Lung Cancer Screening Research Articles

Basics and Imaging Aspects for Lung Cancer Screening

Basics and Imaging Aspects for Lung Cancer Screening

Lung cancer screening: Real screening site data, Vojvodina, Serbia

Abstract Background Lung cancer (LC) is the top cause of cancer-related deaths globally and in Serbia, often diagnosed in advanced stage of disease with when 5-year survival is 10% to 20%. LC screening with low-dose CT (LDCT) can decrease LC mortality and overall mortality. The first pilot LC screening program in Serbia started in the Institute for Pulmonary Diseases of Vojvodina in September 2020. The main objective of this study was to analyze LC patient characteristics according to their screening status. Methods This retrospective study utilized LC hospital registry data from September 2020 to December 2023, including gender, age at diagnosis, settlement area, smoking habits, cancer histological type, TNM classification, disease stage (1-4), and data on participation in LC screening. Group differences were assessed using chi-square and Student’s t-tests, with analyses conducted in SPSS v24.0. Results During observed period from a total of 4649 LC cases 2948 (63.4%) were males, and 73 (1.6%) were included in LC screening. Average age of all LC patients was 66 years, without differences between groups (p = 0.778). Significant differences between groups by gender were find (p = 0.042). Non-screened LC patients were significantly common males compared to females (63.6% vs 36.4%), while among screened difference by gender were lower (52.1% vs 47.9%, respectively). Screened compared to non-screened LC patients have significantly lower percentage of SCLC (9.6% vs 19.1%), and higher percentage of NSCLC (90.4% vs 80.9%), (p = 0.040). According to LC stage, screened compared to non-screened patients were significantly common diagnosed in stage I of disease (45.8% vs 7.8%), and significantly less common in higher LC stages; stage IIIB (11.1% vs 22.5%), and in stage IV (22.2% vs 45.7%), (p < 0.001). Conclusions LC screening with LDCT is proven secondary preventive measure with significant influence on decreasing LC mortality by increasing number of LC patients in early stages of disease. Key messages • Lung cancer screening with low-dose CT significantly increases early-stage diagnoses, improving survival chances. • Population strategies to prevent smoking and screening programs for high-risk groups are needed to reduce lung cancer incidence and mortality rates in Serbia.

A 16-year evaluation of opportunistic lung cancer screening with low-dose CT in China: comparative findings between non-smokers and smokers

BackgroundAlthough low-dose computed tomography (LDCT) screening effectively reduces LC mortality in high-risk individuals with a history of smoking in China, the feasibility and efficacy of lung cancer screening (LCS) in individuals who never smoked versus individuals who smoked remains unclear.MethodsWe conducted a retrospective analysis of prospective cohort studies at the National Cancer Center (NCC) in China from January 2006 to December 2022. A comprehensive LCS initiative was undertaken, involving 30,468 participants (54.5% male). Participants underwent LCS using LDCT. Potential malignancies were managed through joint consensus between patients and their physicians. Epidemiology, screening eligibility criteria, and LC detection rates and survival outcomes were compared between individuals who smoked and individuals who never smoked.ResultsAmong 30,468 participants, 339 LCs were pathologically confirmed in 289 patients. The LC detection rate was 0.9% (289/30,468) overall, 0.8% in individuals who smoked (71/9,042), and 1.0% in individuals who never smoked (218/21,426). In individuals who smoked, LC detection rates were 0.5% (21/4516) and 1.1% (50/4526) in the < 20 and ≥ 20 pack-year subgroups, respectively (P = 0.001). Early-stage LC (stage 0 or I) was detected in 73.8% of the individuals who smoked and in 78.8% of individuals who never smoked, while advanced LC (stage III–IV) was found 8.8% of individuals who smoked and 4.2% of individuals who never smoked, respectively. Significant differences in histologic types were found between individuals who smoked and individuals who never smoked (P = 0.01), although adenocarcinoma was the most prevalent in both groups, at 83.0% and 78.8%, respectively. The median nodule size was 9.9 mm (IQR, 8.0–13.8) in individuals who smoked and 9.2 mm (IQR, 6.8–13.6) in individuals who never smoked (P = 0.228). Individuals who never smoked tended to favour surgical treatment alone (88.0%) more than individuals who smoked (81.3%). The 10-year survival rate was higher in individuals who never smoked (92.6%) than in individuals who smoked (88.8%). Only 15.6% (45/289) of patients with LC met the United States Preventive Services Task Force (USPSTF) criteria for LDCT eligibility, while 29.0% (84/289) met the China guideline for the screening and early detection of lung cancer (CGSL) criteria. Median follow-up for those followed was 25.4 (IQR, 13.7–43.3) months.ConclusionsLDCT screening improves early LC detection and treatment outcomes for both individuals who smoked and individuals who never smoked. Significant differences exist in epidemiology, histologic type, and survival between these groups. The USPSTF and CGSL criteria miss a significant number of LC cases, particularly among individuals who never smoked. Integrating individuals who never smoked into LCS programs is essential, yet it comes with its own challenges, such as managing radiation risks, allocating resources effectively, and considering financial aspects. Consequently, there is an urgent need for LCS programs in China to better identify the “high-risk” non-smoker population susceptible to LC and to ensure that potential risks associated with screening are reduced.

Artificial Intelligence in Medical Diagnostics

Artificial intelligence (AI) is an essential tool in the medical sector that contributes significantly to medical imaging, medical pathology, histology, genomic study, predictive analysis, etc. It is being increasingly used not only in breast and lung cancer diagnosis and screening, and genetic disease identification but also in personalized decision-making during the treatment of these diseases. The quality and availability of unbiased data is a key challenge. Algorithmic bias and interpretability are significant concerns as well. Improving the use of AI in medical diagnostics could be achieved through continuous monitoring, access to highly accurate datasets, and timely intervention by healthcare professionals. J Bangladesh Coll Phys Surg 2024; 42: 379-382

AI-enabled cardiac chambers volumetry in non-contrast coronary artery calcium CT scans vs. contrast-enhanced coronary CT angiography scans in the same patients

Abstract Introduction We have developed an AI-enabled automated volumetry of cardiac chambers (AutoChamber) that works both on non-contrast ECG-gated cardiac CT scans used for coronary artery calcium (CAC) score, and non-contrast non-gated lung cancer screening CT scans. We have recently reported the agreement between AutoChamber measurements vs cardiac MRI measurements. Here we report AutoChamber results on non-contrast CAC scans and contrast enhanced coronary CT angiography (CTA). Methods We have obtained CT images from a previously published study in which 131 cases underwent non-contrast CAC and contrast enhanced CCTA at research institute. The cases consisted of 52.4% women with ages 55.0 ± 10.1 years. The cardiac chambers volume in 131 cases of contrast enhanced CCTA were measured using automated chamber volumetry by Philips Brilliance Volume v 4.5; Philips Healthcare. Results The correlations between Philips’ automated chamber volumetry in contrast enhanced CCTA scans versus AutoChamber automated volumetry in non-contrast CAC scans for left atrium (LA), left ventricle (LV), right atrium (RA), right ventricle (RV), and left ventricular wall (LVW) volume were 0.73, 0.65, 0.85, 0.93, 0.90, respectively (P for all &amp;lt;0.01). Conclusion AI-enabled AutoChamber volumetry based on non-contrast cardiac scans is feasible, and correlates reasonably well with contrast-enhanced cardiac CT scans. Further studies are warranted to reproduce these results and explore the add-on value of AutoChamber to CAC scans.

AI-enabled automated cardiac chambers volumetry in non-contrast ECG-gated cardiac scans vs. non-contrast non-gated lung scans

Abstract Introduction We have developed an AI-enabled automated volume measurement of cardiac chambers (AutoChamber) that works on ECG-gated coronary artery calcium scans and correlates well with contrast enhanced coronary CT angiography scans. We have recently reported that increased left atrial volume measured by AutoChamber is a strong predictor of new onset atrial fibrillation (AF) in asymptomatic individuals of Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we compare the volumetry results in ECG- gated CAC scans with those of non-gated full-chest lung cancer screening scans in the same individuals. Methods We have studied 169 cases of paired ECG-gated cardiac CT scans and non-gated lung scans obtained from Harbor UCLA. Mean±SD for age was 62.1±10.0 years with 52% female participants. All cases were asymptomatic and were scanned for preventive health assessment. AutoChamber was run on all cases by an independent operator who was not involved in data analysis. P value was calculated using a two-tailed test of significance with α=0.05. Results AutoChamber in cardiac scans vs lung scans reported volume (Mean±SD) for left atrium (LA) was 63.8 ± 18.5 vs. 65.5 ± 19.4, left ventricle (LV) 102.8 ± 25.3 vs. 105.5 ± 25.2, right atrium (RA) 81.9 ± 20.5 vs. 85.7 ± 21.9 right ventricle (RV), 140.7 ± 34.2 vs. 134.2 ± 33.7, left ventricle wall (LVW) 113.0 ± 26.6 vs. 109.7 ± 27.0 respectively (P &amp;lt; 0.0001). Strong correlation was shown between cardiac and lung scans for each cardiac chamber: LA (R = 0.92), LV (R = 0.93), RA (R = 0.91), RV (R = 0.92), and left ventricular wall (LVW) R = 0.95. Conclusions AutoChamber volumetry results are similar in ECG-gated cardiac scans vs non-gated full-chest lung scans. This AI-enabled automated tool is promising as it can provide added value to patients undergoing coronary calcium and lung cancer screening scans flagging enlarged cardiac chambers at risk of AF and heart failure.

The triglyceride glucose: high-density lipoprotein cholesterol ratio is associated with coronary artery calcification evaluated via non-gated chest CT

BackgroundCoronary artery calcification (CAC) is a common risk factor of cardiovascular disease. Although triglyceride glucose (TYG) index and high-density lipoprotein cholesterol (HDL-c) are both associated with CAC, no study has evaluated the correlation between the TYG/HDL-c ratio and CAC. In the present study, we investigated the relationships between CAC and the TYG index and the TYG/HDL-c ratio.MethodsA total of 9585 participants who underwent computed tomography (CT) screening for lung cancer from 2018 to 2020 were included in this cross-sectional study. Demographic data, laboratory test data and medical history data were collected from medical records. TYG = Ln[fasting glucose (mg/dL)×fasting TG (mg/dL/2]. The triglyceride glucose-HDL-c ratio was calculated as TYG/HDL-c. CAC was evaluated on chest CT images. Multivariate logistic regression analysis and restricted cubic splines were used to determine the relationships among the TYG index, TYG/HDL-c ratio and risk of CAC. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the TYG index and TYG/HDL-c ratio in identifying CACs in individuals aged 60 years and above.ResultsCAC was detected in 2515 of 9585 participants (mean age 51.8 ± 15.5 years, 61.2% men). The prevalence of CAC was significantly greater in participants with a high TYG/HDL-c ratio (32.6% in the fourth quartile vs. 19.1% in the first quartile, p < 0.001). Multivariate logistic regression revealed that both the TYG index (odds ratio (OR) = 1.06, 95% confidence interval (CI): 1.02–1.10) and the TYG/HDL-c ratio were associated with coronary artery calcification (OR = 1.32, 95% CI: 1.14–1.51). No such association was observed between the TYG index and CAC when further adjusted for the serum lipid level (OR = 1.23, 95% CI: 0.99–1.54). The TYG/HDL-c ratio was still associated with CAC after further adjustment for low-density lipoprotein cholesterol and total cholesterol (OR = 1.21, 95% CI: 1.09–1.35). TYG/HDL-c ratio was associated both with single vessel and multivessel calcification (OR = 1.14, 95%CI:1.05–1.23; OR = 1.15, 95%CI: 1.05–1.21). Similar trends were observed when we categorized individuals by TYG index and TYG/HDL-c quartiles and in subjects older than 60 years. Restricted cubic splines revealed that the TYG/HDL ratio had a better dose‒responsive relationship than did the TYG index. Subgroup analysis revealed that the association between the TYG/HDL-c ratio and coronary artery calcification was mainly observed in nondiabetic or nonhypertensive participants, regardless of low-density lipoprotein cholesterol levels. The ROC curve also revealed that the TYG/HDL-c ratio was better able to identify CAC than the TYG index was (area under the curve = 0.54 vs. 0.52, p < 0.01) in subjects older than 60 years.Conclusion An increase in the TYG/HDL-c ratio is significantly positively associated with the risk of CAC, and the TYG/HDL-c ratio has a more stable association with CAC than TYG.

Association of chronic obstructive pulmonary disease with risk of lung cancer in individuals aged 40 years and older: A cross-sectional study based on NHANES 2013-2018.

It remains unclear whether chronic obstructive pulmonary disease (COPD) is an independent risk factor for lung cancer after excluding confounding factors such as smoking, age, sex, body mass index (BMI), comorbidities, etc. Data from 11,440 participants (≥ 40 years old) in the National Health and Nutrition Examination Survey (NHANES) 2013-2018 were analyzed. Weighted multivariable logistic regression models were used to assess the association between COPD and lung cancer risk. Subgroup analyses were based on age, sex, BMI, and smoking. This study included 660 patients with COPD and 10,780 participants without COPD. The prevalence of lung cancer was significantly higher in patients with COPD compared to participants without COPD (3.39% vs 0.14%). After adjusting for confounding factors, COPD was associated with a significantly increased risk of lung cancer (OR, 12.24, 95% CI, 4.99-30.06, p < 0.001). This association remained significant in all subgroups, particularly in individuals aged > 65 years (OR, 20.05, 95% CI, 6.85-58.72, p < 0.001), smokers (OR, 19.38, 95% CI, 2.02-185.66, p = 0.010), males (OR, 17.39, 95% CI, 5.28-57.31, p < 0.001), individuals who quit smoking within 10 years (OR, 12.86, 95% CI, 2.59, 63.99, p = 0.002), and individuals with a BMI > 25 kg/m2 (OR, 14.56, 95% CI, 3.88-54.69, p < 0.001). COPD is an independent risk factor for lung cancer, especially in certain subgroups. The combination of COPD and smoking greatly amplifies the lung cancer risk. These findings highlight the importance of early lung cancer screening in patients with COPD.

Abstract Highlights

The following abstract highlights spotlight selected abstracts presented at the European Respiratory Society (ERS) Congress 2024. They cover key topics, including lung cancer screening and management, Chronic obstructive pulmonary disease, cystic fibrosis, effects of smoking on airway inflammation, and the role of biologic therapy in asthma. These highlights showcase the latest cutting-edge developments and most talked-about topics in the field today.

The TELEhealth Shared decision-making COaching and navigation in Primary carE (TELESCOPE) intervention: a study protocol for delivering shared decision-making for lung cancer screening by patient navigators.

Lung cancer screening (LCS) can reduce lung cancer mortality but has potential harms for patients. A shared decision-making (SDM) conversation about LCS is required by the Centers for Medicare & Medicaid Services (CMS) for LCS reimbursement. To overcome barriers to SDM in primary care, this protocol describes a telehealth decision coaching and navigationintervention for LCS in primary care clinics delivered by patient navigators. The objective of the study is to evaluate the effectiveness of the intervention and its implementation potential, compared with an enhanced usual care (EUC) arm. Patients (n = 420) of primary care clinicians (n = 120) are being recruited to a cluster randomized controlled trial. Clinicians are randomly assigned to 1) TELESCOPE intervention: prior to an upcoming non-acute clinic visit, patients participate in a telehealth decision coaching and navigationsession about LCS delivered by trained patient navigators and nurse navigators place a low-dose CT scan (LDCT) order for each TELESCOPE patient wanting LCS, or 2) EUC: patients receive enhanced usual care from a clinician. Usual care is enhanced by providing clinicians in both arms with access to a Continuing Medical Education (CME) webinar about LCS and an LCS discussion guide. Patients complete surveys at baseline and 1-week after the scheduled clinic visit to assess quality of the SDM process. Re-navigation is attempted with TELESCOPE patients who have not completed the LDCT within 3months. One month before being due for an annual screening, TELESCOPE patients whose initial LCS showed low-risk findings are randomly assigned to receive a telehealth decision coaching booster session with a navigator or no booster. Electronic health records are abstracted at 6, 12 and 18months after the initial decision coaching session (TELESCOPE) or clinic visit (EUC) to assess initial and annual LCS uptake, imaging results, follow-up testing for abnormal findings, cancer diagnoses, treatment, and tobacco treatment referrals. This study will evaluate factors that facilitate or interfere with program implementation using mixed methods. We will assess whether a decision coaching and patient navigation intervention can feasibly and effectivelysupport high-quality SDM for LCS and guideline-concordant LCS uptake for patients in busy primary care practices serving diverse patient populations. This study was registered at ClinicalTrials.gov (NCT05491213) on August 4, 2022. Version 1, April 10, 2024.

Adherence to a low-fat dietary pattern reduces head and neck cancer risk: evidence from the PLCO trial

PurposeLow-fat dietary (LFD) pattern refers to a dietary structure with reduced fat intake. The aim was to investigate the association between LFD pattern and risk of head and neck cancer (HNC).MethodsData were derived from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. LFD score was used to assess adherence to an LFD pattern, with higher scores indicating greater adherence. Cox regression was used to evaluate the association between LFD score and risk of HNC and its subtypes. To visualize the trend in risk of HNC and its subtypes with changing LFD score, restricted cubic spline plots were utilized. A series of subgroup analyses were conducted to identify potential confounders. Sensitivity analyses were performed to assess the robustness of the results.ResultsAmong 98,459 participants of PLCO trial, 268 cases with HNC were identified during an average of 8.8 years of follow-up. In the fully adjusted model, participants in the highest compared with the lowest quartiles of LFD score had a lower risk of HNC (HR Q4 vs. Q1: 0.60; 95% CI: 0.40–0.90; P for trend = 0.026) and larynx cancer (HRQ4 vs. Q1: 0.46; 95% CI: 0.22–0.96; P for trend = 0.039). The restricted cubic spline plots demonstrated a linear dose-response relationship between the LFD score and the risk of HNC and its subtypes (all P for nonlinearity > 0.05). The primary association remained robust in the sensitivity analysis.ConclusionOur findings suggest that adherence to an LFD pattern may lower the risk of HNC in the US population.

Software using artificial intelligence for nodule and cancer detection in CT lung cancer screening: systematic review of test accuracy studies

ObjectivesTo examine the accuracy and impact of artificial intelligence (AI) software assistance in lung cancer screening using CT.MethodsA systematic review of CE-marked, AI-based software for automated detection and analysis of...

MA04.05 An Evolution and Expanding Engagement to Excel in Lung Cancer Screening

MA04.05 An Evolution and Expanding Engagement to Excel in Lung Cancer Screening

P4.04C.07 Improving the Efficiency of Lung Cancer Screening Through a Blood-based Lung Cancer Screening Test Prior to Low-Dose CT

P4.04C.07 Improving the Efficiency of Lung Cancer Screening Through a Blood-based Lung Cancer Screening Test Prior to Low-Dose CT

OA17.05 A Randomized Controlled Trial of a Digital Lung Health Intervention to Facilitate Smoking Cessation and Lung Cancer Screening

OA17.05 A Randomized Controlled Trial of a Digital Lung Health Intervention to Facilitate Smoking Cessation and Lung Cancer Screening

The Potential Benefit of a Novel Urine Biosensor Platform for Lung Cancer Detection in the Decision-Making Process: From the Bench to the Bedside

Background: Lung cancer is the leading cause of cancer-related mortality worldwide. Lung cancer screening and early detection resulted in a decrease in cancer-specific mortality; however, it introduced additional dilemmas and adherence barriers for patients and providers. Methods: Innovations such as biomolecular diagnosis and biosensor-based technology improve the detection and stratification of high-risk patients and might assist in overcoming adherence barriers, hence providing new horizons for better selection of screened populations. Conclusions: In the present manuscript, we discuss some of the dilemmas clinicians are currently facing during the diagnosis and treatment processes. We further highlight the potential benefits of a novel biosensor platform for lung cancer detection during the decision making process surrounding lung cancer.

P4.04C.03 Nodule Type Classification for Lung Cancer Screening with CT

P4.04C.03 Nodule Type Classification for Lung Cancer Screening with CT

MA18.03 Participant Eligibility for Lung Cancer Screening in Australia: An Analysis of Proposed Criteria

MA18.03 Participant Eligibility for Lung Cancer Screening in Australia: An Analysis of Proposed Criteria

P2.04B.06 Lung Cancer Screening Program in Serbia: A 3-year- Results and Challenges

P2.04B.06 Lung Cancer Screening Program in Serbia: A 3-year- Results and Challenges

P2.04B.09 A Qualitative Evaluation of the Critical Role of Lung Cancer Screening Program Navigators

P2.04B.09 A Qualitative Evaluation of the Critical Role of Lung Cancer Screening Program Navigators