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K. Garg
Moderator of
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ORAL 24 - CT Detected Nodules - Predicting Biological Outcome (ID 122)
- Event: WCLC 2015
- Type: Oral Session
- Track: Screening and Early Detection
- Presentations: 8
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ORAL24.01 - Natural History of Pulmonary Subsolid Nodules: A Prospective Multicenter Study (ID 1245)
10:45 - 10:56 | Author(s): R. Kakinuma, K. Ashizawa, M. Noguchi, N. Koizumi, T. Kondo, K. Kuriyama, H. Matsuguma, H. Ohmatsu, J. Okami, H. Suehisa, A.M. Maeshima, T. Yamaji, Y. Matsuno, S. Murayama, K. Murata
- Abstract
- Presentation
Background:
The purpose of this prospective multicenter study was to evaluate the natural course of progression of pulmonary subsolid nodules.
Methods:
Eight facilities participated in this prospective study. This study was conducted with the approval of the institutional review board of each of the participating institutions. Written informed consent was obtained from all the patients. A total of 845 patients with 1325 pulmonary subsolid nodules were registered, of whom 795 patients (341 men, 454 women; mean age, 62 years [range, 31-88]) with 1238 subsolid nodules were selected as being eligible for this study. In this study, the pulmonary subsolid nodules were classified into three categories: pure ground-glass nodules (hereafter abbreviated as PGGNs), heterogeneous GGNs (solid component detected only in the lung window setting; hereafter abbreviated as HGGN), and part-solid nodules (solid component also detected in the mediastinal window setting). The CT images of the nodules that showed progression were reviewed by an expert radiologists’ panel. Pathological specimens of the resected nodules were reviewed by an expert pathologists’ panel.
Results:
The mean prospective follow-up period was 4.3 ± 2.5 years (range, 0.2–12.1; median, 3.5 [IQR, 2.4–6.0]). After exclusion of 9 resected nodules (2 no-lung-cancer nodules and 7 lung cancers not reviewed by the expert pathologists’ panel), the pulmonary subsolid nodules were classified as follows at the baseline: 1046 PGGNs, 81 HGGNs, and 102 part-solid nodules. Among the 1047 PGGNs, 13 (13/1046; 1.2%) developed into HGGNs, and 56 (56/1046; 5.4%) developed into part-solid nodules. Among the 81 HGGNs, 16 (16/81; 19.8%) developed into part-solid nodules. Thus, the subsolid nodules were classified as follows at the time of the final follow-up: 977 PGGNs, 78 HGGNs and 174 part-solid nodules. Of the 977 PGGNs, 35 (3.6%) were resected; from the histopathologic standpoint, the 35 resected PGGNs consisted of 9 minimally invasive adenocarcinomas (MIAs), 21 adenocarcinomas in situ (AISs), and 5 atypical adenomatous hyperplasias (AAHs). Of the 78 HGGNs, 7 (9%) were resected; from the histopathologic standpoint, the 7 HGGNs consisted of 5 MIAs and 2 AISs. Of the 174 part-solid nodules, 49 (28.2%) were resected; from the histopathologic standpoint, the 49 part-solid nodules consisted of 12 invasive adenocarcinomas, 26 MIAs, 10 AISs, and 1 AAHs. In total, 12 (12/1229, 1%) invasive adenocarcinomas, 40 (40/1229; 3.3%) MIAs, 33 (33/1229; 2.7%) AISs, and 6 (6/1229; 0.5%) AAHs were resected as of December 31, 2013; For the PGGNs, the mean period to development into part-solid nodules was 3.8 ± 2.0 years (range, 0.5-8.7; median, 3.4 [IQR, 2.0–5.2]); for the HGGNs, the mean period to development into part-solid nodules was 2.1 ± 2.3 years (range, 0.2–8.8; median, 1.0 [IQR, 0.7–3.4]) (P=0.0004).
Conclusion:
Our prospective multicenter study revealed the frequency and period of development from PGGNs and HGGNs into part-solid nodules. Invasive adenocarcinomas were only diagnosed in the part-solid nodules. The findings of the study may contribute to the development of guidelines for follow-up of pulmonary subsolid nodules.
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ORAL24.02 - Quantification of Growth Patterns of Screen-Detected Lung Cancers: The NELSON Trial (ID 1455)
10:56 - 11:07 | Author(s): M.A. Heuvelmans, R. Vliegenthart, M.J.A.M. Van Putten, P.A. De Jong, M. Oudkerk
- Abstract
Background:
A wait-and-see principle is not commonly used when lung cancer is suspected, because of the aggressiveness of the disease. In-vivo information on growth patterns of lung cancers, from small nodules barely detectable by imaging techniques to histologically proven lung cancers, is therefore scarce. In low-dose computed tomography (LDCT) lung screening, lung nodules, usually benign, are found in the majority of screenees. Follow-up CT examinations are performed to determine nodule growth, in order to differentiate between benign and malignant nodules. Growth is often defined in terms of volume-doubling time (VDT), under the assumption of exponential growth. However, this pattern has never been quantified in actual patient data. Our purpose was to evaluate and quantify growth patterns of lung cancers detected in LDCT lung cancer screening, in order to elucidate the development and progression of early lung cancer.
Methods:
The study was based on data of the Dutch-Belgian randomized lung cancer screening trial (NELSON trial). Solid lung cancers detected at ≥3 LDCT examinations before referral and diagnosis were included. Nodule volume was calculated by semi-automated software (LungCARE, Siemens, Erlangen). We fitted lung cancer volume (V) growth curves with a single exponential, expressed as V=V~1~exp(t/τ), with t time from baseline (days), V~1~ estimated volume at baseline (mm[3]) and τ estimated time constant. Overall VDT per lung cancer for all time points combined was calculated using τ*log(2). We used R[2] coefficient of determination as a measure for goodness of fit, where a perfect fit results in R[2]=1. A normalized growth curve for all lung cancers combined was created by plotting normalized volume (V/V~1~), on a logarithmic y-axis as a function of normalized time, t*=t/τ. Statistical analyses were performed using SPSS 20.0 and Octave (www.octave.org).
Results:
Forty-seven lung cancers in 46 participants were included. Seven participants were female (13.0%); mean age 61.7 ±6.2 years. Median follow-up time before lung cancer was diagnosed, was 770 days (IQR: 383-1102 days). One cancer (2.1%) was diagnosed after six LDCTs, six (12.8%) after five LDCTs, 14 (29.8%) after four LDCTs, and 26 cancers (55.3%) after three LDCTs. Most lung cancers were stage I disease (35/47, 74.5%) at diagnosis. The majority concerned adenocarcinoma (38/48, 80.9%). Median overall VDT was 348 days (IQR: 222-492). Overall VDT for adenocarcinomas versus other histological cancer types were similar (median 338 days [IQR: 225-470 days] versus 348 days [IQR: 153-558 days], respectively [p=NS]). Good fit to exponential growth was confirmed by the high R[2] coefficient of determination for the individual cancer growth curves (median 0.98; IQR: 0.94-0.99). After normalization, we found linear growth on a logarithmic scale, according to exponential growth, for almost all nodules. Not all cancers showed an exponential growth immediately from baseline; five cancers were identified with constant (low) volume for >500 days before growth expansion occurred. However, when these dormant lung cancers started growing, they followed the exponential function with excellent fit (median 1.00; IQR: 0.98-1.00).
Conclusion:
Screen-detected lung cancers usually evolve at an exponential growth rate. This makes VDT a powerful imaging biomarker to stratify prevalent lung nodules to growth rates.
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ORAL24.03 - Increasing Incidence of Non-Smoking Lung Cancer: Presentation of Patients with Early Disease to a Tertiary Institution in the UK (ID 2717)
11:07 - 11:18 | Author(s): C. Proli, M.E. Cufari, M. Phull, H. Raubenheimer, M. Al Sahaf, N. Asadi, P. Perikleous, A. Allan, L. Shedden, H. Chavan, Z. Niwaz, A. Kubler, A.G. Nicholson, P. Viola, V. Anikin, E. Beddow, N. McGonigle, M. Dusmet, S. Jordan, G. Ladas, E. Lim
- Abstract
- Presentation
Background:
Lung cancer in never-smokers is recognised as a distinct entity. Many are expected to present late. As there are no established aetiological factors, identification of patients at risk is challenging. The aim of the study is to define the incidence and clinical features of never-smokers presenting sufficiently early for surgery to determine if it is possible to identify patients at risk.
Methods:
We retrospectively analysed data from a prospectively collected database of patients who underwent surgery at our institution. The incidence was defined as number of never-smokers versus current and ex-smokers by year. Clinical features at presentation were obtained and collated as frequency (percentage).
Results:
A total of 2170 patients underwent surgical resection for lung cancer from March 2008 to November 2014. The annual incidence of developing lung cancer in never-smokers increased from 13, 15, 18, 19, 20, 20 to 28 percent respectively, attributable to an absolute increase in number and not a change in the ratio of never smokers to current and ex-smokers. A total of 436 (20%) patients were never smokers. The mean age at presentation was 60 (16 SD) years and 295 (67%) were female. Good lung function was observed with mean predicted FEV1 of 90% (23 SD) and FVC of 97% (25 SD). The majority histological types were adenocarcinoma 54% and carcinoid 27%. The main presenting features were non-specific consisting of cough in 142 (34%), chest infections in 75 (18%) and haemoptysis in 46 (11%). Recurrent chest infections were predominantly a symptom of central carcinoid tumours (30 versus 15 percent; P=0.004). A total of 59 (14%) were detected on incidental chest film, 127 (30%) on incidental CT, 32 (7%) on incidental PET/CT and 4(1%) on incidental MRI.
Conclusion:
We observed more than double the annual incidence of never smokers presenting with non small cell lung cancer, in the last 7 years, increasing from 13 to 28 percent, and hypothesise that this is representative of the UK, as we are one of the highest surgical volume centres in our country. Patients present with non-specific symptoms and the majority were detected on incidental imaging. We conclude that imaging is likely to play a more important role and further efforts need to be expended on early detection of lung cancer in this increasing cohort without any observable risk factors.
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ORAL24.04 - Discussant for ORAL24.01, ORAL24.02, ORAL24.03 (ID 3358)
11:18 - 11:28 | Author(s): G. Veronesi
- Abstract
- Presentation
Abstract not provided
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ORAL24.05 - Reclassification of Lung Cancers Detected by CT Imaging in the American College of Radiology Imaging Network National Lung Screening Trial (ID 1454)
11:28 - 11:39 | Author(s): W.A. Franklin, D.T. Merrick, R.D. Achcar, D.R. Aberle
- Abstract
- Presentation
Background:
The National Lung Screening Trial (NLST) found a 20% reduction in lung cancer-specific mortality using low dose CT vs chest radiography for screening. The magnitude of mortality benefit has been questioned given that a higher proportion of tumors in the CT arm were diagnosed as “bronchioloalveolar cell carcinoma”. Subsequent to the initiation of the NLST, the pathological classification of lung cancer was revised to take into account the reported favorable outcome for solitary in situ nodules <3 cm. The term “bronchioloalveolar carcinoma” (BAC) was eliminated in favor of the more explicit terms adenocarcinoma in situ (AIS), microinvasive adenocarcinoma (MIA), and invasive carcinoma with various predominant histological patterns. To better assess the impact of these recent changes in the Pathological classification of lung cancer on possible over-diagnosis in the NLST, we have reviewed the histology of lung tumors detected through the ACRIN-NLST trial and reclassified them according to the most recent WHO pathology classification.
Methods:
Histology was initially classified by the pathologists at sites where NLST participants were managed. Representative slides of 192 surgical resection specimens and 15 non-surgical biopsies from 207 patients were collected from 19 participating institutions. Digital images were prepared from 533 glass H&E stained slides using an Aperio digital slide imager. Digital images were examined by three pulmonary pathologists (WAF, DTM and JDH) and reclassified according to criteria and nomenclature of the recently published 2015 edition of the WHO classification.
Results:
There was 92% concordance between submitting and reference pathologists when cases were grouped into the broad categories of adenocarcinoma, squamous carcinoma, neuroendocrine and large cell lung carcinoma (LCLC). The WHO classification permitted a more detailed analysis of the tumors. Invasive adenocarcinoma was the largest tumor category comprising 61% (127) of all tumors and included 70 acinar tumors, 23 solid, 13 papillary, 8 micropapillary, 5 mixed mucinous/non-mucinous, 4 invasive mucinous, 3 lepidic and 1 adenocarcinoma that could not be further classified. There were 48 (23%) squamous tumors, 10 (5%) LCLC, 15 (7%) neuroendocrine tumors including 6 (3%) small cell lung carcinomas. Finally, one tumor had sarcomatoid histology and an additional tumor was classified at sclerosing pneumocytoma. On reclassification, only 5 of the 26 tumors originally referred to as BAC or as having BAC features by submitting pathologists met criteria for adenocarcinoma in situ or minimally invasive carcinoma. Twenty-one of these 26 tumors were reclassified as invasive adenocarcinoma, most frequently acinar pattern predominant (8 cases).
Conclusion:
Reclassification of tumors identified through low dose CT screening in the National Lung Screening Trial permitted a detailed analysis of histological features and should permit a more nuanced assessment of biology and prognosis of this important cohort than has been available to date. Reclassification of BAC mainly as invasive adenocarcinoma conflicts with the suggestion that much of the benefit in the NLST CT screening trial was derived from surgical removal presumably non-invasive low grade tumor. *ACRIN received funding from the National Cancer Institute through the grants U01 CA079778 and U01 CA080098.
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ORAL24.06 - Stratification of Lung Adenocarcinomas in the National Lung Screening Trial (ID 102)
11:39 - 11:50 | Author(s): F. Maldonado, F. Duan, S. Raghunath, S. Rajagopalan, R. Karwoski, K. Garg, E. Greco, H. Nath, R. Robb, B. Bartholmai, T. Peikert
- Abstract
- Presentation
Background:
Screening for lung cancer with low-dose computed tomography (LDCT) was shown to reduce lung cancer mortality. However, lung cancer screening also detects indolent cancers of unclear clinical significance, which generally belong to the adenocarcinoma spectrum. The individualized management of these more indolent cancers may be facilitated by non-invasive risk stratification. We present our validation study of CANARY (Computer-Aided Nodule Assessment and Risk Yield), a novel LDCT-based software, used to stratify adenocarcinoma nodules in three groups with distinct outcomes.
Methods:
All individuals in the LDCT arm of the National Lung Screening Trial (NLST) with adenocarcinoma were identified. The last LDCT data available were analyzed blinded to clinical data. Using CANARY, all lung adenocarcinoma nodules were classified as Good (G), Intermediate (I) and Poor (P) based on previously established radiologic signatures. This classification was then used for survival analysis using progression-free survival
Results:
LDCT datasets of 294 patients with resected adenocarcinomas with available outcome data were included in the blinded CANARY analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into G, I and P CANARY classes yielded distinct progression-free survival curves (P < 0.0001). A similar separation was seen with adjusted progression-free survival curves, after adjustment for, age, gender, race and smoking status for all pathological stage I cases.
Conclusion:
CANARY allows the non-invasive risk stratification of lung adenocarcinomas into three groups with distinct post-surgical disease-free survival. Our results suggest that CANARY could facilitate individualized management of incidentally- or screen-detected lung adenocarcinomas.
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ORAL24.07 - Behavior Differences of Screen-Detected Lung Cancers in the CT Arm of the National Lung Screening Trial (NLST) (ID 587)
11:50 - 12:01 | Author(s): M.B. Schabath, P.P. Massion, Z.J. Thompson, S.A. Eschrich, Y. Balagurunathan, D. Goldof, D.R. Aberle, R.J. Gillies
- Abstract
Background:
Lung cancer screening identifies cancers with heterogeneous behaviors. In addition to screen-detected incidence lung cancers, screening also identifies prevalence cancers at the baseline screen and interval lung cancers diagnosed following a negative screen at any time point prior to the next screening round. To date, few studies have performed a comprehensive analyses comparing prevalence and interval lung cancers and screen-detected lung cancers based on sequence of screening results in the NLST.
Methods:
The entire CT arm of the NLST was reconstructed according to baseline and follow-up screening results (positive vs. negative screen). Lung cancers immediately following a positive baseline (T0), and prior to the T1 screen, formed the prevalence cancers (PC); interval cancers (IC) were defined as lung cancers diagnosed following a negative screen at any point prior to the next screening round. Two screen-detected lung cancer (SDLC) cohorts were identified based on one (SDLC1) or two (SDLC2) prior positive screens and two screen-detected lung cancer cohorts following one (SDLC3) or two (SDLC4) prior negative screens. Differences in patient characteristics, progression-free survival (PFS), and overall survival (OS) were assessed.
Results:
Since there were no differences in patient characteristics and outcomes between SDLC1 and SDLC2 and between SDLC3 and SDLC4, the four screen-detected cancer case groups were combined into two combined SDLC case groups (SDLC1/SDLC2 and SDLC3/SDLC4). The lung cancer-specific death rate was higher for SDLC3/SDLC4 compared to SDLC1/SDLC2 lung cancers (136.6/1,000 person-years vs. 71.3/1,000 person-years, P < 0.001). PFS and OS were significantly lower for SDLC3/SDLC4 than SDLC1/SDLC2 (P < 0.004; P < 0.002, respectively). Overall, PFS and OS were highest in SDLC1/SDLC2 and lowest in the interval cancers (Figure 1); PFS and OS for the prevalence cancers were intermediate between SDLC1/SDLC2 and SDLC3/SDLC4. All findings were consistent when stratified by stage and histology. Multivariable Cox proportional models revealed that the SDLC3/SDLC4 case groups were associated with significantly poorer PFS (HR=1.72; 95% CI 1.19-2.48) and OS (HR=1.62; 95% CI 1.08-2.45) compared to SDLC1/2 lung cancers (HR=1.00). Figure 1
Conclusion:
This post hoc analysis reveals novel insight to the heterogeneity of lung cancers diagnosed in a screening population. As with interval cancers diagnosed following a negative screen, lung tumors that arise in a lung environment ostensibly free of lung nodules are likely more rapidly growing and aggressive which results in significantly poorer outcomes. Additional research will be needed to understand the potential translational implications of these findings and to reveal biological differences of screen-detected tumors.
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ORAL24.08 - Discussant for ORAL24.05, ORAL24.06, ORAL24.07 (ID 3359)
12:01 - 12:11 | Author(s): M. Noguchi
- Abstract
- Presentation
Abstract not provided
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Author of
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MINI 12 - Biomarkers and Lung Nodule Management (ID 109)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:J.M. Siegfried, H.I. Pass
- Coordinates: 9/07/2015, 16:45 - 18:15, 401-404
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MINI12.02 - Clinical Utility of Chromosomal Aneusomy in High Risk Individuals (ID 1299)
16:50 - 16:55 | Author(s): K. Garg
- Abstract
- Presentation
Background:
In the context of CT screening in current and former smokers at high risk for lung cancer, the false positive rate is high (26% at first NLST screening; 13% with Lung-RADS criteria applied to NLST) and indeterminate nodules are frequently discovered. Noninvasive biomarkers are urgently needed to reduce false positives with screening CT and to improve risk stratification in those with indeterminate nodules. The Colorado (CO) Lung SPORE program performed a retrospective longitudinal evaluation (Pepe Phase 3 validation) to assess the potential of chromosomal aneusomy detected in sputum via fluorescence in situ hybridization (CA-FISH) as a biomarker for early detection in four nested case-control studies. Two of the cohorts (ACRIN/NLST and PLuSS) enrolled current and former smokers to investigate use of low dose CT to diagnose lung cancer. The other two were Colorado cohorts in which pulmonary clinic patients (mostly current and former smokers) were enrolled to investigate biomarkers to predict lung cancer. One of these cohorts (CO High Risk) was a COPD population and the other, still in the accrual phase, comprises patients referred for care of indeterminate lung nodules (CO Nodule).
Methods:
The cohorts were grouped into a Screening cohort (ACRIN/NLST (49 cases, 96 controls) and PLuSS (48 cases, 89 controls)) and a High Risk cohort (CO High Risk (55 cases, 59 controls) and CO Nodule (13 cases, 10 controls)). The CA-FISH assay was a 4-target panel including genomic sequences encompassing the EGFR and MYC genes, and the 5p15 and centromere 6 regions or the FGFR1 and PIK3CA genes. At the subject level, the assay was scored on a 4-category scale representing normal, probably normal, probably abnormal and abnormal. Operating characteristics (with 95% CI) of the assay were estimated for each group of cohorts overall and separately for COPD patients: sensitivity, specificity, likelihood ratio+ (LR+) and likelihood ratio- (LR-).
Results:
Using the cutoff of abnormal vs. not abnormal for CA-FISH, sensitivity and specificity for Screening subjects are 0.20 (0.13, 0.30) and 0.84 (0.78, 0.89), respectively; and for High Risk subjects are 0.67 (0.55, 0.78) and 0.94 (0.85, 0.98), respectively. Likelihood ratios for Screening subjects are LR+: 1.36 (0.81, 2.28) and LR-: 0.93 (0.83, 1.05), and for High Risk subjects are LR+: 11.66 (4.44, 30.63), and LR-: 0.34 (0.24, 0.48). Similar results were observed when only COPD subjects were analyzed.
Conclusion:
The high LR+ of sputum CA-FISH indicates that this noninvasive biomarker could be a clinically useful adjunct to CT among patients in high risk settings. Whether this same high level of LR+ will be reproducible in patients at high risk because of their indeterminate nodules remains to be seen. If so, a hypothetical patient with indeterminate nodules and a pre-test (CA-FISH) lung cancer risk of 20% would have a post-test probability of lung cancer of 78% if the CA-FISH test were positive. In the screening setting, however, the low LR+ of CA-FISH limits its clinical utility. Prospective assessment of sputum CA-FISH is ongoing in the Nodule Cohort of the CO Lung SPORE.
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MINI 36 - Imaging and Diagnostic Workup (ID 163)
- Event: WCLC 2015
- Type: Mini Oral
- Track: Screening and Early Detection
- Presentations: 1
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MINI36.15 - Discussant for MINI36.11, MINI36.12, MINI36.13, MINI36.14 (ID 3557)
19:50 - 20:00 | Author(s): K. Garg
- Abstract
- Presentation
Abstract not provided
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MTE 10 - Subsolid Nodules: What the Clinicians Need to Know / Clinical Workup of CT Detected Nodules (Ticketed Session) (ID 62)
- Event: WCLC 2015
- Type: Meet the Expert (Ticketed Session)
- Track: Screening and Early Detection
- Presentations: 1
- Moderators:
- Coordinates: 9/07/2015, 07:00 - 08:00, 703
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MTE10.01 - Subsolid Nodules: What the Clinicians Need to Know (ID 1992)
07:00 - 07:30 | Author(s): K. Garg
- Abstract
- Presentation
Abstract:
Subsolid is a relatively new descriptor for a pulmonary nodule. Subsolid nodules include nonsolid or ground glass nodules (GGN) or part-solid nodules (PSN). Pure Ground-Glass Nodule (synonym: nonsolid nodule) is a focal area of increased lung attenuation within which the margins of any normal structures, e.g., vessels or airways remain outlined. Solid Nodule is a focal area of increased attenuation of such density that normal structures are completely obscured. Part-solid Nodule (synonym: semisolid nodule) is a focal nodular opacity containing both solid and ground-glass components. Their relative slow growth and indolent behavior compared to the typical spiculated solid nodule has been recognized over time suggesting the possibility of overdiagnosis. Subsolid pulmonary nodules representing the adenocarcinoma spectrum represent the majority of screening CT detected lung cancers, and the behavior of these lesions seem to differ significantly from their clinically detected counterparts, although the data regarding the natural history of these lesions is limited. Because nodule size and growth are strong predictors for malignancy, the accurate assessment of size at baseline and growth on follow up CT is important in diagnostic work up of indeterminate nodules. Nodule growth can be quantified using either diameter or volume. Recently automated volumetric measurements have been suggested because malignant nodules may grow asymmetrically, and therefore, their growth may remain unnoticed with manual diameter measurements alone. Furthermore manual 2D measurements of small nodules have modest repeatability. It is important to differentiate part-solid nodules from pure ground-glass because a solid component typically represents invasion. Part-Solid nodules (PSN) had much higher malignancy rate (62.5 %) than GGN (19%) or solid nodules (7%) in a recent study (1). Given advances in imaging and molecular pathology, 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 (2). 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. 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. Finding a subsolid nodule is expected to increase as screening CT become more prevalent after CMS approval. 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 (3). Despite the decrease in lung cancer mortality by CT screening in the NLST, significant concerns remain regarding its high false positive rate, overdiagnosis, cost effectiveness and concerns related to radiation burden from repeat CT screens. Radiation dose saving is especially important in patients with lung nodules because of the frequent follow up examinations. 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. This is a significant issue as there is high false positive rate greater than 95% reported in many screening CT studies (95% of 39% positive screen (3 rounds) were false positive and 24% underwent surgery for benign nodule and 73% nonsurgical biopsy revealed benign findings in NLST. 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 (4). 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. Smaller nodules will continue annual screening with low-dose CT (LDCT) in 12 months. Nodules larger than 6 mm and smaller than 8 mm will get follow-up LDCT in 6 months and nodules between the sizes of 8-15 mm will get 3 month LDCT and PET/CT may be used when there is larger than 8 mm solid component. 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 (5). 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 (6-8). 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. References: Henschke C, et al. AJR Am J Roentgenol 2002;178(5):1053–1057 Travis W, Brambilla E, Noguchi M, et al. IASLC/ATS/ERS International multidisciplinary classification of lung adenocarcinoma. J Thoracic Oncol 2011;6:244-285 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 American College of Radiology: Lung-RADS Version 1.0 Assessment Categories Release date: April 28, 2014. Accessed at www.acr.org/Quality Safety/Resources/LungRADS on 17 March, 2015 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 Lambin P, et al. Radiomics:extracting more information from medical images using advanced feature analysis. Eur J Cancer 2012;48 (4):441-446 Gatenby RA, Grove O, Gillies RJ. Radiology 2013;269:8-15 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
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ORAL 24 - CT Detected Nodules - Predicting Biological Outcome (ID 122)
- Event: WCLC 2015
- Type: Oral Session
- Track: Screening and Early Detection
- Presentations: 1
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ORAL24.06 - Stratification of Lung Adenocarcinomas in the National Lung Screening Trial (ID 102)
11:39 - 11:50 | Author(s): K. Garg
- Abstract
- Presentation
Background:
Screening for lung cancer with low-dose computed tomography (LDCT) was shown to reduce lung cancer mortality. However, lung cancer screening also detects indolent cancers of unclear clinical significance, which generally belong to the adenocarcinoma spectrum. The individualized management of these more indolent cancers may be facilitated by non-invasive risk stratification. We present our validation study of CANARY (Computer-Aided Nodule Assessment and Risk Yield), a novel LDCT-based software, used to stratify adenocarcinoma nodules in three groups with distinct outcomes.
Methods:
All individuals in the LDCT arm of the National Lung Screening Trial (NLST) with adenocarcinoma were identified. The last LDCT data available were analyzed blinded to clinical data. Using CANARY, all lung adenocarcinoma nodules were classified as Good (G), Intermediate (I) and Poor (P) based on previously established radiologic signatures. This classification was then used for survival analysis using progression-free survival
Results:
LDCT datasets of 294 patients with resected adenocarcinomas with available outcome data were included in the blinded CANARY analysis. Kaplan-Meier analysis of all the 294 adenocarcinoma nodules stratified into G, I and P CANARY classes yielded distinct progression-free survival curves (P < 0.0001). A similar separation was seen with adjusted progression-free survival curves, after adjustment for, age, gender, race and smoking status for all pathological stage I cases.
Conclusion:
CANARY allows the non-invasive risk stratification of lung adenocarcinomas into three groups with distinct post-surgical disease-free survival. Our results suggest that CANARY could facilitate individualized management of incidentally- or screen-detected lung adenocarcinomas.
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