RadioGraphics Update: The 10 Pillars of Lung Cancer Screening-Rationale and Logistics of a Lung Cancer Screening Program.

Editor's Note.-RadioGraphics Update articles supplement or update information found in full-length articles previously published in RadioGraphics. These updates, written by at least one author of the previous article, provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes.

Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data.

Importance: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation. Objective: To validate CXR-LC using EMR data to identify individuals at high-risk for lung cancer to complement 2022 US Centers for Medicare & Medicaid Services (CMS) lung cancer screening eligibility guidelines. Design, Setting, and Participants: This prognostic study compared CXR-LC estimates with CMS screening guidelines using patient data from a large US hospital system. Included participants were persons who currently or formerly smoked cigarettes with an outpatient posterior-anterior chest radiograph between January 1, 2013, and December 31, 2014, with no history of lung cancer or screening CT. Data analysis was performed between May 2021 and June 2022. Exposures: CXR-LC lung cancer screening eligibility (previously defined as having a 3.297% or greater 12-year risk) based on inputs (chest radiograph image, age, sex, and whether currently smoking) extracted from the EMR. Main Outcomes and Measures: 6-year incident lung cancer. Results: A total of 14 737 persons were included in the study population (mean [SD] age, 62.6 [6.8] years; 7154 [48.5%] male; 204 [1.4%] Asian, 1051 [7.3%] Black, 432 [2.9%] Hispanic, 12 330 [85.2%] White) with a 2.4% rate of incident lung cancer over 6 years (361 patients with cancer). CMS eligibility could be determined in 6277 patients (42.6%) using smoking pack-year and quit-date from the EMR. Patients eligible by both CXR-LC and 2022 CMS criteria had a high rate of lung cancer (83 of 974 patients [8.5%]), higher than those eligible by 2022 CMS criteria alone (5 of 177 patients [2.8%]; P < .001). Patients eligible by CXR-LC but not 2022 CMS criteria also had a high 6-year incidence of lung cancer (121 of 3703 [3.3%]). In the 8460 cases (57.4%) where CMS eligibility was unknown, CXR-LC eligible patients had a 5-fold higher rate of lung cancer than ineligible (127 of 5177 [2.5%] vs 18 of 2283 [0.5%]; P < .001). Similar results were found in subgroups, including female patients and Black persons. Conclusions and Relevance: Using routine chest radiographs and other data automatically extracted from the EMR, CXR-LC identified high-risk individuals who may benefit from lung cancer screening CT.

Preoperative CT-guided Fiducial Marker Placement for Surgical Localization of Pulmonary Nodules.

Purpose: To assess the technical success and complication rates of CT-guided fiducial marker placement for the localization of pulmonary nodules and to assess the surgical localization failure rate. Materials and Methods: This was a single-center, retrospective analysis of consecutive patients who underwent CT-guided fiducial marker placement procedures between 2014 and 2020. End points included the technical success of the fiducial marker placement, procedural complications, and the surgical localization failure rate. A two-sample t test and a Fisher exact test were used to compare continuous and categorical variables, respectively. Multivariate logistic regression was used to identify independent risk factors for complications. Results: A total of 198 preoperative CT-guided fiducial marker placement procedures were performed in 190 patients (mean age, 64 years ± 12 [standard deviation]; 121 women) to localize 205 nodules (mean size, 10 mm ± 4; mean distance to the pleura, 10 mm ± 9). The technical success rate was 98.5% (195 of 198). There were no major complications. A total of 202 nodules were resected during 193 procedures performed 5 days ± 13 after the fiducial marker placement (range, 0-123 days). Surgical localization failure occurred in one patient (0.5%). Of the resected nodules, 146 were lung cancers, 26 nodules were metastases, two were carcinoid tumors, and 28 were benign. Conclusion: The CT-guided fiducial marker placement of pulmonary nodules was safe, effective, and resulted in a low surgical localization failure rate.Keywords: CT, Percutaneous, Thorax, Lung.

Incidence of Radiation Therapy Among Patients Enrolled in a Multidisciplinary Pulmonary Nodule and Lung Cancer Screening Clinic.

Importance: The number of pulmonary nodules discovered incidentally or through screening programs has increased markedly. Multidisciplinary review and management are recommended, but the involvement of radiation oncologists in this context has not been defined. Objective: To assess the role of stereotactic body radiation therapy among patients enrolled in a lung cancer screening program. Design, Setting, and Participants: This prospective cohort study was performed at a pulmonary nodule and lung cancer screening clinic from October 1, 2012, to September 31, 2019. Referrals were based on chest computed tomography with Lung Imaging Reporting and Data System category 4 finding or an incidental nodule 6 mm or larger. A multidisciplinary team of practitioners from radiology, thoracic surgery, pulmonology, medical oncology, and radiation oncology reviewed all nodules and coordinated workup and treatment as indicated. Exposures: Patients referred to the pulmonary nodule and lung cancer screening clinic with an incidental or screen-detected pulmonary nodule. Main Outcomes and Measures: The primary outcome was the proportion of patients undergoing therapeutic intervention with radiation therapy, stratified by the route of detection of their pulmonary nodules (incidental vs screen detected). Secondary outcomes were 2-year local control and metastasis-free survival. Results: Among 1150 total patients (median [IQR] age, 66.5 [59.3-73.7] years; 665 [57.8%] female; 1024 [89.0%] non-Hispanic White; 841 [73.1%] current or former smokers), 234 (20.3%) presented with screen-detected nodules and 916 (79.7%) with incidental nodules. For patients with screen-detected nodules requiring treatment, 41 (17.5%) received treatment, with 31 (75.6%) undergoing surgery and 10 (24.4%) receiving radiation therapy. Patients treated with radiation therapy were older (median [IQR] age, 73.8 [67.1 to 82.1] vs 67.6 [61.0 to 72.9] years; P < .001) and more likely to have history of tobacco use (67 [95.7%] vs 128 [76.6%]; P = .001) than those treated with surgery. Fifty-eight patients treated with radiation therapy (82.9%) were considered high risk for biopsy, and treatment recommendations were based on a clinical diagnosis of lung cancer after multidisciplinary review. All screened patients who received radiation therapy had stage I disease and were treated with stereotactic body radiation therapy. For all patients receiving stereotactic body radiation therapy, 2-year local control was 96.3% (95% CI, 91.1%-100%) and metastasis-free survival was 94.2% (95% CI, 87.7%-100%). Conclusions and Relevance: In this unique prospective cohort, 1 in 4 patients with screen-detected pulmonary nodules requiring intervention were treated with stereotactic body radiation therapy. This finding highlights the role of radiation therapy in a lung cancer screening population and the importance of including radiation oncologists in the multidisciplinary management of pulmonary nodules.

Liquid Biopsy, Diagnostic Imaging, and Future Synergies.

Imaging plays an integral role in the initial diagnosis and longitudinal care of patients with cancer. Liquid biopsies, which most commonly involve genetic analysis of circulating free DNA, have emerged as important complementary tools in cancer care with the potential to interface with imaging at each step of the cancer care continuum. Here, the authors use non-small-cell lung cancer as a paradigm to elucidate factors driving the need for liquid biopsy in the spectrum of lung cancer care, demonstrate ways in which liquid biopsy has already changed standard clinical practice, and discuss anticipated synergies of liquid biopsy and imaging in screening and early detection and in monitoring of disease.

Lung-RADS Category 3 and 4 Nodules on Lung Cancer Screening in Clinical Practice.

BACKGROUND. Lung-RADS category 3 and 4 nodules account for most screening-detected lung cancers and are considered actionable nodules with management implications. The cancer frequency among such nodules is estimated in the Lung-RADS recommendations and has been investigated primarily by means of retrospectively assigned Lung-RADS classifications. OBJECTIVE. The purpose of this study was to assess the frequency of cancer among lung nodules assigned Lung-RADS category 3 or 4 at lung cancer screening (LCS) in clinical practice and to evaluate factors that affect the cancer frequency within each category. METHODS. This retrospective study was based on review of clinical radiology reports of 9148 consecutive low-dose CT LCS examinations performed for 4798 patients between June 2014 and January 2021 as part of an established LCS program. Unique nodules assigned Lung-RADS category 3 or 4 (4A, 4B, or 4X) that were clinically categorized as benign or malignant in a multidisciplinary conference that considered histologic analysis and follow-up imaging were selected for further analysis. Benign diagnoses based on stability required at least 12 months of follow-up imaging. Indeterminate nodules were excluded. Cancer frequencies were evaluated. RESULTS. Of the 9148 LCS examinations, 857 (9.4%) were assigned Lung-RADS category 3, and 721 (7.9%) were assigned category 4. The final analysis included 1297 unique nodules in 1139 patients (598 men, 541 women; mean age, 66.0 ± 6.3 years). A total of 1108 of 1297 (85.4%) nodules were deemed benign, and 189 of 1297 (14.6%) were deemed malignant. The frequencies of malignancy of category 3, 4A, 4B, and 4X nodules were 3.9%, 15.5%, 36.3%, and 76.8%. A total of 45 of 46 (97.8%) endobronchial nodules (all category 4A) were deemed benign on the basis of resolution. Cancer frequency was 13.1% for solid, 24.4% for part-solid, and 13.5% for ground-glass nodules. CONCLUSION. In the application of Lung-RADS to LCS clinical practice, the frequency of Lung-RADS category 3 and 4 nodules and the cancer frequency in these categories were higher than the prevalence and cancer risk estimated for category 3 and 4 nodules in the Lung-RADS recommendations and those reported in earlier studies in which category assignments were retrospective. Nearly all endobronchial category 4A nodules were benign. CLINICAL IMPACT. Future Lung-RADS iterations should consider the findings of this study from real-world practice to improve the clinical utility of the system.

E-Cigarette Use, Small Airway Fibrosis, and Constrictive Bronchiolitis.

BACKGROUND: Vaping, including the use of electronic cigarettes (e-cigarettes), has become increasingly prevalent, yet the associated long-term health risks are largely unknown. Given the prevalence of use, particularly among adolescents early in their lifespan, it is vital to understand the potential chronic pathologic sequelae of vaping. METHODS: We present the cases of four patients with chronic lung disease associated with e-cigarette use characterized by clinical evaluation, with pulmonary function tests (PFTs), chest high-resolution computed tomography (HRCT), endobronchial optical coherence tomography (EB-OCT) imaging, and histopathologic assessment. RESULTS: Each patient presented with shortness of breath and chest pain in association with a 3- to 8-year history of e-cigarette use, with mild progressive airway obstruction on PFTs and/or chest HRCT findings demonstrating evidence of air trapping and bronchial wall thickening. EB-OCT imaging performed in two patients showed small airway-centered fibrosis with bronchiolar narrowing and lumen irregularities. The predominant histopathologic feature on surgical lung biopsy was small airway-centered fibrosis, including constrictive bronchiolitis and MUC5AC overexpression in all patients. Patients who ceased vaping had a partial, but not complete, reversal of disease over 1 to 4 years. CONCLUSIONS: After thorough evaluation for other potential etiologies, vaping was considered to be the most likely common causal etiology for all patients due to the temporal association of symptomatic chronic lung disease with e-cigarette use and partial improvement in symptoms after e-cigarette cessation. In this series, we associate the histopathologic pattern of small airway-centered fibrosis, including constrictive bronchiolitis, with vaping, potentially defining a clinical and pathologic entity associated with e-cigarette use. (Funded in part by the National Institutes of Health.).

Racial and Ethnic Disparities in Lung Cancer Screening Eligibility.

Background To address disparities in lung cancer screening (LCS) that may exclude large numbers of high-risk African American smokers, revised U.S. Preventive Services Task Force (USPSTF) recommendations lowered LCS eligibility thresholds. However, there are limited recent data about the impact of newly revised guidelines on disparities in LCS eligibility. Purpose To evaluate the impact of revised USPSTF guidelines on racial and ethnic disparities in LCS eligibility. Materials and Methods Cross-sectional survey data from 20 states were retrospectively evaluated from the 2019 Behavioral Risk Factor Surveillance System survey (median response rate, 49.4%). Respondents without a history of lung cancer aged 55-79 years (ie, under the previous guidelines) or aged 50-79 years (ie, under the revised guidelines) were included. Multivariable logistic regression analyses were performed to evaluate the association between race and ethnicity and LCS eligibility. All analyses were performed accounting for complex survey design features (ie, weighting, stratification, and clustering). Results Under previous guidelines, 11% of 67 567 weighted survey respondents were eligible for LCS (White [12%], Hispanic [4%], African American [7%], American Indian [17%], Asian or Pacific Islander [4%], and other [12%]). Under revised USPSTF guidelines, 14% of 77 689 weighted survey respondents were eligible for LCS (White [15%], Hispanic [5%], African American [9%], American Indian [21%), Asian or Pacific Islander [5%], and other [18%]). Compared with White respondents, African American respondents (adjusted odds ratio [OR] = 0.36; 95% CI: 0.27, 0.47; P < .001) and Hispanic respondents (adjusted OR = 0.15; 95% CI: 0.09, 0.24; P < .001) were less likely to be eligible for LCS under previous guidelines. African American respondents (adjusted OR = 0.39; 95% CI: 0.32, 0.47; P < .001) and Hispanic respondents (adjusted OR = 0.15; 95% CI: 0.10, 0.23; P < .001) were less likely to be eligible under the revised guidelines. The Wald test showed no evidence of differences in the degree to which racial and ethnic minority groups were less likely to be eligible for LCS when comparing previous versus revised USPSTF guidelines (P = .76). Conclusion The revised U.S. Preventive Services Task Force guidelines (version 2.0) may perpetuate lung cancer disparities, as racial and ethnic minority groups are still less likely to be eligible for lung cancer screening. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Jacobs and Springfield in this issue.

Longitudinal CT and MRI Characteristics of Unilocular Thymic Cysts.

Background Isoattenuating and hyperattenuating thymic cysts at CT are often misinterpreted as lymphadenopathy or thymic epithelial neoplasms. Purpose To evaluate the longitudinal change in thymic cyst appearance at CT and MRI. Materials and Methods All chest MRI studies showing thymic cysts between July 2008 and December 2019, identified from a retrospective search of a quality assurance database, were included in this study if initial CT depicted a thymic lesion, the patient was referred for follow-up MRI for characterization, and the baseline (ie, index) MRI indicated a cystic lesion. Follow-up CT scans and/or MRI scans were identified through July 2020. Thymic cyst characteristics, such as size, location, and morphologic features, as well as CT and MRI characteristics, were recorded. Change in size, attenuation, and T1-weighted MRI signal was assessed longitudinally. Descriptive statistics of longitudinal change were tabulated. Results A total of 244 chest MRI studies in 140 patients with 142 unique cysts and 392 CT examinations (636 total examinations and 645 thymic cysts-nine examinations with two cysts each) were evaluated. The median follow-up duration was 2.2 years. Thirty-three patients with 34 unique cysts (34 of 142 cysts [24%]) underwent imaging follow-up for more than 5 years. Thymic cysts followed up for more than 5 years were most commonly saccular (189 of 274 cysts [69% axially]) and retrosternal (14 of 34 cysts [41%]). Craniocaudal dimension was larger than transverse and anteroposterior dimensions in 223 of 274 cysts (81%). Mean thymic cyst attenuation was 25 HU (range, 15-100 HU). Five of 31 cysts (16%) exhibited wall calcification. The median cyst wall thickness was 2.0 mm (range, 0.9-3.0 mm). Most thymic cysts changed in volume (31 of 34 cysts [91%]), CT attenuation (15 of 35 cysts [43%]), and T1-weighted MRI signal (12 of 18 cysts [67%]) over time. None developed mural irregularity, nodularity, or septations. Conclusion Unilocular thymic cysts, defined at index MRI, never developed irregular wall thickening, mural nodularity, or septations that would raise concern for malignant transformation. However, these cysts showed mural calcification and change in size, CT attenuation, and MRI signal over more than 5 years of follow-up. © RSNA, 2021 Online supplemental material is available for this article.

Characteristics and Outcomes of Lung Cancers Detected on Low-Dose Lung Cancer Screening CT.

BACKGROUND: Lung cancer screening (LCS) with low-dose CT (LDCT) was implemented in the United States following the National Lung Screening Trial (NLST). The real-world benefits of implementing LCS are yet to be determined with outcome-oriented data. The study objective is to investigate the characteristics and outcomes of screening-detected lung cancers. METHODS: This single-institution retrospective study included LCS patients between June 2014 and December 2019. Patient demographics, number of screening rounds, imaging features, clinical workup, disease extent, histopathology, treatment, complications, and mortality outcomes of screening-detected lung cancers were extracted and compared with NLST data. RESULTS: LCS LDCTs (7,480) were performed on 4,176 patients. The cancer detection rate was 3.8%, higher than reported by NLST (2.4%, P < 0.0001), and cancers were most often found in patients ≥65 years (62%), older than those in NLST (41%, P < 0.0001). The patients' ethnicity was similar to NLST, P = 0.87. Most LCS-detected cancers were early stage I tumors (71% vs. 54% in NLST, P < 0.0001). Two thirds of cancers were detected in the first round of screening (67.1%) and were multifocal lung cancers in 15%. As in NLST, the complication rate after invasive workup or surgery was low (24% vs. 28% in NLST, P = 0.32). Over a median follow-up of 3.3 years, the mortality rate was 0.45%, lower than NLST (1.33%, P < 0.0001). CONCLUSIONS: LCS implementation achieved a higher cancer detection rate, detection of early-stage cancers, and more multifocal lung cancers compared with the NLST, with low complications and mortality. IMPACT: The real-world implementation of LCS has been successful for detection of lung cancer with favorable outcomes.

Artificial intelligence-based vessel suppression for detection of sub-solid nodules in lung cancer screening computed tomography.

BACKGROUND: Lung cancer screening (LCS) with low-dose computed tomography (LDCT) helps early lung cancer detection, commonly presenting as small pulmonary nodules. Artificial intelligence (AI)-based vessel suppression (AI-VS) and automatic detection (AI-AD) algorithm can improve detection of subsolid nodules (SSNs) on LDCT. We assessed the impact of AI-VS and AI-AD in detection and classification of SSNs [ground-glass nodules (GGNs) and part-solid nodules (PSNs)], on LDCT performed for LCS. METHODS: Following regulatory approval, 123 LDCT examinations with sub-solid pulmonary nodules (average diameter ≥6 mm) were processed to generate three image series for each examination-unprocessed, AI-VS, and AI-AD series with annotated lung nodules. Two thoracic radiologists in consensus formed the standard of reference (SOR) for this study. Two other thoracic radiologists (R1 and R2; 5 and 10 years of experience in thoracic CT image interpretation) independently assessed the unprocessed images alone, then together with AI-VS series, and finally with AI-AD for detecting all ≥6 mm GGN and PSN. We performed receiver operator characteristics (ROC) and Cohen's Kappa analyses for statistical analyses. RESULTS: On unprocessed images, R1 and R2 detected 232/310 nodules (R1: 114 GGN, 118 PSN) and 255/310 nodules (R2: 122 GGN, 133 PSN), respectively (P>0.05). On AI-VS images, they detected 249/310 nodules (119 GGN, 130 PSN) and 277/310 nodules (128 GGN, 149 PSN), respectively (P≥0.12). When compared to the SOR, accuracy (AUC) for detection of PSN on the AI-VS images (AUC 0.80-0.81) was greater than on the unprocessed images (AUC 0.70-0.76). AI-VS images enabled detection of solid components in five nodules deemed as GGN on the unprocessed images. Accuracy of AI-AD was lower than both the radiologists (AUC 0.60-0.72). CONCLUSIONS: AI-VS improved the detection and classification of SSN into GGN and PSN on LDCT of the chest for the two radiologist (R1 and R2) readers.

PET/MRI assessment of lung nodules in primary abdominal malignancies: sensitivity and outcome analysis.

PURPOSE: To evaluate PET/MR lung nodule detection compared to PET/CT or CT, to determine growth of nodules missed by PET/MR, and to investigate the impact of missed nodules on clinical management in primary abdominal malignancies. METHODS: This retrospective IRB-approved study included [18F]-FDG PET/MR in 126 patients. All had standard of care chest imaging (SCI) with diagnostic chest CT or PET/CT within 6 weeks of PET/MR that served as standard of reference. Two radiologists assessed lung nodules (size, location, consistency, position, and [18F]-FDG avidity) on SCI and PET/MR. A side-by-side analysis of nodules on SCI and PET/MR was performed. The nodules missed on PET/MR were assessed on follow-up SCI to ascertain their growth (≥ 2 mm); their impact on management was also investigated. RESULTS: A total of 505 nodules (mean 4 mm, range 1-23 mm) were detected by SCI in 89/126 patients (66M:60F, mean age 60 years). PET/MR detected 61 nodules for a sensitivity of 28.1% for patient and 12.1% for nodule, with higher sensitivity for > 7 mm nodules (< 30% and > 70% respectively, p < 0.05). 75/337 (22.3%) of the nodules missed on PET/MR (follow-up mean 736 days) demonstrated growth. In patients positive for nodules at SCI and negative at PET/MR, missed nodules did not influence patients' management. CONCLUSIONS: Sensitivity of lung nodule detection on PET/MR is affected by nodule size and is lower than SCI. 22.3% of missed nodules increased on follow-up likely representing metastases. Although this did not impact clinical management in study group with primary abdominal malignancy, largely composed of extra-thoracic advanced stage cancers, with possible different implications in patients without extra-thoracic spread.

Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs.

RATIONALE AND OBJECTIVES: Radiographic findings of COVID-19 pneumonia can be used for patient risk stratification; however, radiologist reporting of disease severity is inconsistent on chest radiographs (CXRs). We aimed to see if an artificial intelligence (AI) system could help improve radiologist interrater agreement. MATERIALS AND METHODS: We performed a retrospective multi-radiologist user study to evaluate the impact of an AI system, the PXS score model, on the grading of categorical COVID-19 lung disease severity on 154 chest radiographs into four ordinal grades (normal/minimal, mild, moderate, and severe). Four radiologists (two thoracic and two emergency radiologists) independently interpreted 154 CXRs from 154 unique patients with COVID-19 hospitalized at a large academic center, before and after using the AI system (median washout time interval was 16 days). Three different thoracic radiologists assessed the same 154 CXRs using an updated version of the AI system trained on more imaging data. Radiologist interrater agreement was evaluated using Cohen and Fleiss kappa where appropriate. The lung disease severity categories were associated with clinical outcomes using a previously published outcomes dataset using Fisher's exact test and Chi-square test for trend. RESULTS: Use of the AI system improved radiologist interrater agreement (Fleiss κ = 0.40 to 0.66, before and after use of the system). The Fleiss κ for three radiologists using the updated AI system was 0.74. Severity categories were significantly associated with subsequent intubation or death within 3 days. CONCLUSION: An AI system used at the time of CXR study interpretation can improve the interrater agreement of radiologists.

Management and Outcomes of Suspected Infectious and Inflammatory Lung Abnormalities Identified on Lung Cancer Screening CT.

BACKGROUND. Incidental findings are frequently encountered during lung cancer screening (LCS). Limited data describe the prevalence of suspected acute infectious and inflammatory lung processes on LCS and how they should be managed. OBJECTIVE. The purpose of this study was to determine the prevalence, radiologic reporting and management, and outcome of suspected infectious and inflammatory lung processes identified incidentally during LCS and to propose a management algorithm. METHODS. This retrospective study included 6314 low-dose CT (LDCT) examinations performed between June 2014 and April 2019 in 3800 patients as part of an established LCS program. Radiology reports were reviewed, and patients with potentially infectious or inflammatory lung abnormalities were identified and analyzed for descriptors of imaging findings, Lung-RADS designation, recommendations, and clinical outcomes. Using the descriptors, outcomes, and a greater than 2% threshold risk of malignancy, a follow-up algorithm was developed to decrease additional imaging without affecting cancer detection. RESULTS. A total of 331/3800 (8.7%) patients (178 men, 153 women; mean age [range], 66 [53-87] years) undergoing LCS had lung findings that were attributed to infection or inflammation. These abnormalities were reported as potentially significant findings using the S modifier in 149/331 (45.0%) and as the dominant nodule used to determine the Lung-RADS category in 96/331 (29.0%). Abnormalities were multiple or multifocal in 260/331 (78.5%). Common descriptors were ground-glass (155/331; 46.8%), tree-in-bud (56/331; 16.9%), consolidation (41/331; 12.4%), and clustered (67/331; 20.2%) opacities. A follow-up chest CT outside of screening was performed within 12 months or less in 264/331 (79.8%) and within 6 months or less in 186/331 (56.2%). A total of 260/331 (78.5%) opacities resolved on follow-up imaging. Two malignancies (2/331; 0.6%) were associated with these abnormalities and both had consolidations. Theoretic adoption of a proposed management algorithm for suspected infectious and inflammatory findings reduced unnecessary follow-up imaging by 82.6% without missing a single malignancy. CONCLUSION. Presumed acute infectious or inflammatory lung abnormalities are frequently encountered in the setting of LCS. These opacities are commonly multifocal and resolve on follow-up. Less than 1% are associated with malignancy. CLINICAL IMPACT. Adoption of a conservative management algorithm can standardize recommendations and reduce unnecessary imaging without increasing the risk of missing a malignancy.