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.

Computed tomography-based machine learning for donor lung screening before transplantation.

BACKGROUND: Assessment and selection of donor lungs remain largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo computed tomography (CT) images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs before transplantation. METHODS: Clinical measures and ex situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner before transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning, which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures. RESULTS: Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) before CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the intensive care unit and were at 19 times higher risk of developing chronic lung allograft dysfunction within 2 years posttransplant. CONCLUSIONS: We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of posttransplant complications.

CT-based Machine Learning for Donor Lung Screening Prior to Transplantation.

Background: Assessment and selection of donor lungs remains largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo CT images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs prior to transplantation. Methods: Clinical measures and ex-situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner prior to transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning , which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures. Results: Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) prior to CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the ICU and were at 19 times higher risk of developing CLAD within 2 years post-transplant. Conclusions: We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of post-transplant complications.

Radiologic and Histologic Correlates of Early Interstitial Lung Changes in Explanted Lungs.

Background Interstitial lung abnormalities (ILAs) reflect imaging features on lung CT scans that are compatible with (early) interstitial lung disease. Despite accumulating evidence regarding the incidence, risk factors, and prognosis of ILAs, the histopathologic correlates of ILAs remain elusive. Purpose To determine the correlation between radiologic and histopathologic findings in CT-defined ILAs in human lung explants. Materials and Methods Explanted lungs or lobes from participants with radiologically documented ILAs were prospectively collected from 2010 to 2021. These specimens were air-inflated, frozen, and scanned with CT and micro-CT (spatial resolution of 0.7 mm and 90 µm, respectively). Subsequently, the lungs were cut and sampled with core biopsies. At least five samples per lung underwent micro-CT and subsequent histopathologic assessment with semiquantitative remodeling scorings. Based on area-specific radiologic scoring, the association between radiologic and histopathologic findings was assessed. Results Eight lung explants from six donors (median age at explantation, 71 years [range, 60-83 years]; four men) were included (unused donor lungs, n = 4; pre-emptive lobectomy for oncologic indications, n = 2). Ex vivo CT demonstrated ground-glass opacification, reticulation, and bronchiectasis. Micro-CT and histopathologic examination demonstrated that lung abnormalities were frequently paraseptal and associated with fibrosis and lymphocytic inflammation. The histopathologic results showed varying degrees of fibrosis in areas that appeared normal on CT scans. Regions of reticulation on CT scans generally had greater fibrosis at histopathologic analysis. Vasculopathy and bronchiectasis were also often present at histopathologic examination of lungs with ILAs. Fully developed fibroblastic foci were rarely observed. Conclusion This study demonstrated direct histologic correlates of CT-defined interstitial lung abnormalities. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Jeudy in this issue.

European Respiratory Society guidelines on transbronchial lung cryobiopsy in the diagnosis of interstitial lung diseases.

BACKGROUND: In patients with interstitial lung diseases (ILD), histopathological input is often required to obtain a diagnosis. Surgical lung biopsy (SLB) is considered the reference standard, but many patients are clinically unfit to undergo this invasive procedure, and adverse events, length of hospitalisation and costs are considerable. This European Respiratory Society (ERS) guideline provides evidence-based clinical practice recommendations for the role of transbronchial lung cryobiopsy (TBLC) in obtaining tissue-based diagnosis in patients with undiagnosed ILD. METHODS: The ERS Task Force consisted of clinical experts in the field of ILD and/or TBLC and methodological experts. Four PICO (Patient, Intervention, Comparator, Outcomes) questions and two narrative questions were formulated. Systematic literature searches were performed in MEDLINE and Embase (up to June 2021). GRADE (Grading, Recommendation, Assessment, Development and Evaluation) methodology was applied. RESULTS: In patients with undiagnosed ILD and an indication to obtain histopathological data: 1) TBLC is suggested as a replacement test in patients considered eligible to undergo SLB, 2) TBLC is suggested in patients not considered eligible to undergo SLB, 3) SLB is suggested as an add-on test in patients with a non-informative TBLC, 4) no recommendation is made for or against a second TBLC in patients with a non-informative TBLC and 5) TBLC operators should undergo training, but no recommendation is made for the type of training required. CONCLUSIONS: TBLC provides important diagnostic information in patients with undiagnosed ILD. Diagnostic yield is lower compared to SLB, at reduced serious adverse events and length of hospitalisation. Certainty of the evidence is mostly "very low".

Radiological findings in low-dose CT for COVID-19 pneumonia in 182 patients: Correlation of signs and severity with patient outcome.

ABSTRACT: To characterize computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia and their value in outcome prediction.Chest CTs of 182 patients with a confirmed diagnosis of COVID-19 infection by real-time reverse transcription polymerase chain reaction were evaluated for the presence of CT-abnormalities and their frequency. Regarding the patient outcome each patient was categorized in 5 progressive stages and the duration of hospitalization was determined. Regression analysis was performed to find which CT findings are predictive for patient outcome and to assess prognostic factors for the hospitalization duration.Multivariate statistical analysis confirmed a higher age (OR = 1.023, P  =  .025), a higher total visual severity score (OR = 1.038, P  =  .002) and the presence of crazy paving (OR = 2.160, P  =  .034) as predictive parameters for patient outcome. A higher total visual severity score (+0.134 days; P  =  .012) and the presence of pleural effusion (+13.985 days, P  =  0.005) were predictive parameters for a longer hospitalization duration. Moreover, a higher sensitivity of chest CT (false negatives 10.4%; true positives 78.6%) in comparison to real-time reverse transcription polymerase chain reaction was obtained.An increasing percentage of lung opacity as well as the presence of crazy paving and a higher age are associated with a worse patient outcome. The presence of a higher total visual severity score and pleural effusion are significant predictors for a longer hospitalization duration. These results are underscoring the value of chest CT as a diagnostic and prognostic tool in the pandemic outbreak of COVID-19, to facilitate fast detection and to preserve the limited (intensive) care capacity only for the most vulnerable patients.

Lung Microenvironments and Disease Progression in Fibrotic Hypersensitivity Pneumonitis.

Rationale: Fibrotic hypersensitivity pneumonitis (fHP) is an interstitial lung disease caused by sensitization to an inhaled allergen. Objectives: To identify the molecular determinants associated with progression of fibrosis. Methods: Nine fHP explant lungs and six unused donor lungs (as controls) were systematically sampled (4 samples/lung). According to microcomputed tomography measures, fHP cores were clustered into mild, moderate, and severe fibrosis groups. Gene expression profiles were assessed using weighted gene co-expression network analysis, xCell, gene ontology, and structure enrichment analysis. Gene expression of the prevailing molecular traits was also compared with idiopathic pulmonary fibrosis (IPF). The explant lung findings were evaluated in separate clinical fHP cohorts using tissue, BAL samples, and computed tomography scans. Measurements and Main Results: We found six molecular traits that associated with differential lung involvement. In fHP, extracellular matrix and antigen presentation/sensitization transcriptomic signatures characterized lung zones with only mild structural and histological changes, whereas signatures involved in honeycombing and B cells dominated the transcriptome in the most severely affected lung zones. With increasing disease severity, endothelial function was progressively lost, and progressive disruption in normal cellular homeostatic processes emerged. All six were also found in IPF, with largely similar associations with disease microenvironments. The molecular traits correlated with in vivo disease behavior in a separate clinical fHP cohort. Conclusions: We identified six molecular traits that characterize the morphological progression of fHP and associate with in vivo clinical behavior. Comparing IPF with fHP, the transcriptome landscape was determined considerably by local disease extent rather than by diagnosis alone.

Defining and predicting progression in non-IPF interstitial lung disease.

Randomized placebo-controlled trials demonstrated the efficacy of antifibrotic treatment in non-IPF progressive fibrosing ILD (fILD). Currently, there is no consensus on how progression should be defined and clinical data of non-IPF fILD patients in a real-world setting are scarce. Non-IPF fILD patients presenting at the University Hospitals Leuven between 2012 and 2016 were included. Different definitions of progression according to the selection criteria of the INBUILD, RELIEF and the uILD study were retrospectively evaluated at every hospital visit. Univariate and multivariate analyses were performed to identify predictors of progression and mortality. The study cohort comprised 120 patients; 68.3%, 54.2% and 65.8% had progressive disease based on the INBUILD, RELIEF and uILD study, respectively. A large overlap of progressive fILD patients according to the different clinical trials was observed. Median transplant-free survival time of progressive fILD patients was 3.9, 3.9, 3.8 years and the median time-to-progression after diagnosis was 2.0, 3.1 and 2.3 years according to the INBUILD, RELIEF and uILD study, respectively. We identified several predictors of mortality, but only an underlying diagnosis of HP and uILD was independently associated with progression. Our data show a high prevalence of progressive fibrosis among non-IPF fILD patients and a discrepancy between predictors of mortality and progression. Mortality rate in fILD is high and the identification of progressive disease is only made late during the disease course. Moreover, future treatment decisions will be based upon disease behavior. Therefore, more predictors of progressive disease are needed to guide treatment decisions in the future.

CT-Guided Transthoracic Biopsy of Lung Lesions Using a Non-Coaxial Biopsy Needle Technique: CT Characteristics Predictive for Diagnostic Accuracy and Pneumothorax.

OBJECTIVES: To analyze computed tomography (CT) characteristics predictive for diagnostic accuracy and pneumothorax in CT fluoroscopy-guided transthoracic biopsy (CTF-TTB) of lung lesions using non-coaxial biopsy needle technique. METHODS: Retrospectively 274 lung lesion biopsies with confirmed histology were included in our study. CTF-TTB was done using an 18-gauge non-coaxial cutting needle. Diagnostic accuracy rates were calculated per lesion size and CT and procedural characteristics were evaluated for their predictive value regarding diagnostic accuracy and development of pneumothorax (maximal nodule diameter, distance to pleura, location per lung segment, nodule composition, benign versus malignant histology, and number of specimens). RESULTS: Overall diagnostic accuracy of CTF-TTB was high (93%). Diagnostic accuracy for lesions ≤10 mm was 81%. Maximal nodule diameter was the only predictive CT characteristic for diagnostic success (p = 0.03). Pneumothorax occurred in 27%. Distance of lesion to pleura was the only risk factor for pneumothorax (p < 0.00001). Pneumothorax rates were significantly lower in subpleural lesions (14%) compared to those located 1-10 mm (47%), 10-20 mm (33%), and >20 mm from pleura (29%). CONCLUSIONS: High diagnostic accuracy rates were achieved with CTF-TTB using non-coaxial biopsy technique, even for lesions ≤10 mm. Pneumothorax rates were comparable with other studies. Lesion size was the only predictive CT characteristic for diagnostic accuracy. Distance to pleura was the only risk factor for pneumothorax.

The transition from normal lung anatomy to minimal and established fibrosis in idiopathic pulmonary fibrosis (IPF).

BACKGROUND: The transition from normal lung anatomy to minimal and established fibrosis is an important feature of the pathology of idiopathic pulmonary fibrosis (IPF). The purpose of this report is to examine the molecular and cellular mechanisms associated with this transition. METHODS: Pre-operative thoracic Multidetector Computed Tomography (MDCT) scans of patients with severe IPF (n = 9) were used to identify regions of minimal(n = 27) and established fibrosis(n = 27). MDCT, Micro-CT, quantitative histology, and next-generation sequencing were used to compare 24 samples from donor controls (n = 4) to minimal and established fibrosis samples. FINDINGS: The present results extended earlier reports about the transition from normal lung anatomy to minimal and established fibrosis by showing that there are activations of TGFBI, T cell co-stimulatory genes, and the down-regulation of inhibitory immune-checkpoint genes compared to controls. The expression patterns of these genes indicated activation of a field immune response, which is further supported by the increased infiltration of inflammatory immune cells dominated by lymphocytes that are capable of forming lymphoid follicles. Moreover, fibrosis pathways, mucin secretion, surfactant, TLRs, and cytokine storm-related genes also participate in the transitions from normal lung anatomy to minimal and established fibrosis. INTERPRETATION: The transition from normal lung anatomy to minimal and established fibrosis is associated with genes that are involved in the tissue repair processes, the activation of immune responses as well as the increased infiltration of CD4, CD8, B cell lymphocytes, and macrophages. These molecular and cellular events correlate with the development of structural abnormality of IPF and probably contribute to its pathogenesis.

Comparing Visual Scoring of Lung Injury with a Quantifying AI-Based Scoring in Patients with COVID-19.

OBJECTIVES: Fast diagnosis of Coronavirus Disease 2019 (COVID-19), and the detection of high-risk patients are crucial but challenging in the pandemic outbreak. The aim of this study was to evaluate if deep learning-based software correlates well with the generally accepted visual-based scoring for quantification of the lung injury to help radiologist in triage and monitoring of COVID-19 patients. MATERIALS AND METHODS: In this retrospective study, the lobar analysis of lung opacities (% opacities) by means of a prototype deep learning artificial intelligence (AI)-based software was compared to visual scoring. The visual scoring system used five categories (0: 0%, 1: 0-5%, 2: 5-25%, 3: 25-50%, 4: 50-75% and 5: >75% involvement). The total visual lung injury was obtained by the sum of the estimated grade of involvement of each lobe and divided by five. RESULTS: The dataset consisted of 182 consecutive confirmed COVID-19 positive patients with a median age of 65 ± 16 years, including 110 (60%) men and 72 (40%) women. There was a correlation coefficient of 0.89 (p < 0.001) between the visual and the AI-based estimates of the severity of lung injury. CONCLUSION: The study indicates a very good correlation between the visual scoring and AI-based estimates of lung injury in COVID-19.

Training focal lung pathology detection using an eye movement modeling example.

Purpose: Published reports suggest that nonoptimal visual search behavior is associated with false negatives in chest x-ray interpretation. Eye movement modeling example (EMME)-based training interventions, that is, interventions showing models of visual search to trainees, have been shown to improve visual search as well as task accuracy. Approach: We examined the detection of focal lung pathology on chest x-rays before and after two different EMME training interventions that have been shown to be efficient: (i) an EMME showing moving fixations on a blurred background (spotlight group) and (ii) an EMME showing moving fixations on a nonblurred background (circle group). These two experimental groups were compared to a control group that was only provided with the correct location of pathologies on the chest x-rays. Results: Performance outcomes showed improved detection sensitivity and specificity in all groups (also the control group). It appears that repetitive exposure to pathologies on chest x-rays with feedback resulted in enhanced pattern recognition. In addition, visual search strategies became more efficient during post-tests. Conclusion: Repetitive exposure to a focal lung pathology detection task with feedback improves overall performance. However, the specific EMME training interventions did not add any further advantages. Similar training interventions can be provided online to assess feasibility and reproducibility of such (or similar) training formats. Such training can, for example, reduce the number of false negative errors, especially for novices.

Performance of Low-Dose Chest CT as a Triage Tool for Suspected COVID-19 Patients.

PURPOSE: To investigate the role of low-dose chest computed tomography (CT) imaging in the triage of patients suspected of coronavirus disease 2019 (COVID-19) in an emergency setting. MATERIALS AND METHODS: Data from 610 patients admitted to our emergency unit from March 20, 2020, until April 11, 2020, with suspicion of COVID-19 were collected. Diagnostic values of low-dose chest CT for COVID-19 were calculated using consecutive reverse-transcription polymerase chain reaction (RT-PCR) tests and bronchoalveolar lavage (BAL) as reference. Comparative analysis of the 199 COVID-19 positive versus 411 COVID-19 negative patients was done with identification of risk factors and predictors of worse outcome. RESULTS: Sensitivity and specificity of low-dose CT for the diagnosis of COVID-19 respectively ranged from 75% (150/199) to 88% (175/199) and 94% (386/411) to 99% (386/389), depending on the inclusion of inconclusive results. On multivariate analysis, a higher body mass index (BMI), fever, and dyspnea on admission were risk factors for COVID-19 (all p-values < 0.05). The mortality rate was 12.6% (25/199). Higher age and high levels of C-reactive protein (CRP) and D-dimers were predictors of worse outcome (all p-values < 0.05). CONCLUSION: Low-dose chest CT has a high specificity and a moderate to high sensitivity in symptomatic patients with suspicion of COVID-19 and could be used as an effective tool in setting of triage in high-prevalence areas.

Chest CT Diagnosis and Clinical Management of Drug-Related Pneumonitis in Patients Receiving Molecular Targeting Agents and Immune Checkpoint Inhibitors: A Position Paper From the Fleischner Society.

Use of molecular targeting agents and immune checkpoint inhibitors (ICIs) has increased the frequency and broadened the spectrum of lung toxicity, particularly in patients with cancer. The diagnosis of drug-related pneumonitis (DRP) is usually achieved by excluding other potential known causes. Awareness of the incidence and risk factors for DRP is becoming increasingly important. The severity of symptoms associated with DRP may range from mild or none to life-threatening with rapid progression to death. Imaging features of DRP should be assessed in consideration of the distribution of lung parenchymal abnormalities (radiologic pattern approach). The CT patterns reflect acute (diffuse alveolar damage) interstitial pneumonia and transient (simple pulmonary eosinophilia) lung abnormality, subacute interstitial disease (organizing pneumonia and hypersensitivity pneumonitis), and chronic interstitial disease (nonspecific interstitial pneumonia). A single drug can be associated with multiple radiologic patterns. Treatment of a patient suspected of having DRP generally consists of drug discontinuation, immunosuppressive therapy, or both, along with supportive measures eventually including supplemental oxygen and intensive care. In this position paper, the authors provide diagnostic criteria and management recommendations for DRP that should be of interest to radiologists, clinicians, clinical trialists, and trial sponsors, among others.

Distinct Airway Involvement in Subtypes of End-Stage Fibrotic Pulmonary Sarcoidosis.

BACKGROUND: Sarcoidosis is a systemic granulomatous disease that in most patients affects the lung. Pulmonary fibrotic sarcoidosis is clinically, radiologically, and pathologically a heterogeneous condition. Although substantial indirect evidence suggests small airways involvement, direct evidence currently is lacking. RESEARCH QUESTION: What is the role of the (small) airways in fibrotic sarcoidosis? STUDY DESIGN AND METHODS: Airway morphologic features were investigated in seven explant lungs with end-stage fibrotic sarcoidosis using a combination of CT scanning (large airways), micro-CT scanning (small airways), and histologic examination and compared with seven unused donor lungs as controls with specific attention focused on different radiologically defined sarcoidosis subtypes. RESULTS: Patients with central bronchial distortion (n = 3), diffuse bronchiectasis (n = 3), and usual interstitial pneumonia pattern (n = 1) were identified based on CT scan, showing a decrease and narrowing of large airways, a similar airway number and increased airway diameter of more distal airways, or an increase in airway number and airway diameter, respectively, compared with control participants. The number of terminal bronchioles per milliliter and the total number of terminal bronchioles were decreased in all forms of fibrotic sarcoidosis. Interestingly, the number of terminal bronchioles was inversely correlated with the degree of fibrosis. Furthermore, we identified granulomatous remodeling as a cause of small airways loss using serial micro-CT scanning and histologic examination. INTERPRETATION: The large airways are involved differentially in subtypes of sarcoidosis, but the terminal bronchioles universally are lost. This suggests that small airways loss forms an important aspect in the pathophysiologic features of fibrotic pulmonary sarcoidosis.

Chest CT Diagnosis and Clinical Management of Drug-related Pneumonitis in Patients Receiving Molecular Targeting Agents and Immune Checkpoint Inhibitors: A Position Paper from the Fleischner Society.

Use of molecular targeting agents and immune checkpoint inhibitors (ICIs) has increased the frequency and broadened the spectrum of lung toxicity, particularly in patients with cancer. The diagnosis of drug-related pneumonitis (DRP) is usually achieved by excluding other potential known causes. Awareness of the incidence and risk factors for DRP is becoming increasingly important. The severity of symptoms associated with DRP may range from mild or none to life-threatening with rapid progression to death. Imaging features of DRP should be assessed in consideration of the distribution of lung parenchymal abnormalities (radiologic pattern approach). The CT patterns reflect acute (diffuse alveolar damage) interstitial pneumonia and transient (simple pulmonary eosinophilia) lung abnormality, subacute interstitial disease (organizing pneumonia and hypersensitivity pneumonitis), and chronic interstitial disease (nonspecific interstitial pneumonia). A single drug can be associated with multiple radiologic patterns. Treatment of a patient suspected of having DRP generally consists of drug discontinuation, immunosuppressive therapy, or both, along with supportive measures eventually including supplemental oxygen and intensive care. In this position paper, the authors provide diagnostic criteria and management recommendations for DRP that should be of interest to radiologists, clinicians, clinical trialists, and trial sponsors, among others. This article is a simultaneous joint publication in Radiology and CHEST. The articles are identical except for stylistic changes in keeping with each journal's style. Either version may be used in citing this article. Published under a CC BY 4.0 license. Online supplemental material is available for this article.