Fleischner Society: Glossary of Terms for Thoracic Imaging.

Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition. This latest glossary is focused on terms of clinical importance and on those whose meaning may be perceived as vague or ambiguous. As with previous versions, the aim of the present glossary is to establish standardization of terminology for thoracic radiology and, thereby, to facilitate communications between radiologists and clinicians. Moreover, the present glossary aims to contribute to a more stringent use of terminology, increasingly required for structured reporting and accurate searches in large databases. Compared with the previous version, the number of images (chest radiography and CT) in the current version has substantially increased. The authors hope that this will enhance its educational and practical value. All definitions and images are hyperlinked throughout the text. Click on each figure callout to view corresponding image. © RSNA, 2024 Supplemental material is available for this article. See also the editorials by Bhalla and Powell in this issue.

Recommendations for Measuring Pulmonary Nodules at CT: A Statement from the Fleischner Society.

These recommendations for measuring pulmonary nodules at computed tomography (CT) are a statement from the Fleischner Society and, as such, incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists. The recommendations address nodule size measurements at CT, which is a topic of importance, given that all available guidelines for nodule management are essentially based on nodule size or changes thereof. The recommendations are organized according to practical questions that commonly arise when nodules are measured in routine clinical practice and are, together with their answers, summarized in a table. The recommendations include technical requirements for accurate nodule measurement, directions on how to accurately measure the size of nodules at the workstation, and directions on how to report nodule size and changes in size. The recommendations are designed to provide practical advice based on the available evidence from the literature; however, areas of uncertainty are also discussed, and topics needing future research are highlighted. © RSNA, 2017 Online supplemental material is available for this article.

Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017.

The Fleischner Society Guidelines for management of solid nodules were published in 2005, and separate guidelines for subsolid nodules were issued in 2013. Since then, new information has become available; therefore, the guidelines have been revised to reflect current thinking on nodule management. The revised guidelines incorporate several substantive changes that reflect current thinking on the management of small nodules. The minimum threshold size for routine follow-up has been increased, and recommended follow-up intervals are now given as a range rather than as a precise time period to give radiologists, clinicians, and patients greater discretion to accommodate individual risk factors and preferences. The guidelines for solid and subsolid nodules have been combined in one simplified table, and specific recommendations have been included for multiple nodules. These guidelines represent the consensus of the Fleischner Society, and as such, they incorporate the opinions of a multidisciplinary international group of thoracic radiologists, pulmonologists, surgeons, pathologists, and other specialists. Changes from the previous guidelines issued by the Fleischner Society are based on new data and accumulated experience. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on March 13, 2017.

Lung Adenocarcinoma: Correlation of Quantitative CT Findings with Pathologic Findings.

Purpose To identify the ability of computer-derived three-dimensional (3D) computed tomographic (CT) segmentation techniques to help differentiate lung adenocarcinoma subtypes. Materials and Methods This study had institutional research board approval and was HIPAA compliant. Pathologically classified resected lung adenocarcinomas (n = 41) with thin-section CT data were identified. Two readers independently placed over-inclusive volumes around nodules from which automated computer measurements were generated: mass (total mass) and volume (total volume) of the nodule and of any solid portion, in addition to the solid percentage of the nodule volume (percentage solid volume) or mass (percentage solid mass). Interobserver agreement and differences in measurements among pathologic entities were evaluated by using t tests. A multinomial logistic regression model was used to differentiate the probability of three diagnoses: invasive non-lepidic-predominant adenocarcinoma (INV), lepidic-predominant adenocarcinoma (LPA), and adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA). Results Mean percentage solid volume of INV was 35.4% (95% confidence interval [CI]: 26.2%, 44.5%)-higher than the 14.5% (95% CI: 10.3%, 18.7%) for LPA (P = .002). Mean percentage solid volume of AIS/MIA was 8.2% (95% CI: 2.7%, 13.7%) and had a trend toward being lower than that for LPA (P = .051). Accuracy of the model based on total volume and percentage solid volume was 73.2%; accuracy of the model based on total mass and percentage solid mass was 75.6%. Conclusion Computer-assisted 3D measurement of nodules at CT had good reproducibility and helped differentiate among subtypes of lung adenocarcinoma. (©) RSNA, 2016.

Observer Variability for Classification of Pulmonary Nodules on Low-Dose CT Images and Its Effect on Nodule Management.

PURPOSE: To examine the factors that affect inter- and intraobserver agreement for pulmonary nodule type classification on low-radiation-dose computed tomographic (CT) images, and their potential effect on patient management. MATERIALS AND METHODS: Nodules (n = 160) were randomly selected from the Dutch-Belgian Lung Cancer Screening Trial cohort, with equal numbers of nodule types and similar sizes. Nodules were scored by eight radiologists by using morphologic categories proposed by the Fleischner Society guidelines for management of pulmonary nodules as solid, part solid with a solid component smaller than 5 mm, part solid with a solid component 5 mm or larger, or pure ground glass. Inter- and intraobserver agreement was analyzed by using Cohen κ statistics. Multivariate analysis of variance was performed to assess the effect of nodule characteristics and image quality on observer disagreement. Effect on nodule management was estimated by differentiating CT follow-up for ground-glass nodules, solid nodules 8 mm or smaller, and part-solid nodules smaller than 5 mm from immediate diagnostic work-up for solid nodules larger than 8 mm and part-solid nodules 5 mm or greater. RESULTS: Pair-wise inter- and intraobserver agreement was moderate (mean κ, 0.51 [95% confidence interval, 0.30, 0.68] and 0.57 [95% confidence interval, 0.47, 0.71]). Categorization as part-solid nodules and location in the upper lobe significantly reduced observer agreement (P = .012 and P < .001, respectively). By considering all possible reading pairs (28 possible combinations of observer pairs × 160 nodules = 4480 possible agreements or disagreements), a discordant nodule classification was found in 36.4% (1630 of 4480), related to presence or size of a solid component in 88.7% (1446 of 1630). Two-thirds of these discrepant readings (1061 of 1630) would have potentially resulted in different nodule management. CONCLUSION: There is moderate inter- and intraobserver agreement for nodule classification by using current recommendations for low-radiation-dose CT examinations of the chest. Discrepancies in nodule categorization were mainly caused by disagreement on the size and presence of a solid component, which may lead to different management in the majority of cases with such discrepancies. (©) RSNA, 2015.

Multidetector CT evaluation of airway stents: what the radiologist should know.

Airway stents are increasingly used to treat symptomatic patients with obstructive tracheobronchial diseases who are not amenable to surgical resection or who have poor performance status, precluding them from resection. The most common conditions that are treated with tracheobronchial stents are primary lung cancer and metastatic disease. However, stents have also been used to treat patients with airway stenosis related to a variety of benign conditions, such as tracheobronchomalacia, relapsing polychondritis, postintubation tracheal stenosis, postoperative anastomotic stenosis, and granulomatous diseases. Additionally, airway stents can be used as a barrier method in the management of esophagorespiratory fistulas. Many types of stents are available from different manufacturers. Principally, they are classified as silicone; covered and uncovered metal; or hybrid, which are made of silicone and reinforced by metal rings. The advantages and disadvantages of each type of airway stent are carefully considered when choosing the most appropriate stent for each patient. Multidetector computed tomography plays an important role in determining the cause and assessing the location and extent of airway obstruction. Moreover, it is very accurate in its depiction of complications after airway stent placement.

Fibrosing interstitial lung disease. A practical high-resolution computed tomography-based approach to diagnosis and management and a review of the literature.

Establishing the etiology of fibrosing interstitial lung disease (FILD) remains a clinical challenge. This is because many disorders resulting in lung fibrosis may be similar in their initial clinical and radiographic appearances. High-resolution computed tomography (HRCT) studies are now almost always obtained for patients who present with otherwise nonspecific clinical symptoms and chest radiographic findings. In the majority of cases presenting with FILD, differential diagnosis typically requires differentiating among three most commonly encountered clinical entities: idiopathic pulmonary fibrosis with usual interstitial pneumonia, nonspecific interstitial pneumonia, and chronic hypersensitivity pneumonitis. As a consequence, the development of a simplified diagnostic algorithmic approach initially focusing on the interpretation of HRCT findings may prove of considerable value provided thorough familiarity with optimal HRCT techniques and methods of interpretation. For this purpose, in patients with FILD in whom an underlying etiology is not initially apparent, the recently proposed American Thoracic Society/European Respiratory Society/Japanese Respiratory Society/Latin American Thoracic Association guidelines for the diagnosis of IPF have been modified to create a straightforward, clinically practicable algorithmic approach to clinical management based on the initial interpretation and classification of HRCT findings.

Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification.

TOPIC IMPORTANCE: Chest CT imaging holds a major role in the diagnosis of lung diseases, many of which affect the peribronchovascular region. Identification and categorization of peribronchovascular abnormalities on CT imaging can assist in formulating a differential diagnosis and directing further diagnostic evaluation. REVIEW FINDINGS: The peribronchovascular region of the lung encompasses the pulmonary arteries, airways, and lung interstitium. Understanding disease processes associated with structures of the peribronchovascular region and their appearances on CT imaging aids in prompt diagnosis. This article reviews current knowledge in anatomic and pathologic features of the lung interstitium composed of intercommunicating prelymphatic spaces, lymphatics, collagen bundles, lymph nodes, and bronchial arteries; diffuse lung diseases that present in a peribronchovascular distribution; and an approach to classifying diseases according to patterns of imaging presentations. Lung peribronchovascular diseases can appear on CT imaging as diffuse thickening, fibrosis, masses or masslike consolidation, ground-glass or air space consolidation, and cysts, acknowledging that some diseases may have multiple presentations. SUMMARY: A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.

Assistive AI in Lung Cancer Screening: A Retrospective Multinational Study in the United States and Japan.

Purpose To evaluate the impact of an artificial intelligence (AI) assistant for lung cancer screening on multinational clinical workflows. Materials and Methods An AI assistant for lung cancer screening was evaluated on two retrospective randomized multireader multicase studies where 627 (141 cancer-positive cases) low-dose chest CT cases were each read twice (with and without AI assistance) by experienced thoracic radiologists (six U.S.-based or six Japan-based radiologists), resulting in a total of 7524 interpretations. Positive cases were defined as those within 2 years before a pathology-confirmed lung cancer diagnosis. Negative cases were defined as those without any subsequent cancer diagnosis for at least 2 years and were enriched for a spectrum of diverse nodules. The studies measured the readers' level of suspicion (on a 0-100 scale), country-specific screening system scoring categories, and management recommendations. Evaluation metrics included the area under the receiver operating characteristic curve (AUC) for level of suspicion and sensitivity and specificity of recall recommendations. Results With AI assistance, the radiologists' AUC increased by 0.023 (0.70 to 0.72; P = .02) for the U.S. study and by 0.023 (0.93 to 0.96; P = .18) for the Japan study. Scoring system specificity for actionable findings increased 5.5% (57% to 63%; P < .001) for the U.S. study and 6.7% (23% to 30%; P < .001) for the Japan study. There was no evidence of a difference in corresponding sensitivity between unassisted and AI-assisted reads for the U.S. (67.3% to 67.5%; P = .88) and Japan (98% to 100%; P > .99) studies. Corresponding stand-alone AI AUC system performance was 0.75 (95% CI: 0.70, 0.81) and 0.88 (95% CI: 0.78, 0.97) for the U.S.- and Japan-based datasets, respectively. Conclusion The concurrent AI interface improved lung cancer screening specificity in both U.S.- and Japan-based reader studies, meriting further study in additional international screening environments. Keywords: Assistive Artificial Intelligence, Lung Cancer Screening, CT Supplemental material is available for this article. Published under a CC BY 4.0 license.

Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society.

This report is to complement the original Fleischner Society recommendations for incidentally detected solid nodules by proposing a set of recommendations specifically aimed at subsolid nodules. The development of a standardized approach to the interpretation and management of subsolid nodules remains critically important given that peripheral adenocarcinomas represent the most common type of lung cancer, with evidence of increasing frequency. Following an initial consideration of appropriate terminology to describe subsolid nodules and a brief review of the new classification system for peripheral lung adenocarcinomas sponsored by the International Association for the Study of Lung Cancer (IASLC), American Thoracic Society (ATS), and European Respiratory Society (ERS), six specific recommendations were made, three with regard to solitary subsolid nodules and three with regard to multiple subsolid nodules. Each recommendation is followed first by the rationales underlying the recommendation and then by specific pertinent remarks. Finally, issues for which future research is needed are discussed. The recommendations are the result of careful review of the literature now available regarding subsolid nodules. Given the complexity of these lesions, the current recommendations are more varied than the original Fleischner Society guidelines for solid nodules. It cannot be overemphasized that these guidelines must be interpreted in light of an individual's clinical history. Given the frequency with which subsolid nodules are encountered in daily clinical practice, and notwithstanding continuing controversy on many of these issues, it is anticipated that further refinements and modifications to these recommendations will be forthcoming as information continues to emerge from ongoing research.

Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.

OBJECTIVE: The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT. MATERIALS AND METHODS: For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)). After 4 months, the same cases were reviewed on thick sections (reader(thick)) and subsequently with CAD marks (reader(thick) + CAD(thick)). Sensitivities were evaluated. Additionally, reader(thick) sensitivity with assessment of CAD marks on thin sections was estimated (reader(thick) + CAD(thin)). RESULTS: For 155 nodules (mean, 5.5 mm; range, 4.0-27.5 mm)-74 solid nodules, 22 part-solid (part-solid nodules), and 59 GGO nodules-CAD stand-alone sensitivity was 80%, 95%, and 71%, respectively, with three false-positives on average (0-12) per CT study. Reader(thin) + CAD(thin) sensitivities were higher than reader(thin) for solid nodules (82% vs 57%, p < 0.001), part-solid nodules (97% vs 81%, p = 0.0027), and GGO nodules (82% vs 69%, p < 0.001) for all readers (p < 0.001). Respective sensitivities for reader(thick), reader(thick) + CAD(thick), reader(thick) + CAD(thin) were 40%, 58% (p < 0.001), and 77% (p < 0.001) for solid nodules; 72%, 73% (p = 0.322), and 94% (p < 0.001) for part-solid nodules; and 53%, 58% (p = 0.008), and 79% (p < 0.001) for GGO nodules. For reader(thin), false-positives increased from 0.64 per case to 0.90 with CAD(thin) (p < 0.001) but not for reader(thick); false-positive rates were 1.17, 1.19, and 1.26 per case for reader(thick), reader(thick) + CAD(thick), and reader(thick) + CAD(thin), respectively. CONCLUSION: Detection of GGO nodules and solid nodules is significantly improved with CAD. When interpretation is performed on thick sections, the benefit is greater when CAD marks are reviewed on thin rather than thick sections.

The self-overlap method for assessment of lung nodule morphology in chest CT.

Surface morphology is an important indicator of malignant potential for solid-type lung nodules detected at CT, but is difficult to assess subjectively. Automated methods for morphology assessment have previously been described using a common measure of nodule shape, representative of the broad class of existing methods, termed area-to-perimeter-length ratio (APR). APR is static and thus highly susceptible to alterations by random noise and artifacts in image acquisition. We introduce and analyze the self-overlap (SO) method as a dynamic automated morphology detection scheme. SO measures the degree of change of nodule masks upon Gaussian blurring. We hypothesized that this new metric would afford equally high accuracy and superior precision than APR. Application of the two methods to a set of 119 patient lung nodules and a set of simulation nodules showed our approach to be slightly more accurate and on the order of ten times as precise, respectively. The dynamic quality of this new automated metric renders it less sensitive to image noise and artifacts than APR, and as such, SO is a potentially useful measure of cancer risk for solid-type lung nodules detected on CT.

Lung Imaging in COPD Part 1: Clinical Usefulness.

COPD is a condition characterized by chronic airflow obstruction resulting from chronic bronchitis, emphysema, or both. The clinical picture is usually progressive with respiratory symptoms such as exertional dyspnea and chronic cough. For many years, spirometry was used to establish a diagnosis of COPD. Recent advancements in imaging techniques allow quantitative and qualitative analysis of the lung parenchyma as well as related airways and vascular and extrapulmonary manifestations of COPD. These imaging methods may allow prognostication of disease and shed light on the efficacy of pharmacologic and nonpharmacologic interventions. This is the first of a two-part series of articles on the usefulness of imaging methods in COPD, and it highlights useful information that clinicians can obtain from these imaging studies to make more accurate diagnosis and therapeutic decisions.

Lung Imaging in COPD Part 2: Emerging Concepts.

The diagnosis, prognostication, and differentiation of phenotypes of COPD can be facilitated by CT scan imaging of the chest. CT scan imaging of the chest is a prerequisite for lung volume reduction surgery and lung transplantation. Quantitative analysis can be used to evaluate extent of disease progression. Evolving imaging techniques include micro-CT scan, ultra-high-resolution and photon-counting CT scan imaging, and MRI. Potential advantages of these newer techniques include improved resolution, prediction of reversibility, and obviation of radiation exposure. This article discusses important emerging techniques in imaging patients with COPD. The clinical usefulness of these emerging techniques as they stand today are tabulated for the benefit of the practicing pulmonologist.

Pulmonary Nodules: growth rate assessment in patients by using serial CT and three-dimensional volumetry.

PURPOSE: To determine the precision of a three-dimensional (3D) method for measuring the growth rate of solid and subsolid nodules and its ability to detect abnormal growth rates. MATERIALS AND METHODS: This study was approved by the Institutional Research Board and was HIPAA compliant. Informed consent was waived. The growth rates of 123 lung nodules in 59 patients who had undergone lung cancer screening computed tomography (CT) were measured by using a 3D semiautomated computer-assisted volume method. Clinical stability was established with long-term CT follow-up (mean, 6.4 years±1.9 [standard deviation]; range, 2.0-8.5 years). A mean of 4.1 CT examinations per patient±1.2 (range, two to seven CT examinations per patient) was analyzed during 2.4 years±0.5 after baseline CT. Nodule morphology, attenuation, and location were characterized. The analysis of standard deviation of growth rate in relation to time between scans yielded a normative model for detecting abnormal growth. RESULTS: Growth rate precision increased with greater time between scans. Overall estimate for standard deviation of growth rate, on the basis of 939 growth rate determinations in clinically stable nodules, was 36.5% per year. Peripheral location (P=.01; 37.1% per year vs 25.6% per year) and adjacency to pleural surface (P=.05; 38.9% per year vs 34.0% per year) significantly increased standard deviation of growth rate. All eight malignant nodules had an abnormally high growth rate detected. By using 3D volumetry, growth rate-based diagnosis of malignancy was made at a mean of 183 days±158, compared with radiologic or clinical diagnosis at 344 days±284. CONCLUSION: A normative model derived from the variability of growth rates of nodules that were stable for an average of 6.4 years may enable identification of lung cancer.

Subsolid pulmonary nodules: imaging evaluation and strategic management.

PURPOSE OF REVIEW: Given the higher rate of malignancy of subsolid pulmonary nodules and the considerably lower growth rate of ground-glass nodules (GGNs), dedicated standardized guidelines for management of these nodules have been proposed, including long-term low-dose computed tomography (CT) follow-up (≥3 years). Physicians must be familiar with the strategic management of subsolid pulmonary nodules, and should be able to identify imaging features that suggest invasive adenocarcinoma requiring a more aggressive management. RECENT FINDINGS: Low-dose CT screening studies for early detection of lung cancer have increased our knowledge of pulmonary nodules, and in particular our understanding of the strong although imperfect correlation of the subsolid pulmonary nodules, including pure GGNs and part-solid nodules, with the spectrum of preinvasive to invasive lung adenocarcinoma. Serial CT imaging has shown stepwise progression in a subset of these nodules, characterized by increase in size and density of pure GGNs and development of a solid component, the latter usually indicating invasive adenocarcinoma. SUMMARY: There is close correlation between the CT features of subsolid nodules (SSNs) and the spectrum of lung adenocarcinoma. Standardized guidelines are suggested for management of SSNs.

Clinical significance of lung nodules reported on abdominal CT.

OBJECTIVE: The objective of our study was to identify the significance of lung nodules reported on abdominal CT. MATERIALS AND METHODS: Abdominal CT reports from a 1-year period were reviewed for the terms "nodule," "nodular," or "mass" in reference to the lung bases. Patients with prior chest or abdominal CT examinations were excluded; the study population included patients with an initial abdominal CT study and at least one follow-up chest or abdominal CT examination. Two thoracic radiologists characterized nodules in consensus. Radiology and clinical records were reviewed for nodule growth and clinical diagnoses. RESULTS: The term "nodule," "nodular," or "mass" in reference to the lung bases was reported in 364 of 12,287 abdominal CT studies (3%). Of 125 patients with no prior CT examination, 42 had undergone follow-up chest CT, abdominal CT, or both. Common imaging indications included abdominal pain (13/42, 31%) and preexisting malignancy (n = 7, 16.7%). Regardless of the indication for imaging, 16 (38.1%) had malignancy that was known (n = 13) or newly diagnosed (n = 3) on the initial abdominal CT. Three of 42 patients (7.1%) had malignant nodules representing metastatic disease: Nodule growth was seen in one patient with preexisting colon cancer, one patient with newly diagnosed metastatic pancreatic cancer, and a third with known bladder cancer. The latter patient had suspected lung metastases that were confirmed on chest CT 1 day later. Three of the 16 patients (18.8%) with preexisting or newly diagnosed cancer had malignant nodules. No malignant nodules were identified without such history. Six patients (14.3%) had an infection. CONCLUSION: Lung nodules incidentally detected on abdominal CT were rarely malignant and were seen only in the setting of an underlying abdominal malignancy. Knowledge of such history is of critical importance to both the clinician and the radiologist. Dedicated chest CT is most useful when assessing pulmonary nodules in patients with localized malignancy.

Chest radiography in the ICU: Part 1, Evaluation of airway, enteric, and pleural tubes.

OBJECTIVE: In this pictorial essay, we discuss and illustrate normal and aberrant positioning of nonvascular support and monitoring devices frequently used in critically ill patients, including endotracheal and tracheostomy tubes, chest tubes, and nasogastric and nasoenteric tubes, as well as their inherent complications. CONCLUSION: The radiographic evaluation of the support and monitoring devices used in patients in the ICU is important because the potentially serious complications arising from their introduction and use are often not clinically apparent. Familiarity with normal and abnormal radiographic findings is critical for the detection of these complications.