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.

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.

Current Imaging of Idiopathic Pulmonary Fibrosis.

The major role of imaging (CT) in usual interstitial pneumonia (UIP)/idiopathic pulmonary fibrosis (IPF) is in the initial diagnosis. We propose several modifications to existing guidelines to help improve the accuracy of this diagnosis and to enhance interobserver agreement. CT detects the common complications and associations that occur with UIP/IPF including acute exacerbation, lung cancer, and dendriform pulmonary ossification and is useful in informing prognosis based on baseline fibrosis severity. Serial CT imaging is a topic of great interest; it may identify disease progression before FVC decline or clinical change.

Algorithmic Approach to the Diagnosis of Organizing Pneumonia: A Correlation of Clinical, Radiologic, and Pathologic Features.

Organizing pneumonia (OP), characterized histopathologically by patchy filling of alveoli and bronchioles by loose plugs of connective tissue, may be seen in a variety of conditions. These include but are not limited to after an infection, drug reactions, radiation therapy, and collagen vascular diseases. When a specific cause is responsible for this entity, it is referred to as "secondary OP." When an extensive search fails to reveal a cause, it is referred to as "cryptogenic OP" (previously called "bronchiolitis obliterans with OP"), which is a clinical, radiologic, and pathologic entity classified as an interstitial lung disease. The clinical presentation of OP often mimics that of other disorders, such as infection and cancer, which can result in a delay in diagnosis and inappropriate management of the underlying disease. The radiographic presentation of OP is polymorphous but often has subpleural consolidations with air bronchograms or solitary or multiple nodules, which can wax and wane. Diagnosis of OP sometimes requires histopathologic confirmation and exclusion of other possible causes. Treatment usually requires a prolonged steroid course, and disease relapse is common. The aim of this article is to summarize the clinical, radiographic, and histologic presentations of this disease and to provide a practical diagnostic algorithmic approach incorporating clinical history and characteristic imaging patterns.

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.

The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19: A Review of Literature.

The COVID-19 pandemic has had devastating medical and economic consequences globally. The severity of COVID-19 is related, in a large measure, to the extent of pulmonary involvement. The role of chest CT imaging in the management of patients with COVID-19 has evolved since the onset of the pandemic. Specifically, the description of CT scan findings, use of chest CT imaging in various acute and subacute settings, and its usefulness in predicting chronic disease have been defined better. We performed a review of published data on CT scans in patients with COVID-19. A summary of the range of imaging findings, from typical to less common abnormalities, is provided. Familiarity with these findings may facilitate the diagnosis and management of this disease. A comparison of sensitivity and specificity of chest CT imaging with reverse-transcriptase polymerase chain reaction testing highlights the potential role of CT imaging in difficult-to-diagnose cases of COVID-19. The usefulness of CT imaging to assess prognosis, to guide management, and to identify acute pulmonary complications associated with SARS-CoV-2 infection is highlighted. Beyond the acute stage, it is important for clinicians to recognize pulmonary parenchymal abnormalities, progressive fibrotic lung disease, and vascular changes that may be responsible for persistent respiratory symptoms. A large collection of multi-institutional images were included to elucidate the CT scan findings described.

Shades of Gray: Subsolid Nodule Considerations and Management.

Subsolid nodules are common on chest CT imaging and may be either benign or malignant. Their varied features and broad differential diagnoses present management challenges. Although subsolid nodules often represent lung adenocarcinomas, other possibilities are common and influence management. Practice guidelines exist for subsolid nodule management for both incidentally and screening-detected nodules, incorporating patient and nodule characteristics. This review highlights the similarities and differences among these algorithms, with the intent of providing a resource for comparison and aid in choosing management options.

CT features of electronic-cigarette or vaping-associated lung injury (EVALI); our experience during the recent outbreak.

As an emerging clinical syndrome, our knowledge of the clinical, pathologic and radiologic features of electronic-cigarette or vaping-associated lung injury is evolving. CT appearances are described in six cases imaged at our institution (NYU Langone Health, New York) in the cluster of 2019.

Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic: CHEST Expert Panel Report.

BACKGROUND: The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. METHODS: An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. RESULTS: Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non-small-cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non-small-cell lung cancer. CONCLUSIONS: There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.

Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic: CHEST Expert Panel Report.

BACKGROUND: The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. METHODS: An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. RESULTS: Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non-small cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non-small cell lung cancer. CONCLUSIONS: There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.

Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic: CHEST Expert Panel Report.

Background: The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. Materials and Methods: An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. Results: Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non-small cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non-small cell lung cancer. Conclusion: There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.© 2020 RSNA; The American College of Chest Physicians, published by Elsevier Inc; and The American College of Radiology, published by Elsevier Inc.

Lung Hyperlucency: A Clinical-Radiologic Algorithmic Approach to Diagnosis.

Areas of diminished lung density are frequently identified both on routine chest radiographs and chest CT examinations. Colloquially referred to as hyperlucent foci of lung, a broad range of underlying pathophysiologic mechanisms and differential diagnoses account for these changes. Despite this, the spectrum of etiologies can be categorized into underlying parenchymal, airway, and vascular-related entities. The purpose of this review is to provide a practical diagnostic algorithmic approach to pulmonary hyperlucencies incorporating clinical history and characteristic imaging patterns to narrow the differential.

An Algorithmic Approach to the Interpretation of Diffuse Lung Disease on Chest CT Imaging: A Theory of Almost Everything.

We propose an algorithmic approach to the interpretation of diffuse lung disease on high-resolution CT. Following an initial review of pertinent lung anatomy, the following steps are included. Step 1: a preliminary review of available chest radiographs, including the "scanogram" obtained at the time of the CT examination. Step 2: a review of optimal methods of data acquisition and reconstruction, emphasizing the need for contiguous high-resolution images throughout the entire thorax. Step 3: initial uninterrupted scrolling of contiguous high-resolution images throughout the chest to establish the quality of examination as well as an overview of the presence and extent of disease. Step 4: determination of one of three predominant categories - primarily reticular disease, nodular disease, or diseases associated with diffuse alteration in lung density. Based on this determination, one of the three following Steps are followed: Step 5: evaluation of cases primarily involving diffuse lung reticulation; Step 6: evaluation of cases primarily resulting in diffuse lung nodules; and Step 7: evaluation of cases with diffuse alterations in lung density including those with diffusely diminished lung density vs those with heterogenous or diffusely increased lung density, respectively. It is anticipated that this algorithmic approach will substantially enhance initial interpretations of a wide range of pulmonary disease.

Author Correction: End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Approach to Peribronchovascular Disease on CT.

Diseases that are predominantly peribronchovascular in distribution on computed tomography by definition involve the bronchi, adjacent vasculature, and associated lymphatics involving the central or axial lung interstitium. An understanding of diseases that can present with focal peribronchovascular findings is useful for establishing diagnoses and guiding patient management. This review will cover clinical and imaging features that may assist in differentiating amongst the various causes of primarily peribronchovascular disease.

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States1. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20-43% and is now included in US screening guidelines1-6. Existing challenges include inter-grader variability and high false-positive and false-negative rates7-10. We propose a deep learning algorithm that uses a patient's current and prior computed tomography volumes to predict the risk of lung cancer. Our model achieves a state-of-the-art performance (94.4% area under the curve) on 6,716 National Lung Cancer Screening Trial cases, and performs similarly on an independent clinical validation set of 1,139 cases. We conducted two reader studies. When prior computed tomography imaging was not available, our model outperformed all six radiologists with absolute reductions of 11% in false positives and 5% in false negatives. Where prior computed tomography imaging was available, the model performance was on-par with the same radiologists. This creates an opportunity to optimize the screening process via computer assistance and automation. While the vast majority of patients remain unscreened, we show the potential for deep learning models to increase the accuracy, consistency and adoption of lung cancer screening worldwide.