Interstitial lung abnormalities in a large clinical lung cancer screening cohort: association with mortality and ILD diagnosis.

BACKGROUND: Interstitial lung abnormalities (ILA) are CT findings suggestive of interstitial lung disease in individuals without a prior diagnosis or suspicion of ILD. Previous studies have demonstrated that ILA are associated with clinically significant outcomes including mortality. The aim of this study was to determine the prevalence of ILA in a large CT lung cancer screening program and the association with clinically significant outcomes including mortality, hospitalizations, cancer and ILD diagnosis. METHODS: This was a retrospective study of individuals enrolled in a CT lung cancer screening program from 2012 to 2014. Baseline and longitudinal CT scans were scored for ILA per Fleischner Society guidelines. The primary analyses examined the association between baseline ILA and mortality, all-cause hospitalization, and incidence of lung cancer. Kaplan-Meier plots were generated to visualize the associations between ILA and lung cancer and all-cause mortality. Cox regression proportional hazards models were used to test for this association in both univariate and multivariable models. RESULTS: 1699 subjects met inclusion criteria. 41 (2.4%) had ILA and 101 (5.9%) had indeterminate ILA on baseline CTs. ILD was diagnosed in 10 (24.4%) of 41 with ILA on baseline CT with a mean time from baseline CT to diagnosis of 4.47 ± 2.72 years. On multivariable modeling, the presence of ILA remained a significant predictor of death, HR 3.87 (2.07, 7.21; p < 0.001) when adjusted for age, sex, BMI, pack years and active smoking, but not of lung cancer and all-cause hospital admission. Approximately 50% with baseline ILA had progression on the longitudinal scan. CONCLUSIONS: ILA identified on baseline lung cancer screening exams are associated with all-cause mortality. In addition, a significant proportion of patients with ILA are subsequently diagnosed with ILD and have CT progression on longitudinal scans. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov; No.: NCT04503044.

Improved motivation and readiness to quit shortly after lung cancer screening: Evidence for a teachable moment.

BACKGROUND: For patients at high risk for lung cancer, screening using low-dose computed tomography (lung cancer screening [LCS]) is recommended. The purpose of this study was to examine whether screening may serve as a teachable moment for smoking-related outcomes. METHODS: In a smoking-cessation trial, participants (N = 843) completed 2 phone interviews before randomization: before LCS (T0) and after LCS (T1). By using logistic and linear regression, the authors examined teachable moment variables (perceived risk, lung cancer worry) and outcomes (readiness, motivation, and cigarettes per day [CPD]). RESULTS: Participants were a mean ± SD age of 63.7 ± 5.9 years, had 47.8 ± 7.1 pack-years of smoking, 35.2% had a high school diploma or General Educational Development (high school equivalency) degree or less, and 42.3% were undergoing their first scan. Between T0 and T1, 25.7% of participants increased readiness to quit, 9.6% decreased readiness, and 64.7% reported no change (P < .001). Motivation to quit increased (P < .05) and CPD decreased between assessments (P < .001), but only 1.3% self-reported quitting. Compared with individuals who reported no lung cancer worry/little worry, extreme worry was associated with readiness to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.1-3.0) and with higher motivation (b = 0.83; P < .001) at T1. Individuals undergoing a baseline (vs annual) scan were more ready to quit in the next 30 days (odds ratio, 1.8; 95% CI, 1.3-2.5). CONCLUSIONS: During the brief window between registering for LCS and receiving the results, the authors observed that very few participants quit smoking, but a significant proportion improved on readiness and motivation to quit, particularly among individuals who were undergoing their first scan and those who were extremely worried about lung cancer. These results indicate that providing evidence-based tobacco treatment can build upon this teachable moment.

Outcomes of Positive and Suspicious Findings in Clinical Computed Tomography Lung Cancer Screening and the Road Ahead.

Rationale: Future optimization of computed tomography (CT) lung cancer screening (CTLS) algorithms will depend on clinical outcomes data. Objectives: To report the outcomes of positive and suspicious findings in a clinical CTLS program. Methods: We retrospectively reviewed results for patients from our institution undergoing lung cancer screening from January 2012 through December 2018, with follow-up through December 2019. All exams were retrospectively rescored using Lung-RADS v1.1 (LR). Metrics assessed included positive, probably benign, and suspicious exam rates, frequency/nature of care escalation, and lung cancer detection rates after a positive, probably benign, and suspicious exam result and overall. We calculated time required to resolve suspicious exams as malignant or benign. Results were broken down by subcategories, reason for positive/suspicious designation, and screening round. Results: During the study period 4,301 individuals underwent a total of 10,897 exams. The number of positive (13.9%), suspicious (5.5%), and significant incidental (6.4%) findings was significantly higher at baseline screening. Cancer detection and false-positive rates were 2.0% and 12.3% at baseline versus 1.3% and 5.1% across subsequent screening rounds, respectively. Baseline solid nodule(s) 6 to <8 mm were the only probably benign findings resulting in lung cancer detection within 12 months. New solid nodules 6 to <8 mm were the only LR category 4A (LR4A) findings falling within the LR predicted cancer detection range of 5-15% (12.8%). 38.5% of LR4A cancers were detected within 3 months. Conclusions: Modification of the definition and suggested workup of positive and suspicious lung cancer screening findings appears warranted.

Pathologic and gene expression comparison of CT- screen detected and routinely detected stage I/0 lung adenocarcinoma in NCCN risk-matched cohorts.

INTRODUCTION: Although three randomized control trials have proven mortality benefit of CT lung cancer screening (CTLS), <5% of eligible US smokers are screened. Some attribute this to fear of harm conveyed at shared decision visits, including the harm of overdiagnosis/overtreatment of indolent BAC-like adenocarcinoma. METHODS: Since the frequency of indolent cancers has not been compared between CTLS and routinely detected cohorts, we compare pathology and RNA expression of 86 NCCN high-risk CTLS subjects to 83 high-risk (HR-R) and 51 low-risk (LR-R) routinely detected patients. Indolent adenocarcinoma was defined as previously described for low malignant potential (LMP) adenocarcinoma along with AIS/MIA. Exome RNA sequencing was performed on a subset of high-risk (CTLS and HR-R) FFPE tumor samples. RESULTS: Indolent adenocarcinoma (AIS, MIA, and LMP) showed 100% disease-specific survival (DSS) with similar frequency in CTLS (18%) and HR-R (20%) which were comparatively lower than LR-R (33%). Despite this observation, CTLS exhibited intermediate DSS between HR-R and LR-R (5-year DSS: 88% CTLS, 82% HR-R, & 95% LR-R, p = 0.047), possibly reflecting a 0.4 cm smaller median tumor size and lower frequency of tumor necrosis compared to HR-R. WGCNA gene modules derived from TCGA lung adenocarcinoma correlated with aggressive histologic patterns, mitotic activity, and tumor invasive features, but no significant differential expression between CTLS and HR-R was observed. CONCLUSION: CTLS subjects are at no greater risk of overdiagnosis from indolent adenocarcinoma (AIS, MIA, and LMP) than risk-matched patients whose cancers are discovered in routine clinical practice. Improved outcomes likely reflect detection and treatment at smaller size.

Qualitative coronary artery calcification scores and risk of all cause, COPD and pneumonia hospital admission in a large CT lung cancer screening cohort.

BACKGROUND: Patients at high-risk for lung cancer and qualified for CT lung cancer screening (CTLS) are at risk for numerous cardio-pulmonary comorbidities. We sought to examine if qualitatively assessed coronary artery calcifications (CAC) on CTLS exams could identify patients at increased risk for non-cardiovascular events such as all cause, COPD and pneumonia related hospitalization and to verify previously reported associations between CAC and mortality and cardiovascular events. STUDY DESIGN AND METHODS: Patients (n = 4673) from Lahey Hospital and Medical Center who underwent CTLS from January 12, 2012 through September 30, 2017 were included with clinical follow-up through September 30, 2019. CTLS exams were qualitatively scored for the presence and severity of CAC at the time of exam interpretation using a four point scale: none, mild, moderate, and marked. Multivariable Cox regression models were used to evaluate the association between CT qualitative CAC and all-cause, COPD-related, and pneumonia-related hospital admissions. RESULTS: 3631 (78%) of individuals undergoing CTLS had some degree of CAC on their baseline exam: 1308 (28.0%), 1128 (24.1%), and 1195 (25.6%) had mild, moderate and marked coronary calcification, respectively. Marked CAC was associated with all-cause hospital admission and pneumonia related admissions HR 1.48; 95% CI 1.23-1.78 and HR 2.19; 95% 1.30-3.71, respectively. Mild, moderate and marked CAC were associated with COPD-related admission HR 2.30; 95% CI 1.31-4.03, HR 2.17; 95% CI 1.20-3.91 and HR 2.27; 95% CI 1.24-4.15. CONCLUSION: Qualitative CAC on CTLS exams identifies individuals at elevated risk for all cause, pneumonia and COPD-related hospital admissions.

Towards radiologist-level cancer risk assessment in CT lung screening using deep learning.

PURPOSE: Lung cancer is the leading cause of cancer mortality in the US, responsible for more deaths than breast, prostate, colon and pancreas cancer combined and large population studies have indicated that low-dose computed tomography (CT) screening of the chest can significantly reduce this death rate. Recently, the usefulness of Deep Learning (DL) models for lung cancer risk assessment has been demonstrated. However, in many cases model performances are evaluated on small/medium size test sets, thus not providing strong model generalization and stability guarantees which are necessary for clinical adoption. In this work, our goal is to contribute towards clinical adoption by investigating a deep learning framework on larger and heterogeneous datasets while also comparing to state-of-the-art models. METHODS: Three low-dose CT lung cancer screening datasets were used: National Lung Screening Trial (NLST, n = 3410), Lahey Hospital and Medical Center (LHMC, n = 3154) data, Kaggle competition data (from both stages, n = 1397 + 505) and the University of Chicago data (UCM, a subset of NLST, annotated by radiologists, n = 132). At the first stage, our framework employs a nodule detector; while in the second stage, we use both the image context around the nodules and nodule features as inputs to a neural network that estimates the malignancy risk for the entire CT scan. We trained our algorithm on a part of the NLST dataset, and validated it on the other datasets. Special care was taken to ensure there was no patient overlap between the train and validation sets. RESULTS AND CONCLUSIONS: The proposed deep learning model is shown to: (a) generalize well across all three data sets, achieving AUC between 86% to 94%, with our external test-set (LHMC) being at least twice as large compared to other works; (b) have better performance than the widely accepted PanCan Risk Model, achieving 6 and 9% better AUC score in our two test sets; (c) have improved performance compared to the state-of-the-art represented by the winners of the Kaggle Data Science Bowl 2017 competition on lung cancer screening; (d) have comparable performance to radiologists in estimating cancer risk at a patient level.

Qualitative emphysema and risk of COPD hospitalization in a multicenter CT lung cancer screening cohort study.

BACKGROUND: In the United States, 9 to 10 million Americans are estimated to be eligible for computed tomographic lung cancer screening (CTLS). Those meeting criteria for CTLS are at high-risk for numerous cardio-pulmonary co-morbidities. The objective of this study was to determine the association between qualitative emphysema identified on screening CTs and risk for hospital admission. STUDY DESIGN AND METHODS: We conducted a retrospective multicenter study from two CTLS cohorts: Lahey Hospital and Medical Center (LHMC) CTLS program, Burlington, MA and Mount Auburn Hospital (MAH) CTLS program, Cambridge, MA. CTLS exams were qualitatively scored by radiologists at time of screening for presence of emphysema. Multivariable Cox regression models were used to evaluate the association between CT qualitative emphysema and all-cause, COPD-related, and pneumonia-related hospital admission. RESULTS: We included 4673 participants from the LHMC cohort and 915 from the MAH cohort. 57% and 51.9% of the LHMC and MAH cohorts had presence of CT emphysema, respectively. In the LHMC cohort, the presence of emphysema was associated with all-cause hospital admission (HR 1.15, CI 1.07-1.23; p < 0.001) and COPD-related admission (HR 1.64; 95% CI 1.14-2.36; p = 0.007), but not with pneumonia-related admission (HR 1.52; 95% CI 1.27-1.83; p < 0.001). In the MAH cohort, the presence of emphysema was only associated with COPD-related admission (HR 2.05; 95% CI 1.07-3.95; p = 0.031). CONCLUSION: Qualitative CT assessment of emphysema is associated with COPD-related hospital admission in a CTLS population. Identification of emphysema on CLTS exams may provide an opportunity for prevention and early intervention to reduce admission risk.

Surgery and invasive diagnostic procedures for benign disease are rare in a large low-dose computed tomography lung cancer screening program.

OBJECTIVE: Lung cancer screening with low-dose chest computed tomography improves survival. However, concerns about overdiagnosis and unnecessary interventions persist. We reviewed our lung cancer screening program to determine the rate of surgery and invasive procedures for nonmalignant disease. METHODS: We reviewed all patients undergoing lung cancer screening from January 2012 to June 2017 with follow-up through January 2019. Patients with suspicious findings (Lung CT Screening Reporting and Data System 4) were referred for further evaluation. RESULTS: Of 3280 patients screened, 345 (10.5%) had Lung CT Screening Reporting and Data System 4 findings. A total of 311 patients had complete follow-up, of whom 93 (29.9%) were diagnosed with lung cancer. Eighty-three patients underwent lung surgery (2.5% of screened patients). Forty patients underwent lobectomy (48.2%), 3 patients (3.6%) underwent bilobectomy, and 40 patients (48.2%) underwent sublobar resection. Fourteen patients underwent surgery for benign disease (0.43% of screened patients). Fifty-four patients, 5 with benign disease, had at least 1 invasive diagnostic procedure but never underwent surgery. The incidence of any invasive intervention for nonmalignant disease was 0.95% (31/3280 patients). There were no postprocedural deaths within 60 days. Twenty-five patients (0.76%) underwent stereotactic body radiation therapy; 19 patients (76%) had presumed lung cancer without pretreatment pathologic confirmation. CONCLUSIONS: Surgical resection for benign disease occurred in 0.43% of patients undergoing lung cancer screening. The combined incidence of any invasive diagnostic or therapeutic intervention, including surgical resection, for benign disease was only 0.95%. Periprocedural complications were rare. These results indicate that concern over unnecessary interventions is overstated and should not hinder adoption of lung cancer screening. A multidisciplinary team approach, including thoracic surgeons, is critical to maintain an appropriate rate of interventions in lung cancer screening.

Quantitative Pectoralis Muscle Area is Associated with the Development of Lung Cancer in a Large Lung Cancer Screening Cohort.

BACKGROUND: Studies have demonstrated an inverse relationship between body mass index (BMI) and the risk of developing lung cancer. We conducted a retrospective cohort study evaluating baseline quantitative computed tomography (CT) measurements of body composition, specifically muscle and fat area in a large CT lung screening cohort (CTLS). We hypothesized that quantitative measurements of baseline body composition may aid in risk stratification for lung cancer. METHODS: Patients who underwent baseline CTLS between January 1st, 2012 and September 30th, 2014 and who had an in-network primary care physician were included. All patients met NCCN Guidelines eligibility criteria for CTLS. Quantitative measurements of pectoralis muscle area (PMA) and subcutaneous fat area (SFA) were performed on a single axial slice of the CT above the aortic arch with the Chest Imaging Platform Workstation software. Cox multivariable proportional hazards model for cancer was adjusted for variables with a univariate p < 0.2. Data were dichotomized by sex and then combined to account for baseline differences between sexes. RESULTS: One thousand six hundred and ninety six patients were included in this study. A total of 79 (4.7%) patients developed lung cancer. There was an association between the 25th percentile of PMA and the development of lung cancer [HR 1.71 (1.07, 2.75), p < 0.025] after adjusting for age, BMI, qualitative emphysema, qualitative coronary artery calcification, and baseline Lung-RADS® score. CONCLUSIONS: Quantitative assessment of PMA on baseline CTLS was associated with the development of lung cancer. Quantitative PMA has the potential to be incorporated as a variable in future lung cancer risk models.

Qualitative coronary artery calcium assessment on CT lung screening exam helps predict first cardiac events.

RESULTS: A total of 1,513 individuals underwent CTLS. Downstream data, pre-test cardiac risk factors and CAC scores were available for 88.3% (1,336/1,513). The average length of follow-up was 2.64 (SD ±0.72) years. There were a total of 43 events, occurring in 1.55% (6/386) of patients with mild CAC, 3.24% (11/339) of patients with moderate CAC, and 8.90% (26/292) of patients with marked CAC. There were no events among patients with no reported CAC (0/319). Using multivariable logistic modeling, the increased odds of an initial cardiac event was 2.56 (95% CI, 1.76-3.92, P<0.001) for mild CAC, 6.57 (95% CI, 3.10-15.4, P<0.001) for moderate CAC, and 16.8 (95% CI, 5.46-60.3, P<0.001) for marked CAC, as compared to individuals with no CAC. Time to event analysis showed distinct differences among the four CAC categories (P<0.001). CONCLUSIONS: Qualitative coronary artery calcification scoring of CTLS exams may provide a novel method to help select individuals at elevated risk for an initial cardiac event.

Adherence to Radiology Recommendations in a Clinical CT Lung Screening Program.

BACKGROUND: Assess patient adherence to radiologist recommendations in a clinical CT lung cancer screening program. METHODS: Patients undergoing CT lung cancer screening between January 12, 2012, and June 12, 2013, were included in this institutional review board-approved retrospective review. Patients referred from outside our institution were excluded. All patients met National Comprehensive Cancer Network Guidelines Lung Cancer Screening high-risk criteria. Full-time program navigators used a CT lung screening program management system to schedule patient appointments, generate patient result notification letters detailing the radiologist follow-up recommendation, and track patient and referring physician notification of missed appointments at 30, 60, and 90 days. To be considered adherent, patients could be no more than 90 days past due for their next recommended examination as of September 12, 2014. Patients who died, were diagnosed with cancer, or otherwise became ineligible for screening were considered adherent. Adherence rates were assessed across multiple variables. RESULTS: During the study interval, 1,162 high-risk patients were screened, and 261 of 1,162 (22.5%) outside referrals were excluded. Of the remaining 901 patients, 503 (55.8%) were male, 414 (45.9%) were active smokers, 377 (41.8%) were aged 65 to 73, and >95% were white. Of the 901 patients, 772 (85.7%) were adherent. Most common reasons for nonadherence were patient refusal of follow-up exam (66.7%), inability to successfully contact the patient (20.9%), and inability to obtain the follow-up order from the referring provider (7.8%); 23 of 901 (2.6%) were discharged for other reasons. CONCLUSIONS: High rates of adherence to radiologist recommendations are achievable for in-network patients enrolled in a clinical CT lung screening program.

Automatic Lung-RADS™ classification with a natural language processing system.

BACKGROUND: Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. METHODS: Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines®. All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. RESULTS: The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. CONCLUSIONS: An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

Smoking cessation results in a clinical lung cancer screening program.

BACKGROUND: Lung cancer screening may provide a "teachable moment" for promoting smoking cessation. This study assessed smoking cessation and relapse rates among individuals undergoing follow-up low-dose chest computed tomography (CT) in a clinical CT lung screening program and assessed the influence of initial screening results on smoking behavior. METHODS: Self-reported smoking status for individuals enrolled in a clinical CT lung screening program undergoing a follow-up CT lung screening exam between 1st February, 2014 and 31st March, 2015 was retrospectively reviewed and compared to self-reported smoking status using a standardized questionnaire at program entry. Point prevalence smoking cessation and relapse rates were calculated across the entire population and compared with exam results. All individuals undergoing screening fulfilled the National Comprehensive Cancer Network Clinical Practice Guidelines in Oncology: Lung Cancer Screening v1.2012(®) high-risk criteria and had an order for CT lung screening. RESULTS: A total of 1,483 individuals underwent a follow-up CT lung screening exam during the study interval. Smoking status at time of follow-up exam was available for 1,461/1,483 (98.5%). A total of 46% (678/1,461) were active smokers at program entry. The overall point prevalence smoking cessation and relapse rates were 20.8% and 9.3%, respectively. Prior positive screening exam results were not predictive of smoking cessation (OR 1.092; 95% CI, 0.715-1.693) but were predictive of reduced relapse among former smokers who had stopped smoking for 2 years or less (OR 0.330; 95% CI, 0.143-0.710). Duration of program enrollment was predictive of smoking cessation (OR 0.647; 95% CI, 0.477-0.877). CONCLUSIONS: Smoking cessation and relapse rates in a clinical CT lung screening program rates are more favorable than those observed in the general population. Duration of participation in the screening program correlated with increased smoking cessation rates. A positive exam result correlated with reduced relapse rates among smokers recently quit smoking.

Performance of ACR Lung-RADS in a Clinical CT Lung Screening Program.

PURPOSE: The aim of this study was to assess the effect of applying ACR Lung-RADS in a clinical CT lung screening program on the frequency of positive and false-negative findings. METHODS: Consecutive, clinical CT lung screening examinations performed from January 2012 through May 2014 were retroactively reclassified using the new ACR Lung-RADS structured reporting system. All examinations had initially been interpreted by radiologists credentialed in structured CT lung screening reporting following the National Comprehensive Cancer Network's Clinical Practice Guidelines in Oncology: Lung Cancer Screening (version 1.2012), which incorporated positive thresholds modeled after those in the National Lung Screening Trial. The positive rate, number of false-negative findings, and positive predictive value were recalculated using the ACR Lung-RADS-specific positive solid/part-solid nodule diameter threshold of 6 mm and nonsolid (ground-glass) threshold of 2 cm. False negatives were defined as cases reclassified as benign under ACR Lung-RADS that were diagnosed with malignancies within 12 months of the baseline examination. RESULTS: A total of 2,180 high-risk patients underwent baseline CT lung screening during the study interval; no clinical follow-up was available in 577 patients (26%). ACR Lung-RADS reduced the overall positive rate from 27.6% to 10.6%. No false negatives were present in the 152 patients with >12-month follow-up reclassified as benign. Applying ACR Lung-RADS increased the positive predictive value for diagnosed malignancy in 1,603 patients with follow-up from 6.9% to 17.3%. CONCLUSIONS: The application of ACR Lung-RADS increased the positive predictive value in our CT lung screening cohort by a factor of 2.5, to 17.3%, without increasing the number of examinations with false-negative results.

Surgical Outcomes in a Large, Clinical, Low-Dose Computed Tomographic Lung Cancer Screening Program.

BACKGROUND: Lung cancer screening with low-dose computed tomography is proven to reduce lung cancer mortality among high-risk patients. However, critics raise concern over the potential for unnecessary surgical procedures performed for benign disease as a result of screening. We reviewed our outcomes in a large clinical lung cancer screening program to assess the number of surgical procedures done for benign disease, as we believe this is an important quality metric. METHODS: We retrospectively reviewed our surgical outcomes of consecutive patients who underwent low-dose computed tomography lung cancer screening from January 2012 through June 2014 using a prospectively collected database. All patients met the National Comprehensive Cancer Network lung cancer screening guidelines high-risk criteria. RESULTS: There were 1,654 screened patients during the study interval with clinical follow-up at Lahey Hospital & Medical Center. Twenty-five of the 1,654 (1.5%) had surgery. Five of 25 had non-lung cancer diagnoses: 2 hamartomas, 2 necrotizing granulomas, and 1 breast cancer metastasis. The incidence of surgery for non-lung cancer diagnosis was 0.30% (5 of 1,654), and the incidence of surgery for benign disease was 0.24% (4 of 1,654). Twenty of 25 had lung cancer, 18 early stage and 2 late stage. There were no surgery-related deaths, and there was 1 major surgical complication (4%) at 30 days. CONCLUSIONS: The incidence of surgical intervention for non-lung cancer diagnosis was low (0.30%) and is comparable to the rate reported in the National Lung Screening Trial (0.62%). Surgical intervention for benign disease was rare (0.24%) in our experience.

Low-dose computed tomography screening for lung cancer in a clinical setting: essential elements of a screening program.

The purpose of this article is to review clinical computed tomography (CT) lung screening program elements essential to safely and effectively manage the millions of Americans at high risk for lung cancer expected to enroll in lung cancer screening programs over the next 3 to 5 years. To optimize the potential net benefit of CT lung screening and facilitate medical audits benchmarked to national quality standards, radiologists should interpret these examinations using a validated structured reporting system such as Lung-RADS. Patient and physician educational outreach should be enacted to support an informed and shared decision-making process without creating barriers to screening access. Programs must integrate smoking cessation interventions to maximize the clinical efficacy and cost-effectiveness of screening. At an institutional level, budgets should account for the necessary expense of hiring and/or training qualified support staff and equipping them with information technology resources adequate to enroll and track patients accurately over decades of future screening evaluation. At a national level, planning should begin on ways to accommodate the upcoming increased demand for physician services in fields critical to the success of CT lung screening such as diagnostic radiology and thoracic surgery. Institutions with programs that follow these specifications will be well equipped to meet the significant oncoming demand for CT lung screening services and bestow clinical benefits on their patients equal to or beyond what was observed in the National Lung Screening Trial.

Performance of ACR Lung-RADS in a clinical CT lung screening program.

PURPOSE: The aim of this study was to assess the effect of applying ACR Lung-RADS in a clinical CT lung screening program on the frequency of positive and false-negative findings. METHODS: Consecutive, clinical CT lung screening examinations performed from January 2012 through May 2014 were retroactively reclassified using the new ACR Lung-RADS structured reporting system. All examinations had initially been interpreted by radiologists credentialed in structured CT lung screening reporting following the National Comprehensive Cancer Network's Clinical Practice Guidelines in Oncology: Lung Cancer Screening (version 1.2012), which incorporated positive thresholds modeled after those in the National Lung Screening Trial. The positive rate, number of false-negative findings, and positive predictive value were recalculated using the ACR Lung-RADS-specific positive solid/part-solid nodule diameter threshold of 6 mm and nonsolid (ground-glass) threshold of 2 cm. False negatives were defined as cases reclassified as benign under ACR Lung-RADS that were diagnosed with malignancies within 12 months of the baseline examination. RESULTS: A total of 2,180 high-risk patients underwent baseline CT lung screening during the study interval; no clinical follow-up was available in 577 patients (26%). ACR Lung-RADS reduced the overall positive rate from 27.6% to 10.6%. No false negatives were present in the 152 patients with >12-month follow-up reclassified as benign. Applying ACR Lung-RADS increased the positive predictive value for diagnosed malignancy in 1,603 patients with follow-up from 6.9% to 17.3%. CONCLUSIONS: The application of ACR Lung-RADS increased the positive predictive value in our CT lung screening cohort by a factor of 2.5, to 17.3%, without increasing the number of examinations with false-negative results.