Risk of Lung Cancer in Peripheral Pulmonary Nodules.

PURPOSE: To determine the risk of lung cancer and inter-observer agreement for small pulmonary nodules either touching or near the pleura. METHODS: Nodules were derived from two cohorts: patients from the National Lung Screening Trial with a solid nodule measuring 6-9.5 mm; and patients with incidental pulmonary nodules in our healthcare system with a solid nodule measuring 1-8 mm. Only the dominant nodule was evaluated for each patient. All malignant nodules as well as a random sample of 200 benign nodules from each cohort were included. Two fellowship-trained thoracic radiologists independently reviewed each case to record nodule morphology (compatible with lymph node or not) and nodule location (pleural-based, septal connection to the pleura, or neither). One radiologist measured the distance to the pleura. RESULTS: After exclusion criteria were applied, a total of 434 nodules were included, of which 45 were lung cancers. Considering all pleural-based nodules with lymph node morphology as benign, 0-7% of cancers were misclassified as benign, specificity 33%, and κ = 0.69. Considering subpleural nodules and those with septal connection to the pleura, 7-11% of cancers were misclassified (p = 0.16-0.25 versus pleural-based), specificity 40-52% (p < .0001), and κ = 0.60. Considering nodules with lymph node morphology ≤ 2 mm from the pleura, 2-7% of cancers were misclassified (p = 1 versus pleural-based), specificity 41-36% (p < .0001), and κ = 0.78. CONCLUSION: Considering nodules with lymph node morphology with septal connection, or those ≤ 2 mm from the pleura, as benign does not lead to significant misclassification of lung cancers as benign.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations.

The American College of Radiology created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

ACR Lung-RADS v2022: Assessment Categories and Management Recommendations.

The ACR created the Lung CT Screening Reporting and Data System (Lung-RADS) in 2014 to standardize the reporting and management of screen-detected pulmonary nodules. Lung-RADS was updated to version 1.1 in 2019 and revised size thresholds for nonsolid nodules, added classification criteria for perifissural nodules, and allowed for short-interval follow-up of rapidly enlarging nodules that may be infectious in etiology. Lung-RADS v2022, released in November 2022, provides several updates including guidance on the classification and management of atypical pulmonary cysts, juxtapleural nodules, airway-centered nodules, and potentially infectious findings. This new release also provides clarification for determining nodule growth and introduces stepped management for nodules that are stable or decreasing in size. This article summarizes the current evidence and expert consensus supporting Lung-RADS v2022.

Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study.

BACKGROUND: Contemporary pulmonary embolism (PE) research, in many cases, relies on data from electronic health records (EHRs) and administrative databases that use International Classification of Diseases (ICD) codes. Natural language processing (NLP) tools can be used for automated chart review and patient identification. However, there remains uncertainty with the validity of ICD-10 codes or NLP algorithms for patient identification. METHODS: The PE-EHR+ study has been designed to validate ICD-10 codes as Principal Discharge Diagnosis, or Secondary Discharge Diagnoses, as well as NLP tools set out in prior studies to identify patients with PE within EHRs. Manual chart review by two independent abstractors by predefined criteria will be the reference standard. Sensitivity, specificity, and positive and negative predictive values will be determined. We will assess the discriminatory function of code subgroups for intermediate- and high-risk PE. In addition, accuracy of NLP algorithms to identify PE from radiology reports will be assessed. RESULTS: A total of 1,734 patients from the Mass General Brigham health system have been identified. These include 578 with ICD-10 Principal Discharge Diagnosis codes for PE, 578 with codes in the secondary position, and 578 without PE codes during the index hospitalization. Patients within each group were selected randomly from the entire pool of patients at the Mass General Brigham health system. A smaller subset of patients will also be identified from the Yale-New Haven Health System. Data validation and analyses will be forthcoming. CONCLUSIONS: The PE-EHR+ study will help validate efficient tools for identification of patients with PE in EHRs, improving the reliability of efficient observational studies or randomized trials of patients with PE using electronic databases.

Significance of Right-to-Left Ventricular Ratio as a Quantitative Computed Tomography Biomarker in Patients With Negative Computed Tomography Pulmonary Angiograms.

PURPOSE: The purpose of our study was to determine if the ratio of right-to-left ventricular diameter (RV/LV ratio) on computed tomography (CT) pulmonary angiograms (CTPA) is predictive of 90-day mortality in patients without pulmonary embolism (PE). MATERIALS AND METHODS: This Institutional Review Board-approved single-institution retrospective study was performed on patients who underwent CTPA in the emergency or inpatient setting over a 1-year period. Right and left ventricular diameters were measured and RV/LV ratios calculated for patients without acute PE. Ratios greater than or equal to 0.9 were considered abnormal. Univariate analysis was performed for the outcome of death within 90 days of CT. Multivariable analysis was also performed to control for age, sex, and lung disease. RESULTS: Of the 423 patients included in the study, 55 patients died within 90 days of CT. An RV/LV ratio ≥0.9 was predictive of 90-day mortality: of the 226 patients with RV/LV ≥0.9, 42 (18.6%) died within 90 days, compared with 13 of 197 patients without abnormal ratio (6.6%), with odds ratio (OR) of 3.23 (95% confidence interval [CI]: 1.68-6.22; P<0.01). In multivariate analysis, RV/LV ratio had an OR of 5.19 per unit increase (95%CI: 1.06-25.42; P=0.04); age had an OR of 1.04 per year increase (95% CI: 1.01-1.06; P<0.01). CONCLUSION: Increased RV/LV ratio is a negative prognostic factor even in patients without acute PE and may be a useful CT biomarker to include in radiology reports for all patients undergoing CTPA.

Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data.

BACKGROUND. Lung-RADS version 1.1 (v1.1) classifies all solid nodules less than 6 mm as category 2. Lung-RADS v1.1 also classifies solid intermediate-size (6 to < 10 mm) nodules as category 2 if they are perifissural and have a triangular, polygonal, or ovoid shape (indicative of intrapulmonary lymph nodes). Additional category 2 criteria could reduce false-positive results of screening examinations. OBJECTIVE. The purpose of this study was to evaluate the impact of proposed strategies for reducing false-positive results for intermediate-size nodules on lung cancer screening CT evaluated using Lung-RADS v1.1. METHODS. This retrospective study entailed secondary analysis of National Lung Screening Trial (NLST) data. Of 1387 solid nodules measuring 6.0-9.5 mm on baseline screening CT examinations in the NLST, all 38 nodules in patients who developed cancer and a random sample of 200 nodules in patients who did not develop cancer were selected for further evaluation. Cancers were required to correspond with the baseline nodule on manual review. After exclusions, the sample included 223 patients (median age, 62 years; 143 men, 80 women; 196 benign nodules, 27 malignant nodules). Two thoracic radiologists independently reviewed baseline examinations to record nodule diameter and volume using semiautomated software and to determine whether nodules had perifissural location; other subpleural location; and triangular, polygonal, or ovoid shape. Different schemes for category 2 assignment were compared. RESULTS. Across readers, standard Lung-RADS v1.1 had sensitivity of 89-93% and specificity of 26-31%. A modification assigning nodules less than 10 mm with triangular, polygonal, or ovoid shape in other subpleural locations (vs only perifissural location) as category 2 had sensitivity of 85-93% and specificity of 47-51%. Lung-RADS v1.1 using volume cutoffs had sensitivity of 89-93% and specificity of 37% (both readers). The sensitivity of both modified Lung-RADS v1.1 and Lung-RADS v1.1 with volume cutoffs was not significantly different from standard Lung-RADS v1.1 (all p > .05). However, both schemes' specificity was significantly better than standard Lung-RADS v1.1 (all p < .05). Combining the two strategies yielded sensitivity of 85-93% and specificity of 58-59%. CONCLUSION. Classifying intermediate-size nodules with triangular, polygonal, or ovoid shape in any subpleural (not just perifissural) location as category 2 and using volume- rather than diameter-based measurements improves Lung-RADS specificity without decreased sensitivity. CLINICAL IMPACT. The findings can help reduce false-positive results, decreasing 6-month follow-up examinations for benign findings.

Loss of Pulmonary Vascular Volume as a Predictor of Right Ventricular Dysfunction and Mortality in Acute Pulmonary Embolism.

BACKGROUND: In acute pulmonary embolism, chest computed tomography angiography derived metrics, such as the right ventricle (RV): left ventricle ratio are routinely used for risk stratification. Paucity of intraparenchymal blood vessels has previously been described, but their association with clinical biomarkers and outcomes has not been studied. We sought to determine if small vascular volumes measured on computed tomography scans were associated with an abnormal RV on echocardiography and mortality. We hypothesized that decreased small venous volume would be associated with greater RV dysfunction and increased mortality. METHODS: A retrospective cohort of patients with intermediate risk pulmonary embolism admitted to Brigham and Women's Hospital between 2009 and 2017 was assembled, and clinical and radiographic data were obtained. We performed 3-dimensional reconstructions of vasculature to assess intraparenchymal vascular volumes. Statistical analyses were performed using multivariable regression and cox proportional hazards models, adjusting for age, sex, lung volume, and small arterial volume. RESULTS: Seven hundred twenty-two subjects were identified of whom 573 had documented echocardiography. A 50% reduction in small venous volume was associated with an increased risk of RV dilation (relative risk: 1.38 [95% CI, 1.18-1.63], P<0.001), RV dysfunction (relative risk: 1.62 [95% CI, 1.36-1.95], P<0.001), and RV strain (relative risk: 1.67 [95% CI, 1.37-2.04], P<0.001); increased cardiac biomarkers, and higher 30-day and 90-day mortality (hazard ratio: 2.50 [95% CI, 1.33-4.67], P=0.004 and hazard ratio: 1.84 [95% CI, 1.11-3.04], P=0.019, respectively). CONCLUSIONS: Loss of small venous volume quantified from computed tomography angiography is associated with increased risk of abnormal RV on echocardiography, abnormal cardiac biomarkers, and higher risk of 30- and 90-day mortality. Small venous volume may be a useful marker for assessing disease severity in acute pulmonary embolism.

Quantification of Arterial and Venous Morphologic Markers in Pulmonary Arterial Hypertension Using CT Imaging.

BACKGROUND: Pulmonary hypertension is a heterogeneous disease, and a significant portion of patients at risk for it have CT imaging available. Advanced automated processing techniques could be leveraged for early detection, screening, and development of quantitative phenotypes. Pruning and vascular tortuosity have been previously described in pulmonary arterial hypertension (PAH), but the extent of these phenomena in arterial vs venous pulmonary vasculature and in exercise pulmonary hypertension (ePH) have not been described. RESEARCH QUESTION: What are the arterial and venous manifestations of pruning and vascular tortuosity using CT imaging in PAH, and do they also occur in ePH? STUDY DESIGN AND METHODS: A cohort of patients with PAH and ePH and control subjects with available CT angiograms were retrospectively identified to examine the differential arterial and venous presence of pruning and tortuosity in patients with precapillary pulmonary hypertension not confounded by lung or thromboembolic disease. The pulmonary vasculature was reconstructed, and an artificial intelligence method was used to separate arteries and veins and to compute arterial and venous vascular volumes and tortuosity. RESULTS: A total of 42 patients with PAH, 12 patients with ePH, and 37 control subjects were identified. There was relatively lower (median [interquartile range]) arterial small vessel volume in subjects with PAH (PAH 14.7 [11.7-16.5; P < .0001]) vs control subjects (16.9 [15.6-19.2]) and venous small vessel volume in subjects with PAH and ePH (PAH 8.0 [6.5-9.6; P < .0001]; ePH, 7.8 [7.5-11.4; P = .004]) vs control subjects (11.5 [10.6-12.2]). Higher large arterial volume, however, was only observed in the pulmonary arteries (PAH 17.1 [13.6-23.4; P < .0001] vs control subjects 11.4 [8.1-15.4]). Similarly, tortuosity was higher in the pulmonary arteries in the PAH group (PAH 3.5 [3.3-3.6; P = .0002] vs control 3.2 [3.2-3.3]). INTERPRETATION: Lower small distal pulmonary vascular volume, higher proximal arterial volume, and higher arterial tortuosity were observed in PAH. These can be quantified by using automated techniques from clinically acquired CT scans of patients with ePH and resting PAH.

Radiologist Reporting and Operational Management for Patients With Suspected COVID-19.

PURPOSE: The aim of this study was to evaluate the adoption and outcomes of locally designed reporting guidelines for patients with possible coronavirus disease 2019 (COVID-19). METHODS: A departmental guideline was developed for radiologists that specified reporting terminology and required communication for patients with imaging findings suggestive of COVID-19, on the basis of patient test status and imaging indication. In this retrospective study, radiology reports completed from March 1, 2020, to May 3, 2020, that mentioned COVID-19 were reviewed. Reports were divided into patients with known COVID-19, patients with "suspected" COVID-19 (having an order indication of respiratory or infectious signs or symptoms), and "unsuspected patients" (other order indications, eg, trauma or non-chest pain). The primary outcome was the percentage of COVID-19 reports using recommended terminology; the secondary outcome was percentages of suspected and unsuspected patients diagnosed with COVID-19. Relationships between categorical variables were assessed using the Fisher exact test. RESULTS: Among 77,400 total reports, 1,083 suggested COVID-19 on the basis of imaging findings; 774 of COVID-19 reports (71%) used recommended terminology. Of 574 patients without known COVID-19 at the time of interpretation, 345 (60%) were eventually diagnosed with COVID-19, including 61% (315 of 516) of suspected and 52% (30 of 58) of unsuspected patients. Nearly all unsuspected patients (46 of 58) were identified on CT. CONCLUSIONS: Radiologists rapidly adopted recommended reporting terminology for patients with suspected COVID-19. The majority of patients for whom radiologists raised concern for COVID-19 were subsequently diagnosed with the disease, including the majority of clinically unsuspected patients. Using unambiguous terminology and timely notification about previously unsuspected patients will become increasingly critical to facilitate COVID-19 testing and contact tracing as states begin to lift restrictions.

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.

Cancer Risk in Subsolid Nodules in the National Lung Screening Trial.

Background Subsolid pulmonary nodules, comprising pure ground-glass nodules (GGNs) and part-solid nodules (PSNs), have a high risk of indolent malignancy. Lung Imaging Reporting and Data System (Lung-RADS) nodule management guidelines are based on expert opinion and lack independent validation. Purpose To evaluate Lung-RADS estimates of the malignancy rates of subsolid nodules, using nodules from the National Lung Screening Trial (NLST), and to compare Lung-RADS to the NELSON trial classification as well as the Brock University calculator. Materials and Methods Subsets of GGNs and PSNs were selected from the NLST for this retrospective study. A thoracic radiologist reviewed the baseline and follow-up CT images, confirmed that they were true subsolid nodules, and measured the nodules. The primary outcome for each nodule was the development of malignancy within the follow-up period (median, 6.5 years). Nodules were stratified according to Lung-RADS, NELSON trial criteria, and the Brock model. For analyses, nodule subsets were weighted on the basis of frequency in the NLST data set. Nodule stratification models were tested by using receiver operating characteristic curves. Results A total of 622 nodules were evaluated, of which 434 nodules were subsolid. At baseline, 304 nodules were classified as Lung-RADS category 2, with a malignancy rate of 3%, which is greater than the 1% in Lung-RADS (P = .004). The malignancy rate for GGNs smaller than 10 mm (two of 129, 1.3%) was smaller than that for GGNs measuring 10-19 mm (11 of 153, 6%) (P = .01). The malignancy rate for Lung-RADS category 3 was 14% (13 of 67), which is greater than the reported 2% in Lung-RADS (P < .001). The Brock model predicted malignancy better than Lung-RADS and the NELSON trial scheme (area under the receiver operating characteristic curve = 0.78, 0.70, and 0.67, respectively; P = .02 for Brock model vs NELSON trial scheme). Conclusion Subsolid nodules classified as Lung Imaging Reporting and Data System (Lung-RADS) categories 2 and 3 have a higher risk of malignancy than reported. The Brock risk calculator performed better than measurement-based classification schemes such as Lung-RADS. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Kauczor and von Stackelberg in this issue.

Predictive Features for Anterior Mediastinal Mass Diagnoses.

OBJECTIVE: We set out to evaluate a set of demographic and computed tomography imaging features for diagnosing anterior mediastinal masses. METHODS: We identified 223 patients with anterior mediastinal masses, which we divided into training and validation sets. One radiologist evaluated computed tomography imaging features on the training set. Then, predictive features were identified, and 3 radiologists evaluated these on the validation set. A naive Bayesian classifier based on the features was compared with the radiologists' first-choice diagnosis. RESULTS: Internal mammary lymphadenopathy and mediastinal encasement were strongly associated with lymphomas. Low attenuation and midline location were strongly associated with benign lesions, and older age was associated with thymic epithelial neoplasms. The average accuracy of the 3 radiologists' diagnoses was 78%, compared with 71% for the classifier. CONCLUSIONS: Nine demographic and imaging features were found to be helpful in diagnosing anterior mediastinal masses. By using these features, radiologists can suggest the diagnosis with fair accuracy.

Utility and reproducibility of 3-dimensional printed models in pre-operative planning of complex thoracic tumors.

BACKGROUND AND OBJECTIVES: 3D-printed models are increasingly used for surgical planning. We assessed the utility, accuracy, and reproducibility of 3D printing to assist visualization of complex thoracic tumors for surgical planning. METHODS: Models were created from pre-operative images for three patients using a standard radiology 3D workstation. Operating surgeons assessed model utility using the Gillespie scale (1 = inferior to 4 = superior), and accuracy compared to intraoperative findings. Model variability was assessed for one patient for whom two models were created independently. The models were compared subjectively by surgeons and quantitatively based on overlap of depicted tissues, and differences in tumor volume and proximity to tissues. RESULTS: Models were superior to imaging and 3D visualization for surgical planning (mean score = 3.4), particularly for determining surgical approach (score = 4) and resectability (score = 3.7). Model accuracy was good to excellent. In the two models created for one patient, tissue volumes overlapped by >86.5%, and tumor volume and area of tissues ≤1 mm to the tumor differed by <15% and <1.8 cm2 , respectively. Surgeons considered these differences to have negligible effect on surgical planning. CONCLUSION: 3D printing assists surgical planning for complex thoracic tumors. Models can be created by radiologists using routine practice tools with sufficient accuracy and clinically negligible variability.