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Objectives: Invasive adenocarcinomas (IADs) have been identified among nonsolid nodules (NSNs) assigned as Lung Imaging Reporting and Data System (Lung-RADS) category 2. This study used visual assessment for differentiating IADs from noninvasive lesions (NILs) in this category. Methods: This retrospective study included 222 patients with 242 NSNs, which were resected after preoperative computed tomography (CT)–guided dye localization. Visual assessment was performed by using the lung and bone window (BW) settings to classify NSNs into BW-visible (BWV) and BW-invisible (BWI) NSNs. In addition, nodule size, shape, border, CT attenuation, and location were evaluated and correlated with histopathological results. Logistic regression was performed for multivariate analysis. A p value of < 0.05 was considered statistically significant. Results: A total of 242 NSNs (mean diameter, 7.6 ± 2.8 mm), including 166 (68.6%) BWV and 76 (31.4%) BWI NSNs, were included. IADs accounted for 31% (75) of the nodules. Only 4 (5.3%) IADs were identified in the BWI group and belonged to the lepidic-predominant (n = 3) and acinar-predominant (n = 1) subtypes. In univariate analysis for differentiating IADs from NILs, the nodule size, shape, CT attenuation, and visual classification exhibited statistical significance. Nodule size and visual classification were the significant predictors for IAD in multivariate analysis with logistic regression (p < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value of visual classification in IAD prediction were 94.7%, 43.1%, 42.8%, and 94.7%, respectively. Conclusions: The window-based visual classification of NSNs is a simple and objective method to discriminate IADs from NILs. Clinical relevance statement: The present study shows that using the bone window to classify nonsolid nodules helps discriminate invasive adenocarcinoma from noninvasive lesions. Key Points: • Evidence has shown the presence of lung adenocarcinoma in Lung-RADS category 2 nonsolid nodules. • Nonsolid nodules are classified into the bone window–visible and the bone window–invisible nonsolid nodules, and this classification differentiates invasive adenocarcinoma from noninvasive lesions. • The Lung-RADS category 2 nonsolid nodules are unlikely invasive adenocarcinoma if they show nonvisualization in the bone window. [ABSTRACT FROM AUTHOR]

Objective: Mobile low-dose computed tomography (LDCT) lung screenings are part of an outreach program in rural Appalachia to detect early lung cancer. Coronary artery calcium (CAC) scoring on LDCT can identify calcium deposits in coronary arteries and can prompt consideration of risk modification for prevention of cardiovascular disease (CVD) events. It is not known if Lung CT Screening Reporting & Data System (Lung-RADS) scoring correlates with CAC scores. There is no clear guidance for patients undergoing LDCT screenings to receive follow-up regarding CAC or prevention of associated CVD risk. Methods: This was a retrospective review of mobile LDCT LCS in adults with no known history of CVD. CT images were obtained at 100 kVp with a slice thickness of 3 mm. Agatston CAC scoring was performed retroactively. Lung-RADS scores were categorized as: Negative (1), Benign (2), Probably Benign (3), and Suspicious (4). CAC scoring was grouped as 0, 1–100, 101–399, and ≥400. Descriptive statistics and chi-square analyses were utilized. Results: A total of 526 LDCT screenings were included. Over 54 % of patients had coronary calcification on LDCT LCS. 161 patients (30.6 %) had a CAC score of ≥100 and 75 patients (14.3 %) had a CAC score ≥400. Of patients with a CAC score ≥100, 7.5 % received referrals for follow-up after the LDCT screen and 9.3 % had additional cardiac testing. Of those with a CAC score ≥100 not already on a statin (45.3 %) and not already on aspirin (63.3 %), few were started within 3 months of LDCT for prevention (8.2 % and 5.9 % respectively). Among patients with a Lung-RADS score of 4, 17 % had a CAC score >400, whereas only 12 % with a Lung-RADS score of 1 fell into the same CAC category. Higher Lung-RADS scores correlated with fewer patients with CAC of 0. A significant correlation was observed between higher Lung-RADS scores and elevated CAC scores (p = 0.02). Conclusion: In patients with no CVD history, coronary artery calcification was frequently identified on mobile LDCT lung screenings in rural communities. Patients with higher probabilities of malignant lung nodules may also be at increased risk for significant coronary artery disease. Calcium scoring from LDCT screenings allowed for simultaneous assessment of lung cancer and CVD risk. Unfortunately, few referrals or CVD prevention medications were initiated. Awareness of CAC score utility, follow-up for identified coronary calcifications, and consideration of primary prevention medications when indicated, would be beneficial in patients undergoing LDCT lung screenings, especially in rural areas with limited healthcare access.

Purpose: Lung cancer screening (LCS) by low-dose computed tomography (LDCT) demonstrated a 20–40% reduction in lung cancer mortality. National stakeholders and international scientific societies are increasingly endorsing LCS programs, but translating their benefits into practice is rather challenging. The "Model for Optimized Implementation of Early Lung Cancer Detection: Prospective Evaluation Of Preventive Lung HEalth" (PEOPLHE) is an Italian multicentric LCS program aiming at testing LCS feasibility and implementation within the national healthcare system. PEOPLHE is intended to assess (i) strategies to optimize LCS workflow, (ii) radiological quality assurance, and (iii) the need for dedicated resources, including smoking cessation facilities. Methods: PEOPLHE aims to recruit 1.500 high-risk individuals across three tertiary general hospitals in three different Italian regions that provide comprehensive services to large populations to explore geographic, demographic, and socioeconomic diversities. Screening by LDCT will target current or former (quitting < 10 years) smokers (> 15 cigarettes/day for > 25 years, or > 10 cigarettes/day for > 30 years) aged 50–75 years. Lung nodules will be volumetric measured and classified by a modified PEOPLHE Lung-RADS 1.1 system. Current smokers will be offered smoking cessation support. Conclusion: The PEOPLHE program will provide information on strategies for screening enrollment and smoking cessation interventions; administrative, organizational, and radiological needs for performing a state-of-the-art LCS; collateral and incidental findings (both pulmonary and extrapulmonary), contributing to the LCS implementation within national healthcare systems. [ABSTRACT FROM AUTHOR]

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I2 = 99% for defined adherence, I2 = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings.

Background: Lung cancer screening (LCS) with low‐dose computed tomography (LDCT) of the chest of eligible patients remains low. Accordingly, augmentation of appropriate LCS referrals by primary care providers (PCPs) was sought. Methods: The quality improvement (QI) project was performed between April 2021 and June 2022. It incorporated patient education, shared decision‐making (SDM) with PCPs, and tracking of initial LDCT completion. In each case, lag time (LT) to LCS and pack‐years (PYs) were calculated from initial LCS eligibility. The cohort's scores were compared to national scores. Patient zip codes were used to create a geographic map of our cohort for comparison with public health data. Results: An immediate and sustained increase in weekly LCS referrals from PCPs was recorded. Of 337 initial referrals, 95% were men, consisting of 66.2% Black, 28.4% White, and 5.4% other. Mean PY was less for minorities (45.3 vs. 37.3 years; p =.0002) but mean LT was greater for Whites (7.9 vs. 6.2 years; p =.03). Twenty‐five percent of veterans failed to report to their scheduled screening, and two declined referrals. Notably, most no‐show patients lived in transit deserts. Furthermore, Lung‐RADS scores 4B/4X were more than double the expected prevalence (p =.008). Conclusions: The PCPs in this study successfully augmented LCS referrals. A substantial proportion of these patients were no‐shows, and our data suggest complex racial and socioeconomic factors as contributing variables. In addition, a higher‐than‐expected number of initial Lung‐RADS scores 4B/4X were reported. A large, multisite QI project is warranted to address overcoming potential transportation barriers in high‐risk patient populations. In this article, a process is outlined of how a quality improvement project can be used to increase lung cancer screening rates. More importantly, data from this project can be used to further characterize an underserved population and understand the socioeconomic impacts of society on these populations. [ABSTRACT FROM AUTHOR]

The harm associated with imaging abnormalities related to lung cancer screening (LCS) is not well documented, especially outside the clinical trial and academic setting. What is the frequency of invasive procedures and complications associated with a community based LCS program, including procedures for false-positive and benign, but clinically important, incidental findings? We performed a single-center retrospective study of an LCS program at a nonuniversity teaching hospital from 2016 through 2019 to identify invasive procedures prompted by LCS results, including their indication and complications. Among 2,003 LCS participants, 58 patients (2.9%) received a diagnosis of lung cancer and 71 patients (3.5%) received a diagnosis of any malignancy. Invasive procedures were performed 160 times in 103 participants (5.1%), including 1.7% of those without malignancy. Eight invasive procedures (0.4% of participants), including four surgeries (12% of diagnostic lung resections), were performed for false-positive lung nodules. Only 1% of Lung Imaging Reporting and Data System category 4A nodules that proved benign were subject to an invasive procedure. Among those without malignancy, an invasive procedure was performed in eight participants for extrapulmonary false-positive findings (0.4%) and in 19 participants (0.9%) to evaluate incidental findings considered benign but clinically important. Procedures for the latter indication resulted in treatment, change in management, or diagnosis in 79% of individuals. Invasive procedures in those without malignancy resulted in three complications (0.15%). Seventy nonsurgical procedures (6% complication rate) and 48 thoracic surgeries (4% major complication rate) were performed in those with malignancy. The use of invasive procedures to resolve false-positive findings was uncommon in the clinical practice of a nonuniversity LCS program that adhered to a nodule management algorithm and used a multidisciplinary approach. Incidental findings considered benign but clinically important resulted in invasive procedure rates that were similar to those for false-positive findings and frequently had clinical value. [ABSTRACT FROM AUTHOR]

To review Lung CT Screening Reporting and Data System (Lung-RADS) scores from 2014 to 2021, before changes in eligibility criteria proposed by the US Preventative Services Taskforce. A registered systematic review and meta-analysis was conducted in MEDLINE, Embase, CINAHL, and Web of Science in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines; eligible studies examined low-dose CT (LDCT) lung cancer screening at institutions in the United States and reported Lung-RADS from 2014 to 2021. Patient and study characteristics, including age, gender, smoking status, pack-years, screening timeline, number of individual patients, number of unique studies, Lung-RADS scores, and positive predictive value (PPV) were extracted. Meta-analysis estimates were derived from generalized linear mixed modeling. The meta-analysis included 24 studies yielding 36,211 LDCT examinations for 32,817 patient encounters. The meta-analysis Lung-RADS 1-2 scores were lower than anticipated by ACR guidelines, at 84.4 (95% confidence interval [CI] 83.3-85.6) versus 90% respectively (P <.001). Lung-RADS 3 and 4 scores were both higher than anticipated by the ACR, at 8.7% (95% CI 7.6-10.1) and 6.5% (95% CI 5.707.4), compared with 5% and 4%, respectively (P <.001). The ACR's minimum estimate of PPV for Lung-RADS 3 to 4 is 21% or higher; we observed a rate of 13.1% (95% CI 10.1-16.8). However, our estimated PPV rate for Lung-RADS 4 was 28.6% (95% CI 21.6-36.8). Lung-RADS scores and PPV rates in the literature are not aligned with the ACR's own estimates, suggesting that perhaps Lung-RADS categorization needs to be reexamined for better concordance with real-world screening populations. In addition to serving as a benchmark before screening guideline broadening, this study provides guidance for future reporting of lung cancer screening and Lung-RADS data. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract Background Lung cancer is one of the most common causes of cancer-related deaths in developed and developing countries. Therefore, early detection of lung cancer has a significant impact on lung cancer surveillance. Interpretation of lung CT scans for cancer screening is considered an intensive task for most radiologists, and long experience is required for accurate diagnosis through visual processing. This cross-sectional study introduces automated CAD software (Careline Soft’s AVIEW Metric software). This software can detect and classify lung nodules in CT scans. The performance of a deep learning (DL) model embedded in that software will be compared with that of the radiologists. Also, the feasibility of lung cancer screening protocol is evaluated in Suez Canal University Hospital, Ismailia, Egypt, by implementing Lung Imaging Reporting and Data System (Lung-RADS). Results As for the detection of the pulmonary nodules, the initial review by the CAD system (without validation by the researcher radiologist) has high sensitivity (93.0%) and specificity (95.5%) with overall accuracy of 93.6%. After review of the automatically detected nodules by the researcher radiologist was done, the final CAD has higher sensitivity (98.2%) and comparable specificity (95.5%) for the detection of pulmonary nodules with overall accuracy of 97.4%. As for lung cancer screening (categorization of Lung-RADS 3 and 4 nodules), unrevised initial computer-aided detection has 97.9% specificity and 96.9% for lung cancer screening with overall accuracy of 97.4%. After second look and review of the CAD result by the researcher radiologist, there is total agreement in total number of nodules and categorization of Lung-RADS 3 and 4. This gives an excellent agreement of 88.6% (κ = 0.951) between the CAD system and reference radiologist in the overall categorization of all lung nodules according to Lung-RADS classification. Conclusions The application of CAD system demonstrated increased sensitivity and specificity for the detection of lung nodules and total agreement in the detection of suspicious and probably benign nodules (lung cancer screening) and excellent level of agreement in the overall lung nodule categorization (Lung-RADS).

Background: In addition to the diameters of pulmonary nodules, the number and morphology of blood vessels in pure ground-glass nodules (pGGNs) were closely related to the occurrence of lung cancer. Moreover, the benign and malignant signs of nodules were also valuable for the identification of nodules. Based on these two points, we tried to revise Lung-RADS 2022 and proposed our Modified Lung-RADS. The aim of the study was to verify the diagnostic performance of Modified Lung-RADS for pulmonary solid nodules (SNs) and pure ground-glass nodules (pGGNs) in patients with previous malignancies. Methods: The chest CT and clinical data of patients with prior cancer who underwent pulmonary nodulectomies from 1 January 2018 to 30 November 2021 were enrolled according to inclusion and exclusion criteria. A total of 240 patients with 293 pulmonary nodules were included in this study. In contrast with the original version, the risk classification of pGGNs based on the GGN–vascular relationships (GVRs), and the SNs without burrs and with benign signs, could be downgraded to category 2. The sensitivity, specificity, and agreement rate of the original Lung-RADS 2022 and Modified Lung-RADS for pGGNs and SNs were calculated and compared. Results: Compared with the original version, the sensitivity and agreement rate of the Modified version for pGGNs increased from 0 and 23.33% to 97.10% and 92.22%, respectively, while the specificity decreased from 100% to 76.19%. As regards SNs, the specificity and agreement rate of the Modified version increased from 44.44% to 75.00% (p < 0.05) and 88.67% to 94.09% (p = 0.052), respectively, while the sensitivity was unchanged (98.20%). Conclusions: In general, the diagnostic efficiency of Modified Lung-RADS was superior to that of the original version, and Modified Lung-RADS could be a preliminary attempt to improve Lung-RADS 2022. [ABSTRACT FROM AUTHOR]

Low-dose computed tomography-based lung cancer screening represents a complex clinical undertaking that could require multiple referrals, appointments, and time-intensive procedures. These steps may pose difficulties and raise concerns among patients, particularly minority, under-, and uninsured populations. The authors implemented patient navigation to identify and address these challenges. They conducted a pragmatic randomized controlled trial of telephone-based navigation for lung cancer screening in an integrated, urban safety-net health care system. Following standardized protocols, bilingual (Spanish and English) navigators educated, motivated, and empowered patients to traverse the health system. Navigators made systematic contact with patients, recording standardized call characteristics in a study-specific database. Call type, duration, and content were recorded. Univariable and multivariable multinomial logistic regression was performed to investigate associations between call characteristics and reported barriers. Among 225 patients (mean age 63 years, 46% female, 70% racial/ethnic minority) assigned navigation, a total of 559 barriers to screening were identified during 806 telephone calls. The most common barrier categories were personal (46%), provider (30%), and practical (17%). System (6%) and psychosocial (1%) barriers were described by English-speaking patients, but not by Spanish-speaking patients. Over the course of the lung cancer screening process, provider-related barriers decreased 80% (P = 0.008). The authors conclude that patients undergoing lung cancer screening frequently report personal and health care provider-related barriers to successful participation. Barrier types may differ among patient populations and over the course of the screening process. Further understanding of these concerns may increase screening uptake and adherence. Clinical Trial Registration number: (NCT02758054). [ABSTRACT FROM AUTHOR]

Background: Lung cancer is one of the most common causes of cancer-related deaths in developed and developing countries. Therefore, early detection of lung cancer has a significant impact on lung cancer surveillance. Interpretation of lung CT scans for cancer screening is considered an intensive task for most radiologists, and long experience is required for accurate diagnosis through visual processing. This cross-sectional study introduces automated CAD software (Careline Soft's AVIEW Metric software). This software can detect and classify lung nodules in CT scans. The performance of a deep learning (DL) model embedded in that software will be compared with that of the radiologists. Also, the feasibility of lung cancer screening protocol is evaluated in Suez Canal University Hospital, Ismailia, Egypt, by implementing Lung Imaging Reporting and Data System (Lung-RADS). Results: As for the detection of the pulmonary nodules, the initial review by the CAD system (without validation by the researcher radiologist) has high sensitivity (93.0%) and specificity (95.5%) with overall accuracy of 93.6%. After review of the automatically detected nodules by the researcher radiologist was done, the final CAD has higher sensitivity (98.2%) and comparable specificity (95.5%) for the detection of pulmonary nodules with overall accuracy of 97.4%. As for lung cancer screening (categorization of Lung-RADS 3 and 4 nodules), unrevised initial computer-aided detection has 97.9% specificity and 96.9% for lung cancer screening with overall accuracy of 97.4%. After second look and review of the CAD result by the researcher radiologist, there is total agreement in total number of nodules and categorization of Lung-RADS 3 and 4. This gives an excellent agreement of 88.6% (κ = 0.951) between the CAD system and reference radiologist in the overall categorization of all lung nodules according to Lung-RADS classification. Conclusions: The application of CAD system demonstrated increased sensitivity and specificity for the detection of lung nodules and total agreement in the detection of suspicious and probably benign nodules (lung cancer screening) and excellent level of agreement in the overall lung nodule categorization (Lung-RADS). [ABSTRACT FROM AUTHOR]

This article reviews the evidence supporting low-dose CT to screen for lung cancer, and the risks, costs, and challenges of implementing broad-based screening for eligible patients. Increased familiarity with lung cancer screening guidelines by primary care and specialty clinicians presents an opportunity to improve lung cancer screening rates and to save lives from the most common cause of cancer death in the United States. [ABSTRACT FROM AUTHOR]

Abstract Background Lung assessment is highly recommended in the management of oncology patients as it is the commonest affected site in metastatic dissemination. The low-dose CT with nodule reporting system based on Lung Reporting and Data System (lung-RADS) is a promising non-invasive tool for the characterization of incidentally detected pulmonary nodules. The authors aimed to assess the accuracy of the “lung-RADS” classification system as a non-invasive tool for the characterization of any newly developed pulmonary nodules among oncology patients. Ethics committee approval and informed written consent were obtained from the studied patients. A non-contrast LDCT study was performed on all patients with a nodule reporting system based on the lung-RADS classification system applied for evaluation of each detected pulmonary nodule. Diagnoses were established using the help of either histopathology or follow-up clinical results as a gold standard. Results In this prospective study, we enrolled 187 known malignancy patients with 200 suspicious newly developed pulmonary nodules. Their mean patient age was 48.4 ± 9.7 years. The studied 200 pulmonary nodular lesions were categorized using a nodule reporting system based on the lung-RADS into 6 sub-groups with 122 lesions found to be malignant and 78 lesions were of benign etiology, which showed a high sensitivity of 92.08%, specificity of 78.79%, and accuracy of 85.50% with 81.58% positive predictive value and 90.70% negative predictive value in the diagnosis of pulmonary nodules in cancer patients. Conclusion Low-density CT with a nodule reporting system based on the lung-RADS classification system was found to be an accurate non-invasive tool to characterize and to risk stratify pulmonary nodules in oncology patients.

Background: In addition to the diameters of pulmonary nodules, the number and morphology of blood vessels in pure ground-glass nodules (pGGNs) were closely related to the occurrence of lung cancer. Moreover, the benign and malignant signs of nodules were also valuable for the identification of nodules. Based on these two points, we tried to revise Lung-RADS 2022 and proposed our Modified Lung-RADS. The aim of the study was to verify the diagnostic performance of Modified Lung-RADS for pulmonary solid nodules (SNs) and pure ground-glass nodules (pGGNs) in patients with previous malignancies. Methods: The chest CT and clinical data of patients with prior cancer who underwent pulmonary nodulectomies from 1 January 2018 to 30 November 2021 were enrolled according to inclusion and exclusion criteria. A total of 240 patients with 293 pulmonary nodules were included in this study. In contrast with the original version, the risk classification of pGGNs based on the GGN–vascular relationships (GVRs), and the SNs without burrs and with benign signs, could be downgraded to category 2. The sensitivity, specificity, and agreement rate of the original Lung-RADS 2022 and Modified Lung-RADS for pGGNs and SNs were calculated and compared. Results: Compared with the original version, the sensitivity and agreement rate of the Modified version for pGGNs increased from 0 and 23.33% to 97.10% and 92.22%, respectively, while the specificity decreased from 100% to 76.19%. As regards SNs, the specificity and agreement rate of the Modified version increased from 44.44% to 75.00% (p < 0.05) and 88.67% to 94.09% (p = 0.052), respectively, while the sensitivity was unchanged (98.20%). Conclusions: In general, the diagnostic efficiency of Modified Lung-RADS was superior to that of the original version, and Modified Lung-RADS could be a preliminary attempt to improve Lung-RADS 2022.

Lung cancer screening is slowly but steadily entering the realm of preventive health maintenance. Standardization of reporting of positive findings identified on screening low-dose CT (LDCT) scans, specifically lung nodules, is a key element of high-quality lung cancer screening. The American College of Radiology developed the Lung CT Screening Reporting and Data System (Lung-RADS) system for this purpose. In addition to detailed categorization of lung nodules, Lung-RADS identifies category S for other incidental findings identified on screening LDCT scans. In contrast to the highly structured reporting for nodules, category S findings are reported at the discretion of individual readers, with the potential for high variability of reporting. Incidental findings on lung cancer screening studies are common, may trigger unwarranted evaluation with potential harm and cost, and may precipitate patient distress. In response to these concerns, our multidisciplinary lung cancer screening program developed a structured system for standardized reporting of category S findings based on recommendations of the American College of Radiology and relevant specialty societies. [ABSTRACT FROM AUTHOR]

Rationale: Lung-RADS classification was developed to standardize reporting and management of lung cancer screening using low-dose computed tomographic (LDCT) imaging. Although variation in Lung-RADS distribution between healthcare systems has been reported, it is unclear if this is explained by patient characteristics, radiologist experience with lung cancer screening, or other factors. Objectives: Our objective was to determine if patient or radiologist factors are associated with Lung-RADS score. Methods: In the Population-based Research to Optimize the Screening Process (PROSPR) Lung consortium, we conducted a study of patients who received their first screening LDCT imaging at one of the five healthcare systems in the PROSPR Lung Research Center from May 1, 2014, through December 31, 2017. Data on LDCT scans, patient factors, and radiologist characteristics were obtained via electronic health records. LDCT scan findings were categorized using Lung-RADS (negative [1], benign [2], probably benign [3], or suspicious [4]). We used generalized estimating equations with a multinomial distribution to compare the odds of Lung-RADS 3, and separately Lung-RADS 4, versus Lung-RADS 1 or 2 and estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between Lung-RADS assignment and patient and radiologist characteristics. Results: Analyses included 8,556 patients; 24% were assigned Lung-RADS 1, 60% Lung-RADS 2, 10% Lung-RADS 3, and 5% Lung-RADS 4. Age was positively associated with Lung-RADS 3 (OR, 1.02; 95% CI, 1.01-1.03) and 4 (OR, 1.03; 95% CI, 1.01-1.05); chronic obstructive pulmonary disease (COPD) was positively associated with Lung-RADS 4 (OR, 1.78; 95% CI, 1.45-2.20); obesity was inversely associated with Lung-RADS 3 (OR, 0.70; 95% CI, 0.58-0.84) and 4 (OR, 0.58; 95% CI, 0.45-0.75). There was no association between sex, race, ethnicity, education, or smoking status and Lung-RADS assignment. Radiologist volume of interpreting screening LDCT scans, years in practice, and thoracic specialty were also not associated with Lung-RADS assignment. Conclusions: Healthcare systems that are comprised of patients with an older age distribution or higher levels of COPD will have a greater proportion of screening LDCT scans with Lung-RADS 3 or 4 findings and should plan for additional resources to support appropriate and timely management of noted positive findings. [ABSTRACT FROM AUTHOR]

Purpose: To identify factors influencing the likelihood of a false positive lung cancer screening (LCS) computed tomography (CT), which may lead to increased costs and patient anxiety.Materials and Methods: In this retrospective study, we examined all LCS CTs performed across our healthcare network from 2014 to 2018, recording Lung-RADS category and diagnosis of lung cancer. A false positive was defined by Lung-RADS 3-4X and no diagnosis of lung cancer within 1 year. Patient demographics and smoking history, presence of emphysema, diagnosis of chronic obstructive pulmonary disease, radiologist years of experience and annual volume, income level by patient zip code, and screening institution were evaluated in a multivariate logistic regression model for false positive exams.Results: A total of 5835 LCS CTs were included from 3735 patients. Lung cancer was diagnosed in 142 cases (2%). Of the LCS CTs, 905 (16%) were positive by Lung-RADS, and 766 (13%) represented false positives. Logistic regression analysis showed that screening institution (odds ratios [OR] 0.91 - 2.43), baseline scan (OR 1.43), radiologist experience (OR 0.59), patient age (OR 2.08), diagnosis of chronic obstructive pulmonary disease (OR 1.34), presence of emphysema (OR 1.32), and income level (OR 0.43) were significant predictors of false positives.Conclusion: A number of patient-specific and site/radiologist-specific factors influence the false positive rate in CT LCS. In particular, radiologists with less experience had a higher false positive rate. Screening programs may wish to develop quality assurance programs to compare the false positive rates of their radiologists to national benchmarks. [ABSTRACT FROM AUTHOR]

The National Lung Cancer Screening Trial (NLST) demonstrated the use of low dose helical computed tomography (LDCT) scans for lung cancer screening. However, the NLST was implemented in urban hospitals and prior to the Lung CT Screening Reporting and Data System (Lung-RADS). In this retrospective cohort study, 774 eligible patients received LDCT screening using Lung-RADS criteria. Eighty-four patients (10.9%) had subsequent testing performed compared to 24.2% in the NLST study. Of those with subsequent testing, 21.4% were diagnosed with lung cancer compared to only 4.6% in the NLST study. Lung-RADS significantly reduced unnecessary testing while identifying higher rates of lung cancer compared to the NLST.

Objective: Mobile low-dose computed tomography (LDCT) lung screenings are part of an outreach program in rural Appalachia to detect early lung cancer. Coronary artery calcium (CAC) scoring on LDCT can identify calcium deposits in coronary arteries and can prompt consideration of risk modification for prevention of cardiovascular disease (CVD) events. It is not known if Lung CT Screening Reporting & Data System (Lung-RADS) scoring correlates with CAC scores. There is no clear guidance for patients undergoing LDCT screenings to receive follow-up regarding CAC or prevention of associated CVD risk., Methods: This was a retrospective review of mobile LDCT LCS in adults with no known history of CVD. CT images were obtained at 100 kVp with a slice thickness of 3 mm. Agatston CAC scoring was performed retroactively. Lung-RADS scores were categorized as: Negative (1), Benign (2), Probably Benign (3), and Suspicious (4). CAC scoring was grouped as 0, 1-100, 101-399, and ≥400. Descriptive statistics and chi-square analyses were utilized., Results: A total of 526 LDCT screenings were included. Over 54 % of patients had coronary calcification on LDCT LCS. 161 patients (30.6 %) had a CAC score of ≥100 and 75 patients (14.3 %) had a CAC score ≥400. Of patients with a CAC score ≥100, 7.5 % received referrals for follow-up after the LDCT screen and 9.3 % had additional cardiac testing. Of those with a CAC score ≥100 not already on a statin (45.3 %) and not already on aspirin (63.3 %), few were started within 3 months of LDCT for prevention (8.2 % and 5.9 % respectively). Among patients with a Lung-RADS score of 4, 17 % had a CAC score >400, whereas only 12 % with a Lung-RADS score of 1 fell into the same CAC category. Higher Lung-RADS scores correlated with fewer patients with CAC of 0. A significant correlation was observed between higher Lung-RADS scores and elevated CAC scores ( p = 0.02)., Conclusion: In patients with no CVD history, coronary artery calcification was frequently identified on mobile LDCT lung screenings in rural communities. Patients with higher probabilities of malignant lung nodules may also be at increased risk for significant coronary artery disease. Calcium scoring from LDCT screenings allowed for simultaneous assessment of lung cancer and CVD risk. Unfortunately, few referrals or CVD prevention medications were initiated. Awareness of CAC score utility, follow-up for identified coronary calcifications, and consideration of primary prevention medications when indicated, would be beneficial in patients undergoing LDCT lung screenings, especially in rural areas with limited healthcare access., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

Background: Lung-RADS classification and CT signs can both help in the differential diagnosis of SPNs. The purpose of this study was to investigate the diagnostic value of these two methods and the combination of the two methods for solitary pulmonary nodules (SPNs). Methods: A total of 296 cases of SPNs were retrospectively analyzed. All the SPNs were classified according to the Lung-RADS grading version 1.1. The scores of each lesion were calculated according to their CT signs. Imaging features, such as the size and margin of the lesions, pleural traction, spiculation, lobulation, bronchial cutoff, air bronchogram, vacuoles, tumor vasculature, and cavity signs, were analyzed. The imaging results were compared with the pathology examination findings. Receiver operating characteristic (ROC) curves were applied to compare the values of the different methods in differentially diagnosing benign and malignant SPNs. Results: The sensitivity, specificity, and accuracy of Lung-RADS grading for diagnosing SPNs were 34.0%, 94.4%, and 47.6%, respectively. The area under the ROC curve (AUC) was 0.600 (p < 0.001). The sensitivity, specificity, and accuracy of the CT sign scores were 56.3%, 70.0%, and 60.5%, respectively, and the AUC was 0.657 (p < 0.001). The sensitivity, specificity, and accuracy of the combination of the two methods for diagnosing SPNs were 93.2%, 61.1%, and 83.5%, and the AUC was 0.777 (p < 0.001). Conclusion: The combination of Lung-RADS classification and CT signs significantly improved the differential diagnosis of SPNs.

Purpose: To test the performance of the American College of Chest Physicians (ACCP) and British Thoracic Society (BTS) algorithms to stratify high-risk nodules identified at lung cancer screening.Method and Materials: Patients with Lung-RADS category 4 nodules identified on lung cancer screening computed tomography (CT) between March 2014 and August 2018 were identified, and a subset of 150 were randomly selected. Nodule characteristics and, if available, fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET)-CT scan were recorded. Radiologists blinded to final diagnosis and downstream testing performed five-point visual assessment score for probability of nodule malignancy; their accuracies are averaged below. Probabilities of malignancy according to Brock and Herder models were calculated. ACCP and BTS algorithms were applied to the nodules.Results: Final diagnosis of malignancy was made in 65/150 (43%) of patients. The sensitivity, specificity and accuracy for nodule malignancy were: radiologist visual score (92%, 85%, 88%); BTS (76%, 91%, 85%); ACCP (63%, 89%, 78%); and Brock calculator (77%, 71%, 73%). The sensitivity, specificity, and accuracy for nodule malignancy in patients with FDG PET-CT scan (n = 78) were: FDG uptake (91%, 64%, 83%); Herder probability (91%, 68%, 83%); radiologist visual score (93%, 69%, 86%); BTS (84%, 64%, 78%); Brock probability (82%, 50%, 72%); and ACCP (68%, 59%, 65%).Conclusion: Thoracic radiologist visual analysis yielded the greatest accuracy for nodule triage in the entire cohort. BTS performed better than ACCP guidelines and both performed better than the Brock model alone. [ABSTRACT FROM AUTHOR]

Qingcheng Meng,1,* Pengfei Ren,2,* Pengrui Gao,1 Xinmin Dou,1 Xuejun Chen,1 Lanwei Guo,3 Yongping Song4 1Department of Radiology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 2Department of Molecular Pathology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 3Department of Cancer Prevention Office, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China; 4Department of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yongping SongDepartment of Hematology, The Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou 450008, People’s Republic of ChinaTel/Fax +86 371 65587016Email songyongping001@126.comPurpose: To evaluate the effectiveness of using a modified lung imaging reporting and data system (Lung-RADS) for risk stratification of pure ground-glass nodules (pGGNs) in low-dose computed tomography (LDCT) for lung cancer (LC) screenings in China.Patients and Methods: Eight subjects with nine pGGNs originating from a Cancer Screening Program were enrolled as training set and 32 asymptomatic subjects with 35 pGGNs were selected as validation set from November 2013 to October 2018. The complementary Lung-RADS categories were set based on the GGN-vessel relationship (GVR). The correlations between GGN-vessel relationships and pathology were evaluated, and the diagnostic value of complementary Lung-RADS version 1.1 in discriminating malignant pGGNs were analyzed.Results: The inter-reader agreements for Lung-RADS 1.1 (intraclass correlation coefficient (ICC= 0.999) and complementary Lung-RADS 1.1 (ICC= 0.971) displayed good reliability. The combined incidence of invasive adenocarcinoma in type III and IV was more than that of benign and preinvasive diseases (30% vs 75%, P=0.013). Type II GVR between two benign (66.7%), seven preinvasive (53.8%), and six invasive (21.4%) GGN cases was statistically significant (χ2=5.415, P=0.019). GGN pathological groups and GVR had a significant correlation (r=0.584, P=0.00). Compared to Lung-RADS 1.1, complementary Lung-RADS 1.1 had better performance in the training set, with its sensitivity increased from 33.3% to 88.9%, accuracy increased from 44.4% to 88.9%, false-negative proportion (FNP) decreased from 66.7% to 11.1%, and the sensitivity to predict malignant nodules increased from 13.8% to 93.1%, accuracy increased from 28.6% to 80.0%, and FNP decreased from 86.2% to 6.9% in validation set. The detection rate of preinvasive disease and adenocarcinoma was increased from 12.5% to 90.6% and that of missed diagnosis decreased from 87.5% to 9.4% in the validation set, P=0.004.Conclusion: Complementary Lung-RADS 1.1 is superior to Lung-RADS 1.1 and would be beneficial for LC screening of LDCT in China.Keywords: low-dose computed tomography, lung neoplasms, lung-RADS, mass screening, ground-glass nodules

Background: Lung assessment is highly recommended in the management of oncology patients as it is the commonest affected site in metastatic dissemination. The low-dose CT with nodule reporting system based on Lung Reporting and Data System (lung-RADS) is a promising non-invasive tool for the characterization of incidentally detected pulmonary nodules. The authors aimed to assess the accuracy of the "lung-RADS" classification system as a non-invasive tool for the characterization of any newly developed pulmonary nodules among oncology patients. Ethics committee approval and informed written consent were obtained from the studied patients. A non-contrast LDCT study was performed on all patients with a nodule reporting system based on the lung-RADS classification system applied for evaluation of each detected pulmonary nodule. Diagnoses were established using the help of either histopathology or follow-up clinical results as a gold standard. Results: In this prospective study, we enrolled 187 known malignancy patients with 200 suspicious newly developed pulmonary nodules. Their mean patient age was 48.4 ± 9.7 years. The studied 200 pulmonary nodular lesions were categorized using a nodule reporting system based on the lung-RADS into 6 sub-groups with 122 lesions found to be malignant and 78 lesions were of benign etiology, which showed a high sensitivity of 92.08%, specificity of 78.79%, and accuracy of 85.50% with 81.58% positive predictive value and 90.70% negative predictive value in the diagnosis of pulmonary nodules in cancer patients. Conclusion: Low-density CT with a nodule reporting system based on the lung-RADS classification system was found to be an accurate non-invasive tool to characterize and to risk stratify pulmonary nodules in oncology patients. [ABSTRACT FROM AUTHOR]

Rural populations face many health disadvantages including higher rates of tobacco use and lung cancer than more populated areas. Given this, we specifically sought to understand the current screening landscape in a cohort of patients with resected lung cancer to help direct improvements in the screening process. We retrospectively reviewed our prospective database at a rural, quaternary, academic institution from January 2015 to June 2018. All patients who underwent resection for primary lung cancer were studied to assess the frequency of preoperative low-dose chest computed tomography per accepted guidelines. The intent was to evaluate participant demographics, clinical stage, frequency, and distribution of Lung-RADS reporting. About 446 patients underwent primary resection, of which 252 were deemed screening-eligible. About 57 (22.6%) underwent low-dose chest computed tomography screening and 195 (77.4%) did not. No significant demographic differences were identified between groups. However, 82.5% (47/57) of the screened patients presented with clinical stage IA disease, compared with 67.1% (131/195) of the nonscreened patients (P = 0.03). Among those screened, 36.8% (21/57) did not have a Lung-RADS score documented despite 52.3% (11/21) of those coming from accredited programs. Our screening completion rate was only 22.6% of eligible patients and 36.8% of those patients did not have a documented Lung-RADS score. These findings, in combination with the increased rate of diagnosis of stage IA disease, provide compelling reasons to further investigate factors designed to improve access and screening practices at rural institutions. [ABSTRACT FROM AUTHOR]

Objectives: 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.Materials and Methods: 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.Results: 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.Conclusion: 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. [ABSTRACT FROM AUTHOR]

Background: Large language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored., Objective: This study aims to evaluate 3 large language model chatbots-Claude-2, GPT-3.5, and GPT-4-on assigning RADS categories to radiology reports and assess the impact of different prompting strategies., Methods: This cross-sectional study compared 3 chatbots using 30 radiology reports (10 per RADS criteria), using a 3-level prompting strategy: zero-shot, few-shot, and guideline PDF-informed prompts. The cases were grounded in Liver Imaging Reporting & Data System (LI-RADS) version 2018, Lung CT (computed tomography) Screening Reporting & Data System (Lung-RADS) version 2022, and Ovarian-Adnexal Reporting & Data System (O-RADS) magnetic resonance imaging, meticulously prepared by board-certified radiologists. Each report underwent 6 assessments. Two blinded reviewers assessed the chatbots' response at patient-level RADS categorization and overall ratings. The agreement across repetitions was assessed using Fleiss κ., Results: Claude-2 achieved the highest accuracy in overall ratings with few-shot prompts and guideline PDFs (prompt-2), attaining 57% (17/30) average accuracy over 6 runs and 50% (15/30) accuracy with k-pass voting. Without prompt engineering, all chatbots performed poorly. The introduction of a structured exemplar prompt (prompt-1) increased the accuracy of overall ratings for all chatbots. Providing prompt-2 further improved Claude-2's performance, an enhancement not replicated by GPT-4. The interrun agreement was substantial for Claude-2 (k=0.66 for overall rating and k=0.69 for RADS categorization), fair for GPT-4 (k=0.39 for both), and fair for GPT-3.5 (k=0.21 for overall rating and k=0.39 for RADS categorization). All chatbots showed significantly higher accuracy with LI-RADS version 2018 than with Lung-RADS version 2022 and O-RADS (P<.05); with prompt-2, Claude-2 achieved the highest overall rating accuracy of 75% (45/60) in LI-RADS version 2018., Conclusions: When equipped with structured prompts and guideline PDFs, Claude-2 demonstrated potential in assigning RADS categories to radiology cases according to established criteria such as LI-RADS version 2018. However, the current generation of chatbots lags in accurately categorizing cases based on more recent RADS criteria., (©Qingxia Wu, Qingxia Wu, Huali Li, Yan Wang, Yan Bai, Yaping Wu, Xuan Yu, Xiaodong Li, Pei Dong, Jon Xue, Dinggang Shen, Meiyun Wang. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 17.07.2024.)

Lung cancer screening via low-dose computed tomography (CT) reduces mortality from lung cancer, and eligibility criteria have recently been expanded to include patients aged 50 to 80 with at least 20 pack-years of smoking history. Lung cancer screening CTs should be interepreted with use of Lung Imaging Reporting and Data System (Lung-RADS), a reporting guideline system that accounts for nodule size, density, and growth. The revised version of Lung-RADS includes several important changes, such as expansion of the definition of juxtapleural nodules, discussion of atypical pulmonary cysts, and stepped management for suspicious nodules. By using Lung-RADS, radiologists and clinicians can adopt a uniform approach to nodules detected during CT lung cancer screening and reduce false positives., Competing Interests: Disclosure M M. Hammer received funding from NIH, United StatesR01CA260889. No additional disclosures., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objectives: The National Lung Screening Trial (NLST) demonstrated a 20% reduction in mortality with low-dose computed tomography (CT) for lung cancer screening (LCS). The NLST found the greatest benefit to LCS for patients who underwent annual screening for a full 3-year follow-up period. The adherence to serial imaging in the NLST was 95%.Methods: We conducted a prospective study of 268 patients who presented for LCS and who were not enrolled in a research study to determine the adherence to recommended follow-up imaging and biopsy at a single center. We evaluated the correlations among sociodemographic characteristics, Lung Imaging and Reporting Data System, and adherence.Results: Only 48% of the patient population received recommended follow-up (either imaging or biopsy) after their referent LCS. Patients with abnormal LCS (Lung Imaging and Reporting Data System 3 or 4) were more likely to adhere to the recommended follow-up (additional imaging or biopsy) compared with those with negative screens. Sex, ethnicity, smoking status, and household income were not correlated with adherence to screening and biopsy.Conclusions: The benefits from LCS observed in the NLST may be undermined by low adherence to follow-up screening. Studies targeting LCS patients to bolster adherence to follow-up are needed. [ABSTRACT FROM AUTHOR]

The National Lung Cancer Screening Trial (NLST) demonstrated the use of low dose helical computed tomography (LDCT) scans for lung cancer screening. However, the NLST was implemented in urban hospitals and prior to the Lung CT Screening Reporting and Data System (Lung-RADS). In this retrospective cohort study, 774 eligible patients received LDCT screening using Lung-RADS criteria. Eighty-four patients (10.9%) had subsequent testing performed compared to 24.2% in the NLST study. Of those with subsequent testing, 21.4% were diagnosed with lung cancer compared to only 4.6% in the NLST study. Lung-RADS significantly reduced unnecessary testing while identifying higher rates of lung cancer compared to the NLST. [ABSTRACT FROM AUTHOR]

Purpose To compare the Lung Imaging Reporting and Data System (Lung-RADS) version 1.1 with version 2022 classification of airway nodules detected at lung cancer screening CT examinations. Materials and Methods This retrospective study included all patients who underwent a lung cancer screening CT examination in the authors' health care network between 2015 and 2021 with a reported airway or endobronchial nodule. A fellowship-trained cardiothoracic radiologist reviewed these CT images and characterized the airway nodules by size, location, multiplicity, morphology, dependent portions of airway, internal air, fluid attenuation, distal changes, outcome at follow-up, and final pathologic diagnosis, if malignant. Sensitivity and specificity of Lung-RADS version 1.1 in detecting malignant nodules were compared with those of Lung-RADS version 2022 using the McNemar test. Results A total of 174 patients were included. Of these, 163 (94%) had airway nodules that were deemed benign, while 11 (6%) had malignant nodules. Airway nodules in the trachea and mainstem bronchi were all benign, while lobar and segmental airway nodules had the highest risk for lung cancer (17.2% and 11.1%, respectively). Of the 12 subsegmental airway nodules that were obstructive, three (25%) were malignant and nine (75%) were benign. Nodules with nonobstructive morphologies, dependent portions of airway, internal air, or fluid attenuation were all benign. Only 10 of the 92 (10.9%) patients with positive Lung-RADS by clinical report had cancer. Lung-RADS version 2022 resulted in higher specificity than version 1.1 (82% vs 50%, P < .001), without sacrificing sensitivity (91% for both). Conclusion Compared with the previous version, Lung-RADS version 2022 reduced the number of false-positive screening CT examinations while still identifying malignant airway nodules. Keywords: CT, Lung, Primary Neoplasms, Pulmonary, Lung Cancer Screening, Lung-RADS, Nodule Risk, Airway Nodule, Endobronchial Nodule © RSNA, 2024.

Background: Concern over high false-positive rates and the potential for unintended harm to patients is a critical component of the lack of widespread adoption of lung cancer screening. Methods: An institutional database was used to identify patients who underwent lung cancer screening between 2/2015 and 2/2018 at Rush University Medical Center and Rush Oak Park Hospital. Reads were executed by dedicated thoracic radiologists and communicated using the Lung Imaging Reporting and Data System (Lung-RADS V.1). Results: Six hundred and four patients were screened over the study period. We identified 21 primary lung cancers and 8 incidental cancers. We identified a false-positive rate of 17.5%. Only 9 patients underwent further investigative workup for benign disease (5.3%); however, only 4 (2.9%) of those patients were found to have inflammatory or infectious lesions, which are common mimickers of lung cancer. Excluding Lung-RADS category 3 for the purpose of quantifying risk of unintended harm from unnecessary procedures, we found a 6.9% false-positive rate, while diagnosing 25% of all Lung-RADS category 4 patients with primary lung cancer. Conclusion: False-positive rates in lung cancer screening programs continue to decline with improved radiologic expertise. Additionally, false-positive reporting overestimates the risk of unintended harm from further investigative procedures as only a percentage of positive findings are generally considered for tissue diagnosis (i.e., Lung-RADS category 4). [ABSTRACT FROM AUTHOR]

Purpose: The Lung CT Screening Reporting and Data SystemTM (Lung-RADSTM) was created to standardize lung cancer screening CT reporting and recommendations but has not been well validated prospectively in clinical practice. The aim of this study was to determine the effectiveness of lung cancer screening using Lung-RADS in a diverse, underserved, academic clinical screening program, focusing on whether Lung-RADS would successfully reduce the 23.3% false-positive rate found in the National Lung Screening Trial.Methods: Institutional review board approval was obtained to study the clinical lung cancer screening cohort. Low-dose CT results were prospectively assigned a Lung-RADS or equivalent score. The proportion of examinations in each Lung-RADS category and the corresponding lung cancer rate, subsequent imaging, interventions, mortality, and compliance were tracked. The National Death Index was queried for follow-up losses.Results: The cohort comprised 1,181 patients with 2,270 person-years of follow-up from December 2012 to December 2016. The mean age was 64 ± 16.2 years, with 51% women, 63% nonwhite, 71% current smokers, 69% overweight and obese, and multiple comorbidities. The Lung-RADS false-positive rate was 10.4% (95% confidence interval, 8.8%-12.3%). Baseline CT results were negative in 87% (n = 1,031): for Lung-RADS 1, the lung cancer rate was 0.2%, and for Lung-RADS 2, the cancer rate was 0.5%. Positive baseline examinations were Lung-RADS 3 in 10% (n = 119), 4a in 1.2% (n = 14), and 4b in 1.5% (n = 18). Corresponding cancer rates were 3.4%, 43%, and 83%, respectively. Lung cancer prevalence was 2.1%. Mortality was 40% in patients with lung cancer versus 2.5% in the remaining cohort (P < .001). Fifty-four percent of patients were overdue for first annual examinations. Eighty-four percent of patients (n = 989) had follow-up verified via electronic records or personal contact, and the remainder had vital status ascertained via the National Death Index.Conclusions: Lung cancer screening using Lung-RADS was effective in reducing the false-positive rate compared with the National Lung Screening Trial in a diverse and underserved urban population. [ABSTRACT FROM AUTHOR]

• Refining of estimated malignancy rates across Lung-RADS 4 categories is necessary. • The probability of lung cancer increases from category 4A to 4X. • CT imaging features may help differentiate benign from malignant nodules. • Imaging features can help formulate risk prediction models. To assess the prevalence of lung cancer in Lung-RADS category 4 patients, and to elucidate if clinical or imaging features help differentiate benign lesions from lung cancer. A retrospective review of lung cancer screening (LCS) studies at a single university screening program between January 2018 and December 2021 identified all patients with Lung-RADS category 4 lesions. Patient demographics, symptoms within the prior 6 months, and imaging features were recorded. During the defined period, 4819 baseline and annual LCS exams were performed; 7.6 % (n = 368) of exams had category 4 nodules and 59 (1.2 %) patients had biopsy-proven lung cancer. Distribution of Lung-RADS category 4 lesions and lung cancer diagnosis were as follows: 4A − 223 nodules, 6.3 % malignant; 4B − 114 nodules, 20.2 % malignant; and 4X − 31 nodules, 71.0 % malignant. Symptoms were reported in 9.0 % (n = 20) of category 4A (2 were malignant), 15.8 % (n = 18) category 4B (1 was malignant) and 22.6 % (n = 7) category 4X (5 were malignant). Imaging features associated with malignancy included endobronchial obstruction with distal atelectasis, pleural tethering, irregular shape, cavitation, and heterogeneous cystic appearance. Twenty-four nodules increased in size, however, only 7 were biopsy proven. Relative to the risk seen with 4A disease, multivariable logistic analyses showed that the odds of a malignancy increased significantly by 3.8 fold (95 % CI: 1.9, 7.9) and 39.2 fold (95 % CI: 14.9, 103.0) with 4B and 4X disease, respectively (p < 0.0001). A separate analysis involving only category 4A and 4B patients jointly showed that disease category (OR = 3.0; 95 % CI: 1.5, 6.4) and additional imaging features (OR = 3.2; 95 % CI: 1.4, 7.0) were significant predictors of malignancy. The presence of clinical symptoms was not statistically associated with lung cancer. Lung-RADS 4 nodules were found in 7.6% of LCS examinations and 16% of these nodules were lung cancer. The probability of lung cancer increases from category 4A to 4X, and imaging features may help differentiate benign from malignant nodules in this LCS category. [ABSTRACT FROM AUTHOR]

Background: Cooking oil fumes (COFs) from cooking with hot oil may contribute to the pathogenesis of lung cancer. Since 2021, occupational lung cancer for individual cafeteria workers has been recognized in South Korea. In this study, we aimed to identify the distribution of lung-imaging reporting and data system (Lung-RADS) among cafeteria workers and to determine factors related to Lung-RADS distribution., Methods: We included 203 female participants who underwent low-dose computed tomography (LDCT) screening at a university hospital and examined the following variables: age, smoking status, second-hand smoke, height, weight, and years of service, mask use, cooking time, heat source, and ventilation. We divided all participants into culinary and non-culinary workers. Binomial logistic regression was conducted to determine the risk factors on LDCT of Category ≥ 3, separately for the overall group and the culinary group., Results: In this study, Lung-RADS-positive occurred in 17 (8.4%) individuals, all of whom were culinary workers. Binary logistic regression analyses were performed and no variables were found to have a significant impact on Lung-RADS results. In the subgroup analysis, the Lung-RADS-positive, and -negative groups differed only in ventilation. Binary logistic regression showed that the adjusted odds ratio (aOR) of the Lung-RADS-positive group for inappropriate ventilation at the workplace was 14.89 (95% confidence interval [CI]: 3.296-67.231) compared to appropriate ventilation as the reference, and the aOR for electric appliances at home was 4.59 (95% CI: 1.061-19.890) using liquid fuel as the reference., Conclusions: The rate of Lung-RADS-positive was significantly higher among culinary workers who performed actual cooking tasks than among nonculinary workers. In addition, appropriate ventilation at the workplace made the LDCT results differ. More research is needed to identify factors that might influence LDCT findings among culinary workers, including those in other occupations., Competing Interests: Competing interests: The authors declare that they have no competing interests., (Copyright © 2024 Korean Society of Occupational & Environmental Medicine.)

Background Safety net hospitals provide care mostly to low-income, uninsured, and vulnerable populations, in whom delays in cancer screening are established barriers. Socioeconomic barriers might pose important challenges to the success of a lung cancer screening program at a safety net hospital. We aimed to determine screening follow-up compliance, rates of diagnostic and treatment procedures, and the rate of cancer diagnosis in patients classified as category 4 by the Lung CT Screening Reporting and Data System (Lung-RADS 4). Methods We conducted a retrospective review of all patients enrolled in our multidisciplinary lung cancer screening program between March 2015 and July 2016. Demographics, smoking status, Lung-RADS score, and number of diagnostic and therapeutic interventions and cancer diagnoses were captured. Results A total of 554 patients were screened over a 16-month period. The mean patient age was 63 years (range, 47-85 years), and 60% were male. The majority (92%; 512 of 554) were classified as Lung-RADS 1 to 3, and 8% (42 of 554) were classified as Lung-RADS 4. Among the Lung-RADS 4 patients, 98% (41 of 42) completed their recommended follow-up; 29% (12 of 42) underwent a diagnostic procedure, for an overall diagnostic intervention rate of 2% (12 of 554). Eleven of these 12 patients had cancer, and 1 patient had sarcoidosis. The overall rate of surgical resection was 0.9% (5 of 554), and the rate of diagnostic intervention for noncancer diagnosis was 0.1% (1 of 554). Conclusions Implementation of a multidisciplinary lung cancer screening program at a safety net hospital is feasible. Compliance with follow-up and interventional recommendations in Lung-RADS 4 patients was high despite anticipated social challenges. Overall diagnostic and surgical resection rates and interventions for noncancer diagnosis were low in our initial experience. [ABSTRACT FROM AUTHOR]

Lung cancer screening using low-dose CT scanning reduces lung-cancer-specific and overall mortality in high-risk patients. A significant limitation of lung cancer screening is the false-positive rate. The American College of Radiology Lung Imaging Reporting and Data System (Lung-RADS) was designed to standardize reporting of low-dose lung cancer screening results and to decrease the false-positive rate without significantly compromising sensitivity. Implementing Lung-RADS can also improve cost-effectiveness. However, Lung-RADS has never been studied in a prospective fashion. It also does not have a specific reporting category for patients with isolated hilar and mediastinal adenopathy or pleural effusion in the absence of lung nodules. We report four such cases from our lung cancer screening program. We believe that this is a significant limitation of Lung-RADS and should be revised in its new version. [ABSTRACT FROM AUTHOR]

Background: For lung cancer screening in patients with previous malignant tumors, Lung Imaging Reporting and Data System (Lung-RADS) and other lung cancer screening tools are controversial in terms of requirements for the previous cancer history. This study investigated the effect of the length and type of malignancy history on the diagnostic efficacy of Lung Imaging Reporting and Data System (Lung-RADS) 2022 in pulmonary nodules (PNs)., Methods: Chest computed tomography and clinical data of PNs in patients with a history of cancer who underwent surgical resection in The First Affiliated Hospital of Chongqing Medical University from January 1, 2018, to November 30, 2021, were retrospectively collected and evaluated based on Lung-RADS. All PNs were divided into 2 groups: the prior lung cancer (PLC) and the prior extrapulmonary cancer (PEPC) groups. Each group was divided into the ≥5 years and <5 years groups based on the duration of cancer history. The diagnostic agreement of Lung-RADS was evaluated based on the pathological diagnosis of nodules after operation. The diagnostic agreement rate (AR) of Lung-RADS and the composition ratios of different types between different groups were calculated and compared., Results: A total of 451 patients with 565 PNs were included in this study. These patients were divided into the PLC group (<5 years: 135 cases, 175 PNs; ≥5 years: 9 cases, 12 PNs) and the PEPC group (<5 years: 219 cases, 278 PNs; ≥5 years: 88 cases, 100 PNs). The diagnostic AR of partial solid nodules (93.0%; 95% CI: 88.7-97.2%) and solid nodules (88.1%; 95% CI: 84.1-92.1%) was close (P=0.13), while both were higher than that of the pure ground-glass nodules (24.0%; 95% CI: 17.5-30.4%; all P values <0.001). Within 5 years, the composition ratio of PNs and the diagnostic AR (PLC: 58.9%, 95% CI: 51.5-66.2%; PEPC: 76.6%, 95% CI: 71.6-81.6%) between the PLC and PEPC groups were all different (all P values <0.001), and the others [composition ratio of PNs & the diagnostic AR: PLC (≥5 years) vs. PEPC (≥5 years); PLC (<5 years) vs. PLC (≥5 years); PEPC (<5 years) vs. PEPC (≥5 years)] were similar (all P values >0.05; range: 0.10-0.93)., Conclusions: The length of prior cancer history may affect the diagnostic agreement of Lung-RADS, especially for patients with prior lung cancer within 5 years., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-22-1039/coif). The authors have no conflicts of interest to declare., (2023 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Lung cancer remains the leading cause of cancer-related death in the United States. An effective screening tool for early lung cancer detection has long been sought. Early chest radiograph and low-dose computed tomography (LDCT) screening trials were promising and demonstrated increased cancer detection. However, these studies were not able to improve lung cancer mortality. The National Lung Screening Trial resulted in decreased lung cancer mortality with LDCT screening in a high-risk population. Similar trials are currently underway in Europe. With LDCT now being widely implemented, it is paramount for radiologists to understand the evidence for lung cancer screening. [ABSTRACT FROM AUTHOR]