Screening Tool For Lung Cancer Research Articles

Future implications of artificial intelligence in lung cancer screening: a systematic review.

The aim of this study was to systematically review the literature to assess the application of AI-based interventions in lung cancer screening, and its future implications. Relevant published literature was screened using PRISMA guidelines across three databases: PubMed, Scopus, and Web of Science. Search terms for article selection included "artificial intelligence," "radiology," "lung cancer," "screening," and "diagnostic." Included studies evaluated the use of AI in lung cancer screening and diagnosis. Twelve studies met the inclusion criteria. All studies concerned the role of AI in lung cancer screening and diagnosis. The AIs demonstrated promising ability across four domains: (1) detection, (2) characterization and differentiation, (3) augmentation of the work of human radiologists, (4) AI implementation of the LUNG-RADS framework and its ability to augment this framework. All studies reported positive results, demonstrating in some cases AI's ability to perform these tasks to a level close to that of human radiologists. The AI systems included in this review were found to be effective screening tools for lung cancer. These findings hold important implications for the future use of AI in lung cancer screening programmes as they may see use as an adjunctive tool for lung cancer screening that would aid in making early and accurate diagnosis. AI-based systems appear to be powerful tools that can assist radiologists with lung cancer screening and diagnosis.

Cross-sectional study of assessment of lung cancer (LC) screening awareness in an underserved community in the Bronx, New York.

155 Background: LC remains the second most diagnosed cancer but is the leading cause of cancer death in the USA, accounting for 21% of all cancer deaths. Despite advances in screening and treatment, it remains the principal cause of cancer mortality worldwide. Notably, survival rates have improved from 21% to 25% over the past 5 years. However, LC screening with low-dose computed tomography (LDCT) is underutilized, with only 5.8% of eligible individuals screened in 2021. Methods: A prospective 29-question survey was conducted at St. Barnabas Health Care System in the Bronx, NY, from February to April 2024. The survey included patients aged 50-80, both former and active smokers. Data on demographics, social determinants, and knowledge of LC and LDCT screening were collected and processed using JASP Version 0.18.3. The study aimed to assess the community's knowledge of lung cancer screening, with demographic characteristics as secondary outcomes. Results: From all the surveys collected, 115 met the inclusion criteria, 53% male (61) and 47% female (54), with no significant difference between proportions (p=0.576). The median age was 63 years. Race: 73% were Hispanic, 22% Black, and 5% White, with significant differences from an equal distribution (p< 0.001). Legal Status, citizens (74%), followed by green card holders (17%). Most of the patients lived in the USA for over 20 years (90%), with very few having lived for less than five years (1%), indicating a long-term residency trend (p < 0.001). Education Level: high school education was the most common (58%), followed by middle school (17%) and elementary school (15%). Doctorate and graduate degrees were less common (7%). 91% of patients were aware of the relationship between cigarette smoking and LC, while 9% did not (p<0.001). On the other hand, 66% believed there was a relationship between e-cigarette use and LC, while 44% believed there was not. Patients with an income greater than $50,000 have significantly more knowledge of the screening tool for LC (STLC), as indicated by a Chi-square value of 50.87 (p < 0.05, with a critical value of 5.99). Patients with low education levels have less knowledge of the existing STLC, with a Chi-square of 143.587 (p<0.05 and a critical value of 9.488). Conclusions: Our study highlights critical disparities in LC awareness and knowledge of screening tools among different demographic groups. There is a clear need for targeted educational initiatives, especially for lower-income and less-educated populations, to improve understanding of LC risks associated with both traditional and electronic cigarette use. The significant presence of long-term Hispanic residents suggests that culturally tailored interventions could be particularly effective. Addressing these gaps is essential for enhancing lung cancer prevention and early detection efforts across diverse communities.

Patient Perspectives on a Patient-Facing Tool for Lung Cancer Screening.

Individuals with high risk for lung cancer may benefit from lung cancer screening, but there are associated risks as well as benefits. Shared decision-making (SDM) tools with personalized information may provide key support for patients. Understanding patient perspectives on educational tools to facilitate SDM for lung cancer screening may support tool development. This study aimed to explore patient perspectives related to a SDM tool for lung cancer screening using a qualitative approach. We elicited patient perspectives by showing a provider-facing SDM tool. Focus group interviews that ranged in duration from 1.5 to 2 h were conducted with 23 individuals with high risk for lung cancer. Data were interpreted inductively using thematic analysis to identify patients' thoughts on and desires for a patient-facing SDM tool. The findings highlight that patients would like to have educational information related to lung cancer screening. We identified several key themes to be considered in the future development of patient-facing tools: barriers to acceptance, preference against screening and seeking empowerment. One further theme illustrated effects of patient-provider relationship as a limitation to meeting lung cancer screening information needs. Participants also noted several suggestions for the design of technology decision aids. These findings suggest that patients desire additional information on lung cancer screening in advance of clinical visits. However, there are several issues that must be considered in the design and development of technology to meet the information needs of patients for lung cancer screening decisions. Patients, service users, caregivers or members of the public were not involved in the study design, conduct, analysis or interpretation of the data. However, clinical experts in health communication provided detailed feedback on the study protocol, including the focus group approach. The study findings contribute to a better understanding of patient expectations for lung cancer screening decisions and may inform future development of tools for SDM.

Development of an Electronic Health Record Self-Referral Tool for Lung Cancer Screening: One-Group Posttest Study.

Approximately 14 million individuals in the United States are eligible for lung cancer screening (LCS), but only 5.8% completed screening in 2021. Given the low uptake despite the potential great health benefit of LCS, interventions aimed at increasing uptake are warranted. The use of a patient-facing electronic health record (EHR) patient portal direct messaging tool offers a new opportunity to both engage eligible patients in preventative screening and provide a unique referral pathway for tobacco treatment. This study sought to develop and pilot an EHR patient-facing self-referral tool for an established LCS program in an academic medical center. Guided by constructs of the Health Belief Model associated with LCS uptake (eg, knowledge and self-efficacy), formative development of an EHR-delivered engagement message, infographic, and self-referring survey was conducted. The survey submits eligible self-reported patient information to a scheduler for the LCS program. The materials were pretested using an interviewer-administered mixed methods survey captured through venue-day-time sampling in 5 network-affiliated pulmonology clinics. Materials were then integrated into the secure patient messaging feature in the EHR system. Next, a one-group posttest quality improvement pilot test was conducted. A total of 17 individuals presenting for lung screening shared-decision visits completed the pretest survey. More than half were newly referred for LCS (n=10, 60%), and the remaining were returning patients. When asked if they would use a self-referring tool through their EHR messaging portal, 94% (n=16) reported yes. In it, 15 participants provided oral feedback that led to refinement in the tool and infographic prior to pilot-testing. When the initial application of the tool was sent to a convenience sample of 150 random patients, 13% (n=20) opened the self-referring survey. Of the 20 who completed the pilot survey, 45% (n=9) were eligible for LCS based on self-reported smoking data. A total of 3 self-referring individuals scheduled an LCS. Pretest and initial application data suggest this tool is a positive stimulus to trigger the decision-making process to engage in a self-referral process to LCS among eligible patients. This self-referral tool may increase the number of patients engaging in LCS and could also be used to aid in self-referral to other preventative health screenings. This tool has implications for clinical practice. Tobacco treatment clinical services or health care systems should consider using EHR messaging for LCS self-referral. This approach may be cost-effective to improve LCS engagement and uptake. Additional referral pathways could be built into this EHR tool to not only refer patients who currently smoke to LCS but also simultaneously trigger a referral to clinical tobacco treatment.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries.

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

175 Community lung health check as a screening tool for lung cancer: Outcomes after completing 24 months of nodule surveillance

175 Community lung health check as a screening tool for lung cancer: Outcomes after completing 24 months of nodule surveillance

Adaptation of a Tailored Lung Cancer Screening Decision Aid for People With HIV

BackgroundPeople with HIV (PWH) are both at elevated risk of lung cancer and high risk of multimorbidity, which makes shared decision-making (SDM) for lung cancer screening (LCS) in PWH complex. There are currently no tools adapted for SDM in PWH. Research QuestionCan a SDM decision aid be adapted to include HIV-specific measures with input from both PWH and their providers? Study Design and MethodsThis study utilized qualitative methods including focus groups with PWH and interviews with HIV-care providers to adapt and iterate an SDM tool for PWH. Eligible participants were PWH enrolled in an HIV primary care clinic who met age and smoking eligibility criteria for LCS and HIV care providers at the clinic. Both the focus groups and interviews included semi-structured discussions of SDM and decision aid elements for PWH. We used a framework-guided thematic analysis, mapping themes onto the Health Equity Implementation framework. ResultsForty-three PWH participated in 8 focus groups; 10 providers were interviewed. Key themes from patients included broad interest in adapting LCS SDM specifically for PWH, a preference for clear LCS recommendations, and the need for positive framing emphasizing survival. Providers were enthusiastic about personalized LCS risk assessments and point-of-care tools. Both patients and providers had mixed views on the utility of HIV-specific risk measures in patient-facing tools. Themes were utilized to adapt a personalized and flexible SDM tool for LCS in PWH. InterpretationPWH and providers were enthusiastic about specific tools for SDM which are personalized and tailored for PWH, make recommendations, and that inform LCS decision-making. Divergent views on presenting patient-facing quantitative risk assessments suggests these elements could be optional but available for review. This tool may have utility in complex decision-making for LCS in this population and is currently being evaluated in a pilot prospective trial.

How well does your e-nose detect cancer? Application of artificial breath analysis for performance assessment

Comparing electronic nose (e-nose) performance is a challenging task because of a lack of standardised method. This paper proposes a method for defining and quantifying an indicator of the effectiveness of multi-sensor systems in detecting cancers by artificial breath analysis. To build this method, an evaluation of the performances of an array of metal oxide sensors built for use as a lung cancer screening tool was conducted. Breath from 20 healthy volunteers has been sampled in fluorinated ethylene propylene sampling bags. These healthy samples were analysed with and without the addition of nine volatile organic compound (VOC) cancer biomarkers, chosen from literature. The concentration of the VOC added was done in increasing amounts. The more VOC were added, the better the discrimination between ‘healthy’ samples (breath without additives) and ‘cancer’ samples (breath with additives) was. By determining at which level of concentration the e-nose fails to reliably discriminate between the two groups, we estimate its ability to well predict the presence of the disease or not in a realistic situation. In this work, a home-made e-nose is put to the test. The results underline that the biomarkers need to be about 5.3 times higher in concentration than in real breath for the home-made nose to tell the difference between groups with a sufficient confidence.

Cost effective quality improvement initiative in lung cancer screening: A single institutional pilot program.

458 Background: US Preventive Services Task Force (USPSTF) recommends lung cancer screening (LCS) with annual low-dose computed tomography (LDCT) screening for individuals aged 50-80 years with ≥20 pack-year smoking history. Nevertheless, only 4%-13% of eligible individuals are screened nationally. Lung cancer mortality is higher in the South where low socioeconomic status and racial minorities predominate and the screening rate in Alabama is between 4.7% - 7.7%. Thomas Hospital belongs to this catchment area and the goal of our study was to improve LCS with LDCT by embarking on a quality improvement initiative which was commenced as a pilot program for a larger healthcare system (>5 large outpatient clinics with over 12,000 visits/month). Methods: Data were obtained retrospectively by reviewing the electronic medical records of eligible patients for LCS from 01/22 to 01/23 who visited the Thomas Hospital Internal Medicine Residency Clinic (pilot study site). A multidisciplinary team was created involving Thoracic oncologists, radiologists, Thoracic surgeons, resident physicians, and PCPs to identify barriers to LCS and discuss methods on how to improve LCS. We identified areas to be improved on and utilized performance improvement tools such as a Pareto chart and a PICK chart. Data was then collected prospectively. Results: In the initial 12-month period, only 6.95% (total n=185) of patients who qualified for LCS had LDCT done for LCS. The major barriers to screening were poor smoking history documentation, lack of proper identification of screening candidates, lack of awareness of screening guidelines, infrequent follow-up, discrepancies in smoking history within the EMR, and lack of a consistent system for LDCT referral. We identified 4 main initiatives which were introduced monthly, one at a time. The interventions include Educational services/Awareness campaigns on LCS, Distribution of current LCS guidelines in the clinic rooms/offices, Patient self-reported questionnaire on smoking history, and Implementation of an EPIC flag tool for LCS. We reviewed our performance after the interventions and the total LCS after 4 interventions included 48 (47%) patients compared to 102 patients who fit the screening criteria. 5 patients had LDCT ordered but yet to be completed and 6 patients had findings that needed immediate evaluation and received appropriate referrals. Conclusions: Lung cancer screening remains suboptimal in the United States, especially in the southern region. With our approach, the screening rates have increased exponentially only within a few months compared to the previous year and this model is to be adopted by other clinics affiliated with the umbrella health system. LDCT does carry certain risks including false positive results and unnecessary biopsies; hence shared decision-making is needed before ordering the test.

B-360 Usefulness of the Ratios of CYFRA21-1 and p53 Autoantibody Immune Complexes to Their Free Antigens in Lung Cancer

Abstract Background Autoantibodies against specific cancer-associated antigens are produced in the early stages of tumorigenesis. In lung cancer, the possibility of autoantibodies as diagnostic biomarkers has been proposed. This study was to evaluate the usefulness of novel DNA-guided sandwich immunoassay detecting CYFRA21-1 and p53 autoantibody immune complexes and their free antigens in diagnosis of lung cancer. Methods In total, 100 patients with lung cancer and 119 healthy controls were analyzed with 9G testTM Lung/Cancer (Biometrix Technology, South Korea) measuring plasma autoantibody immune complexes (CYFRA21-1 with anti-CYFRA21-1 autoantibody immune complex (CIC), p53 with anti-p53 autoantibody immune complex (PIC)) and their free antigens (CYFRA 21-1 and p53). The ratios of CIC to CYFRA21-1 (CIC/CYFRA21-1) and PIC to p53 (PIC/p53), and the multiplication of the two ratios, named as LC index were calculated. Results The levels of CIC and PIC were significantly increased in lung cancer compared with those in healthy control (P = 0.0062 and P = 0.0026, respectively), while free antigens didn’t distinguish between lung cancer and healthy control. The ratios CIC/CYFRA21-1 and PIC/p53 were significantly higher in lung cancer than those in healthy control (all, P < 0.0001). Diagnostic performances expressed as area under the curve (AUC) were higher in the ratios of autoantibody immune complexes to each free antigen (PIC/p53 and CIC/CYFRA21-1) than autoantibody immune complexes (PIC and CIC) (AUC; 0.887, 0.847 vs 0.618, 0.608, respectively). The most excellent diagnostic performance was proven with LC index at diagnostic cut-off 3.60, which showed 81% sensitivity and 95% specificity with 0.945 AUC (P < 0.001). It was more sensitive to early lung cancer than to advanced lung cancer (sensitivity 87.5% vs 72.7%). Conclusion The ratios of CIC to CYFRA21-1 and PIC to p53 are useful biomarkers in lung cancer diagnosis and the combination of the ratios, LC index could be complementary tool for lung cancer screening with radiological tests.

Novel tools for early diagnosis and precision treatment based on artificial intelligence.

Lung cancer has the highest mortality rate among all cancers in the world. Hence, early diagnosis and personalized treatment plans are crucial to improving its 5-year survival rate. Chest computed tomography (CT) serves as an essential tool for lung cancer screening, and pathology images are the gold standard for lung cancer diagnosis. However, medical image evaluation relies on manual labor and suffers from missed diagnosis or misdiagnosis, and physician heterogeneity. The rapid development of artificial intelligence (AI) has brought a whole novel opportunity for medical task processing, demonstrating the potential for clinical application in lung cancer diagnosis and treatment. AI technologies, including machine learning and deep learning, have been deployed extensively for lung nodule detection, benign and malignant classification, and subtype identification based on CT images. Furthermore, AI plays a role in the non-invasive prediction of genetic mutations and molecular status to provide the optimal treatment regimen, and applies to the assessment of therapeutic efficacy and prognosis of lung cancer patients, enabling precision medicine to become a reality. Meanwhile, histology-based AI models assist pathologists in typing, molecular characterization, and prognosis prediction to enhance the efficiency of diagnosis and treatment. However, the leap to extensive clinical application still faces various challenges, such as data sharing, standardized label acquisition, clinical application regulation, and multimodal integration. Nevertheless, AI holds promising potential in the field of lung cancer to improve cancer care.

R.E.A.C.T-Rapid Electro-Analytical graphitic Carbon nitride-based screening Tool for lung cancer – Case study using heptane

Early disease detection and diagnosis through breath-based chemical assessment is broadly studied as a non-invasive tool and used as a cutting-edge opportunity in health care. Breath analytics or Breathomics is based on the recognition of levels of metabolites such as Volatile Organic Compounds (VOCs) and inorganic gases in an exhaled human breath. Lung cancer, one such disease state, alters the concentrations of hydrocarbons released in breath due to oxidative stress and lipid pre-oxidation. Heptane can be utilized as a VOC biomarker for the non-invasive diagnosis of lung cancer. This work outlines the fabrication of a graphitic carbon nitride-based electrochemical sensor platform that possesses increased catalytic activity and can be used for the screening of heptane vapors in the range of 0.45–5 ppm limit of detection of 0.45 ppm with 95% confidence interval. The synthesized material is characterized and validated using various standard analytical methods. Chronoamperometry is employed as an electrochemical technique to examine the diffusion dynamics of the target analyte. We demonstrated the specific sensing responses of the system in the presence of interferants by executing a cross-reactivity study with respect to other commonly found interferants in breath. We effectively established the use of a graphitic carbon nitride-based electrochemical sensor for point-of-care screening (qualitative analysis with p < 0.05) of heptane levels by the development of a prototype device utilizing a commercial microelectronic board. We envision that the in-house fabricated modified electrode platform can aid in early screening for lung cancer, thus leading to a reduction in the mortality rate.

Biomarkers in Lung Cancer Screening: a Narrative Review.

Although when used as a lung cancer screening tool low-dose computed tomography (LDCT) has demonstrated a significant reduction in lung cancer related mortality, it is not without pitfalls. The associated high false positive rate, inability to distinguish between benign and malignant nodules, cumulative radiation exposure, and resulting patient anxiety have all demonstrated the need for adjunctive testing in lung cancer screening. Current research focuses on developing liquid biomarkers to complement imaging as non-invasive lung cancer diagnostics. Biomarkers can be useful for both the early detection and diagnosis of disease, thereby decreasing the number of unnecessary radiologic tests performed. Biomarkers can stratify cancer risk to further enrich the screening population and augment existing risk prediction. Finally, biomarkers can be used to distinguish benign from malignant nodules in lung cancer screening. While many biomarkers require further validation studies, several, including autoantibodies and blood protein profiling, are available for clinical use. This paper describes the need for biomarkers as a lung cancer screening tool, both in terms of diagnosis and risk assessment. Additionally, this paper will discuss the goals of biomarker use, describe properties of a good biomarker, and review several of the most promising biomarkers currently being studied including autoantibodies, complement fragments, microRNA, blood proteins, circulating tumor DNA, and DNA methylation. Finally, we will describe future directions in the field of biomarker development.

Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation.

BackgroundLung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account for this heterogeneity during decision-making, web-based decision support tools are needed to enable quick calculations and streamline the process of obtaining individualized information that more accurately informs patient-clinician LCS discussions. We created DecisionPrecision, a clinician-facing web-based decision support tool, to help tailor the LCS discussion to a patient’s individualized lung cancer risk and estimated net benefit.ObjectiveThe objective of our study is to test two strategies for implementing DecisionPrecision in primary care at eight Veterans Affairs medical centers: a quality improvement (QI) training approach and academic detailing (AD).MethodsPhase 1 comprised a multisite, cluster randomized trial comparing the effectiveness of standard implementation (adding a link to DecisionPrecision in the electronic health record vs standard implementation plus the Learn, Engage, Act, and Process [LEAP] QI training program). The primary outcome measure was the use of DecisionPrecision at each site before versus after LEAP QI training. The second phase of the study examined the potential effectiveness of AD as an implementation strategy for DecisionPrecision at all 8 medical centers. Outcomes were assessed by comparing absolute tool use before and after AD visits and conducting semistructured interviews with a subset of primary care physicians (PCPs) following the AD visits.ResultsPhase 1 findings showed that sites that participated in the LEAP QI training program used DecisionPrecision significantly more often than the standard implementation sites (tool used 190.3, SD 174.8 times on average over 6 months at LEAP sites vs 3.5 SD 3.7 at standard sites; P<.001). However, this finding was confounded by the lack of screening coordinators at standard implementation sites. In phase 2, there was no difference in the 6-month tool use between before and after AD (95% CI −5.06 to 6.40; P=.82). Follow-up interviews with PCPs indicated that the AD strategy increased provider awareness and appreciation for the benefits of the tool. However, other priorities and limited time prevented PCPs from using them during routine clinical visits.ConclusionsThe phase 1 findings did not provide conclusive evidence of the benefit of a QI training approach for implementing a decision support tool for LCS among PCPs. In addition, phase 2 findings showed that our light-touch, single-visit AD strategy did not increase tool use. To enable tool use by PCPs, prediction-based tools must be fully automated and integrated into electronic health records, thereby helping providers personalize LCS discussions among their many competing demands. PCPs also need more time to engage in shared decision-making discussions with their patients.Trial RegistrationClinicalTrials.gov NCT02765412; https://clinicaltrials.gov/ct2/show/NCT02765412

43 - Community lung health check as a screening tool for lung cancer: the prevalence and impact of significant other findings

43 - Community lung health check as a screening tool for lung cancer: the prevalence and impact of significant other findings

Detection of antibodies against benzo[a]pyrene in blood sera of lung cancer patients by ELISA using human recombinant idiotypic and anti-idiotypic antibodies.

ELISA was developed and applied for the detection of endogenous idiotypic and anti-idiotypic antibodies against Bp in human blood sera using recombinant human idiotypic and anti-idiotypic antibodies against Bp. Serum samples of LC patients (n = 22) and healthy donors (n = 24) were analyzed by the new method. Statistical analysis showed that in sera of LC patients the levels of endogenous idiotypic and anti-idiotypic antibodies against Bp were significantly higher than in healthy donors. A logistic regression model for the LC detection utilizing such predictors as the serum levels of idiotypic and anti-idiotypic antibodies against Bp, smoking status, and age, identified LC patients with 83% specificity and 82% sensitivity. The proposed method could be further developed as additional lung cancer screening tool.

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.

64 - Community lung health check as a screening tool for lung cancer: initial results from a Bradford pilot

64 - Community lung health check as a screening tool for lung cancer: initial results from a Bradford pilot

Primary care and pulmonary physicians' knowledge and practice concerning screening for lung cancer in Lebanon, a middle-income country.

ABSTRACTBackgroundScreening for lung cancer with low‐dose computed tomography (LDCT) was shown to reduce lung cancer incidence and overall mortality, and it has been recently included in international guidelines. Despite the rising burden of lung cancer in low and middle‐income countries (LMICs) such as Lebanon, little is known about what primary care physicians or pulmonologists know and think about LDCT as a screening procedure for lung cancer, and if they recommend it.ObjectivesEvaluate the knowledge about LDCT and implementation of international guidelines for lung cancer screening among Lebanese primary care physicians (PCPs) and pulmonary specialists.MethodologyPCPs and PUs based in Lebanon were surveyed concerning knowledge and practices related to lung cancer screening by self‐administered paper questionnaires.Results73.8% of PCPs and 60.7% of pulmonary specialists recognized LDCT as an effective tool for lung cancer screening, with 63.6% of PCPs and 71% of pulmonary specialists having used it for screening. However, only 23.4% of PCPs and 14.5% of pulmonary specialists recognized the eligibility criteria for screening. Chest X‐ray was recognized as ineffective by only 55.8% of PCPs and 40.7% of pulmonary specialists; indeed, 30.2% of PCPs and 46% of pulmonary specialists continue using it for screening. The majority have initiated a discussion about the risks and benefits of lung cancer screening.ConclusionPCPs and pulmonary specialists are initiating discussions and ordering LDCT for lung cancer screening. However, a significant proportion of both specialties are still using a non‐recommended screening tool (chest x‐ray); only few PCPs and pulmonary specialists recognized the population at risk for which screening is recommended. Targeted provider education is needed to close the knowledge gap and promote proper implementation of guidelines for lung cancer screening.

Patient Perspectives on the Risk-Based NLST Outcomes Tool for Lung Cancer Screening.

Researchers at the NCI have developed the Risk-Based NLST Outcomes Tool (RNOT), an online tool that calculates risk of lung cancer diagnosis and death with and without lung cancer screening, and false-positive risk estimates. This tool has the potential to facilitate shared decision making for screening. The objective of this study was to examine how current heavy and former smokers understand and respond to personalized risk estimates from the RNOT. Individuals who were eligible for lung cancer screening and were visiting Walter Reed National Military Medical Center were invited to participate in a semi-structured interview to assess their experiences with and perceptions of the RNOT. Results were analyzed using template analysis. Participants found their risk of lung cancer death to be lower than anticipated and were confused by changes in risk for lung cancer diagnosis with and without screening. Most participants indicated that the RNOT would be helpful in making screening decisions, despite reporting that there was no maximum risk for a false positive that would lead them to forgo lung cancer screening. Participants provided actionable needs and recommendations to optimize this tool. Risk-based screening tools may enhance shared decision making. The RNOT is being updated to incorporate these findings.