8 mm solid component. False positive rate would still be likely not acceptable for an individual using this approach. There is need for more accurate nodule assessment and risk stratification as given our current understanding that genetic make-up of a nodule is the ultimate determinant of clinical outcome (4). Further improvements in stage discrimination and management of lung nodules could be expected in the future, as more robust data related to texture analyses of tumors, their genetic profiles and impact of those on clinical outcome becomes available (5-8). Simple measuring the tumor size with one-dimentional (Response Evaluation Criteria in Solid Tumors (or RECIST) long-axis measurements do not reflect the complexity of tumor morphology or behavior. Also, it may not be predictive of therapeutic benefit. In contrast, the emerging field of radiomics is a high-throughput process in which a large number of shape, edge, and texture imaging features are extracted, quantified, and stored in databases in an objective, reproducible, and mineable form. Once transformed into a quantifiable form, radiologic tumor properties can be linked to underlying genetic alterations and to medical outcomes. Marked heterogeneity in genetic properties of different cells in the same tumor is typical and reflects ongoing intratumoral evolution. Clinical imaging is well suited to measure temporal and spatial heterogeneity. Subjective imaging descriptors of cancers are inadequate to capture this heterogeneity and must be replaced by quantitative metrics that enable statistical comparisons between features describing intratumoral heterogeneity and clinical outcomes and molecular properties. A recent study adds further support toward taking a conservative approach in the management and treatment of patients with part-solid nodules especially when the solid component is small. This strategy is already reflected in the Lung-RADS guidelines, which recommend focusing on the size of the solid component in the part-solid nodule instead of on the overall nodule size. For the future, the critical issue will be further refinements for the follow-up of nonsolid and part-solid nodules based on the size or volume that allow a process of shared decision making in selecting appropriate management and treatment (9-10). This lecture will address the radiologic implications of this new lung adenocarcinoma classification. References: 1. Travis W, Brambilla E, Noguchi M, et al. IASLC/ATS/ERS International multidisciplinary classification of lung adenocarcinoma. J Thoracic Oncol 2011;6:244-285 2. Aberle DR, Adams AM, Berg CD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365:395-409 3. American College of Radiology: Lung-RADS Version 1.0 Assessment Categories Release date: April 28, 2014. Accessed on 17 March, 2015 4. McWilliams, A. et al. Probability of cancer in pulmonary nodules detected on first screening CT. The New England journal of medicine 2013;369: 910-919, doi:10.1056/NEJMoa1214726 5. Lambin P, et al. Radiomics: extracting more information from medical images using advanced feature analysis. Eur J Cancer 2012;48 (4):441-446 6. Gatenby RA, Grove O, Gillies RJ. Radiology 2013;269:8-15 7. Bartholmai BJ, Koo CW, Johnson GB, et al. Pulmonary nodule characterization including computer analysis and quantitative features. J Thorac Imaging 2015;30 (2) 139-156 8. Song SH, Park H, Lee G, et al. Imaging phenotyping using Radiomics to predict micropapillary pattern within lung adenocarcinoma. JTO 2017;12:624-632 9. Rowena Yip, Henschke CI, Xu DM, et al. Lung cancers manifesting as part-solid nodules in the National Lung Screening Trial. AJR 2017;208:1011-1021 10. American College of Radiology website. Lung CT Screening Reporting and Data System (Lung-RADS). Accessed January 11, 2016 11. MacMahon H, Naidich DP, Goo JM, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: FROM THE Fleischner Society 2017. Radiology 2017;284:228-243
    
    

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  • 22857

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    ES 02.04 - Interventional Radiology on Personalized Medicine for Lung Cancer (ID 7590)

    11:45 - 12:00  |  Presenting Author(s): Tae Jung Kim
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Recent advances molecular target therapies have provided a remarkable benefit to patients harboring specific genetic alterations. Most patients treated against molecular targets eventually develop resistance even after initial dramatic response. T790M mutation is a major mechanism for clinical failure in non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) therapy. Osimertinib has been recently approved and demonstrated dramatic response in NSCLC patients with T790M mutation. In tumors with anaplastic lymphoma kinase (ALK) or ROS-1 rearrangement, cereitinib has been approved and recommended in case of crizotinib resistance. Therefore, clinical demand for rebiopsy to identify these druggable mutations has been increasing, and rebiopsy plays an important role in clinical application for exploring resistant mechanisms and determining further therapeutic strategies. This session will focus on rebiopsy issues in relapsed NSCLCs. We will describe the growing need for rebiopsy and review the current data about rebiopsy, both published and unpublished. We will discuss the technical aspects of interventional radiology-guided rebiopsy; patient selection, guiding-modalities, lesion targeting, and tissue sampling. Hurdles and solutions for rebiopsy will be discussed with appropriate examples. Current role of liquid biopsy in comparison with conventional tissue biopsy will be briefly covered. Finally, we will discuss how to collaborate more effectively as a lung cancer multidisciplinary team from radiologists’ perspective.
    
    

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  • 22858

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    ES 02.05 - MRI and Advanced Applications for Lung Cancer (ID 7591)

    12:00 - 12:15  |  Presenting Author(s): Yoshiharu Ohno
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Since magnetic resonance imaging (MRI) was introduced for the assessment of thoracic and lung diseases, various limitations. However, from 2000, various techniques have been demonstrated their utility for lung cancer evaluations, and is now covered by health insurance in many countries including North America, Eastern Asia and Europe. In this lecture, I will show you these recent advances in lung MRI focusing on its application in lung cancer evaluation, especially with regard to 1) pulmonary nodule detection, 2) pulmonary nodule and mass assessment, and 3) lung cancer stage and recurrence evaluations.
    
    

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Author of

• 18933

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  MTE 14 - Imaging of Lung Cancer (Sign Up Required) (ID 563)

  • Event: WCLC 2017
  • Type: Meet the Expert
  • Track: Radiology/Staging/Screening
  • Presentations: 1
  • Moderators:
  • Coordinates: 10/17/2017, 07:00 - 08:00, F205 + F206 (Annex Hall)

  • 23096

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    MTE 14.02 - Diagnostic Intervention for Lung Cancer (ID 7795)

    07:30 - 08:00  |  Presenting Author(s): David F Yankelevitz
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Diagnostic procedures for lung cancer can broadly be defined as those that lead to the initial diagnosis, evaluation of extent of disease, and obtaining tissue for further characterization of molecular and genetic properties of the cancer. In each of these areas there have been tremendous technologic advances which ultimately lead to added complexity in terms of best utilization of tissue. Tissue can be obtained by the radiologist through either the use of fine needles (either single-needle or co-axial) or through the use of cutting needles which obtain cores of tissues) and through a variety of guidance techniques including fluoroscopy, CT guidance (including CT fluoroscopy), sonography, and MR. Most commonly, now for lung procedures is CT guidance. With the increasing use of CT imaging lung nodules are detected at smaller and smaller sizes and the diagnostic approach becomes increasingly challenging. In addition, since there is better chance for cure when treatment is performed earlier the desire to obtain early diagnosis is strong. The question that arises primarily relates to what level of confidence is needed before a definitive surgical procedure is performed. Factors to be balanced are the diagnostic accuracy of competing non-invasive tests such as growth analysis or PET-CT, compared to needle biopsy. All this must also be balanced with the type of surgical procedure that is being considered and the tremendous improvements that often allow patients to be discharged within 1-2 days post surgery. Evaluating extent of disease includes biopsy of either lymph nodes or other structures such as ribs, adrenal glands, liver etc. Within the chest, evaluation of lymph nodes pre-operatively has been greatly enhanced through the use of bronchoscopy with ultrasound. However, there are many nodal stations that remain difficult to reach using this approach that can be reached with CT guided needle biopsy, including all compartments of the mediastinum and hilum. Lesions outside the lung can also be evaluated including the soft tissues and the ribs. These lesions are often detected on PET-CT and are amenable to needle biopsy. Most rib lesions can easily be accessed with simple aspiration type needles. The need for further characterization of cancers through molecular or genetic testing is rapidly gaining in importance. As new therapeutic techniques become available the need for more complete characterization of tumors becomes increasingly important. Here the question relates to how much tissue is needed to perform the desired test. This is a continuously evolving area and depends on which particular tests are being requested, availability of the institution to perform the particular test, and the potential to obtain the appropriate amount of material given the particular characteristics of the lesion. Critical to these considerations is developing a close working relationship with the pathology department so as to make sure all of these considerations are taken into account prior to performing a procedure. Collaboration with the pathology department is critical on many levels and may need to vary depending on available resources. Best would be having rapid on-site evaluation (ROSE), although this is not always possible. For each situation, a plan as to how to best maximize yield needs to be developed. In this talk, I will outline the many considerations for how best to optimize the diagnostic yield of material obtained by interventional radiologist depending on the characteristics of the lesion and present various strategies to integrate these approaches into various scenarios where tissue is required.
    
    

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• 20148

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  OA 15 - Diagnostic Radiology, Staging and Screening for Lung Cancer II (ID 684)

  • Event: WCLC 2017
  • Type: Oral
  • Track: Radiology/Staging/Screening
  • Presentations: 1
  • Moderators:Y. Satoh, Jin Mo Goo
  • Coordinates: 10/18/2017, 14:30 - 16:15, Room 303 + 304

  • 24423

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    OA 15.05 - Discussant - OA 15.01, OA 15.02, OA 15.03, OA 15.04 (ID 10835)

    15:10 - 15:25  |  Presenting Author(s): David F Yankelevitz
    • Abstract
    • Presentation
    • Slides

    Abstract not provided

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• 20177

  +

  P2.13 - Radiology/Staging/Screening (ID 714)

  • Event: WCLC 2017
  • Type: Poster Session with Presenters Present
  • Track: Radiology/Staging/Screening
  • Presentations: 2
  • Moderators:
  • Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)

  • 23495

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    P2.13-026 - Determining the Effect of Screening on Lung Cancer Mortality (ID 9553)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract

    Background:
    The current lung cancer screening recommendation of the United States Preventive Services Task Force (USPSTF) is to perform annual low-dose computed tomography (CT) scans for high risk current smokers (at least 30 pack-years), or quitters in the past 15 years, age 55-80 years. Our study aims to assess if early detection of lung cancer by screening decreases the lung cancer mortality burden and, if so, how drastically for those considered at highest lung cancer risk.
    
    Method:
    Lung cancer screening prevalence was calculated from the 2010 to 2015 National Health Interview Surveys (NHIS). Probability of screening was derived from logistic regression models using race, age, gender, smoking and health insurance status as predictors. Beta values for these covariates were then used to estimate the probability of screening in the 1999-2004 National Health and Nutrition Examination (NHANES) cohort, for which lung cancer mortality information was available through linkage with the National Death Index. Using the predictor values generated in the NHIS dataset, probability of screening was estimated for the at risk NHANES participants, to make inferences about the effects of screening on lung cancer mortality.
    
    Result:
    Of the 60829 NHIS study participants, 2296 met the definition for being at high for lung cancer. The overall screening prevalence for this at-risk population was 10.4%; 7.7% had chest radiography while 5.7% had CT scans. Screening occurred more frequently in former smokers (p=0.0474), people who had health insurance coverage (p= 0.0017), and those older than 68 years (p = 0.0439). In the NHANES cohort, out of 31126 participants, 668 met the USPSTF recommendation for screening and 25 of them died of lung cancer. Lung cancer mortality was significantly higher in the high-risk group than in the low-risk group (HR~adj~ 8.59, 95% CI: 5.12-14.41). Based on the screening predictors obtained from NHIS data, 347 (51.95%) of the 688 high risk individuals would undergo a screening; 16 of them (4.6%) have died of lung cancer. If screening had occurred, overall lung cancer mortality would have potentially been reduced by 64%, provided that individuals had screening-detected early stage operable tumors.
    
    Conclusion:
    Increasing CT screening among those at high-risk for lung cancer should significantly reduce deaths from lung cancer in this population. Screening needs to be combined with continued smoking cessation efforts.
    
    

  • 24644

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    P2.13-026b - A Novel Ultra Low Cost CT Image Quality Measurement Device (ID 10341)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract

    Background:
    Assessing CT image quality is becoming of increasing concern in the domain of quantitative imaging. Current calibration devices tend to be time-consuming to use and often require special expertise for analysis. We have developed a novel approach for measuring image quality on CT scanners that is automated and inexpensive.
    
    Method:
    Three new rolls of 3M 3/4x1000 Inch Scotch Magic tape($1.50 each) were placed radially out from iso-center and CT scanned using standard head, body,and low dose lung protocols on a GE VCT and a Siemens Somatom Definition AS scanner. A Gammex 464 ACR CT Accreditation phantom was also scanned on the same scanners with identical protocols. GE and Siemens scans were reconstructed with 0.625, 1.25,and 2.5mm and 0.6, 1.0,and 2.0mm slice thickness and spacing, respectively. A total of 36 3D CT scans(36=2 objects x 2 scanners x 3 protocols x 3 thicknesses) were used for this study. Automated analysis was performed using Radia Diagnostic Software(Radiological Image Technology, Inc.) for the Gammex scans and Accumetra software for the tape scans. Both software tools produced measurements for CT linearity(air and acrylic HU), in-plane resolution, slice thickness,and image noise. Mean, standard deviation,and difference in measurements was used to evaluate performance.
    
    Result:
    

    	Gammex Mean, SD	Tape Mean, SD	(Tape-Gammex) Mean, SD
    Air (HU)	-988, 10.4	-995, 4.6	-6.97, 6.38
    Acrylic (HU)	130, 2.0	121, 12.3	-8.90, 12.75
    In-plane Resolution (LP/cm)	6.32, 0.31	6.09, 0.67	-0.23, 0.91
    Slice Thickness (mm)	1.88, 1.13	1.42, 0.57	-0.46, 0.63
    Image Noise (HU SD)	13.39, 9.93	7.05, 2.65	-6.35, 8.47

    Given that mean tape measurements differed from Gammex phantom measurements by <10 for HU density,<0.25 for LP/cm of in-plane resolution,<0.5 for mm of slice thickness, and <10 for HU SD of image noise, scotch tape has the potential to be used as a fast, accurate, and inexpensive tool for assessing CT scanner and protocol image quality.
    
    Conclusion:
    A new automated and inexpensive method for CT scan image quality assessment that relies on advanced image processing techniques provides results comparable to standard calibration methods thus allowing CT scan calibration to be performed rapidly and inexpensively allowing for more comprehensive integration of quality standards into daily practice.
    
    

• 20180

  +

  P2.16 - Surgery (ID 717)

  • Event: WCLC 2017
  • Type: Poster Session with Presenters Present
  • Track: Surgery
  • Presentations: 5
  • Moderators:
  • Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)

  • 23544

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    P2.16-013 - Peripheral or Central Lung Nodules: How do Thoracic Surgeons Define it? (ID 9534)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    “Peripheral” is ubiquitously used in thoracic surgery literature, but definitions differ. Our purpose was to ascertain opinions of thoracic surgeons on CT images and assess the frequency of peripheral nodules according to their definitions.
    
    Method:
    We developed a survey and obtained an IRB exemption. Surgeons were asked to choose one of methods A-D to define the peripheral pleura: A=costal pleura, B=costal and mediastinal pleura (diaphragmatic pleura also on coronal and sagittal views), C=costal and fissural pleura, D=any pleural surfaces on: Question#1) axial images, Question#2) coronal images, Question#3) sagittal images. Question#4 asked whether the peripheral lung was: 1, 2, or 3 cm, outer 1/3, outer 1/2 or outer 2/3. Question#5 asked whether the measurement from the nodule to the pleura started at the inner edge, center, or outer edge of the nodule. By applying the possible choices to a database of 76 patients with documented lung cancer we determined the frequency of peripheral cancers for each combination.
    
    Result:
    Ten thoracic surgeons participated, all had different answers. The most frequent response to Question#1 was Method A (n=4), Question#2 Method A (n=5), and Question#3 Method B (n=4). The most frequent answer for Question#4 was the outer 1/3 of the lungs (n=6), and for Question#5, the outer border of the nodule, closest to the relevant pleura (n=5). The frequency of nodules classified as peripheral according to these answers ranged from 13% (10/78) to 91% (71/78).
    
    Conclusion:
    There was no consensus. Standardization and rationale for this would be highly useful.
    
    

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  • 23545

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    P2.16-014 - Deconstructing Surgical Decision Making (ID 9543)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    With the increase in number of individuals undergoing CT screening, lung cancers are now being detected at an earlier stage. Curative treatment can thus be performed on these patients, resulting in better lung cancer survival. Effective surgical decision making depends upon the degree of knowledge and experience the treating surgeon has about the outcome of actions, ability to assess risk and its subsequent impact. Use of a gnostic expert system would increase cost-effectiveness and efficiency. Our objective is to garner experts’ tacit knowledge about surgical decision making in a form of probability function.
    
    Method:
    Nine surgeons with extensive experiences in thoracic surgery were presented with a set of hypothetical cases, specified by indicators for surgical treatment (lobectomy or limited resection). Their choice of surgery and probability of performing limited resection were recorded for each case. Probabilities were translated into a logistic probability function for limited resection by 1) taking logits of the probabilities: Y=log[P/(1-P)], then 2) applying a general linear model for the mean of Y, Ŷ=β~1~+ β~2~X~2~+ β~3~X~3~+ β~4~X~4~+ β~5~X~5~+ β~6~X~6~+ β~7~X~7~ + ε. Standardized coefficients were computed and ranked to determine the effect of each indicator on limited resection.
    
    Result:
    Across the 24 cases, the median probabilities of limited resection among experts ranged from 0.0% to 100.0%, their case-specific IQR had values from 5 to 90 (Q3-Q1) percentage points, and ranges had values from 10-100(max-min) percentage points. Considering the expert-specific median probabilities, five out of eight experts favored lobectomy (median probabilities of limited resection ≤12.5%). Two other experts had median probabilities of 42.5% and 49% while the remaining expert favored limited resection (median probability 65%). The effect of each indicator on preferring limited resection over lobectomy varied between surgeons. Overall, distance from relevant pleura and nodule size were important factors for considering limited resection.
    
    Conclusion:
    There was great inter-surgeons variability on surgical decision making. Garnering experts’tacit knowledge on surgical decision making will enhance efficiency of health care and potentially change surgical practice.
    
    

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  • 23553

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    P2.16-022 - Initiative for Early Lung Cancer Research on Treatment: Pilot Implementation (ID 10165)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    We have initiated a new multi-center, international collaborative cohort study, the Initiative for Early Lung Cancer Research for Treatment (IELCART), which focuses on identifying optimal treatment for early stage lung cancer An issue under discussion is the extent of surgery (i.e., sublobar resection and no mediastinal lymph node resection) in order to decrease the length and morbidity of the surgical procedure, preserves pulmonary function, and increases the likelihood of resection of future new occurrences of lung cancers. The role of Stereotactic Body Radiation (SBRT), and for certain cases, Watchful Waiting (WW) also needs to be better delineated. Increasingly, the power of large prospective databases collected in the context of clinical care is being recognized as providing important information.
    
    Method:
    Based on an extensive literature review, scientific articles, and a series of focus sessions with patients and treating physicians, a common protocol has been developed. Relevant data forms were developed for both physicians and patients, both for pre- and post-surgery to account for potential confounders. These forms have been tested and entered into a web-based data collection system that also includes relevant imaging data. Initial enrollment focused on surgery.
    
    Result:
    Initial enrollment was limited to surgical clinics of 8 surgeons and a total of 174 patients (94 women, 80 men) agreed. Average age was 67.5 years and pack-years of smoking was 31.4. Patients stated that the internet was the most frequent source of information (35%), while family/friends, medical literature were used much less frequently (each <20%). Factors influencing the patient pre-treatment choice was that the physician thought it was best (93%) or what would provide the best outcome (87%); only 38% got a second opinion. The surgeon’s choice of procedure depended mainly on the location (75%), size of the nodule (64%), and the ability to have negative parenchymal margin (40%), with other considerations being much less likely (<26%). There was good agreement between patients’ and surgeons’ perceptions of the procedure, although the patients not fully prepared about the post-treatment consequences of surgery. Patients also thought that support groups were important in patients’ decisions on what was the best surgery.
    
    Conclusion:
    These results together with quality of life information and focus sessions suggest that more support in the post-operative phase of the treatment would be beneficial. Within the next 3 years, we anticipate to have statistically meaningful results to start to compare outcomes of alternative treatments.
    
    

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  • 23554

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    P2.16-023 - Changes of the Pulmonary Artery After Resection of Stage I Lung Cancer (ID 10238)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    Radiologists focus on the anatomic changes in the lung itself when interpreting postoperative surveillance CT scans, but the anatomic and physiologic effects of lung resection on the other organs of the thorax, specifically the pulmonary artery (PA), have not been well studied. Potential variations in PA size over time have been recognized as predictors of post-surgical complications and the development of pulmonary hypertension.
    
    Method:
    The International Early Lung Cancer Action Program (I-ELCAP) database was queried for lung cancer patients who underwent lobectomy and had both preoperative and postoperative CT imaging. Case-specific details were previously recorded in the database as per I-ELCAP protocol. All surgeries were performed by general thoracic surgeons. All CT imaging for each patient was reviewed by a fellowship-trained chest radiologist. Figure 1
    
    
    
    Result:
    Among the 142 subjects who underwent lobectomy, the median follow-up time from the pre-surgical CT to the last reviewable CT was 53.2 months (IQR: 27.9-100.4 months). The average increase in the size of the main pulmonary artery (mPA) was 1.5 mm (19.9 mm to 21.4 mm, P < 0.0001). There was also a significant increase between the pre-surgical CT and the initial postoperative CT which was on average 12.6 months later from 19.9 mm to 20.7 mm (P = 0.0002). Considering patients with and without CT evidence of emphysema, the 82 with emphysema had a smaller average change of the main PA between the pre-surgical and the last reviewable CT than the 60 without emphysema (1.0 mm vs. 1.8 mm, P = 0.08).
    
    Conclusion:
    Patients undergoing lobectomy appear to be at increased risk for enlargement of their pulmonary artery diameters after surgery. These results show that a focus on all the organs in the thorax, not just the lungs themselves, is important when evaluating postoperative lung resection CTs.
    
    

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  • 23555

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    P2.16-024 - Effect of Resection of Stage 1 Lung Cancer on Lung Volume (ID 10248)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    The anatomic and physiologic effects of lung resection for early stage lung cancer patients have not been extensively reported. We hypothesize that patients who have undergone lobectomy or wedge resection will have reduced lung volume on the affected side immediately after surgery while the lung volume on the opposing side may increase to compensate.
    
    Method:
    The Mount Sinai database was queried for stage 1 lung cancer patients who underwent lobectomy or wedge resection and had both pre-operative and postoperative CT imaging. Surgeries were performed by thoracic surgeons. The lung volumes on all CT scans were measured using previously published research software including actual volumes for each lung (left and right) at each time point as well as a set of volumes normalized to the overall chest volume in order to compensate for differences in inspiration.
    
    Result:
    In the cohort of 21 patients who met the above criteria, the median follow-up time from the date of surgery to the most recent CT was 44.6 months (IQR: 23.5-94.7 months). The median age was 63 and the median pack years was 40. There were 2 patients for which only one post-op scan was successfully analyzed; the remaining cases all had two postop scans. In 20 of the 21 patients, the lung volume on the side where the surgery occurred was reduced in the first postop CT scan (average reduction in volume of 5.6%). The change in volume of the contralateral side (not undergoing surgery), was highly variable, with 11 cases showing an increase in volume on both post-op scans, 2 cases showing a decrease, and 8 cases showing an increase in volume at the first postop scan followed by a decrease in volume on the second post-op scan.
    
    Conclusion:
    Stage 1 lung cancer patients undergoing resection have reduced lung volume on the side of surgery, however there was marked variability in the contralateral lung suggesting that the extent to which patients compensate post operatively is complex and dependent on many factors.
    
    

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• 20192

  +

  P3.13 - Radiology/Staging/Screening (ID 729)

  • Event: WCLC 2017
  • Type: Poster Session with Presenters Present
  • Track: Radiology/Staging/Screening
  • Presentations: 2
  • Moderators:
  • Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)

  • 24180

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    P3.13-028 - Controversies on Lung Cancers Manifesting as Part-Solid Nodules (ID 10074)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Background:
    Questions have been raised about the appropriate treatment of lung cancers manifesting as subsolid nodules (nonsolid nodules (NSNs) and part-solid nodules (PSNs)), as these have very high reported survival rates and have been observed in up to 10% of screening participants. Our goal in this report is to summarize the publications on survival of patients with resected lung cancers manifesting as PSNs and to further the development of consensus definitions of the CT appearance and the workup of such nodules.
    
    Method:
    PubMed/MEDLINE and EMBASE databases were searched for all studies/ clinical trials on CT-detected lung cancer in English before Dec 21, 2015 to identify surgically-resected lung cancers manifesting as PSNs. Outcome measures were lung cancer-specific survival (LCS), overall survival (OS), or disease free survival (DFS). All PSNs were classified by the percentage of solid component to the entire nodule diameter into: Category PSNs < 80% or Category PSNs ≥ 80%.
    
    Result:
    Twenty studies reported on PSNs < 80%: 7 reported DFS and 2 OS of 100%, 6 DFS 96.3-98.7%, and 11 OS 94.7-98.9% (median DFS 100% and OS 97.5%). Twenty-seven studies reported on PSNs ≥ 80%: 1 DFS and 2 OS of 100%, 19 DFS 48.0%-98.0% (median 82.6%), and 16 reported OS 43.0%-98.0% (median DFS 82.6%, OS 85.5%). Both DFS and OS were always higher for PSNs<80%.
    
    Conclusion:
    A clear definition of the upper limit of solid component of a PSN is needed to avoid misclassification because cell-types and outcomes are different for PSN and solid nodules. The workup should be based on the size of the solid component.
    
    

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  • 24187

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    P3.13-035 - Automatic Estimation of Measurement Error on CT Imaging (ID 10333)

    09:30 - 09:30  |  Author(s): David F Yankelevitz
    • Abstract

    Background:
    There has been increasing recognition that lung nodule measurement on CT scans is imprecise and that an understanding of the extent of this imprecision is necessary when trying to determine whether actual change in volume has occurred. The various factors that influence this are numerous with two of the most prominent being the overall quality of the CT scan (including all of the adjustable parameters) and the size of the nodule.
    
    Method:
    We have developed an automated system whereby a calibration device is scanned on a given scanner with a given protocol and then the system can automatically predict the extent of measurement error for a given size solid nodule. We compared this approach to empirically derived results obtained from a database of 117 screen-detected stable nodule ranging in size from 2.2 to 18.7 mm that were scanned twice on the same CT scanner using the same protocol. Automated volumetric analysis was performed using commercial software. This allowed us to determine the relationship between standard deviation of the measurements versus nodule size. We then scanned our calibration device using the same scanning protocol as was used on those nodules to automatically calculate the size and standard deviation relationship.
    
    Result:
    Predicted solid nodule volume standard deviation compared with empirically derived values across a range of nodule sizes was within 20% (see figure)Figure 1
    
    
    
    Conclusion:
    Results from our automated approach were highly correlated with results obtained from scans obtained in actual clinical practice. The ability to predict extent of error specific to a given scanner and scanning protocol is an essential step in understanding whether change has occurred and has implications for both diagnosis and therapy assessment, including predicting when a follow up scan should be obtained. This type of information will ultimately become a necessary component of all quantitative imaging programs.
    
    

• 18956

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  PL 01 - Prevention, Screening, and Management of Screen-Detected Lung Cancer (ID 586)

  • Event: WCLC 2017
  • Type: Plenary Session
  • Track: Radiology/Staging/Screening
  • Presentations: 1
  • Moderators:Michael Boyer, Matthijs Oudkerk
  • Coordinates: 10/16/2017, 08:15 - 09:45, Plenary Hall (Exhibit Hall D)

  • 22404

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    PL 01.02 - Major Advances in CT Screening: A Radiologist's Perspective (ID 7838)

    08:35 - 08:55  |  Author(s): David F Yankelevitz
    • Abstract
    • Presentation
    • Slides

    Abstract:
    Advances in CT scanners. CT screening was first introduced when helical CT scanners became available in the early 1990’s (1-4). Since then, there have been remarkable advances in CT scanner technology with concurrent increase in the number of CT examinations per year by approximately 10% annually. More powerful hardware and image reconstruction algorithms have allowed faster scanning at lower radiation doses in today’s multidetector CT (MDCT) scanners. Ultra low-dose techniques are gaining acceptance. With respect to lung cancer screening, thinner collimation now possible has led to the detection of many more small pulmonary nodules. Also, there have been evolutions in diagnostic techniques such as percutaneous biopsies, navigational bronchoscopy, and PET scans and these advances have been integrated into the regimen of screening with a resulting decrease in the frequency of surgical resection of benign nodules (5). Definition of Positive Results. Updates in the definition of positive results have continued to be developed that allow for improvements in the efficiency of workups. One of the major changes has been to update the size thresholds for positive results from 4 to 6 mm and also to avoid rounding errors (6, 7). The NELSON trial introduced the concept that a positive result should be based on the initial CT scan and a follow-up CT scan for small nodules, rather than solely on the initial CT scan and this has been adopted by I-ELCAP (6). The I-ELCAP and NLST databases have been used to provide follow-up strategies for nonsolid and part-solid nodules (6). Considerations as to screening frequency may substantially reduce costs for lower risk individuals. There is increasing recognition that different approaches are needed for baseline and repeat scans where even when nodules might have the same characteristics as they should be managed differently. The management of both nonsolid and part-solid nodules has dramatically changed. For the first time, imaging as a biomarker for aggressiveness has been used to monitor whether a cancer is progressing. Growing nonsolid nodules can be followed on an annual basis and only the emergence of a solid component triggers more aggressive intervention. For the part-solid nodule it has now been recognized that the important component from a prognostic perspective is the solid portion not the overall size. Quantitative assessments. Quantitative assessment of many findings on chest CT scans have been developed (6). In particular, assessment of nodule size and growth as to the probability of malignancy and lung cancer aggressiveness has progressed. Most guideline organizations have moved from a single measurement of length to an average diameter (average of length and width) (6) and to three measurements of volume (7). The errors involved in any of these measurements are influenced by multiple factors including the intrinsic properties of the nodule and the software used to make the measurement (8, 9). Additionally, they are impacted by the variability of CT scanners and their adjustable scan parameters. Advances in incorporating measurement errors into growth assessment by RSNA’s Quantitative Imaging Biomarkers Alliance (QIBA) has led to a web-based calculator. The American College of Radiology (ACR) specifies that growth for a nodule of any size requires “an increase of 1.5 mm or more.” Both approaches allow for large measurement errors for the wide range of CT scanners and the protocols. The I-ELCAP guidelines for solid and the solid component of part-solid nodules is given explicitly in I-ELCAP protocol (6). Each of these approaches has specific technical requirements as measurement error is influenced by both the scanner itself, the choice of various adjustable parameters on the scanner (slice thickness, slice spacing, dose, FOV, pitch, recon kernel etc.) as well as characteristics of the nodule itself. Additional considerations for computer-assisted volume change assessment requires: 1) inspecting the computer scans and the segmentation for image quality (e.g. motion artifacts) and for the quality of the segmentation; 2) the radiologist visually inspecting both nodule image sets side-by-side to verify the quality of the computer segmentation for each image that contains a portion of the nodule; 3) examination of the segmentations for errors such as when a vessel is segmented as part of a nodule in one scan but not in the other; 4) that the scan slice thickness for the purpose of volumetric analysis should be 1.25 mm or less. When using any computer-assisted software, the radiologist must be satisfied with the CT image quality and the computer segmentation results, further substantiating the notion that the decision of whether growth has occurred is ultimately based on clinical judgment. Innovations in use of imaging and genetic information. Radiomics is an emerging field of study on the quantitative processing and analysis of radiologic images and metadata to extract information on tumor behavior and patient survival (10). The hypothesis is that data analysis through automated or semi-automated software can provide more information than that of a physician. Its use has shown improved diagnostic accuracy in discriminating lung cancer from benign nodules. It has been used successfully in breast imaging, with 2017 FDA approval of a computer-aided diagnosis tool which utilizes advanced machine learning analytics. Furthermore, radiomics has been linked with the field of genomics, inferring that imaging features are closely linked to gene signatures such as EGFR expression, a known therapeutic target. In the future, as larger data sets emerge and inter-institutional sharing of images becomes more commonplace, radiomics will become more tightly integrated with lung cancer diagnosis, treatment planning, and patient survival prognostication. References 1. Henschke C, McCauley D, Yankelevitz D, Naidich D, McGuinness G, Miettinen O, Libby D, Pasmantier M, Koizumi J, Altorki N, and Smith J. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999; 354:99-105. 2. The International Early Lung Cancer Action Program Investigators. Survival of Patients with Stage I lung cancer detected on CT screening. NEJM 2006; 355:1763-71 3. Kaneko M, Eguchi K, Ohmatsu H, Kakinuma R, Naruke T, Suemasu K, and Moriyama N. Peripheral lung cancer: screening and detection with low-dose spiral CT versus radiography. Radiology 1996; 201: 798-802. 4. Sone S, Nakayama T, Honda T, Tsushima K, Li F, Haniuda M, et al. Long-term follow-up study of a population-based 1996-1998 mass screening programme for lung cancer using mobile low-dose spiral computed tomography. Lung Cancer. 2007; 58:329-41. 5. Linek HC, Flores RM, Yip R, Hu M, Yankelevitz DF, Powell CA. Non-malignant resection rate is lower in patients who undergo pre-operative fine needle aspiration for diagnosis of suspected early-stage lung cancer. Am J Respir and Crit Care Med 2015; 191: A3561 6. International Early Lung Cancer Action Program protocol. http://www.ielcap.org/sites/default/files/I-ELCAP%20protocol-v21-3-1-14.pdf Accessed March 27, 2015 7. Van Klaveren RJ et al. Management of Lung Nodules Detected by Volume CT Scanning. N Engl J of Medicine 2009; 361: 2221-9 8. Henschke CI, Yankelevitz DF, Yip R, Archer V, Zahlmann G, Krishnan K, Helba B, Avila R. Tumor volume measurement error using computed tomography (CT) imaging in a Phase II clinical trial in lung cancer. Journal of Medical Imaging 2016; 3:035505 9. Avila RS, Jirapatnakul A, Subramaniam R, Yankelevitz D. A new method for predicting CT lung nodule volume measurement performance. SPIE Medical Imaging 2017: 101343Y 10. Lee G, Lee HY, Park H, et al. Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art. Eur J Radiol. 2017; 86:297-307.
    
    

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• 19428

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  WS 01 - IASLC Supporting the Implementation of Quality Assured Global CT Screening Workshop (By Invitation Only) (ID 632)

  • Event: WCLC 2017
  • Type: Workshop
  • Track: Radiology/Staging/Screening
  • Presentations: 5
  • Moderators:
  • Coordinates: 10/14/2017, 08:30 - 21:00, F203 (Annex Hall)

  • 22236

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    WS 01.10 - Reviews of International Guidelines for Management of Pulmonary Nodules (i.e. NCCN/ LUNG-RADS, BTS, Fleischner IELCAP, etc.) (ID 10648)

    09:50 - 10:05  |  Presenting Author(s): David F Yankelevitz
    • Abstract

    Abstract:
    In this session, the focus will be on comparison of existing screening guidelines and the rationale for how they have developed. It will also highlight the similarities and the areas where different approaches have been taken. Among the guidelines that will be compared will be the Lung-RADS, National Comprehensive Cancer Center (NCCN), International Early Lung Cancer Action Program (I-ELCAP), British Thoracic Society (BTS), and Fleischner Society. We will also discuss the protocols previously recommended during the National Lung Screening Trial (NLST) and the NELSON trial as points of reference as these trials have been completed. The main points of similarity among these various protocols is there are various size criteria for workups to be initiated, with increasing size raising the suspicion of lung cancer. The differences in size threshold, especially in the baseline round for determining a positive result has had the greatest impact in terms of limiting the number of positive results. Many protocols now have moved to the six millimeter threshold which has lowered positive results in the baseline round into the range of 10-15%. Aside from different size threshold cutoffs, a main area of difference has been the way size is measured. Some rely on uni or bi-dimensional measures while others use volumetrics. For those uni-and bi-dimensional measures there are also differences in terms of whether to perform rounding. The effect of rounding is most pronounced in that baseline round where the frequency of the smaller nodules is highest, and rounding up to the nearest whole number can substantially increase the rate of positive results. The protocols also differ in terms of the number of size categories given and the options within each category. For any given size threshold that initiates further work up, there are various options that are considered. The most common includes the use of repeat imaging prior to the next annual screening round. While there are differences in terms of the length of these intervals in part based on the nodule size, all include a three or six month follow-up and some also include a one month follow up under certain conditions, As a general principle the time interval between scans is provided so as to allow for change to occur. The protocols all seek to measure this change either in terms of change in diameter or change in volume. The extent to which the amount of change is measured also varies. Some protocols include a fixed amount of change regardless of size while others require the extent of change to differ depending on size. Each of these has implication towards how often a result will be considered as positive. Most recently the Quantitative Imaging Biomarkers Alliance has provided additional guidance in this regard, and there are similar recommendations being developed by European and Japanese counterparts. One of the most important considerations in terms of management protocols is the differentiation between findings made on the baseline round compared to the annual repeat round. Findings on baseline occur only once while those on repeat rounds potentially can occur on numerous rounds throughout the course of screening and all protocols treat findings in each repeat screening round the same regardless of whether it is the first repeat screen or the tenth. Cancers in the baseline round tend to be larger and also more slowly growing compared to annual cancers, and similarly there are many more nodules found on the baseline round compared to new nodules found on repeat rounds. These factors all influence the way protocols are designed. While all protocols provide guidance for when to perform more invasive procedures, there tends to be several options. These factors allow for differences between institutions where there are differences in expertise in performing these procedures as well as availability of equipment. Another area of difference between protocols relates to how results are defined in terms of “positive” or “false positive” or “semi-positive.” An approach adopted in the NELSON trial allowed for positive result to only be determined for a certain size category of nodules based on the combination of results from the initial scan where a finding was made and the determination of whether growth had occurred. This approach allows for dramatically lowering the rate of positive results because it implies that the initial test needs to be thought of as being a test to measure growth which requires two time separated scans. A final area of difference has been the treatment of nonsolid and part-solid nodules. Here there is a general recognition that even those these nodules may be cancers, they are of a more indolent nature and there is relative safety in terms of following them over time. Some differences between the protocols include the amount of time allowed between scans and the trigger for more invasive management. Direct comparison of the different protocols will be made and examples will be provided to highlight some of the differences.
    
    

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    WS 01.12 - Planning for USA Registries for CT Screened Images – What Are Their Objectives? (ID 10650)

    10:20 - 10:35  |  Author(s): David F Yankelevitz
    • Abstract
    • Slides

    Abstract:
    The reimbursement of low dose CT lung cancer screening for high risk populations in the United States by the Centers for Medicare and Medicaid Services (CMS) [1] has been implemented with a requirement to participate in a nationwide registry run by the American College of Radiology (ACR) [2]. This registry’s main purpose is to enable the collection of basic information on lung cancer screening including patients’ demographic information, medical history and risk factors, procedure indications, and follow-up information. Owing in part to the large data sizes of low dose CT lung cancer screening studies, which can exceed 500 MB for each 3D CT scan acquisition, this important US lung cancer screening registry is not collecting CT image data. However, the I-ELCAP study has been collecting international lung cancer screening data, including CT scan images, for over two decades [3]. There are several important benefits to collecting CT lung cancer screening image datasets in addition to basic lung cancer screening information. CT image data provides important information on the quality of actual scans and findings in the field, which can help identify areas of improvement for national screening efforts as well as for the local lung cancer screening site. One of the most important benefits is that expert review of these scans and findings can help train local radiologists on how to improve delivery of lung cancer screening. In addition, many image acquisition characteristics can be automatically evaluated that influence lung cancer screening performance. Determining whether patients are being over scanned (outside the lung region), whether the CT table was properly positioned, and whether the CT reconstruction field of view was properly set can be evaluated are some of the areas that can be evaluated using automated analysis methods provided that the CT scan datasets are available for processing. Also, new image quality standards for CT lung cancer screening data acquisition are becoming available and these requirements can potentially be evaluated against actual scans acquired. Another important benefit that is enabled by CT lung cancer screening image data registries is the potential to identify new imaging biomarkers as well as help improve existing imaging biomarkers. A persistent challenge for lung cancer imaging research groups is to continuously collect lung cancer screening image data obtained from current day patients and using modern CT scanners. Given that CT scanner technology and methods are changing rapidly it is particularly important to have a large continuous source of imaging data, which a large image-based registry can provide. In addition to informed consent to conduct research and patient privacy protections, studies based on registry data can support the lung cancer imaging research community by further collecting additional quantitative metadata with each CT scan. The collection of images allows for retrospective reviews of imaging findings that were not known to be important for the different diseases that may occur in the lungs. One such example is recognition of early interstitial lung disease which can be as deadly as lung cancer [4]. Having the prior images for review once a diagnosis is made allows for future early recognition and for development of follow-up recommendations. Growing recognition of subtypes of nodules (subsolid and solid), both solitary and multiple ones, and review of prior imaging has been important in limiting invasive procedures for certain subtypes [5, 6]. Automated methods can potentially be used by image-based registries to calculate and store the location, surface geometry, and volume of the lungs, suspicious nodules, cancer tumors, and relevant anatomy and pathology. If data transmission bandwidth is a roadblock to collecting image data, automated methods can be employed to at least collect images of identified lung cancers and other targeted areas (e.g. suspicious lung nodule regions). Another opportunity is to document the fundamental image quality characteristics of CT scans, as is becoming available using automated methods. Documenting image quality information within large lung cancer screening image datasets will enable the research community to better understand the relationship between image quality and measures of lung cancer screening success, such as the ability to detect and measure small lung nodules. This data will be critical to help inform the establishment of new minimum imaging standards that are being developed for lung cancer screening studies. Over the next few years several new lung cancer screening initiatives will launch in the United States including an effort to deploy lung cancer screening services at US Department of Veterans Affairs Medical Centers. These lung cancer screening studies will offer a fresh opportunity to collect lung cancer screening image data with modern tools, research targets, and methods. References 1. CMS recommendation to support reimbursement for lung cancer screening, , February 5, 2015. 2. Pederson JH, Ashraf H, Implementation and organization of lung cancer screening, Ann Transl Med. 2016 Apr; 4(8): 152. 3. Yankelevitz DF, Henschke CI, Advancing and sharing the knowledge base of CT screening for lung cancer, Ann Transl Med. 2016 Apr; 4(8): 154. 4. Salvatore M, Henschke CI, Yip R, Jacobi A, Eber C, Padilla M, Koll A, Yankelevitz D. Journal Club: Evidence of Interstitial Lung Disease on Low-Dose Chest CT: Prevalence, Patterns and Progression. AJR AM J Roentgenol 2016: 206:487-94 5. Yankelevitz DF, Yip R, Smith JP, Liang M, Liu Y, Xu DM, Salvatore M, Wolf A, Flores R, Henschke CI. CT screening for lung cancer: nonsolid nodules in baseline and annual repeat rounds. Radiology 2015; 277: 555-64 6. Henschke CI, Yip R, Wolf A, Flores R, Liang M, Salvatore M, Liu Y, Xu DM, Smith JP, Yankelevitz DF. CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds. AJR Am J Roentgenol 2016; 11:1-9
    
    

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    WS 01.21 - Session 4: The Concept of Collaboration in CT Screening Programs (ID 10659)

    13:25 - 13:25  |  Presenting Author(s): David F Yankelevitz
    • Abstract

    Abstract not provided

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    WS 01.23 - Radiology Leading But Integrated? (ID 10664)

    13:33 - 13:41  |  Presenting Author(s): David F Yankelevitz
    • Abstract

    Abstract:
    Screening programs require the coordination of multiple disciplines, including radiology, pulmonology, thoracic surgery and pathology. Each provides critical components for the management of screening findings beginning with the initial screening finding and all the way through treatment. In addition, there needs to coordination with the necessary support staff, including coordinators, nurse practitioners and radiology technologists. Screening programs are typically led by radiologists, but this varies with some programs led by pulmonary medicine and others by thoracic surgery, nevertheless integration is required. Part of the challenge of screening is the information that is provided by the initial screening test, the low dose CT scan, involves an extensive amount of information. First and foremost, it provides information regarding findings related to potential lung cancer, notably lung nodules. These are now typically managed through a protocol that has been adopted by that institution. In the United States, typically Lung–RADs is followed, although others are also used and outside the US other countries also have various protocols. Beyond the findings related to potential lung cancer, the CT scan also identifies findings related to a variety of other illnesses. Most prominent has been coronary artery calcium. Currently, in the US, it is required to make note of this findings in order to submit insurance claims. Recently, a joint statement was developed by the Society of Cardiovascular Computed Tomography and Society of Thoracic Radiology for how to manage these findings. In addition to the cardiac findings there are other findings that can be made on the CT scan where there is already evidence of their importance. One of the most common findings in screening exams includes emphysema. While the majority of participants in screening programs know that they have emphysema, a substantial minority are unaware including even a small percentage with CT evidence of severe emphysema. While this finding is routinely reported, no specific recommendation is made regarding what to do in terms of seeing a pulmonologist or even getting pulmonary function studies. A variety of other findings can also be made and quantified such as pulmonary artery size, aortic calcification, breast density, bone density and even liver density. In each of these examples various quantitative metrics can be ascertained, the challenge remains as to how to utilize these measures in a clinical management protocol that fits within the framework of a particular health care institution. In a recent editorial published in Radiology regarding the ability to now measure and quantify these types of findings, the authors noted the following, “Rather than shying away from this new responsibility, the radiology leadership should embrace the possibility of adding a new dimension to our profession…In doing so, we can also expand our role and value in the overall well-being of patients in the current climate of health care reform.” Beyond the issue of reporting findings and developing management plans, potentially specific to the institution, there are two additional areas where deep integration within the healthcare system are necessary. First and perhaps most important is smoking cessation. While some form of smoking cessation counseling is required in the US in order to obtain reimbursement from CMS, full deployment of resources in this would seem to be a natural extension of any screening program and here the health care benefits, especially in regard to heart disease become apparent quickly. A second and more challenging area in regard to integration is the actual message regarding screening and potential benefits. Here there is great confusion is not only among the radiologists, but among referring clinician as well. Results of the NLST underestimate the benefit for a person enrolled in a screening program over the long term. The challenge of understanding that clinical trials do not fully reflect what will happen once they are brought out into the community is becoming an increasingly important topic in therapeutics, but it is particularly evident in screening where by necessity, the screening is only provided for a very limited time frame for those in the trial, but in fact, people enrolled in a trial will have ongoing screening perhaps for as long as 20 years. The potential benefit here is substantially different than what can be directly measured based on just results from a trial such as NLST with only 3 rounds of screening and a follow up period that does not include screening. Specific examples of various image findings and recommendations will be provided. In addition, examples of what might be told to people who are interested in enrolling in a screening program will also be explored.
    
    

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    WS 01.42 - 4. Can we Implement International Standards for Quantitative CT Imaging within Lung Cancer? (ID 10687)

    18:00 - 18:00  |  Presenting Author(s): David F Yankelevitz
    • Abstract

    Abstract not provided

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  WS 02 - IASLC Symposium on the Advances in Lung Cancer CT Screening (Ticketed Session SOLD OUT) (ID 631)

  • Event: WCLC 2017
  • Type: Symposium
  • Track: Radiology/Staging/Screening
  • Presentations: 3
  • Moderators:
  • Coordinates: 10/14/2017, 09:00 - 18:15, F201 + F202 (Annex Hall)

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    WS 02.03 - Lung Cancer Screening – IELCAP Contribution to CT Screening Implementation (ID 10620)

    09:10 - 10:10  |  Author(s): David F Yankelevitz
    • Abstract
    • Presentation

    Abstract:
    1. Introduction of CT screening and showing its value. First to introduce CT screening in a novel cohort design comparing CT with chest radiography, providing a workup strategy for screen-detected nodules. Predicted outcome of well-designed and correctly powered RCT studies Henschke C, McCauley D, Yankelevitz D, Naidich D, McGuinness G, Miettinen O, Libby D, Pasmantier M, Koizumi J, Altorki N, and Smith J. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999; 354:99-105. 2. Long-term survival rates of patients diagnosed with lung cancer in a program of CT screening. First to provide estimated cure rates under screening by measuring long-term survivial. The International Early Lung Cancer Action Program Investigators. Survival of Patients with Stage I lung cancer detected on CT screening. NEJM 2006; 355:1763-71 3. First to provide information on the value of CT scans in delivering smoking cessation advice. Ostroff J, Buckshee N, Mancuso C, Yankelevitz D, and Henschke C. Smoking cessation following CT screening for early detection of lung cancer. Prev Med 2001; 33:613-21. Anderson CM, Yip R, Henschke CI, Yankelevitz DF, Ostroff JS, and Burns DM. Smoking cessation and relapse during a lung cancer screening program. Cancer Epidemiol Biomarkers Prev 2009; 18:3476-83. 4. First to introduce computer-assisted CT determined growth rates into the workup of pulmonary nodules. Yankelevitz DF, Gupta R, Zhao B, and Henschke CI. Small pulmonary nodules: evaluation with repeat CT--preliminary experience. Radiology 1999; 212:561-6. Yankelevitz DF, Reeves AP, Kostis WJ, Zhao B, and Henschke CI. Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. Radiology 2000; 217:251-6. Kostis WJ, Yankelevitz DF, Reeves AP, Fluture SC, Henschke CI. Small pulmonary nodules: reproducibility of three-dimensional volumetric measurement and estimation of time to follow-up CT. Radiology 2004; 231:446-52. Henschke C, Yankelevitz D, Yip R, Reeves A, Farooqi A, Xu D, Smith J, Libby D, Pasmantier M, and Miettinen O. Lung cancers diagnosed at annual CT screening: volume doubling times. Radiology 2012; 263:578-83. 5. Development of size threshold values and short-term followup and importance of a regimen of screening. Henschke C, Yankelevitz D, Naidich D, McCauley D, McGuinness G, Libby D, Smith J, Pasmantier M, and Miettinen O. CT screening for lung cancer: suspiciousness of nodules according to size on baseline scans. Radiology 2004; 231:164-8. Libby DM, Wu N, Lee IJ, Farooqi A, Smith JP, Pasmantier MW, McCauley D, Yankelevitz DF, and Henschke CI. CT screening for lung cancer: the value of short-term CT follow-up. Chest 2006; 129:1039-42. Henschke C, Yip R, Yankelevitz D, and Smith J. Definition of a positive test result in computed tomography screening for lung cancer: a cohort study. Ann Intern Med 2013; 158:246- 52. Yip R, Henschke CI, Yankelevitz DF, and Smith JP. CT screening for lung cancer: alternative definitions of positive test result based on the national lung screening trial and international early lung cancer action program databases. Radiology 2014; 273:591-6. Yip R, Henschke C, Yankelevitz D, Boffetta P, Smith J, The International Early Lung Cancer Investigators. The impact of the regimen of screening on lung cancer cure: a comparison of I-ELCAP and NLST. Eur J Cancer Prev. 2015;24(3):201-8. 6. Nomenclature and management protocols for nonsolid and part-solid nodules. Henschke C, Yankelevitz D, Mirtcheva R, McGuinness G, McCauley D, and Miettinen O. CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules. AJR Am J Roentgenol 2002; 178:1053-7. Yankelevitz DF, Yip R, Smith JP, Liang M, Liu Y, Xu DM, Salvatore MM, Wolf AS, Flores RM, Henschke CI, and International Early Lung Cancer Action Program Investigators Group. CT Screening for Lung Cancer: Nonsolid Nodules in Baseline and Annual Repeat Rounds. Radiology 2015; 277:555-64. Henschke CI, Yip R, Wolf A, Flores R, Liang M, Salvatore M, Liu Y, Xu DM, Smith JP, Yankelevitz DF. CT screening for lung cancer: part-solid nodules in baseline and annual repeat rounds. AJR Am J Roentgenol 2016; 11:1-9. 7. Differences in management of nodules found in baseline and annual repeat rounds of screening. International Early Lung Cancer Investigators. Baseline and annual repeat rounds of screening: implications for optimal regimens of screening. Eur Radiol 2017. In press. 8. Assessment of risk of lung cancer among women and never smokers. International Early Lung Cancer Action Program Investigators. Women’s susceptibility to tobacco carcinogens and survival after diagnosis of lung cancer. JAMA 2006; 296:180-4. Yankelevitz DF, Henschke CI, Yip R, Boffetta P, Shemesh J, Cham MD, Narula J, Hecht HS, FAMRI-IELCAP Investigators. Second-hand tobacco smoke in never smokers is a significant risk factor for coronary artery calcification. JACC Cardiovasc Imaging 2013; 6:651-7. Henschke CI, Yip R, Boffetta P, Markowitz S, Miller A, Hanaoka T, Zulueta J, Yankelevitz D. CT screening for lung cancer: importance of emphysema for never smokers and smokers. Lung Cancer 2015; 88:42-7 PMID:25698134. Yankelevitz DF, Cham MD, Hecht HS, Yip R, Shemesh S, Narula J, Henschke CI. The Association of Secondhand Tobacco Smoke and CT angiography-verified coronary atherosclerosis. JACC Imaging. 2016. 9. Determination of cardiac risk on nongated, low-dose CT scans and development of an ordinal scale. Shemesh J, Henschke CI, Farooqi A, Yip R, Yankelevitz DF, Shaham D, and Miettinen OS. Frequency of coronary artery calcification on low-dose computed tomography screening for lung cancer. Clin Imaging 2006; 30:181-5. Shemesh J, Henschke CI, Shaham D, Yip R, Farooqi AO, Cham MD, McCauley DI, Chen M, Smith JP, Libby DM, Pasmantier MW, and Yankelevitz DF. Ordinal scoring of coronary artery calcifications on low-dose CT scans of the chest is predictive of death from cardiovascular disease. Radiology 2010; 257:541-8. 10. Recommendations for reporting findings of emphysema, coronary arteries, breast, and abdomen on low-dose CT scans. Zulueta JJ, Wisnivesky JP, Henschke CI, Yip R, Farooqi AO, McCauley DI, Chen M, Libby DM, Smith JP, Pasmantier MW, and Yankelevitz DF. Emphysema scores predict death from COPD and lung cancer. Chest 2012. Henschke CI, Lee IJ, Wu N, Farooqi A, Khan A, Yankelevitz D, and Altorki NK. CT screening for lung cancer: prevalence and incidence of mediastinal masses. Radiology 2006; 239:586-90. Salvatore M, Margolies L, Kale M, Wisnivesky J, Kotkin S, Henschke CI, and Yankelevitz DF. Breast density: comparison of chest CT with mammography. Radiology 2014; 270:67-73. Hu M, Yip R, Yankelevitz D, and Henschke C. CT screening for lung cancer: frequency of enlarged adrenal glands identified in baseline and annual repeat rounds. Eur Radiol 2016. Chen X, Li K, Yip R, Perumalswami P, Branch AD, Lewis S, Del Bello D, Becker BJ, Yankelevitz DF, and Henschke CI. Hepatic steatosis in participants in a program of low-dose CT screening for lung cancer. European Journal of Radiology 2017. In Press. 11. Quantatative assessment of the vascular system on low-dose CT scans. Fully automated evaluation of quantitaive image biomarkers for multple organs and anatomic regions including: pulmoanry nodules, lungs (emphysema, ILD, major airways), coronary arteries, aorta, pulmoanry artery, breast, and vertebra. Kostis, W. J., Reeves, A. P., Yankelevitz, D. F., and Henschke, C. I. Three-dimensional segmentation and growth-rate estimation of small pulmonary nodules in helical CT images. IEEE Transactions on Medical Imaging 2003; 22: 1259-1274. Enquobahrie, A., Reeves, A. P., Yankelevitz, D. F., and Henschke, C. I. Automated detection of small solid pulmonary nodules in whole lung CT scans from a lung cancer screening study. Academic Radiology 2003; 14, 5: 579-593. Keller, B. M., Reeves, A. P., Henschke, C. I., and Yankelevitz, D. F. Multivariate Compensation of Quantitative Pulmonary Emphysema Metric Variation from Low-Dose, Whole-Lung CT Scans. AJR 2011; 197, 3: W495-W502. Xie Y. Htwe YM, Padgett J, Henschke CI, Yankelevitz DF, Reeves AP. Automated aortic calcification detection in low-dose chest CT images. SPIE Medical Imaging 2014; 9035:90250P. Xie Y, Cham M, Henschke CI, Yankelevitz DF, Reeves AP. Automated coronary artery calcification detection on low-dose chest CT images. SPIE Medical Imaging 2014; 9035:90250F.
    
    

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    WS 02.09 - Lung Cancer Guidelines (ID 10624)

    12:00 - 13:00  |  Presenting Author(s): David F Yankelevitz
    • Abstract
    • Presentation

    Abstract not provided

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    WS 02.15 - Quality Control for Lung Imaging Biomarkers (ID 10628)

    15:30 - 16:00  |  Author(s): David F Yankelevitz
    • Abstract
    • Presentation

    Abstract:
    Computed Tomography (CT) imaging of the lung has been routinely used over the last few decades to detect and treat early lung cancer and other related diseases. As CT image acquisition technology has improved, the use of CT for quantitative and precise lung imaging clinical applications has greatly expanded. High resolution CT studies, which now easily obtain sub-millimeter resolution of the entire chest within a breath-hold, are now widely used to detect and measure changes in early lung cancer lesions and COPD. Traditionally, several concurrent methods have been used to ensure that the quality of acquired CT images is adequate for general clinical use. This includes regular scanning and analysis of CT quality control phantoms from ACR (as well as from individual CT scanner manufacturers) and visual inspection of acquired images by radiologists for significant image artifacts. While these methods have served the field of radiology well for identifying and correcting major image quality issues, there has not been standard image quality assessment methods available for specific clinical applications that require precise image-based measurements. To improve global quality control of lung imaging studies, several clinical societies and organizations have provided image acquisition and measurement guidance documents intended to be followed by clinical sites [1, 2, 3]. We are entering a new era of quantitative imaging where easy to use tools are available that ensure that precise quantitative image measurements can be routinely and reliably obtained. To achieve this goal, a new set of task-based image quality control measures is being developed by research groups and radiology societies such as the RSNA’s Quantitative Imaging Biomarkers Alliance [4]. Each major quantitative imaging-based clinical task is being extensively studied to determine the fundamental image quality properties needed (e.g. resolution, sampling rate, noise, intensity linearity, spatial warping) to achieve a minimum level of measurement performance. In addition, new low-cost phantoms are being developed that can be quickly scanned and automatically analyzed to estimate these fundamental properties throughout the full three-dimensional CT scanner field of view. Deploying these low-cost phantoms and automated phantom analysis software on the cloud further enables global clinical sites to quickly and easily verify the quality of a CT scanner and acquisition protocol for a specific quantitative clinical task. In addition to providing a fast method for verifying conformance with minimum quantitative imaging performance standards, the reports generated can provide guidance as to the best protocols observed for a particular CT scanner model, thereby allowing a clinical site to optimize image acquisition protocols with the best evidence obtained through crowd-sourcing task-specific image quality information. The QIBA CT lung nodule task force is now preparing to launch a pilot project to evaluate the utility of these new image quality control measures for the quantitative measurement of the change in volume of solid lung nodules (6mm to 10mm diameter) [5]. Over the coming months this new “active” and cloud-based analysis approach will be deployed at international lung cancer screening institutions and use statistics will be assembled. The data collected has the potential not only to inform the lung cancer screening community on the global quality of lung cancer screening imaging, but also to establish early data on whether these new methods can one day serve as a more effective approach to providing quality control for quantitative imaging methods. References 1. Kauczor HU, Bonomo L, Gaga M, Nackaerts K, Peled N, Prokop M, Remy-Jardin M, von Stackelberg O, Sculier JP; European Society of Radiology (ESR); European Respiratory Society (ERS), ESR/ERS white paper on lung cancer screening, ESR/ERS white paper on lung cancer screening. 2. IELCAP, IELCAP Protocol Document, http://www.ielcap.org/sites/default/files/I-ELCAP-protocol.pdf Accessed May 31, 2017. 3. Fintelmann FJ, Bernheim A, Digumarthy SR, Lennes IT, Kalra MK, Gilman MD, Sharma A, Flores EJ, Muse VV, Shepard JA, The 10 Pillars of Lung Cancer Screening: Rationale and Logistics of a Lung Cancer Screening Program, Radiographics. 2015 Nov-Dec;35(7):1893-908. 4. https://www.rsna.org/QIBA/ 5. RSNA QIBA, Draft QIBA Profile: Lung Nodule Volume Assessment and Monitoring in Low Dose CT Screening, http://qibawiki.rsna.org/images/e/e6/QIBA_CT_Vol_LungNoduleAssessmentInCTScreening_2017.05.15.docx, May 15, 2017.
    
    

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