Comparison of the characteristics of the population eligible for lung cancer screening under 2013 and population newly eligible under 2021 US Preventive Services Task Force recommendations.

PURPOSE: In 2021, the United States Preventive Services Task Force (USPSTF) revised their 2013 recommendations for lung cancer screening eligibility by lowering the pack-year history from 30+ to 20+ pack-years and the recommended age from 55 to 50 years. Simulation studies suggest that Black persons and females will benefit most from these changes, but it is unclear how the revised USPSTF recommendations will impact geographic, health-related, and other sociodemographic characteristics of those eligible. METHODS: This cross-sectional study employed data from the 2017-2020 Behavioral Risk Factor Surveillance System surveys from 23 states to compare age, gender, race, marital, sexual orientation, education, employment, comorbidity, vaccination, region, and rurality characteristics of the eligible population according to the original 2013 USPSTF recommendations with the revised 2021 USPSTF recommendations using chi-squared tests. This study compared those originally eligible to those newly eligible using the BRFSS raking-dervived weighting variable. RESULTS: There were 30,190 study participants. The results of this study found that eligibility increased by 62.4% due to the revised recommendations. We found that the recommendation changes increased the proportion of eligible females (50.1% vs 44.1%), Black persons (9.2% vs 6.6%), Hispanic persons (4.4% vs 2.7%), persons aged 55-64 (55.8% vs 52.6%), urban-dwellers(88.3% vs 85.9%), unmarried (3.4% vs 2.5%) and never married (10.4% vs 6.6%) persons, as well as non-retirees (76.5% vs 56.1%) Respondents without comorbidities and COPD also increased. CONCLUSION: It is estimated that the revision of the lung cancer screening recommendations decreased eligibility disparities in sex, race, ethnicity, marital status, respiratory comorbidities, and vaccination status. Research will be necessary to estimate whether uptake patterns subsequently follow the expanded eligibility patterns.

Enhancing diagnostic precision for acute chest syndrome in sickle cell disease: insights from dual-energy CT lung perfusion mapping.

PURPOSE: Acute chest syndrome (ACS) is secondary to occlusion of the pulmonary vasculature and a potentially life-threatening complication of sickle cell disease (SCD). Dual-energy CT (DECT) iodine perfusion map reconstructions can provide a method to visualize and quantify the extent of pulmonary microthrombi. METHODS: A total of 102 patients with sickle cell disease who underwent DECT CTPA with perfusion were retrospectively identified. The presence or absence of airspace opacities, segmental perfusion defects, and acute or chronic pulmonary emboli was noted. The number of segmental perfusion defects between patients with and without acute chest syndrome was compared. Sub-analyses were performed to investigate robustness. RESULTS: Of the 102 patients, 68 were clinically determined to not have ACS and 34 were determined to have ACS by clinical criteria. Of the patients with ACS, 82.4% were found to have perfusion defects with a median of 2 perfusion defects per patient. The presence of any or new perfusion defects was significantly associated with the diagnosis of ACS (P = 0.005 and < 0.001, respectively). Excluding patients with pulmonary embolism, 79% of patients with ACS had old or new perfusion defects, and the specificity for new perfusion defects was 87%, higher than consolidation/ground glass opacities (80%). CONCLUSION: DECT iodine map has the capability to depict microthrombi as perfusion defects. The presence of segmental perfusion defects on dual-energy CT maps was found to be associated with ACS with potential for improved specificity and reclassification.

Optimisation of virtual monoenergetic reconstructions for the diagnosis of pulmonary embolism using photon-counting detector computed tomography angiography.

Purpose: Computed tomography (CT) pulmonary angiography is considered the gold standard for pulmonary embolism (PE) diagnosis, relying on the discrimination between contrast and embolus. Photon-counting detector CT (PCD-CT) generates monoenergetic reconstructions through energy-resolved detection. Virtual monoenergetic images (VMI) at low keV can be used to improve pulmonary artery opacification. While studies have assessed VMI for PE diagnosis on dual-energy CT (DECT), there is a lack of literature on optimal settings for PCD-CT-PE reconstructions, warranting further investigation. Material and methods: Twenty-five sequential patients who underwent PCD-CT pulmonary angiography for suspicion of acute PE were retrospectively included in this study. Quantitative metrics including signal-to-noise ratio (SNR) and contrast-to-noise (CNR) ratio were calculated for 4 VMI values (40, 60, 80, and 100 keV). Qualitative measures of diagnostic quality were obtained for proximal to distal pulmonary artery branches by 2 cardiothoracic radiologists using a 5-point modified Likert scale. Results: SNR and CNR were highest for the 40 keV VMI (49.3 ± 22.2 and 48.2 ± 22.1, respectively) and were inversely related to monoenergetic keV. Qualitatively, 40 and 60 keV both exhibited excellent diagnostic quality (mean main pulmonary artery: 5.0 ± 0 and 5.0 ± 0; subsegmental pulmonary arteries 4.9 ± 0.1 and 4.9 ± 0.1, respectively) while distal segments at high (80-100) keVs had worse quality. Conclusions: 40 keV was the best individual VMI for the detection of pulmonary embolism by quantitative metrics. Qualitatively, 40-60 keV reconstructions may be used without a significant decrease in subjective quality. VMIs at higher keV lead to reduced opacification of the distal pulmonary arteries, resulting in decreased image quality.

Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT.

Background Limited data are available regarding whether computer-aided diagnosis (CAD) improves assessment of malignancy risk in indeterminate pulmonary nodules (IPNs). Purpose To evaluate the effect of an artificial intelligence-based CAD tool on clinician IPN diagnostic performance and agreement for both malignancy risk categories and management recommendations. Materials and Methods This was a retrospective multireader multicase study performed in June and July 2020 on chest CT studies of IPNs. Readers used only CT imaging data and provided an estimate of malignancy risk and a management recommendation for each case without and with CAD. The effect of CAD on average reader diagnostic performance was assessed using the Obuchowski-Rockette and Dorfman-Berbaum-Metz method to calculate estimates of area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Multirater Fleiss κ statistics were used to measure interobserver agreement for malignancy risk and management recommendations. Results A total of 300 chest CT scans of IPNs with maximal diameters of 5-30 mm (50.0% malignant) were reviewed by 12 readers (six radiologists, six pulmonologists) (patient median age, 65 years; IQR, 59-71 years; 164 [55%] men). Readers' average AUC improved from 0.82 to 0.89 with CAD (P < .001). At malignancy risk thresholds of 5% and 65%, use of CAD improved average sensitivity from 94.1% to 97.9% (P = .01) and from 52.6% to 63.1% (P < .001), respectively. Average reader specificity improved from 37.4% to 42.3% (P = .03) and from 87.3% to 89.9% (P = .05), respectively. Reader interobserver agreement improved with CAD for both the less than 5% (Fleiss κ, 0.50 vs 0.71; P < .001) and more than 65% (Fleiss κ, 0.54 vs 0.71; P < .001) malignancy risk categories. Overall reader interobserver agreement for management recommendation categories (no action, CT surveillance, diagnostic procedure) also improved with CAD (Fleiss κ, 0.44 vs 0.52; P = .001). Conclusion Use of computer-aided diagnosis improved estimation of indeterminate pulmonary nodule malignancy risk on chest CT scans and improved interobserver agreement for both risk stratification and management recommendations. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yanagawa in this issue.

Assessing the Accuracy of a Deep Learning Method to Risk Stratify Indeterminate Pulmonary Nodules.

Rationale: The management of indeterminate pulmonary nodules (IPNs) remains challenging, resulting in invasive procedures and delays in diagnosis and treatment. Strategies to decrease the rate of unnecessary invasive procedures and optimize surveillance regimens are needed.Objectives: To develop and validate a deep learning method to improve the management of IPNs.Methods: A Lung Cancer Prediction Convolutional Neural Network model was trained using computed tomography images of IPNs from the National Lung Screening Trial, internally validated, and externally tested on cohorts from two academic institutions.Measurements and Main Results: The areas under the receiver operating characteristic curve in the external validation cohorts were 83.5% (95% confidence interval [CI], 75.4-90.7%) and 91.9% (95% CI, 88.7-94.7%), compared with 78.1% (95% CI, 68.7-86.4%) and 81.9 (95% CI, 76.1-87.1%), respectively, for a commonly used clinical risk model for incidental nodules. Using 5% and 65% malignancy thresholds defining low- and high-risk categories, the overall net reclassifications in the validation cohorts for cancers and benign nodules compared with the Mayo model were 0.34 (Vanderbilt) and 0.30 (Oxford) as a rule-in test, and 0.33 (Vanderbilt) and 0.58 (Oxford) as a rule-out test. Compared with traditional risk prediction models, the Lung Cancer Prediction Convolutional Neural Network was associated with improved accuracy in predicting the likelihood of disease at each threshold of management and in our external validation cohorts.Conclusions: This study demonstrates that this deep learning algorithm can correctly reclassify IPNs into low- or high-risk categories in more than a third of cancers and benign nodules when compared with conventional risk models, potentially reducing the number of unnecessary invasive procedures and delays in diagnosis.

Screening for Lung Cancer: Lexicon for Communicating With Health Care Providers.

OBJECTIVE: The effectiveness of lung cancer screening with low-dose CT (LDCT) has been shown by multiple clinical trials, particularly the National Lung Screening Trial. Accurate communication of LDCT results to health care providers is critical to optimal patient care. CONCLUSION: The Lung CT Screening Reporting and Data System (Lung-RADS), a structured decision-oriented reporting system designed to minimize the rate of false-positive results and developed by the American College of Radiology, is recommended for use with all LDCT examinations.

Association of Coronary Artery Calcification and Mortality in the National Lung Screening Trial: A Comparison of Three Scoring Methods.

PURPOSE: To evaluate three coronary artery calcification (CAC) scoring methods to assess risk of coronary heart disease (CHD) death and all-cause mortality in National Lung Screening Trial (NLST) participants across levels of CAC scores. MATERIALS AND METHODS: The NLST was approved by the institutional review board at each participating institution, and informed consent was obtained from all participants. Image review was HIPAA compliant. Five cardiothoracic radiologists evaluated 1575 low-dose computed tomographic (CT) scans from three groups: 210 CHD deaths, 315 deaths not from CHD, and 1050 participants who were alive at conclusion of the trial. Radiologists used three scoring methods: overall visual assessment, segmented vessel-specific scoring, and Agatston scoring. Weighted Cox proportional hazards models were fit to evaluate the association between scoring methods and outcomes. RESULTS: In multivariate analysis of time to CHD death, Agatston scores of 1-100, 101-1000, and greater than 1000 (reference category 0) were associated with hazard ratios of 1.27 (95% confidence interval: 0.69, 2.53), 3.57 (95% confidence interval: 2.14, 7.48), and 6.63 (95% confidence interval: 3.57, 14.97), respectively; hazard ratios for summed segmented vessel-specific scores of 1-5, 6-11, and 12-30 (reference category 0) were 1.72 (95% confidence interval: 1.05, 3.34), 5.11 (95% confidence interval: 2.92, 10.94), and 6.10 (95% confidence interval: 3.19, 14.05), respectively; and hazard ratios for overall visual assessment of mild, moderate, or heavy (reference category none) were 2.09 (95% confidence interval: 1.30, 4.16), 3.86 (95% confidence interval: 2.02, 8.20), and 6.95 (95% confidence interval: 3.73, 15.67), respectively. CONCLUSION: By using low-dose CT performed for lung cancer screening in older, heavy smokers, a simple visual assessment of CAC can be generated for risk assessment of CHD death and all-cause mortality, which is comparable to Agatston scoring and strongly associated with outcome.

Feasibility of a patient decision aid about lung cancer screening with low-dose computed tomography.

OBJECTIVE: New clinical guidelines endorse the use of low-dose computed tomography (LDCT) for lung cancer screening among selected heavy smokers while recommending patients be counseled about the potential benefits and harms. We developed and field tested a brief, video-based patient decision aid about lung cancer screening. METHODS: Smokers in a cancer center tobacco treatment program aged 45 to 75 years viewed the video online between November 2011 and September 2012. Acceptability, knowledge, and clarity of values related to the decision were assessed. RESULTS: Fifty-two patients completed the study (mean age=58.5 years; mean duration smoking=34.8 years). Acceptability of the aid was high. Most patients (78.8%) indicated greater interest in screening after viewing the aid. Knowledge about lung cancer screening increased significantly as a result of viewing the aid (25.5% of questions answered correctly before the aid, and 74.8% after; P<.01) although understanding of screening eligibility remained poor. Patients reported being clear about which benefits and harms of screening mattered most to them (94.1% and 86.5%, respectively). CONCLUSIONS: Patients have high information needs related to lung cancer screening. A video-based decision aid may be helpful in promoting informed decision-making, but its impact on lung cancer screening decisions needs to be explored.

Radiation dose reduction for CT lung cancer screening using ASIR and MBIR: a phantom study.

The purpose of this study was to reduce the radiation dosage associated with computed tomography (CT) lung cancer screening while maintaining overall diagnostic image quality and definition of ground-glass opacities (GGOs). A lung screening phantom and a multipurpose chest phantom were used to quantitatively assess the performance of two iterative image reconstruction algorithms (adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR)) used in conjunction with reduced tube currents relative to a standard clinical lung cancer screening protocol (51 effective mAs (3.9 mGy) and filtered back-projection (FBP) reconstruction). To further assess the algorithms' performances, qualitative image analysis was conducted (in the form of a reader study) using the multipurpose chest phantom, which was implanted with GGOs of two densities. Our quantitative image analysis indicated that tube current, and thus radiation dose, could be reduced by 40% or 80% from ASIR or MBIR, respectively, compared with conventional FBP, while maintaining similar image noise magnitude and contrast-to-noise ratio. The qualitative portion of our study, which assessed reader preference, yielded similar results, indicating that dose could be reduced by 60% (to 20 effective mAs (1.6 mGy)) with either ASIR or MBIR, while maintaining GGO definition. Additionally, the readers' preferences (as indicated by their ratings) regarding overall image quality were equal or better (for a given dose) when using ASIR or MBIR, compared with FBP. In conclusion, combining ASIR or MBIR with reduced tube current may allow for lower doses while maintaining overall diagnostic image quality, as well as GGO definition, during CT lung cancer screening.

Lung cancer screening: state of the art.

Results from the National Lung Screening Trial have confirmed that lung cancer mortality is reduced using low-dose CT screening. Opening a lung cancer screening program requires a multidisciplinary approach. While the fundamental aspects of a screening program are similar, such as scheduling, performing, and managing follow-up, there are aspects of a lung cancer screening program that are unique. This article will discuss factors important in establishing a state of the art lung cancer screening program.

Intermittent testicular torsion in the pediatric patient: sonographic indicators of a difficult diagnosis.

OBJECTIVE: The purpose of this study was to determine whether intermittent testicular torsion, defined as the sudden onset of unilateral scrotal pain of short duration with spontaneous resolution, has sonographic indicators that can be used to establish the diagnosis. MATERIALS AND METHODS: A retrospective search for pediatric patients presenting with suspected intermittent testicular torsion over a 2-year period was performed. The sonographic findings, medical records for clinical presentation, surgical outcomes, and comorbidities relevant to intermittent testicular torsion were reviewed. RESULTS: Analysis was performed on two separate categories for intermittent testicular torsion: total patient episodes (n = 19) and surgical cases (n = 10), with a total of 15 patients with 1.26 episodes per patient. Of the 19 episodes of intermittent testicular torsion, 63% (12) had either absent flow followed by normal to increased flow (n = 6, p = 0.18) or increased testicular flow (n = 6), 26% (5) had normal flow, and 10.5% (2) had decreased flow. Of the total episodes of intermittent testicular torsion, 79% (15) had a whirlpool sign or pseudomass, 10.5% (2) had neither a whirlpool sign or pseudomass but a "boggy" thickened cord, and 10.5% (2) had a normal appearance of the spermatic cord with no pseudomass. CONCLUSION: The whirlpool sign or an abnormal boggy cord and pseudomass formation below the twisted spermatic cord were both significant findings to support a diagnosis of intermittent testicular torsion. Although change from no perfusion to perfusion during the examination was not statistically significant in our cases, when present it led to the correct diagnosis in each case.

Ultra-high-resolution photon-counting detector computed tomography of the lungs: Phantom and clinical assessment of radiation dose and image quality.

PURPOSE: Photon-counting-detector computed tomography (PCD-CT) offers enhanced noise reduction, spatial resolution, and image quality in comparison to energy-integrated-detectors CT (EID-CT). These hypothesized improvements were compared using PCD-CT ultra-high (UHR) and standard-resolution (SR) scan-modes. METHODS: Phantom scans were obtained with both EID-CT and PCD-CT (UHR, SR) on an adult body-phantom. Radiation dose was measured and noise levels were compared at a minimum achievable slice thickness of 0.5 mm for EID-CT, 0.2 mm for PCD-CT-UHR and 0.4 mm for PCD-CT-SR. Signal-to-noise ratios (SNR) and contrast-to-noise ratios (CNR) were calculated for five tissue densities. Additionally, data from 25 patients who had PCD-CT of chest were reconstructed at 1 mm and 0.2 mm (UHR) slice-thickness and compared quantitatively (SNR) and qualitatively (noise, quality, sharpness, bone details). RESULTS: Phantom PCD-CT-UHR and PCD-CT-SR scans had similar measured radiation dose (16.0mGy vs 15.8 mGy). Phantom PCD-CT-SR (0.4 mm) had lower noise level in comparison to EID-CT (0.5 mm) (9.0HU vs 9.6HU). PCD-CT-UHR (0.2 mm) had slightly higher noise level (11.1HU). Phantom PCD-CT-SR (0.4 mm) had higher SNR in comparison to EID-CT (0.5 mm) while achieving higher resolution (Bone 115 vs 96, Acrylic 14 vs 14, Polyethylene 11 vs 10). SNR was slightly lower across all densities for PCD-CT UHR (0.2 mm). Interestingly, CNR was highest in the 0.2 mm PCD-CT group; PCD-CT CNR was 2.45 and 2.88 times the CNR for 0.5 mm EID-CT for acrylic and poly densities. Clinical comparison of SNR showed predictably higher SNR for 1 mm (30.3 ± 10.7 vs 14.2 ± 7, p = 0.02). Median subjective ratings were higher for 0.2 mm UHR vs 1 mm PCD-CT for nodule contour (4.6 ± 0.3 vs 3.6 ± 0.1, p = 0.02), bone detail (5 ± 0 vs 4 ± 0.1, p = 0.001), image quality (5 ± 0.1 vs 4.6 ± 0.4, p = 0.001), and sharpness (5 ± 0.1 vs 4 ± 0.2). CONCLUSION: Both UHR and SR PCD-CT result in similar radiation dose levels. PCD-CT can achieve higher resolution with lower noise level in comparison to EID-CT.

ACR Appropriateness Criteria® Incidentally Detected Indeterminate Pulmonary Nodule.

Incidental pulmonary nodules are common. Although the majority are benign, most are indeterminate for malignancy when first encountered making their management challenging. CT remains the primary imaging modality to first characterize and follow-up incidental lung nodules. This document reviews available literature on various imaging modalities and summarizes management of indeterminate pulmonary nodules detected incidentally. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

A transformer-based deep-learning approach for classifying brain metastases into primary organ sites using clinical whole-brain MRI images.

Treatment decisions for brain metastatic disease rely on knowledge of the primary organ site and are currently made with biopsy and histology. Here, we develop a deep-learning approach for accurate non-invasive digital histology with whole-brain magnetic resonance imaging (MRI) data. Contrast-enhanced T1-weighted and fast spoiled gradient echo brain MRI exams (n = 1,582) were preprocessed and input to the proposed deep-learning workflow for tumor segmentation, modality transfer, and primary site classification into one of five classes. Tenfold cross-validation generated an overall area under the receiver operating characteristic curve (AUC) of 0.878 (95% confidence interval [CI]: 0.873,0.883). These data establish that whole-brain imaging features are discriminative enough to allow accurate diagnosis of the primary organ site of malignancy. Our end-to-end deep radiomic approach has great potential for classifying metastatic tumor types from whole-brain MRI images. Further refinement may offer an invaluable clinical tool to expedite primary cancer site identification for precision treatment and improved outcomes.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.

PURPOSE: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process. METHODS: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories ("nodule > or =3 mm," "nodule <3 mm," and "non-nodule > or =3 mm"). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. RESULTS: The Database contains 7371 lesions marked "nodule" by at least one radiologist. 2669 of these lesions were marked "nodule > or =3 mm" by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. CONCLUSIONS: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.

Impact and costs of targeted recruitment of minorities to the National Lung Screening Trial.

BACKGROUND: To promote results in the National Lung Screening Trial (NLST) that are generalizable across the entire US population, a subset of NLST sites developed dedicated strategies for minority recruitment. PURPOSE: To report the effects of targeted strategies on the accrual of underrepresented groups, to describe participant characteristics, and to estimate the costs of targeted enrollment. METHODS: The 2002-2004 Tobacco Use Supplement was used to estimate eligible proportions of racial and ethnic categories. Strategic planning included meetings/conferences with key stakeholders and minority organizations. Potential institutions were selected based upon regional racial/ethnic diversity and proven success in recruitment of underrepresented groups. Seven institutions submitted targeted recruitment strategies with budgets. Accrual by racial/ethnic category was tracked for each institution. Cost estimates were based on itemized receipts for minority strategies relative to minority accrual. RESULTS: Of 18,842 participants enrolled, 1576 (8.4%) were minority participants. The seven institutions with targeted recruitment strategies accounted for 1223 (77.6%) of all minority participants enrolled. While there was a significant increase in the rate of minority accrual pre-implementation to post-implementation for the institutions with targeted recruitment (9.3% vs. 15.2%, p < 0.0001), there was no significant difference for the institutions without (3.5% vs. 3.8%, p = 0.46). Minority enrollees at the seven institutions tended to have less than a high school education, be economically disadvantaged, and were more often uninsured. These socio-demographic differences persisted at the seven institutions even after adjusting for race and ethnicity. The success of different strategies varied by institution, and no one strategy was successful across all institutions. Costs for implementation were also highly variable, ranging from $146 to $749 per minority enrollee. LIMITATIONS: Data on minority recruitment processes were not consistently kept at the individual institutions. In addition, participant responses via newspaper advertisements and the efforts of minority staff hired by the institutions could not be coded on Case Report Forms. CONCLUSIONS: Strategic efforts were associated with significant increases in minority enrollment. The greatest successes require that a priori goals be established based on eligible racial/ethnic proportions; the historical performance of sites in minority accrual should factor into the selection of sites; recruitment planning must begin well in advance of trial launch; and there must be endorsement by prominent representatives of the racial groups of interest.

SMARCA4 mutations in KRAS-mutant lung adenocarcinoma: a multi-cohort analysis.

KRAS is a key oncogenic driver in lung adenocarcinoma (LUAD). Chromatin-remodeling gene SMARCA4 is comutated with KRAS in LUAD; however, the impact of SMARCA4 mutations on clinical outcome has not been adequately established. This study sought to shed light on the clinical significance of SMARCA4 mutations in LUAD. The association of SMARCA4 mutations with survival outcomes was interrogated in four independent cohorts totaling 564 patients: KRAS-mutant patients with LUAD who received nonimmunotherapy treatment from (a) The Cancer Genome Atlas (TCGA) and (b) the MSK-IMPACT Clinical Sequencing (MSK-CT) cohorts; and KRAS-mutant patients with LUAD who received immune checkpoint inhibitor-based immunotherapy treatment from (c) the MSK-IMPACT (MSK-IO) and (d) the Wake Forest Baptist Comprehensive Cancer Center (WFBCCC) immunotherapy cohorts. Of the patients receiving nonimmunotherapy treatment, in the TCGA cohort (n = 155), KRAS-mutant patients harboring SMARCA4 mutations (KS) showed poorer clinical outcome [P = 6e-04 for disease-free survival (DFS) and 0.031 for overall survival (OS), respectively], compared to KRAS-TP53 comutant (KP) and KRAS-only mutant (K) patients; in the MSK-CT cohort (n = 314), KS patients also exhibited shorter OS than KP (P = 0.03) or K (P = 0.022) patients. Of patients receiving immunotherapy, KS patients consistently exhibited the shortest progression-free survival (PFS; P = 0.0091) in the MSK-IO (n = 77), and the shortest PFS (P = 0.0026) and OS (P = 0.0014) in the WFBCCC (n = 18) cohorts, respectively. Therefore, mutations of SMARCA4 represent a genetic factor leading to adverse clinical outcome in lung adenocarcinoma treated by either nonimmunotherapy or immunotherapy.

Managing Incidental Findings on Thoracic CT: Lung Findings. A White Paper of the ACR Incidental Findings Committee.

The ACR Incidental Findings Committee presents recommendations for managing incidentally detected lung findings on thoracic CT. The Chest Subcommittee is composed of thoracic radiologists who endorsed and developed the provided guidance. These recommendations represent a combination of current published evidence and expert opinion and were finalized by informal iterative consensus. The recommendations address commonly encountered incidental findings in the lungs and are not intended to be a comprehensive review of all pulmonary incidental findings. The goal is to improve the quality of care by providing guidance on management of incidentally detected thoracic findings.

Effect of a Patient Decision Aid on Lung Cancer Screening Decision-Making by Persons Who Smoke: A Randomized Clinical Trial.

Importance: Lung cancer screening with low-dose computed tomography lowers lung cancer mortality but has potential harms. Current guidelines support patients receiving information about the benefits and harms of lung cancer screening during decision-making. Objective: To examine the effect of a patient decision aid (PDA) about lung cancer screening compared with a standard educational material (EDU) on decision-making outcomes among smokers. Design, Setting, and Participants: This randomized clinical trial was conducted using 13 state tobacco quitlines. Current and recent tobacco quitline clients who met age and smoking history eligibility for lung cancer screening were enrolled from March 30, 2015, to September 12, 2016, and followed up for 6 months until May 5, 2017. Data analysis was conducted between May 5, 2017, and September 30, 2018. Interventions: Participants were randomized to the PDA video Lung Cancer Screening: Is It Right for Me? (n = 259) or to EDU (n = 257). Main Outcomes and Measures: The primary outcomes were preparation for decision-making and decisional conflict measured at 1 week. Secondary outcomes included knowledge, intentions, and completion of screening within 6 months of receiving the intervention measured by patient report. Results: Of 516 quit line clients enrolled, 370 (71.7%) were younger than 65 years, 320 (62.0%) were female, 138 (26.7%) identified as black, 47 (9.1%) did not have health insurance, and 226 (43.8%) had a high school or lower educational level. Of participants using the PDA, 153 of 227 (67.4%) were well prepared to make a screening decision compared with 108 of 224 participants (48.2%) using EDU (odds ratio [OR], 2.31; 95% CI, 1.56-3.44; P < .001). Feeling informed about their screening choice was reported by 117 of 234 participants (50.0%) using a PDA compared with 66 of 233 participants (28.3%) using EDU (OR, 2.56; 95% CI, 1.72-3.79; P < .001); 159 of 234 participants (68.0%) using a PDA compared with 110 of 232 (47.4%) participants using EDU reported being clear about their values related to the harms and benefits of screening (OR, 2.37; 95% CI, 1.60-3.51; P < .001). Participants using a PDA were more knowledgeable about lung cancer screening than participants using EDU at each follow-up assessment. Intentions to be screened and screening behaviors did not differ between groups. Conclusions and Relevance: In this study, a PDA delivered to clients of tobacco quit lines improved informed decision-making about lung cancer screening. Many smokers eligible for lung cancer screening can be reached through tobacco quit lines. Trial Registration: ClinicalTrials.gov identifier: NCT02286713.