Factors Associated With Delay in Lung Cancer Diagnosis and Surgery in a Lung Cancer Screening Program.

PURPOSE: Delays to biopsy and surgery after lung nodule detection can impact survival from lung cancer. The aim of this study was to identify factors associated with delay in a lung cancer screening (LCS) program. MATERIALS AND METHODS: We evaluated patients in an LCS program from May 2015 through October 2021 with a malignant lung nodule classified as lung CT screening reporting and data system (Lung-RADS) 4B/4X. A cutoff of more than 30 days between screening computed tomography (CT) and first tissue sampling and a cutoff of more than 60 days between screening CT and surgery were considered delayed. We evaluated the relationship between delays to first tissue sampling and surgery and patient sex, age, race, smoking status, median income by zip code, language, Lung-RADS category, and site of surgery (academic vs community hospital). RESULTS: A total of 185 lung cancers met the inclusion criteria, of which 150 underwent surgical resection. The median time from LCS CT to first tissue sampling was 42 days, and the median time from CT to surgery was 52 days. 127 (69%) patients experienced a first tissue sampling delay and 60 (40%) had a surgical delay. In multivariable analysis, active smoking status was associated with delay to first tissue sampling (odds ratio: 3.0, CI: 1.4-6.6, P = 0.005). Only performing enhanced diagnostic CT of the chest before surgery was associated with delayed lung cancer surgery (odds ratio: 30, CI: 3.6-252, P = 0.02). There was no statistically significant difference in delays with patients' sex, age, race, language, or Lung-RADS category. CONCLUSION: Delays to first tissue sampling and surgery in a LCS program were associated with current smoking and performing diagnostic CT before surgery.

Risk of Malignancy in Incidentally Detected Lung Nodules in Patients Aged Younger Than 35 Years.

BACKGROUND: The risk of malignancy in pulmonary nodules incidentally detected on computed tomography (CT) in patients who are aged younger than 35 years is unclear. OBJECTIVE: The aim of this study was to evaluate the incidence of lung cancer in incidental pulmonary nodules in patients who are 15-34 years old. METHODS: This retrospective study included patients aged 15-34 years who had an incidental pulmonary nodule on chest CT from 2010 to 2018 at our hospital. Patients with prior, current, or suspected malignancy were excluded. A chart review identified patients with diagnosis of malignancy. Incidental pulmonary nodule was deemed benign if stable or resolved on a follow-up CT at least 2 years after initial or if there was a medical visit in our health care network at least 2 years after initial CT without diagnosis of malignancy.Receiver operating characteristic curve analysis was performed with nodule size. Association of categorical variables with lung cancer diagnosis was performed with Fisher exact test, and association of continuous variables was performed with logistic regression. RESULTS: Five thousand three hundred fifty-five chest CTs performed on patients aged 15-34 years between January 2010 and December 2018. After excluding patients without a reported pulmonary nodule and prior or current malignancy, there were a total of 779 patients. Of these, 690 (89%) had clinical or imaging follow-up after initial imaging. Of these, 545 (70% of total patients) patients had imaging or clinical follow-up greater than 2 years after their initial imaging.A malignant diagnosis was established in 2/779 patients (0.3%; 95% confidence interval, 0.1%-0.9%). Nodule size was strongly associated with malignancy (P = 0.007), with area under the receiver operating characteristic curve of 0.97. There were no malignant nodules that were less than 10 mm in size. Smoking history, number of nodules, and nodule density were not associated with malignancy. CONCLUSIONS: Risk of malignancy for incidentally detected pulmonary nodules in patients aged 15-34 years is extremely small (0.3%). There were no malignant nodules that were less than 10 mm in size. Routine follow-up of subcentimeter pulmonary nodules should be carefully weighed against the risks.

Comparison of Lung-RADS Version 1.1 and Lung-RADS Version 2022 in Classifying Airway Nodules Detected at Lung Cancer Screening CT.

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.

Clinical Outcomes of Resected Pure Ground-Glass, Heterogeneous Ground-Glass, and Part-Solid Pulmonary Nodules.

Background: Increased (but not definitively solid) density within pure ground-glass nodules (pGGNs) may indicate invasive adenocarcinoma and need for resection rather than surveillance. Objective: To compare clinical outcomes between resected pGGNs, heterogeneous ground-glass nodules (GGNs), and part-solid nodules (PSNs). Methods: This retrospective study included 469 patients (median age, 68 years [IQR, 11 years]; 335 female, 134 male) who underwent resection between January 2012 and December 2020 of lung adenocarcinoma appearing as a subsolid nodule on CT. Two radiologists using lung windows independently classified each nodule as a pGGN, heterogeneous GGN, or PSN, resolving discrepancies through discussion. Heterogeneous GGN was defined as a GGN with internal increased density not quite as dense as pulmonary vessels; PSN had an internal solid component as dense as pulmonary vessels. Outcomes included pathologic diagnosis of invasive adenocarcinoma, 5-year recurrence rates (locoregional or distant), and recurrence-free survival (RFS) and overall survival (OS) through 7 years analyzed by Kaplan-Meier and Cox proportional hazards regression analyses, censoring patients with incomplete follow-up. Results: Interobserver agreement for nodule type, expressed as kappa, was 0.69. Using consensus assessments, 59 nodules were pGGNs, 109 were heterogeneous GGNs, and 301 were PSNs. Frequency of invasive adenocarcinoma was 39.0% in pGGNs, 67.9% in heterogeneous GGNs, and 75.7% in PSNs (pGGN vs heterogeneous GGN: P<.001; pGGN vs PSN: P<.001; heterogeneous GGN vs PSN: P=.28). The 5-year recurrence rate was 0.0% in pGGNs, 6.3% in heterogeneous GGNs, and 10.8% in PSNs (pGGN vs heterogeneous GGN: P=.06; pGGN vs PSN: P=.02; heterogeneous GGN vs PSN: P=.18). At 7 years, RFS was 97.7% in pGGNs, 82.0% in heterogeneous GGNs, and 79.4% in PSNs (pGGN vs heterogeneous GGN: P=.02; pGGN vs PSN: P=.006; heterogeneous GGN v PSN: P=.40); OS was 98.0% in pGGNs, 84.6% in heterogeneous GGNs, and 82.9% in PSNs (pGGN vs heterogeneous GGN: P=.04; pGGN vs PSN: P=.01; heterogeneous GGN vs PSN: P=.50). Conclusion: Resected pGGNs had excellent clinical outcomes. Heterogeneous GGNs had relatively worse outcomes, more closely resembling outcomes for PSNs. Clinical Impact: The findings support surveillance for truly homogeneous pGGNs, versus resection for GGNs exhibiting internal increased density, even if not a true solid component.

Rate of benign nodule resection in a lung cancer screening program.

PURPOSE: Screening with low dose computed tomography (CT) can reduce lung cancer related death at the expense of unavoidable false positive results. The purpose of this study is to measure the rate of surgery for benign nodules, and evaluate characteristics of those nodules. MATERIALS AND METHODS: In this study, we evaluated patients in the Lung Cancer Screening (LCS) program across a large tertiary healthcare network from 5/2015 through 10/2021 who underwent surgical resection for a lung nodule. We reviewed the pathology reports and subsequent follow-up to establish whether the nodule was benign or malignant. Imaging characteristics of the nodules were evaluated by a radiology fellow, and we recorded Lung-RADS category, nodule status (baseline, stable, new, growing), FDG uptake on PET/CT, and calculated the risk from the Brock model. RESULTS: During this time period, a total of 21,366 LCS CT was performed in 9050 patients, and 260 patients underwent a following surgical resection. Review of the pathology results revealed: 220 lung cancer (85%), 2 other malignancies (1%), and 38 benign findings (15%). Pathology of the benign nodules was as follows: 12 with scarring/fibrosis, 5 with benign neoplasms, 14 with infection/inflammation, and 7 with other diagnoses. Lung-RADS category was as follows: 4 (11%) Lung-RADS 2, 2 (5%) Lung-Rad 3, 11 (29%) Lung-RADS 4A, 13 (34%) Lung-RADS 4B, and 8 (21%) Lung-RADS 4X. The size of the nodules ranged from 4 to 41 mm with a median of 13 mm. 2 (5%) were ground glass, 10 (26%) were part-solid, and 26 (68%) were solid. FDG-PET/CT was performed in 19 out of 38 cases, of which: 2 (11%) had no uptake, 10 (53%) had mild uptake, 3 (16%) had moderate uptake, and 4 (21%) had intense uptake. Risk assessment by Brock calculator revealed that 9 (24) had <5% (very low) risk; 27 (71%) had 5-65% (low-intermediate) risk, and 2 (5%) had >65% (high) risk. CONCLUSION: Surgical resection of benign nodules is unavoidable despite application of Lung-RADS guidelines in a modern screening program, with approximately 15% of surgeries being done for benign lesions.

Volume Doubling Times of Benign and Malignant Nodules in Lung Cancer Screening.

The purpose of this study was to measure the fractions of benign and malignant nodules in lung cancer screening that grow on follow-up, and to measure the volume doubling time (VDT) of those that grow. In this retrospective study, we included nodules from CT lung cancer screening in our healthcare network, for which a follow-up CT performed at least 2 months later showed the nodule to be persistent. The nodules were measured using semiautomated volumetric segmentation software at both timepoints. Growth was defined as an increase in volume by 25%. VDTs were calculated, and the fraction <400 days was recorded. Categorical variables were compared with Fisher's exact test, and continuous variables by the Wilcoxon test. The study included 153 nodules, of which 44 were malignant and 109 benign. Thirty (68%) of malignant nodules and 36 (33%) of benign nodules grew (P < 0.001). For growing nodules, VDT was 318 days for malignant nodules and 389 for benign nodules (P = 0.21). For growing solid nodules, VDT was 204 days for malignant nodules and 386 days for benign nodules (P = 0.01); of these, VDT was <400 days for 12/13 (92%) of malignant nodules and 15/26 (58%) of benign nodules. In conclusion, malignant nodules were more likely to grow, and solid malignant nodules grew faster, than benign nodules. However, there was substantial overlap between benign and malignant nodules. This limits the utility of volume doubling time in determining malignant nodules.

Reporting and Outcomes of Coronary Calcification on Lung Cancer Screening CT.

RATIONALE AND OBJECTIVES: To evaluate the accuracy and downstream testing and statin prescribing of real-world reporting of coronary calcification on lung cancer screening (LCS) CT. MATERIALS AND METHODS: We retrospectively reviewed LCS CTs from January 2015 to November 2021 for reporting of coronary calcification; reports that denoted coronary calcification as a significant incidental finding ("S" modifier) were also noted. We evaluated calcium scoring accuracy in patients in whom a cardiac or calcium scoring CT was performed within 1 year of the LCS CT. For the first LCS CT in all patients, we evaluated whether a stress test was performed within 6 months and whether a new statin prescription was written within 90 days of the LCS CT. Patients were stratified by atherosclerotic cardiovascular disease (ASCVD) risk group, used in a multivariable regression analysis for new statin prescriptions. RESULTS: Eight thousand nine hundred eighty-seven patients underwent screening. In 117 patients who had a paired cardiac CT, scores were concordant in 65 (56%), and LCS CTs did not mention or underestimated calcifications in 40 (34%). Reporting of coronary artery calcifications led to new statin prescriptions, with OR of 1.8 for calcifications without S modifier and 4.4 for calcifications with S modifier. Reporting of coronary artery calcification with S modifier led to subsequent stress testing in 141/1582 (9%) of patients. CONCLUSION: Coronary calcifications are frequently not mentioned or underestimated at LCS CT. Reporting of coronary calcifications leads to new statin prescriptions, and radiologists should consider reporting these to allow for a risk-benefit discussion with the patient's physician.

Malignant Nodules Detected on Lung Cancer Screening CT: Yield of Short-Term Follow-Up CT in Showing Nodule Growth.

BACKGROUND. Lung-RADS recommends 3-month follow-up for category 4A nodules and downgrading to category 2 of all category 3 or 4 nodules that are unchanged for 3 months or longer, indicating benign behavior. This guidance may be problematic considering the potential for slow-growing cancers in that lack of nodule growth, particularly at short follow-up intervals, may provide false reassurance. OBJECTIVE. The purpose of this study was to evaluate the yield of short-term follow-up CT in showing growth among malignant nodules detected on lung cancer screening CT. METHODS. This retrospective study included 76 patients (53 women, 23 men; median age, 68 years) with a positive lung cancer screening CT result (Lung-RADS category ≥ 3) between June 2015 and May 2021 with a subsequent lung cancer diagnosis and at least one follow-up CT examination at least 3 months before diagnostic or therapeutic intervention. Semiautomated software was used for linear and volumetric nodule measurements. Diameter was defined as the mean of short- and long-axis measurements. For solid nodules, growth was defined as an at least 1.5-mm increase in mean diameter or an at least 25% increase in volume; part-solid nodules, an at least 1.5-mm increase in solid-component mean diameter or an at least 25% increase in volume; and ground-glass nodules, an at least 3-mm increase in mean diameter or development of a new solid component within the nodule. RESULTS. Median time to growth was 13 months by linear and 11 months by volumetric measurement. Frequency of growth at 3 months was 5% by linear and 7% by volumetric measurement. By linear measurement, median time to growth and frequency of growth at 3 months were 13 months and 7% (solid nodules), 18 months and 6% (part-solid nodules), not reached and 0% (ground-glass nodules), not reached and 0% (category 3 nodules), 13 months and 6% (category 4A nodule)s, 6 months and 11% (category 4B nodules), and 12 months and 10% (category 4X nodules). CONCLUSION. Malignant nodules manifest growth slowly on follow-up CT, and 3-month follow-up CT has very low yield. Stability at 3-month follow-up should not instill high confidence in benignancy, and downgrading all such nodules to Lung-RADS category 2 may be problematic. CLINICAL IMPACT. This study highlights the possibility of slow-growing malignancy and associated challenges in application of Lung-RADS to management of unchanged nodules on follow-up imaging.

Use of Diagnostic CT and Patient Retention in a Lung Cancer Screening Program.

PURPOSE: The aims of this study were to assess the rate of subsequent diagnostic chest CT examinations in a lung cancer screening (LCS) program and examine the effect on retention of patients in the program. METHODS: Patients who underwent LCS CT between June 2011 and August 2018 were included. The occurrence of patients' being subsequently imaged with diagnostic CT versus LCS CT and the effect this had on patients' returning for LCS CT (patient retention) were evaluated. Multivariable logistic regression was used to evaluate variables associated with undergoing diagnostic CT and risk factors associated with loss of patient retention. RESULTS: Of the 5,912 patients who underwent LCS CT, 2,756 underwent subsequent diagnostic or LCS chest CT. Increasing Lung-RADS® score was more likely to lead to subsequent diagnostic chest CT (P < .0001). A total of 1,240 patients underwent at least three chest CT examinations in the time interval. For the 711 patients whose subsequent CT studies were for LCS, 585 (82%) were retained, whereas of the 529 patients who underwent subsequent diagnostic CT, only 208 (39%) were retained (P < .0001). For the 197 subsequent diagnostic CT examinations performed for pulmonary nodule or screening indications, 81 patients (41%) returned for LCS CT, compared with 498 of 612 patients (81%) who underwent subsequent LCS CT (P < .0001). In multivariable analysis, subsequent diagnostic chest CT and increasing Lung-RADS score were associated with loss of retention. CONCLUSIONS: A higher Lung-RADS score is a risk factor for subsequent diagnostic chest CT, and this is an independent risk factor for loss from the LCS program.

Cancer Risk in Nodules Detected at Follow-Up Lung Cancer Screening CT.

BACKGROUND. Nodules may have different lung cancer risks when new on follow-up CT versus when present on previously performed CT (i.e., existing nodules). Diameter-based Lung-RADS and volume-based NELSON (Nederlands-Leuvens Longkanker Screenings ONderzoek trial) categories have shown variable performance in nodule risk assessment. OBJECTIVE. The purpose of this study was to assess Lung-RADS and NELSON classifications of nodules detected on follow-up lung cancer screening CT examinations. METHODS. This retrospective study included 185 patients (100 women and 85 men; median age, 66 years) who underwent a lung cancer screening CT examination for which a prior CT examination was available. Stratified random sampling was performed to enrich the sample with suspicious nodules, yielding 50, 45, 47, 30, and 13 nodules with Lung-RADS categories 2, 3, 4A, 4B, and 4X, respectively. Lung-RADS categories were recorded from clinical reports. The linear measurements of the nodules were extracted from clinical reports to generate Lung-RADS categories by use of strict criteria from Lung-RADS version 1.1. Two radiologists used a semiautomated tool to obtain nodule volumes, which were used to generate NELSON categories. Lung cancer risk was assessed. ROC analysis was performed. Percentages and AUCs were weighted on the basis of Lung-RADS category frequencies in the underlying screening cohort. RESULTS. Twenty-nine cancers were diagnosed. The weighted cancer risk was 5% for new nodules, 1% for stable existing nodules, and 44% for growing existing nodules. None of the clinical Lung-RADS category 2 nodules were cancer. With use of strict Lung-RADS version 1.1 criteria, 34 nodules, including seven cancers, were downgraded to category 2. The AUC for cancer was 0.96 for clinical Lung-RADS, 0.81 for strict Lung-RADS, 0.71-0.84 for the NELSON algorithm (two readers), and 0.89 for nodule diameter measurement. Clinical Lung-RADS achieved weighted sensitivity and specificity, respectively, of 100% and 85% for the entire sample, 100% and 41% for new nodules, and 100% and 94% for existing nodules. The optimal diameter threshold was 8 mm for existing nodules versus 6 mm for new nodules. CONCLUSION. Lung-RADS, as applied by radiologists in clinical practice, achieved excellent performance on follow-up screening examinations. Strict Lung-RADS resulted in the downgrading of some cancers to category 2. Volumetric assessments had weaker performance than clinical Lung-RADS. New nodules warrant smaller size thresholds than existing nodules. CLINICAL IMPACT. The findings of the present study provide insight into radiologists' management of nodules detected on follow-up screening examinations.

Factors Influencing the False Positive Rate in CT Lung Cancer Screening.

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.

Thoracic and Extrathoracic Malignancies in Lung Cancer Screening Patients With Histories of Malignancy.

PURPOSE: The objective of this study was to assess whether a history of malignancy affects the incidence of extrathoracic malignancies and lung cancer in patients undergoing CT lung cancer screening (LCS). METHODS: All patients who underwent a LCS CT between June 2014 and August 2018 in a single health care system were included. History of prior nonskin malignancy was extracted from billing records. Subsequent diagnoses of malignancy were extracted from clinical pathology reports. Risk for subsequent malignancy was compared between patients with and those without prior malignancy and evaluated using multivariate logistic regression including age and history of malignancy. RESULTS: A total of 5,835 LCS CT studies were included, and 1,243 (21%) were performed on patients with diagnoses of malignancy before CT. For the 4,592 scans performed on patients without histories of malignancy, 87 patients (1.9%) were diagnosed with lung cancer and 68 (1.5%) were diagnosed with nonlung malignancies in the following year. Among patients with histories of malignancy, 17 (1.4%) were diagnosed with lung cancer, and 25 (2%) were diagnosed with nonlung malignancies. Logistic regression for subsequent diagnosis of malignancy (including lung cancer) demonstrated age to be predictive, with an odds ratio of 1.6 per decade (P < .0001); history of malignancy was not predictive of subsequent malignancy (P = .50). CONCLUSIONS: Patients with histories of malignancy referred for LCS have a similar risk for developing lung cancers and extrathoracic malignancies as patients without histories of malignancy. Patients with histories of malignancy who are believed by their referring providers to be at low risk for metastasis should not be excluded from LCS.

Contribution of FDG-PET/CT to the management of esophageal cancer patients at multidisciplinary tumor board conferences.

BACKGROUND: A multidisciplinary team approach to the management of esophageal cancer patients leads to better clinical decisions. PURPOSE: The contribution of CT, endoscopic and laparoscopic ultrasound to clinical staging and treatment selection by multidisciplinary tumor boards (MTB) in patients with esophageal cancer is well documented. However, there is a paucity of data addressing the role that FDG-PET/CT (PET/CT) plays to inform the clinical decision-making process at MTB conferences. The aim of this study was to assess the impact and contribution of PET/CT to clinical management decisions and to the plan of care for esophageal cancer patients at the MTB conferences held at our institution. MATERIALS AND METHODS: This IRB approved study included all the cases discussed in the esophageal MTB meetings over a year period. The information contributed by PET/CT to MTB decision making was grouped into four categories. Category I, no additional information provided for clinical management; category II, equivocal and misguiding information; category III, complementary information to other imaging modalities, and category IV, information that directly changed clinical management. The overall impact on management was assessed retrospectively from prospectively discussed clinical histories, imaging, histopathology, and the official minutes of the MTB conferences. RESULTS: 79 patients (61 males and 18 females; median age, 61 years, range, 33-86) with esophageal cancer (53 adenocarcinomas and 26 squamous cell carcinomas) were included. The contribution of PET/CT-derived information was as follows: category I in 50 patients (63%); category II in 3 patients (4%); category III in 8 patients (10%), and category IV information in 18 patients (23%). Forty-five patients (57%) had systemic disease, and in 5 (11%) of these, metastatic disease was only detected by PET/CT. In addition, PET/CT detected previously unknown recurrence in 4 (9%) of 43 patients. In summary, PET/CT provided clinically useful information to guide management in 26 of 79 esophageal cancer patients (33%) discussed at the MTB. CONCLUSION: The study showed that PET/CT provided additional information and changed clinical management in 1 out of 3 (33%) esophageal cancer cases discussed at MTB conferences. These results support the inclusion whenever available, of FDG-PET/CT imaging information to augment and improve the patient management decision process in MTB conferences.

Rheumatoid arthritis-related lung disease detected on clinical chest computed tomography imaging: Prevalence, risk factors, and impact on mortality.

OBJECTIVE: We aimed to determine the real-world prevalence and investigate risk factors for rheumatoid arthritis (RA)-related lung disease on chest computed tomography (CT) imaging. We also investigated the impact of RA-related lung disease on mortality. METHODS: We studied chest CT imaging abnormalities among RA patients. We determined the presence and type of abnormalities using the chest CT imaging radiologic report. RA-related lung disease was defined as interstitial lung disease (ILD), bronchiectasis, or pleural disease. We examined whether demographics and RA characteristics were associated with RA-related lung disease using logistic regression. RA-related lung disease and mortality was described using survival curves and Cox regression. RESULTS: We analyzed 190 patients who had chest CT imaging performed for clinical indications. Mean age was 64.2 years (SD 11.8), 80.0% were female, and 75.3% were seropositive. RA-related lung disease was detected in 54 patients (28.4%); 30 (15.8%) had ILD, 27 (14.2%) had bronchiectasis, and 18 (9.5%) had pleural disease. RA-related lung disease was reported in both seropositive and seronegative RA (28.7% vs. 27.7%, p = 1.00). Male sex (OR 2.62, 95%CI 1.17-5.88) and current methotrexate use (OR 2.73, 95%CI 1.27-5.61 vs. not current) were associated with RA-related lung disease. Twenty-four (44.4%) patients with RA-related lung disease died during mean 7.0 years of follow-up. RA-related lung disease had HR of 5.35 (95%CI 0.72-39.9) for mortality compared to normal chest CT. CONCLUSIONS: In this real-world study, RA-related lung disease was commonly detected on chest CT imaging regardless of RA serostatus. RA-related lung disease had high mortality, emphasizing the importance in close monitoring of these patients.

Radiologic-Pathologic Correlation for Nondiagnostic CT-Guided Lung Biopsies Performed for the Evaluation of Lung Cancer.

OBJECTIVE. For nondiagnostic CT-guided lung biopsies, we tested whether radiologicpathologic correlation could identify patients who may benefit from repeat biopsy. MATERIALS AND METHODS. In this retrospective study, 1525 lung biopsies were performed between July 2013 and June 2017, 243 of which were nondiagnostic. Of these 243 lung biopsies, 98 were performed to evaluate for lung malignancy; 17 were excluded because of insufficient follow-up, leaving a total of 81 cases. The Brock and Herder models were used to calculate risk; in addition, cases were independently blindly reviewed by two thoracic radiologists who assigned a score from 1 (probably benign) to 5 (probably malignant). The final diagnosis was established by pathology results or benignancy was established if the lesion resolved or remained stable for at least 2 years. RESULTS. Of the 81 nondiagnostic lung biopsies, initial pathology results included 33 cases of inflammation, 28 cases of normal lung tissue or insufficient sample, 10 cases of organizing pneumonia, and 10 cases of atypical cells. 42% (34/81) of cases were eventually determined to be malignant (negative predictive value [NPV] of 58%). Pathology results of organizing pneumonia had the lowest rate of malignancy (2/10 = 20%), and pathology results of atypical cells had the highest rate of malignancy (5/10 = 50%, p = 0.51). Within this highly selected cohort, the Brock and Herder models were not predictive of malignancy, with areas under the ROC curve (AUCs) of 0.52 and 0.52, respectively. Evaluation by thoracic radiologists yielded AUCs of 0.85 and 0.77. When radiologist-assigned scores of 1 and 2 were considered as benign, the NPV was 90% and 95%. CONCLUSION. Review of nondiagnostic lung biopsies for radiologic-pathologic concordance by thoracic radiologists can triage patients who may benefit from repeat biopsy.

Determinants of Chest X-Ray Sensitivity for COVID- 19: A Multi-Institutional Study in the United States.

PURPOSE: To evaluate the sensitivity, specificity, and severity of chest x-rays (CXR) and chest CTs over time in confirmed COVID-19+ and COVID-19- patients and to evaluate determinants of false negatives. METHODS: In a retrospective multi-institutional study, 254 RT-PCR verified COVID-19+ patients with at least one CXR or chest CT were compared with 254 age- and gender-matched COVID-19- controls. CXR severity, sensitivity, and specificity were determined with respect to time after onset of symptoms; sensitivity and specificity for chest CTs without time stratification. Performance of serial CXRs against CTs was determined by comparing area under the receiver operating characteristic curves (AUC). A multivariable logistic regression analysis was performed to assess factors related to false negative CXR. RESULTS: COVID-19+ CXR severity and sensitivity increased with time (from sensitivity of 55% at ≤2 days to 79% at >11 days; p<0.001 for trends of both severity and sensitivity) whereas CXR specificity decreased over time (from 83% to 70%, p=0.02). Serial CXR demonstrated increase in AUC (first CXR AUC=0.79, second CXR=0.87, p=0.02), and second CXR approached the accuracy of CT (AUC=0.92, p=0.11). COVID-19 sensitivity of first CXR, second CXR, and CT was 73%, 83%, and 88%, whereas specificity was 80%, 73%, and 77%, respectively. Normal and mild severity CXR findings were the largest factor behind false-negative CXRs (40% normal and 87% combined normal/mild). Young age and African-American ethnicity increased false negative rates. CONCLUSION: CXR sensitivity in COVID-19 detection increases with time, and serial CXRs of COVID-19+ patients has accuracy approaching that of chest CT.

Reducing Wait Time for Lung Cancer Diagnosis and Treatment: Impact of a Multidisciplinary, Centralized Referral Program.

BACKGROUND: A multidisciplinary, centralized referral program was established at our institution in 2014 to reduce delays in lung cancer diagnosis and treatment following diagnostic imaging observed with the traditional, primary care provider-led referral process. The main objectives of this retrospective cohort study were to determine if referral to a Thoracic Triage Panel (TTP): 1) expedites lung cancer diagnosis and treatment initiation; and 2) leads to more appropriate specialist consultation. METHODS: Patients with a diagnosis of lung cancer and initial diagnostic imaging between March 1, 2015, and February 29, 2016, at a Memorial University-affiliated tertiary care centre in St John's, Newfoundland, were identified and grouped according to whether they were referred to the TTP or managed through a traditional referral process. Wait times (in days) from first abnormal imaging to biopsy and treatment initiation were recorded. Statistical analysis was performed using the Wilcoxon rank-sum test. RESULTS: A total of 133 patients who met inclusion criteria were identified. Seventy-nine patients were referred to the TTP and 54 were managed by traditional means. There was a statistically significant reduction in median wait times for patients referred to the TTP. Wait time from first abnormal imaging to biopsy decreased from 61.5 to 36.0 days (P < .0001). Wait time from first abnormal imaging to treatment initiation decreased from 118.0 to 80.0 days (P < .001). The percentage of specialist consultations that led to treatment was also greater for patients referred to the TTP. CONCLUSIONS: A collaborative, centralized intake and referral program helps to reduce wait time for diagnosis and treatment of lung cancer.