The role of coronary CT angiography in athletes.

The sudden death of a young or high-level athlete or adolescent during recreational sports is one of the events with the greatest impact on public opinion in modern society. Sudden cardiac death (SCD) is the principal medical cause of death in athletes and can be the first and last clinical presentation of underlying disease. To prevent such episodes, pre-participation screening has been introduced in many countries to guarantee cardiovascular safety during sports and has become a common target among medical sports/governing organizations. Different cardiac conditions may cause SCD, with incidence depending on definition, evaluation methods, and studied populations, and a prevalence and etiology changing according to the age of athletes, with CAD most frequent in master athletes, while coronary anomalies and non-ischemic causes prevalent in young. To detect silent underlying causes early would be of considerable clinical value. This review summarizes the pre-participation screening in athletes, the specialist agonistic suitability visit performed in Italy, the anatomical characteristics of malignant coronary anomalies, and finally, the role of coronary CT angiography in such arena. In particular, the anatomical conditions suggesting potential disqualification from sport, the post-treatment follow-up to reintegrate young athletes, the diagnostic workflow to rule-out CAD in master athletes, and their clinical management are analyzed.

Leptin-mediated meta-inflammation may provide survival benefit in patients receiving maintenance immunotherapy for extensive-stage small cell lung cancer (ES-SCLC).

BACKGROUND: Only few ES-SCLC patients experience long-term survival benefit by maintenance IT. Adipokines-induced metabolic meta-inflammation has been related to enhanced responsiveness to IT in obese patients; however, their prognostic role in SCLC is currently controversial. METHODS: Pre-treatment CT scan was used for determining distribution of abdominal adiposity, and blood samples were collected at fasting for measuring glycemia, insulin, ghrelin, leptin and adipokines (TNF-α, IFN-γ, IL-6 and MCP-1). Patients with known history of DM type II or metabolic syndrome with HOMA index > 2.5 were considered insulin resistant (IR). RESULTS: In ES-SCLC pts receiving maintenance IT, increased leptin concentration and higher leptin/visceral adipose tissue (VAT) ratio were significantly associated with prolonged PFS. By applying a hierarchical clustering algorithm, we identified a cluster of patients characterized by higher leptin values and lower pro-inflammatory cytokines (TNF-α, IFN-γ and IL-6) who experienced longer PFS (13.2 vs 8.05 months; HR: 0.42 [0.18-0.93] p = 0.02) and OS (18.04 vs 12.09 mo; HR: 0.53 [0.25-1.29] p = 0.07). CONCLUSIONS: Adipokines can play a crucial role to determining effectiveness of anti-cancer immunotherapy. The role of metabolic immune dysfunctions needs further pre-clinical validation and is currently investigated in the larger prospective cohort.

Lung vascular changes as biomarkers of severity in systemic sclerosis-associated interstitial lung disease.

OBJECTIVES: It has recently become possible to assess lung vascular and parenchymal changes quantitatively in thoracic CT images using automated software tools. We investigated the vessel parameters of patients with SSc, quantified by CT imaging, and correlated them with interstitial lung disease (ILD) features. METHODS: SSc patients undergoing standard of care pulmonary function testing and CT evaluation were retrospectively evaluated. CT images were analysed for ILD patterns and total pulmonary vascular volume (PVV) extents with Imbio lung texture analysis. Vascular analysis (volumes, numbers and densities of vessels, separating arteries and veins) was performed with an in-house developed software. A threshold of 5% ILD extent was chosen to define the presence of ILD, and commonly used cut-offs of lung function were adopted. RESULTS: A total of 79 patients [52 women, 40 ILD, mean age 56.2 (s.d. 14.2) years, total ILD extent 9.5 (10.7)%, PVV/lung volume % 2.8%] were enrolled. Vascular parameters for total and separated PVV significantly correlated with functional parameters and ILD pattern extents. SSc-associated ILD (SSc-ILD) patients presented with an increased number and volume of arterial vessels, in particular those between 2 and 4 mm of diameter, and with a higher density of arteries and veins of <6 mm in diameter. Considering radiological and functional criteria concomitantly, as well as the descriptive trends from the longitudinal evaluations, the normalized PVVs, vessel numbers and densities increased progressively with the increase/worsening of ILD extent and functional impairment. CONCLUSION: In SSc patients CT vessel parameters increase in parallel with ILD extent and functional impairment, and may represent a biomarker of SSc-ILD severity.

Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study.

BACKGROUND: The current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients. METHODS: The LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management. DISCUSSION: The LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols. ETHICS COMMITTEE APPROVAL NUMBER: 5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee. TRIAL REGISTRATION: clinicaltrial.gov - NCT05802771.

Implementation of artificial intelligence in thoracic imaging-a what, how, and why guide from the European Society of Thoracic Imaging (ESTI).

This statement from the European Society of Thoracic imaging (ESTI) explains and summarises the essentials for understanding and implementing Artificial intelligence (AI) in clinical practice in thoracic radiology departments. This document discusses the current AI scientific evidence in thoracic imaging, its potential clinical utility, implementation and costs, training requirements and validation, its' effect on the training of new radiologists, post-implementation issues, and medico-legal and ethical issues. All these issues have to be addressed and overcome, for AI to become implemented clinically in thoracic radiology. KEY POINTS: • Assessing the datasets used for training and validation of the AI system is essential. • A departmental strategy and business plan which includes continuing quality assurance of AI system and a sustainable financial plan is important for successful implementation. • Awareness of the negative effect on training of new radiologists is vital.

Multi-center validation of an artificial intelligence system for detection of COVID-19 on chest radiographs in symptomatic patients.

OBJECTIVES: While chest radiograph (CXR) is the first-line imaging investigation in patients with respiratory symptoms, differentiating COVID-19 from other respiratory infections on CXR remains challenging. We developed and validated an AI system for COVID-19 detection on presenting CXR. METHODS: A deep learning model (RadGenX), trained on 168,850 CXRs, was validated on a large international test set of presenting CXRs of symptomatic patients from 9 study sites (US, Italy, and Hong Kong SAR) and 2 public datasets from the US and Europe. Performance was measured by area under the receiver operator characteristic curve (AUC). Bootstrapped simulations were performed to assess performance across a range of potential COVID-19 disease prevalence values (3.33 to 33.3%). Comparison against international radiologists was performed on an independent test set of 852 cases. RESULTS: RadGenX achieved an AUC of 0.89 on 4-fold cross-validation and an AUC of 0.79 (95%CI 0.78-0.80) on an independent test cohort of 5,894 patients. Delong's test showed statistical differences in model performance across patients from different regions (p < 0.01), disease severity (p < 0.001), gender (p < 0.001), and age (p = 0.03). Prevalence simulations showed the negative predictive value increases from 86.1% at 33.3% prevalence, to greater than 98.5% at any prevalence below 4.5%. Compared with radiologists, McNemar's test showed the model has higher sensitivity (p < 0.001) but lower specificity (p < 0.001). CONCLUSION: An AI model that predicts COVID-19 infection on CXR in symptomatic patients was validated on a large international cohort providing valuable context on testing and performance expectations for AI systems that perform COVID-19 prediction on CXR. KEY POINTS: • An AI model developed using CXRs to detect COVID-19 was validated in a large multi-center cohort of 5,894 patients from 9 prospectively recruited sites and 2 public datasets. • Differences in AI model performance were seen across region, disease severity, gender, and age. • Prevalence simulations on the international test set demonstrate the model's NPV is greater than 98.5% at any prevalence below 4.5%.

Deep Learning-based Outcome Prediction in Progressive Fibrotic Lung Disease Using High-Resolution Computed Tomography.

Rationale: Reliable outcome prediction in patients with fibrotic lung disease using baseline high-resolution computed tomography (HRCT) data remains challenging. Objectives: To evaluate the prognostic accuracy of a deep learning algorithm (SOFIA [Systematic Objective Fibrotic Imaging Analysis Algorithm]), trained and validated in the identification of usual interstitial pneumonia (UIP)-like features on HRCT (UIP probability), in a large cohort of well-characterized patients with progressive fibrotic lung disease drawn from a national registry. Methods: SOFIA and radiologist UIP probabilities were converted to Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED)-based UIP probability categories (UIP not included in the differential, 0-4%; low probability of UIP, 5-29%; intermediate probability of UIP, 30-69%; high probability of UIP, 70-94%; and pathognomonic for UIP, 95-100%), and their prognostic utility was assessed using Cox proportional hazards modeling. Measurements and Main Results: In multivariable analysis adjusting for age, sex, guideline-based radiologic diagnosis, anddisease severity (using total interstitial lung disease [ILD] extent on HRCT, percent predicted FVC, DlCO, or the composite physiologic index), only SOFIA UIP probability PIOPED categories predicted survival. SOFIA-PIOPED UIP probability categories remained prognostically significant in patients considered indeterminate (n = 83) by expert radiologist consensus (hazard ratio, 1.73; P < 0.0001; 95% confidence interval, 1.40-2.14). In patients undergoing surgical lung biopsy (n = 86), after adjusting for guideline-based histologic pattern and total ILD extent on HRCT, only SOFIA-PIOPED probabilities were predictive of mortality (hazard ratio, 1.75; P < 0.0001; 95% confidence interval, 1.37-2.25). Conclusions: Deep learning-based UIP probability on HRCT provides enhanced outcome prediction in patients with progressive fibrotic lung disease when compared with expert radiologist evaluation or guideline-based histologic pattern. In principle, this tool may be useful in multidisciplinary characterization of fibrotic lung disease. The utility of this technology as a decision support system when ILD expertise is unavailable requires further investigation.

Interobserver variability in the evaluation of primary graft dysfunction after lung transplantation: impact of radiological training and analysis of discordant cases.

PURPOSE: Radiologic criteria for the diagnosis of primary graft dysfunction (PGD) after lung transplantation are nonspecific and can lead to misinterpretation. The primary aim of our study was to assess the interobserver agreement in the evaluation of chest X-rays (CXRs) for PGD diagnosis and to establish whether a specific training could have an impact on concordance rates. Secondary aim was to analyze causes of interobserver discordances. MATERIAL AND METHODS: We retrospectively enrolled 164 patients who received bilateral lung transplantation at our institution, between February 2013 and December 2019. Three radiologists independently reviewed postoperative CXRs and classified them as suggestive or not for PGD. Two of the Raters performed a specific training before the beginning of the study. A senior thoracic radiologist subsequently analyzed all discordant cases among the Raters with the best agreement. Statistical analysis to calculate interobserver variability was percent agreement, Cohen's kappa and intraclass correlation coefficient. RESULTS: A total of 473 CXRs were evaluated. A very high concordance among the two trained Raters, 1 and 2, was found (K = 0.90, ICC = 0.90), while a poorer agreement was found in the other two pairings (Raters 1 and 3: K = 0.34, ICC = 0.40; Raters 2 and 3: K = 0.35, ICC = 0.40). The main cause of disagreement (52.4% of discordant cases) between Raters 1 and 2 was the overestimation of peribronchial thickening in the absence of unequivocal bilateral lung opacities or the incorrect assessment of unilateral alterations. CONCLUSION: To properly identify PGD, it is recommended for radiologists to receive an adequate specific training.

Low-dose CT for lung cancer screening: position paper from the Italian college of thoracic radiology.

Smoking is the main risk factor for lung cancer (LC), which is the leading cause of cancer-related death worldwide. Independent randomized controlled trials, governmental and inter-governmental task forces, and meta-analyses established that LC screening (LCS) with chest low dose computed tomography (LDCT) decreases the mortality of LC in smokers and former smokers, compared to no-screening, especially in women. Accordingly, several Italian initiatives are offering LCS by LDCT and smoking cessation to about 10,000 high-risk subjects, supported by Private or Public Health Institutions, envisaging a possible population-based screening program. Because LDCT is the backbone of LCS, Italian radiologists with LCS expertise are presenting this position paper that encompasses recommendations for LDCT scan protocol and its reading. Moreover, fundamentals for classification of lung nodules and other findings at LDCT test are detailed along with international guidelines, from the European Society of Thoracic Imaging, the British Thoracic Society, and the American College of Radiology, for their reporting and management in LCS. The Italian College of Thoracic Radiologists produced this document to provide the basics for radiologists who plan to set up or to be involved in LCS, thus fostering homogenous evidence-based approach to the LDCT test over the Italian territory and warrant comparison and analyses throughout National and International practices.

Lung Ultrasound for COVID-19 Patchy Pneumonia: Extended or Limited Evaluations?

OBJECTIVES: The 2019 novel coronavirus (severe acute respiratory syndrome coronavirus 2) is causing cases of severe pneumonia. Lung ultrasound (LUS) could be a useful tool for physicians detecting a bilateral heterogeneous patchy distribution of pathologic findings in a symptomatic suggestive context. The aim of this study was to focus on the implications of limiting LUS examinations to specific regions of the chest. METHODS: Patients were evaluated with a standard sequence of LUS scans in 14 anatomic areas. A scoring system of LUS findings was reported, ranging from 0 to 3 (worst score, 3). The scores reported on anterior, lateral, and posterior landmarks were analyzed separately and compared with each other and with the global findings. RESULTS: Thirty-eight patients were enrolled. A higher prevalence of score 0 was observed in the anterior region (44.08%). On the contrary, 21.05% of posterior regions and 13.62% of lateral regions were evaluated as score 3, whereas only 5.92% of anterior regions were classified as score 3. Findings from chest computed tomography performed in 16 patients with coronavirus disease 2019 correlated with and matched the distribution of findings from LUS. CONCLUSIONS: To assess the quantity and severity of lung disease, a comprehensive LUS examination is recommended. Omitting areas of the chest misses involved lung.

Practical instructions for using drugs in CT and MR cardiac imaging.

The progressive increase in numbers of noninvasive cardiac imaging examinations broadens the spectrum of knowledge radiologists are expected to acquire in the management of drugs during CT coronary angiography (CTCA) and cardiac MR (CMR) to improve image quality for optimal visualization and assessment of the coronary arteries and adequate MR functional analysis. Aim of this review is to provide an overview on different class of drugs (nitrate, beta-blockers, ivabradine, anxiolytic, adenosine, dobutamine, atropine, dipyridamole and regadenoson) that can be used in CTCA and CMR, illustrating their main indications, contraindications, efficacy, mechanism of action, metabolism, safety, side effects or complications, and providing advices in their use.

Impact of the COVID-19 pandemic on the selection of chest imaging modalities and reporting systems: a survey of Italian radiologists.

PURPOSE: Chest imaging modalities play a key role for the management of patient with coronavirus disease (COVID-19). Unfortunately, there is no consensus on the optimal chest imaging approach in the evaluation of patients with COVID-19 pneumonia, and radiology departments tend to use different approaches. Thus, the main objective of this survey was to assess how chest imaging modalities have been used during the different phases of the first COVID-19 wave in Italy, and which diagnostic technique and reporting system would have been preferred based on the experience gained during the pandemic. MATERIAL AND METHODS: The questionnaire of the survey consisted of 26 questions. The link to participate in the survey was sent to all members of the Italian Society of Medical and Interventional Radiology (SIRM). RESULTS: The survey gathered responses from 716 SIRM members. The most notable result was that the most used and preferred chest imaging modality to assess/exclude/monitor COVID-19 pneumonia during the different phases of the first COVID-19 wave was computed tomography (51.8% to 77.1% of participants). Additionally, while the narrative report was the most used reporting system (55.6% of respondents), one-third of participants would have preferred to utilize structured reporting systems. CONCLUSION: This survey shows that the participants' responses did not properly align with the imaging guidelines for managing COVID-19 that have been made by several scientific, including SIRM. Therefore, there is a need for continuing education to keep radiologists up to date and aware of the advantages and limitations of the chest imaging modalities and reporting systems.

Fibrotic Hypersensitivity Pneumonitis: Diagnosis and Management.

Fibrotic hypersensitivity pneumonitis is a complex interstitial lung disease that is not entirely understood. In its chronic and fibrotic form, hypersensitivity pneumonitis is one of the main mimickers of idiopathic pulmonary fibrosis (IPF). Distinguishing between these two conditions is challenging but is of particular clinical relevance. Two approved therapies are available for IPF, and a considerable number of clinical trials are now exploring newer pharmacological options. This impressive research effort is a consequence of new pathogenetic understanding, updated diagnostic criteria and a long history of pharmacological trials. Conversely, current knowledge gaps on pathogenesis of chronic hypersensitivity pneumonitis, coupled with lack of validated diagnostic criteria, make the management of this disease an unsolved clinical challenge. This also reflects the paucity of therapeutic clinical trials in this field. In this review, we describe the current evidence and the possible future options to approach this complex disease.

Mediastinal lymph node enlargement in idiopathic pulmonary fibrosis: relationships with disease progression and pulmonary function trends.

BACKGROUND AND OBJECTIVES: Evidence of mediastinal Lymph Node Enlargement (LNE) on CT scan is a common finding in idiopathic pulmonary fibrosis (IPF). We sought to investigate whether the involvement of mediastinal lymph nodes is associated with accelerated disease progression, and explored the changes occurring in mediastinal lymph nodes during the radiological follow up of these patients. METHODS: This retrospective study included IPF patients referred to a single ILD centre in Italy. A consensus-based assessment of mediastinal LNE on chest CT scan was performed by two thoracic radiologists. Kaplan-Meier curves and multivariate Cox proportional hazards regression were used to assess hazard ratios for mortality and disease progression (defined as categorical FVC decline ≥10%). The annualized rates of change in functional parameters for each patient were calculated using mixed linear models. RESULTS: The study population consisted of 152 IPF patients, of whom 135 (89%) received antifibrotic treatment for IPF during the study follow up. Patients having evidence of 3 or more enlarged mediastinal lymph nodes on baseline CT scan showed increased rates of mortality (HR 5.03, 95% CI 1.86-13.62, p ≤ 0.001) and significant disease progression (HR 2.99, 95% CI 1.22-7.33, p = 0.17) as compared to patients without LNE, after adjusting for GAP stage. Among 62 patients with LNE who underwent a follow up CT scan of the chest and received antifibrotic treatment, 57 (92%) maintained evidence mediastinal LNE over time. CONCLUSIONS: Diffuse mediastinal lymph node involvement predicts clinically meaningful functional deterioration in patients with IPF.

Exploring technical issues in personalized medicine: NSCLC survival prediction by quantitative image analysis-usefulness of density correction of volumetric CT data.

The aim of this study was to apply density correction method to the quantitative image analysis of non-small cell lung cancer (NSCLC) computed tomography (CT) images, determining its influence on overall survival (OS) prediction of surgically treated patients. Clinicopathological (CP) data and preoperative CT scans, pre- and post-contrast medium (CM) administration, of 57 surgically treated NSCLC patients, were retrospectively collected. After CT volumetric density measurement of primary gross tumour volume (GTV), aorta and tracheal air, density correction was conducted on GTV (reference values: aortic blood and tracheal air). For each resulting data set (combining CM administration and normalization), first-order statistical and textural features were extracted. CP and imaging data were correlated with patients 1-, 3- and 5-year OS, alone and combined (uni-/multivariate logistic regression and Akaike information criterion). Predictive performance was evaluated using the ROC curves and AUC values and compared among non-normalized/normalized data sets (DeLong test). The best predictive values were obtained when combining CP and imaging parameters (AUC values: 1 year 0.72; 3 years 0.82; 5 years 0.78). After normalization resulted an improvement in predicting 1-year OS for some of the grey level size zonebased features (large zone low grey level emphasis) and for the combined CP-imaging model, a worse performance for grey level co-occurrence matrix (cluster prominence and shade) and first-order statistical (range) parameters for 1- and 5-year OS, respectively. The negative performance of cluster prominence in predicting 1-year OS was the only statistically significant result (p value 0.05). Density corrections of volumetric CT data showed an opposite influence on the performance of imaging quantitative features in predicting OS of surgically treated NSCLC patients, even if no statistically significant for almost all predictors.

Pulmonary arteriovenous malformations: what the interventional radiologist needs to know.

Pulmonary arteriovenous malformations (PAVMs) or fistulas are rare direct pathological connections between pulmonary arterial and venous circulation. Most of PAVMs are congenital and closely associated with hereditary hemorrhagic telangiectasia, but acquired PAVMs have also been described in the literature. Diagnosis of PAVMs is a priority for clinicians, in order to prevent potentially fatal events such as cerebrovascular stroke, systemic septic embolization, hemoptysis and hemothorax. In this scenario, the radiologist plays a key role in both diagnostic and therapeutic workups of PAVMs: Chest X-ray, computed tomography and magnetic resonance are effective tools for PAVMs identification and confirmation of the suspected diagnosis. Furthermore, imaging modalities provide most of the elements for PAVMs classification according to their angioarchitecture (simple and complex) and help the clinicians in establishing which lesion requires prompt treatment and which one will benefit of imaging follow-up alone. Endovascular management of PAVMs has grown up as the first-line treatment in respect of surgery during last decades, showing lower risk of intra- and post-procedural complications and offering a wide number of treatment options and materials, ensuring effective management in virtually any clinical situation; interventional treatment aims to exclude PAVMs from pulmonary circulation, and specific technique and embolic agents should be selected according to pre-treatment imaging, in order to obtain the best procedural outcome. This paper proposes a review of the clinical and radiological features that a radiologist needs to know for PAVMs diagnosis and proper management, also showing an overview of the most common endovascular treatment strategies and embolization materials.

Management of incidental pulmonary nodule in CT: a survey by the Italian College of Chest Radiology.

OBJECTIVES: The aim of this study is to present the results of the Italian survey on the management of pulmonary nodules incidentally identified at computed tomography (CT). MATERIALS AND METHODS: An online electronic survey, consisting of 23 multiple-choice questions, was created using the SurveyMonkey web-based tool. The questionnaire was developed by the Board of the Italian College of Chest Radiology of the Italian Society of Medical and Interventional Radiology (SIRM) and by an experienced group of Italian Academic Chest Radiologists. The link to the online electronic survey was submitted by email to all the SIRM members. RESULTS: A total of 767 radiologists, corresponding to 7.5% of all the SIRM members, participated in the online survey. The majority of participants (92%) routinely describe the attenuation of pulmonary nodules in the report, and 84.1% recommend the further follow-up, with 92.7% of respondents taking CT nodule morphological features into consideration. The 57.7% of participants adhere to the Fleischner Society guidelines for the management of incidental pulmonary nodules. However, 56.6% and 75.6% of respondents have a more cautious approach than that recommended by the guidelines and tend to use a shorter follow-up for both solid and ground-glass nodules, respectively. Finally, 94.5% of participants favor congresses and refresher courses dedicated to insights on lung nodule diagnosis and management. CONCLUSIONS: This survey demonstrates that the management of pulmonary nodules incidentally detected on CT is still complex and controversial. The majority of SIRM members express a need for an update on this topic.

Emphysematous and Nonemphysematous Gas Trapping in Chronic Obstructive Pulmonary Disease: Quantitative CT Findings and Pulmonary Function.

Purpose To identify a prevalent computed tomography (CT) subtype in patients with chronic obstructive pulmonary disease (COPD) by separating emphysematous from nonemphysematous contributions to total gas trapping and to attempt to predict and grade the emphysematous gas trapping by using clinical and functional data. Materials and Methods Two-hundred and two consecutive eligible patients (159 men and 43 women; mean age, 70 years [age range, 41-85 years]) were prospectively studied. Pulmonary function and CT data were acquired by pulmonologists and radiologists. Noncontrast agent-enhanced thoracic CT scans were acquired at full inspiration and expiration, and were quantitatively analyzed by using two software programs. CT parameters were set as follows: 120 kVp; 200 mAs; rotation time, 0.5 second; pitch, 1.1; section thickness, 0.75 mm; and reconstruction kernels, b31f and b70f. Gas trapping obtained by difference of inspiratory and expiratory CT density thresholds (percentage area with CT attenuation values less than -950 HU at inspiration and percentage area with CT attenuation values less than -856 HU at expiration) was compared with that obtained by coregistration analysis. A logistic regression model on the basis of anthropometric and functional data was cross-validated and trained to classify patients with COPD according to the relative contribution of emphysema to total gas trapping, as assessed at CT. Results Gas trapping obtained by difference of inspiratory and expiratory CT density thresholds was highly correlated (r = 0.99) with that obtained by coregistration analysis. Four groups of patients were distinguished according to the prevalent CT subtype: prevalent emphysematous gas trapping, prevalent functional gas trapping, mixed severe, and mixed mild. The predictive model included predicted forced expiratory volume in 1 second/vital capacity, percentage of predicted forced expiratory volume in 1 second, percentage of diffusing capacity for carbon monoxide, and body mass index as emphysema regressors at CT, with 81% overall accuracy in classifying patients according to its extent. Conclusion The relative contribution of emphysematous and nonemphysematous gas trapping obtained by coregistration of inspiratory and expiratory CT scanning can be determined accurately by difference of CT inspiratory and expiratory density thresholds. CT extent of emphysema can be predicted with accuracy suitable for clinical purposes by pulmonary function data and body mass index. © RSNA, 2018 Online supplemental material is available for this article.