Management Of Lung Nodules Research Articles

Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research.

Lung cancer causes more deaths than breast, cervical, and colorectal cancer combined. Nevertheless, population‐based lung cancer screening is still not considered standard practice in most countries worldwide. Early lung cancer detection leads to better survival outcomes: patients diagnosed with stage 1A lung cancer have a >75% 5‐year survival rate, compared to <5% at stage 4. Low‐dose computed tomography (LDCT) thorax imaging for the secondary prevention of lung cancer has been studied at length, and has been shown to significantly reduce lung cancer mortality in high‐risk populations. The US National Lung Screening Trial reported a 20% overall reduction in lung cancer mortality when comparing LDCT to chest X‐ray, and the Nederlands‐Leuvens Longkanker Screenings Onderzoek (NELSON) trial more recently reported a 24% reduction when comparing LDCT to no screening. Hence, the focus has now shifted to implementation research. Consequently, the 4‐IN‐THE‐LUNG‐RUN consortium based in five European countries, has set up a large‐scale multicenter implementation trial. Successful implementation of and accessibility to LDCT lung cancer screening are dependent on many factors, not limited to population selection, recruitment strategy, computed tomography screening frequency, lung‐nodule management, participant compliance, and cost effectiveness. This review provides an overview of current evidence for LDCT lung cancer screening, and draws attention to major factors that need to be addressed to successfully implement standardized, effective, and accessible screening throughout Europe. Evidence shows that through the appropriate use of risk‐prediction models and a more personalized approach to screening, efficacy could be improved. Furthermore, extending the screening interval for low‐risk individuals to reduce costs and associated harms is a possibility, and through the use of volumetric‐based measurement and follow‐up, false positive results can be greatly reduced. Finally, smoking cessation programs could be a valuable addition to screening programs and artificial intelligence could offer a solution to the added workload pressures radiologists are facing.

Nodule net: A centralized prospective lung nodule tracking and safety-net program

BackgroundInadequate follow-up of suspicious lung nodules can result in diagnostic delays and potential progression to advanced lung cancer. In 2015, a multidisciplinary lung nodule management program, Nodule Net, was implemented to increase the timely follow-up rate. In this study, we sought to evaluate the effectiveness of the program. Methods2398 chest CT reports were reviewed for the presence of a lung nodule. Baseline demographics, nodule characteristics, and follow-up recommendations were collected. For reports that did not include structured recommendations, Fleischner Society guidelines were applied if appropriate. The rate of follow-up imaging was recorded and compared with historical rates. ResultsLung nodules were reported on 1367 (57%) of scans. Of the 632 participants with recommendations for follow-up, the Nodule Net nurse navigator was notified on 523 (83%). Of these, 408 (78%) completed follow-up, compared to 57/109 (52%) in those who were not reported to Nodule Net tracking system (risk ratio: 1.49, 95% CI: 1.24–1.79, p-value < 0.05). Out of these 408, nodule net outreach was required to prompt the follow-up in 116 (28%). Of these, a lung malignancy was diagnosed in 4 (4%). ConclusionsManagement of lung nodules is a complex process. Implementation of a lung nodule tracking program led to a significant increase in the completion of recommended follow-up imaging compared with usual care. Developing a comprehensive lung nodule program using an automated software system rather than manual processes to refer and track incidental findings may further reduce barriers to completion of follow-up.

FLUORO-CT GUIDED BIOPSY OF LUNG NODULES: A STEP BY STEP REVISION.

Transthoracic biopsies under fluoro-computer tomography (CT) guidance play an important role on the diagnosis and management of lung nodules, permitting histological examination and differentiation between benign and malignant lesions(1). Furthermore, with recent advances in target therapy, it is increasingly necessary to obtain tumor tissue for the analysis of molecular fingerprints allowing personalized treatment(1). Although many studies report low complication rates for this procedure, they are not negligible, urging the need for a structured and reproducible guide to reduce technique-related complications(1,2).

Low-dose computed tomography screening, follow-up, and management of lung nodules – An expert consensus statement from Taiwan

Low-dose computed tomography screening, follow-up, and management of lung nodules – An expert consensus statement from Taiwan

Management of screen-detected lung nodule

Low-dose computed tomography screening has recently increased the detection rate of small pulmonary nodules. The surgical techniques and policies for managing screen-detected lung nodules are different from those for advanced lung cancer. In the past decade, several novel tumor localization methods and surgical management policies have been developed for such patients. In this article, we reviewed studies related to two different screen-detected lung nodule localization techniques at our institute. We also reviewed studies related to the surgical policies of sublobar resection and the application of nonintubated thoracoscopy in the management of screen-detected lung nodules at our institute. These novel techniques and surgical policies may be helpful to physicians in the management of screen-detected lung nodules.

Lung-RADS Versus Pan-Canadian Early Detection of Lung Cancer Study Screening for Patients at High Risk of Lung Cancer

&#x0D; Evidence of variable quality from 6 diagnostic test accuracy studies indicates that the Pan-Canadian Early Detection of Lung Cancer (PanCan) model may perform better at determining which lung nodules identified by low-dose CT are cancerous compared to the Lung Imaging Reporting and Data System. However, evidence from 3 other studies, also of variable quality, suggests that the risk calculators have similar diagnostic test accuracy.&#x0D; No studies were identified that compared the clinical utility of PanCan versus the Lung Imaging Reporting and Data System.&#x0D; Results from 2 economic evaluations were inconsistent about the cost-effectiveness of the 2 lung cancer risk models. However, each study applied the models to different types of lung nodules.&#x0D; One evidence-based guideline recommended that PanCan be used in the UK for initial risk assessment and for the management of lung nodules.&#x0D;

MA10.01 Prospective Evaluation of the International Lung Screening Trial (ILST) Protocol for Management of First Screening LDCT

The first (baseline) screening LDCT generates more early recall imaging studies or diagnostic referrals compares to subsequent screening rounds where management decisions have the advantage of information on nodule growth or appearance of new nodules. The ILST protocol (Ann Am Thorac Soc. 2020 Apr;17(4):503-512) - a personalized approach to lung nodule management is based on malignancy probability of lung nodules (N Engl J Med 2013;369:908-17). Currently, this is the only protocol that triages screenees with no lung nodule or very low risk lung nodules to biennial screening instead of annual screening.

Contemporary issues in the implementation of lung cancer screening.

Lung cancer screening with low-dose computed tomography can reduce death from lung cancer by 20-24% in high-risk smokers. National lung cancer screening programmes have been implemented in the USA and Korea and are being implemented in Europe, Canada and other countries. Lung cancer screening is a process, not a test. It requires an organised programmatic approach to replicate the lung cancer mortality reduction and safety of pivotal clinical trials. Cost-effectiveness of a screening programme is strongly influenced by screening sensitivity and specificity, age to stop screening, integration of smoking cessation intervention for current smokers, screening uptake, nodule management and treatment costs. Appropriate management of screen-detected lung nodules has significant implications for healthcare resource utilisation and minimising harm from radiation exposure related to imaging studies, invasive procedures and clinically significant distress. This review focuses on selected contemporary issues in the path to implement a cost-effective lung cancer screening at the population level. The future impact of emerging technologies such as deep learning and biomarkers are also discussed.

The impact of lung parenchyma attenuation on nodule volumetry in lung cancer screening

BackgroundRecent recommendations for lung nodule management include volumetric analysis using tools that present intrinsic measurement variability, with possible impacts on clinical decisions and patient safety. This study was conducted to evaluate whether changes in the attenuation of the lung parenchyma adjacent to a nodule affect the performance of nodule segmentation using computed tomography (CT) studies and volumetric tools.MethodsTwo radiologists retrospectively applied two commercially available volumetric tools for the assessment of lung nodules with diameters of 5–8 mm detected by low-dose chest CT during a lung cancer screening program. The radiologists recorded the success and adequacy of nodule segmentation, nodule volume, manually and automatically (or semi-automatically) obtained long- and short-axis measurements, mean attenuation of adjacent lung parenchyma, and presence of interstitial lung abnormalities or disease, emphysema, pleural plaques, and linear atelectasis. Regression analysis was performed to identify predictors of good nodule segmentation using the volumetric tools. Interobserver and intersoftware agreement on good nodule segmentation was assessed using the intraclass correlation coefficient.ResultsIn total, data on 1265 nodules (mean patient age, 68.3 ± 5.1 years; 70.2% male) were included in the study. In the regression model, attenuation of the adjacent lung parenchyma was highly significant (odds ratio 0.987, p < 0.001), with a large effect size. Interobserver and intersoftware agreement on good segmentation was good, although one software package performed better and measurements differed consistently between software packages.ConclusionFor lung nodules with diameters of 5–8 mm, the likelihood of good segmentation declines with increasing attenuation of the adjacent parenchyma.

Efficacy of Low Dose Computed Tomography Using Adaptive Statistical Iterative Reconstruction in Lung Cancer Screening

Abstract Background: Lung cancer is the most common malignant tumor and the leading cause of cancer-related deaths all over the world. Early detection and treatment are important to increase survival rate. Therefore, screening of lung cancer should target those individuals at high risk. Aim of Study: To detect the efficacy of low dose computed tomography (LDCT) of the chest with adaptive statistical iterative reconstruction (ASIR) algorithmas a screening method in diagnosing early stages of lung cancer and thus decrease the disease related morbidity and mortality as itminimizes exposure to ionizing radiation while maintaining sufficient image quality. Material and Methods: Ninety-six high risk cases (current smokers or ex-smokers), 94 males and 2 females, withage range from 50-78 yearswere included in this study. All cases underwent CT of the chest using low dose protocol with-ASIR algorithm with different blending levels of reconstruction (40%, 60%) for lung cancer screening. All images were interpreted using the International Early Lung Cancer Action Program (I-ELCAP) diagnostic protocol for lung nodule diagnosis and management. Results: From 96 cases included in the study, 82 cases had normal chest CT and 14 cases showed abnormal findings in chest CT (4 of them showed nodular lung lesions and the other 10 cases showed other findings related to smoking as bullae, bronchial wall thickening, emphysema, honey combing and bronchiectasis). Among the 6 nodules detected in the 4 cases, one nodule was >!15mm, and 5 nodules were <15mm. According to I-ELCAP diagnostic protocol, one nodule was considered positive and 5 nodules were considered semi-positive. LDCT chest using ASIR algorithm for lung cancer screening revealed high sensitivity and specificity for detecting lesions at cut off point size 6 mm (84.9% and 100% respec-tively). The area under receiver operating characteristic (ROC) curve for prediction of nodule with cutoff point size 6mm was 0.938 with 95% confidence interval (0.887-0.990). Conclusion: LDCT of the chest using ASIR algorithm is a promising and efficient tool for lung cancer screening with significant minimization of ionizing radiation exposure as well as preserved optimum image quality.

45 - Lung nodule management in Covid-19: does postponed surveillance matter?

45 - Lung nodule management in Covid-19: does postponed surveillance matter?

Nodule net: A prospective safety net program to reduce loss to follow-up and increase early detection of lung cancer.

1564 Background: Inadequate follow-up of suspicious lung nodules can result in a delay in diagnosis and potential progression to advanced staged lung cancer. A multidisciplinary lung nodule program entitled "Nodule Net" was implemented in 2017 to provide a safety net, increase the rate of follow-up, streamline management. The program consisted of a multidisciplinary team with EMR notification by the radiologist to a centralized nurse navigator for inclusion in a follow-up database, outreach with reminders to the primary care provider if follow-up was not completed, and referral for management where appropriate. In this study, we sought to evaluate program effectiveness in tracking and rate of follow-up imaging of suspicious pulmonary nodules. Methods: 2,398 chest CT scans were reviewed between January and May 2018 for the presence of a lung nodule that required follow-up. Nodules known to be inflammatory or associated with a metastatic malignancy were excluded. Baseline demographics, medical history, primary care affiliation, type of imaging scan, nodule characteristics, and presence and specifics of follow-up recommendations were collected. For reports that did not include a follow-up recommendation, Fleischner’s recommendations were applied or an independent pulmonologist’s review was completed. The rate of follow-up imaging was recorded and compared with historical rates prior to Nodule Net implementation. Prevalence ratios were generated for each comparison. Results: 1,367 (57%) reported lung nodules. Recommendations for follow-up imaging were recorded in 632 (46.2%), and 523 (82.8%) of these were reported to the program navigator. The rate of follow-up completion of those referred to the program was significantly higher [408 (78%)] than standard of care prior to program implementation [442/1202 (36.8%), (2.90, 95% CI: 2.65-3.18)]. Out of 408 patients who completed follow-up, nodule net outreach was required in 116 (28.4%). Of these 116, malignancy was identified in 4/116 (3.4%). Increased nodule size requiring referral was identified in 17 (14.7%). Out of 109 who were not transmitted to the program navigator and not present in the database, 57 (52.3%) had completed the recommended follow-up compared with 78% among those referred (1.49, 95% CI:1.23-1.79). Conclusions: Management of lung nodules is a complex process with poor follow-up completion reported in prior studies (29%-33%). Implementation of a multidisciplinary lung nodule care program for tracking lung nodules led to a significant increase in completion of recommended follow-up imaging. Developing a comprehensive lung nodule management program using software and navigation may further enhance detection, reduce human errors, augment the necessary follow-up for suspicious lung nodules, and ultimately the prevalence of advanced stage lung cancer.

Early candidate nasal swab classifiers developed using machine learning and whole transcriptome sequencing may improve early lung cancer detection.

8551 Background: The goal of lung nodule management is to make an early diagnosis in patients with lung cancer while avoiding unnecessary, costly and potentially harmful procedures in patients with benign lesions. Increased implementation of low dose CT screening will lead to increased numbers of both benign and malignant nodules that will require effective management. We have previously described the feasibility of detecting gene expression changes associated with lung cancer (“field of injury”) in nasal epithelium utilizing whole transcriptome RNA sequencing from non-invasive nasal brush samples. Using this approach, we now report the performance of candidate nasal classifiers that combine both genomic and clinical features to risk stratify lung nodules from ever-smokers to aid in the diagnosis of lung cancer. Methods: Patients from several clinical cohorts who were ever-smokers with a lung nodule &lt; 30 mm and without a history of prior cancer underwent nasal epithelium sampling. All patients had at least one year of follow up or until a final diagnosis of benign or malignant nodule was made. Candidate classifiers were developed using whole-transcriptome RNA sequencing and machine learning. Training of these classifiers included genomic and clinical information (age, sex, pack-years, years-since-quit, nodule size and nodule spiculation). Two decision boundaries were chosen to maximize sensitivity and specificity for low and high-risk nodules, respectively. The performance of these classifiers was evaluated using cross-validation (CV). Results: All candidate nasal classifiers underwent CV assessment on over 700 patients with lung nodules. All candidate classifiers achieved CV performance of &gt; 40% specificity at 95% sensitivity in low- risk nodules and all candidate classifiers achieved CV performance of &gt; 60% sensitivity at 90% specificity in high-risk nodules. The classifiers stratified benign nodules as low- risk with &gt; 95% negative predictive value (NPV), intermediate risk nodules were stratified as 5-65% risk and malignant nodules were stratified as high- risk with &gt; 65% positive predictive value (PPV) in a population with estimated 25% prevalence. This performance was robust across subgroups of age ( &lt; 65 year vs. &gt;65 year), sex, and current versus former smokers. Conclusions: The nasal genomic-clinical candidate classifiers have a high NPV effectively identifying benign nodules when calling them low- risk, thereby, informing decisions to more safely avoid a diagnostic workup. Additionally, the high PPV of these classifiers identifies malignant nodules when calling them high- risk and informs decisions regarding the urgency of a further diagnostic work-up. A nasal genomic-clinical classifier has the potential to serve as a non-invasive tool for lung cancer risk-stratification to help inform decision making in patients with lung nodules.

Transbronchial microwave ablation of lung nodules with electromagnetic navigation bronchoscopy guidance-a novel technique and initial experience with 30 cases.

BackgroundMicrowave ablation of lung nodules may provide a faster, larger and more predictable ablation zone than other energy sources, while bronchoscopic transbronchial ablation has theoretical advantage of fewer pleural-based complications than percutaneous approach. Our study aims to determine whether the novel combination of bronchoscopic approach and microwave ablation in management of lung nodules is technically feasible, safe and effective.MethodsThis is a retrospective analysis of a single center experience in electromagnetic navigation bronchoscopy microwave ablation in hybrid operating room. Patients had high surgical risks while lung nodules were either proven malignant or radiologically suspicious. Primary endpoints include technical feasibility and safety.ResultsTotal of 30 lung nodules from 25 patients were treated. Mean nodule size was 15.1 mm, and bronchus directly leads to the nodules (bronchus sign positive) in only half of them. Technical success rate was 100%, although some nodules required double ablation for adequate coverage. Mean minimal ablation margin was 5.51 mm. The mean actual ablation zone volume was −21.4% compared to predicted, likely due to significant tissue contraction ranging from 0–43%. There was no significant heat sink effect. Mean hospital stay was 1.73 days, and only 1 patient stayed for more than 3 days. Complications included pain (13.3%), pneumothorax requiring drainage (6.67%), post-ablation reaction (6.67%), pleural effusion (3.33%) and hemoptysis (3.33%). After median follow up of 12 months, none of the nodules had evidence of progression.ConclusionsBronchoscopic transbronchial microwave ablation is safe and feasible for treatment of malignant lung nodules. Prospective study on clinical application of this novel technique is warranted.

Strategies to optimize management of incidental radiographic findings in the primary care setting: A mixed methods study

BackgroundIncidental adrenal masses (IAMs) are common. Primary care providers (PCPs) are frequently responsible for incidentaloma evaluations. We evaluated whether PCPs view this paradigm effective, barriers faced, and strategies to optimize care delivery. MethodsThis is a sequential explanatory study, comprised of surveys followed by focus groups of PCPs. Because lung nodules are another type of common incidental finding, we compared PCP views on management of lung nodules to their views on IAMs. ResultsFor IAMs, 22.3% of PCPs “always refer” to specialists, but for lung nodules this was 11.5% (p = 0.026). For lung nodules, the most significant barrier was insufficient time/support to longitudinally follow results (69%), but for IAMs it was uncertainty about which tests to order (68%). Fear of litigation was equal (lung = 22.5%, IAMs = 21.3%). Consistent themes regarding the “ideal” system included specific recommendations in radiology reports; automation of orders for follow-up tests; longitudinal tracking tools; streamlined consultations; and decision guides embedded within the electronic health record. ConclusionsRespondents are more comfortable with lung nodules than IAMs. Management of “incidentalomas” is within their scope of practice, but the current system can be optimized.

P45.03 Lung Nodule Management Based on Diameter and Volume in Lung Cancer Screening with Low-Dose Computed Tomography

P45.03 Lung Nodule Management Based on Diameter and Volume in Lung Cancer Screening with Low-Dose Computed Tomography

Improvement in Follow-up Imaging With a Patient Tracking System and Computerized Registry for Lung Nodule Management

Despite established guidelines, radiologists' recommendations and timely follow-up of incidental lung nodules remain variable. To improve follow-up of nodules, a system using standardized language (tracker phrases) recommending time-based follow-up in chest CT reports, coupled with a computerized registry, was created. Data were obtained from the electronic health record and a facility-built electronic lung nodule registry. We evaluated two randomly selected patient cohorts with incidental nodules on chest CT reports: before intervention (September 2008 to March 2011) and after intervention (August 2011 to December 2016). Multivariable logistic regression was used to compare the cohorts for the main outcome of timely follow-up, defined as a subsequent report within 13 months of the initial report. In all, 410 patients were included in the pretracker cohort versus 626 in the tracker cohort. Before system inception, 30% of CT reports lacked an explicit time-based recommendation for nodule follow-up. The proportion of patients with timely follow-up increased from 46% to 55%, and the proportion of those with no documented follow-up or follow-up beyond 24 months decreased from 48% to 31%. The likelihood of timely follow-up increased 41%, adjusted for high risk for lung cancer and age 65 years or older. After system inception, reports missing a tracker phrase for nodule recommendation averaged 6%, without significant interyear variation. Standardized language added to CT reports combined with a computerized registry designed to identify and track patients with incidental lung nodules was associated with improved likelihood of follow-up imaging.

Pulmonary nodule radiological diagnostic algorithm in lung cancer screening.

Publications of the final results of the two largest randomized lung cancer screening (LCS) trials in the United States and Europe confirmed the reduction in the mortality rate associated with the use of screening with low-dose computed tomography (LDCT). Results of these trials led to widespread acceptance of LCS in properly defined high-risk populations, and its implementation in the clinical practice. Many countries started preparation for national LCS and refreshed still open debate about lung nodule management. Detection of lung cancer in the early stage with a reduction of lung cancer mortality requires dedicated programs with optimized protocols, including a specified pulmonary nodule diagnostic algorithm. The screening protocol should be clear with a precise nodule diameter or volume threshold, based on which a positive screen result is defined. The application of risk-prediction models and the introduction of the semiautomated assessment of detected nodules improves screening accuracy and should be applied in LCS protocols as verified tools to aid radiological diagnosis. In this review, we have summarized recent data about the radiological protocols from the most important LCS programs and pulmonary diagnostic algorithms. These protocols should be taken into consideration in the ongoing and planned LCS programs.

Development and Cost Analysis of a Lung Nodule Management Strategy Combining Artificial Intelligence and Lung-RADS for Baseline Lung Cancer Screening.

To develop a lung nodule management strategy combining the Lung CT Screening Reporting and Data System (Lung-RADS) with an artificial intelligence (AI) malignancy risk score and determine its impact on follow-up investigations and associated costs in a baseline lung cancer screening population. Secondary analysis was undertaken of a data set consisting of AI malignancy risk scores and Lung-RADS classifications from six radiologists for 192 baseline low-dose CT studies. Low-dose CT studies were weighted to model a representative cohort of 3,197 baseline screening patients. An AI risk score threshold was defined to match average sensitivity of six radiologists applying Lung-RADS. Cases initially Lung-RADS category 1 or 2 with a high AI risk score were upgraded to category 3, and cases initially category 3 or higher with a low AI risk score were downgraded to category 2. Follow-up investigations resulting from Lung-RADS and the AI-informed management strategy were determined. Investigation costs were based on the 2019 US Medicare Physician Fee Schedule. The AI-informed management strategy achieved sensitivity and specificity of 91% and 96%, respectively. Average sensitivity and specificity of six radiologists using Lung-RADS only was 91% and 66%, respectively. Using the AI-informed management strategy, 41 (0.2%) category 1 or 2 classifications were upgraded to category 3, and 5,750 (30%) category 3 or higher classifications were downgraded to category 2. Minimum net cost savings using the AI-informed management strategy was estimated to be $72 per patient screened. Using an AI risk score combined with Lung-RADS at baseline lung cancer screening may result in fewer follow-up investigations and substantial cost savings.

Computed tomography-guided core needle biopsy for lung nodules: low-dose versus standard-dose protocols.

IntroductionComputed tomography (CT)-guided core needle biopsy (CNB) is an essential step in the management of lung nodules (LNs). Low-dose CT (LDCT)-guided CNB has been used to decrease the radiation exposure.AimTo evaluate the technical success, safety, diagnostic capacity, and radiation exposure to patients between LDCT-guided and standard-dose CT (SDCT)-guided CNB for LNs.Material and methodsThis is a retrospective, single-centre study. Patients who underwent LDCT-guided or SDCT-guided CNB for LNs from January 2015 to December 2017 were included. Data on technical success, diagnostic performance, complications, and radiation exposure were collected and analysed.ResultsA total of 70 and 65 patients underwent LDCT-guided and SDCT-guided CNB procedure, respectively. The technical success rates were 100% in both groups. The diagnostic yield, sensitivity, specificity, and overall diagnostic accuracy in the LDCT and SDCT groups were 71.4% and 67.7% (p = 0.637), 97.8% and 93.2% (p = 0.625), 100%, and 100%, and 98.6% and 95.4% (p = 0.560), respectively. The independent risk factor of diagnostic failure was less sample tissues (p = 0.012; 95% confidence interval: 0.033–0.651). Pneumothorax was found in 9 and 12 patients in the LDCT and SDCT groups, respectively (p = 0.369). Lung haemorrhage was found in 11 and 12 patients in the LDCT and SDCT groups, respectively (p = 0.671). The mean dose-length product was 38.3 ±17.0 mGy · cm and 376.0 ±118.7 mGy · cm in the LDCT and SDCT groups, respectively (p < 0.001).ConclusionsCompared to SDCT, LDCT-guided CNB can provide comparable safety and diagnostic performance for LNs while reducing exposure to radiation.