A three month old infant with severe respiratory distress.

This case report discusses the diagnostic challenge of congenital lobar emphysema (CLE) in a three-month old infant with severe respiratory distress. The infant was initially misdiagnosed and managed as a case of pneumothorax. This case highlights the importance of CT scans as a diagnostic tool for early diagnosis and lifesaving management of CLE. It also signifies the need for adequate funds and infrastructure in the health care system especially in rural areas of developing countries like Pakistan.

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). METHODS: Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30-100 mm3 and 101-300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. RESULTS: Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57-0.77) in emphysema versus 0.71 (0.62-0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65-0.84) and 0.80 (0.72-0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30-100 mm3 nodules in non-emphysema (p = 0.009). CONCLUSIONS: AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. RELEVANCE STATEMENT: In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. KEY POINTS: • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI.

Association between emphysema and other pulmonary computed tomography patterns in primary varicella pneumonia: A retrospective cohort study.

This study aims to evaluate chest computed tomography (CT) findings in hospital patients with primary varicella pneumonia (PVP). We retrospectively analyzed CT images of 77 PVP patients using 3D Slicer, an open-source software, to model lesions and lungs. This retrospective cohort study was approved by the Institutional Review Board (Ethical Committee, Renmin Hospital, Hubei University of Medicine, Shiyan, China) and waived the requirement for written informed consent. The left lung was more frequently and severely affected in PVP, with significant differences between the 2 groups in CT involvement percentage of each lung region, except for total lung inflation. Group A showed higher median percentages of lung collapse compared to Group B. The extent of left lung involvement is a critical predictor of emphysema in PVP patients, highlighting the importance of also monitoring the right lung for more severe cases. Lower emphysema levels correspond to more collapsed and infiltrated lung segments, suggesting a more severe clinical presentation.

Delayed targeted atelectasis in a case of bronchoscopic lung volume reduction with endobronchial valves.

A woman in her late 60s with severe chronic obstructive pulmonary disease (COPD) and emphysema underwent bronchoscopic lung volume reduction (BLVR) with endobronchial valves (EBV) to address hyperinflation. The initial EBV placement has led to partial lobar atelectasis of the left lower lobe and resulted in significant improvement in the patient's symptoms and lung function. However, valve migration occurred later due to pneumothorax unrelated to valves, leading to suboptimal clinical improvement. The patient achieved delayed full lobar atelectasis 21 months after EBV placement, which led to a significant clinical improvement. The patient decided to be delisted from the lung transplant list due to the improvement. This case highlights the importance of considering delayed atelectasis as a possible outcome of EBV placement and suggests the need for further exploration of the long-term implications and associations of this procedure.

Body composition impacts outcome of bronchoscopic lung volume reduction in patients with severe emphysema: a fully automated CT-based analysis.

Chronic Obstructive Pulmonary Disease (COPD) is characterized by progressive and irreversible airflow limitation, with individual body composition influencing disease severity. Severe emphysema worsens symptoms through hyperinflation, which can be relieved by bronchoscopic lung volume reduction (BLVR). To investigate how body composition, assessed through CT scans, impacts outcomes in emphysema patients undergoing BLVR. Fully automated CT-based body composition analysis (BCA) was performed in patients with end-stage emphysema receiving BLVR with valves. Post-interventional muscle and adipose tissues were quantified, body size-adjusted, and compared to baseline parameters. Between January 2015 and December 2022, 300 patients with severe emphysema underwent endobronchial valve treatment. Significant improvements were seen in outcome parameters, which were defined as changes in pulmonary function, physical performance, and quality of life (QoL) post-treatment. Muscle volume remained stable (1.632 vs. 1.635 for muscle bone adjusted ratio (BAR) at baseline and after 6 months respectively), while bone adjusted adipose tissue volumes, especially total and pericardial adipose tissue, showed significant increase (2.86 vs. 3.00 and 0.16 vs. 0.17, respectively). Moderate to strong correlations between bone adjusted muscle volume and weaker correlations between adipose tissue volumes and outcome parameters (pulmonary function, QoL and physical performance) were observed. Particularly after 6-month, bone adjusted muscle volume changes positively corresponded to improved outcomes (ΔForced expiratory volume in 1 s [FEV1], r = 0.440; ΔInspiratory vital capacity [IVC], r = 0.397; Δ6Minute walking distance [6MWD], r = 0.509 and ΔCOPD assessment test [CAT], r = -0.324; all p < 0.001). Group stratification by bone adjusted muscle volume changes revealed that groups with substantial muscle gain experienced a greater clinical benefit in pulmonary function improvements, QoL and physical performance (ΔFEV1%, 5.5 vs. 39.5; ΔIVC%, 4.3 vs. 28.4; Δ6MWDm, 14 vs. 110; ΔCATpts, -2 vs. -3.5 for groups with ΔMuscle, BAR% < -10 vs. > 10, respectively). BCA results among patients divided by the minimal clinically important difference for forced expiratory volume of the first second (FEV1) showed significant differences in bone-adjusted muscle and intramuscular adipose tissue (IMAT) volumes and their respective changes after 6 months (ΔMuscle, BAR% -5 vs. 3.4 and ΔIMAT, BAR% -0.62 vs. 0.60 for groups with ΔFEV1 ≤ 100 mL vs > 100 mL). Altered body composition, especially increased muscle volume, is associated with functional improvements in BLVR-treated patients.

Sublobar resection or lobectomy and postoperative respiratory complications in emphysematous lungs.

OBJECTIVES: Pulmonary resection in patients with severe emphysema may impact postoperative respiratory complications. Low-attenuation areas evaluated using three-dimensional computed tomography to assess emphysematous changes are strongly associated with postoperative respiratory complications. Herein, we investigated the relationship between low-attenuation area, the surgical procedure and resected lung volume, which has not been explored in previous studies. METHODS: We retrospectively evaluated patients with primary or metastatic lung cancer who underwent surgical resection. The low-attenuation area percentage (low-attenuation area/total lung area × 100) and resected lung volume were calculated using three-dimensional computed tomography software, and the relationship with postoperative respiratory complications was analysed. RESULTS: Postoperative respiratory complications occurred in 66 patients (17%) in the total cohort (n = 383). We set the median value of 1.1% as the cut-off value for low-attenuation area percentage to predict postoperative respiratory complications, which occurred in 24% and 10% of patients with low-attenuation area >1.1% and <1.1%, respectively (P < 0.001). Postoperative respiratory complications occurred in approximately one-third of the patients with low-attenuation area >1.1%, whose resected lung volume was ≥15.8% or ≥5 resected subsegments. Multivariable analysis revealed that sublobar resection was associated with a significantly lower risk of postoperative respiratory complications in patients with low-attenuation area >1.1% (odds ratio 0.4, 95% confidence interval 0.183-0.875). CONCLUSIONS: Emphysema is a risk factor for postoperative respiratory complications, and lobectomy is an independent predictive risk factor. Preserving more lung parenchyma may yield better short-term prognoses in patients with emphysematous lungs.

Alpha-1 Antitrypsin Gene Variants in Patients without Severe Deficiency Diagnosed with Pulmonary Emphysema on Chest CT.

Introduction: Although pulmonary involvement due to alpha-1 antitrypsin (AAT) deficiency has been widely described, most studies focus on the genotypes causing severe deficiency (<60 mg/dL). Objective: The aim of this study was to analyze the prevalence of the different AAT gene variants that do not cause severe deficiency in patients with pulmonary emphysema diagnosed by thoracic computed tomography (CT). Furthermore, we assessed the risk associated with a non-severe decrease in AAT values in the pathogenesis of emphysema. Methods: Case-control study design that included patients who had a CT scan available of the entire thorax. In total, 176 patients with emphysema (cases) and 100 control subjects without emphysema were analyzed. Results: The prevalence of variants was higher among cases (25.6%; 45/176) than controls (22%; 22/100), although the difference was not statistically significant (P=0.504) when analyzed globally. In the control group, all the variants detected were MS. Excluding this variant, statistically significant differences were observed in the remaining variants (MZ, SS and SZ). Only 18% of the controls (all MS) presented values below our limit of normality, and all had values very close to the reference value (90 mg/dL). In contrast, 76% of patients with the other variants presented pathological levels. In a logistic regression model, both smoking and a non-severe reduction in AAT (60 to 90 mg/dL) increased the probability of emphysema. Conclusion: Our study confirms an association between certain variants in the alpha-1 antitrypsin gene that do not cause severe deficiency and the presence of pulmonary emphysema. This association with variants that are associated with reductions in serum AAT values is statistically significant and independent of smoking habit.

Quantification of Emphysema Progression at CT Using Simultaneous Volume, Noise, and Bias Lung Density Correction.

Background CT attenuation is affected by lung volume, dosage, and scanner bias, leading to inaccurate emphysema progression measurements in multicenter studies. Purpose To develop and validate a method that simultaneously corrects volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT in a longitudinal multicenter study. Materials and Methods In this secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, lung function data were obtained from participants who completed baseline and 5-year follow-up visits from January 2008 to August 2017. CT emphysema progression was measured with volume-adjusted lung density (VALD) and compared with the joint volume-noise-bias-adjusted lung density (VNB-ALD). Reproducibility was studied under change of dosage protocol and scanner model with repeated acquisitions. Emphysema progression was visually scored in 102 randomly selected participants. A stratified analysis of clinical characteristics was performed that considered groups based on their combined lung density change measured by VALD and VNB-ALD. Results A total of 4954 COPDGene participants (mean age, 60 years ± 9 [SD]; 2511 male, 2443 female) were analyzed (1329 with repeated reduced-dose acquisition in the follow-up visit). Mean repeatability coefficients were 30 g/L ± 0.46 for VALD and 14 g/L ± 0.34 for VNB-ALD. VALD measurements showed no evidence of differences between nonprogressors and progressors (mean, -5.5 g/L ± 9.5 vs -8.6 g/L ± 9.6; P = .11), while VNB-ALD agreed with visual readings and showed a difference (mean, -0.67 g/L ± 4.8 vs -4.2 g/L ± 5.5; P < .001). Analysis of progression showed that VNB-ALD progressors had a greater decline in forced expiratory volume in 1 second (-42 mL per year vs -32 mL per year; Tukey-adjusted P = .002). Conclusion Simultaneously correcting volume, noise, and interscanner bias for lung density change estimation in emphysema progression at CT improved repeatability analyses and agreed with visual readings. It distinguished between progressors and nonprogressors and was associated with a greater decline in lung function metrics. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Goo in this issue.

A formula for predicting emphysema extent in combined idiopathic pulmonary fibrosis and emphysema.

BACKGROUND: No single pulmonary function test captures the functional effect of emphysema in idiopathic pulmonary fibrosis (IPF). Without experienced radiologists, other methods are needed to determine emphysema extent. Here, we report the development and validation of a formula to predict emphysema extent in patients with IPF and emphysema. METHODS: The development cohort included 76 patients with combined IPF and emphysema at the Royal Brompton Hospital, London, United Kingdom. The formula was derived using stepwise regression to generate the weighted combination of pulmonary function data that fitted best with emphysema extent on high-resolution computed tomography. Test cohorts included patients from two clinical trials (n = 455 [n = 174 with emphysema]; NCT00047645, NCT00075998) and a real-world cohort from the Royal Brompton Hospital (n = 191 [n = 110 with emphysema]). The formula is only applicable for patients with IPF and concomitant emphysema and accordingly was not used to detect the presence or absence of emphysema. RESULTS: The formula was: predicted emphysema extent = 12.67 + (0.92 x percent predicted forced vital capacity) - (0.65 x percent predicted forced expiratory volume in 1 second) - (0.52 x percent predicted carbon monoxide diffusing capacity). A significant relationship between the formula and observed emphysema extent was found in both cohorts (R2 = 0.25, P < 0.0001; R2 = 0.47, P < 0.0001, respectively). In both, the formula better predicted observed emphysema extent versus individual pulmonary function tests. A 15% emphysema extent threshold, calculated using the formula, identified a significant difference in absolute changes from baseline in forced vital capacity at Week 48 in patients with baseline-predicted emphysema extent < 15% versus ≥ 15% (P = 0.0105). CONCLUSION: The formula, designed for use in patients with IPF and emphysema, demonstrated enhanced ability to predict emphysema extent versus individual pulmonary function tests. TRIAL REGISTRATION: NCT00047645; NCT00075998.

Sex-specific emphysematous changes evaluated by a three-dimensional computed tomography volumetric analysis among patients with smoking histories who underwent resection for lung cancer.

PURPOSE: The present study evaluated the sex-specific susceptibility to the development of emphysema in patients with smoking histories who underwent lung cancer surgeries. METHODS: Lung cancer patients with smoking histories who underwent lung resection at the University of Tsukuba Hospital, Japan, were enrolled. Radiologic emphysematous changes were analyzed using three-dimensional computed tomography (3D-CT). The volume proportion of emphysematous lung per unit of smoking and the relationship between emphysematous change and clinicopathologic factors were evaluated. RESULTS: Radiologic emphysematous changes analyzed using 3D-CT per pack-year smoked, defined as the Smoking-Emphysema Index (SEI), were greater in females than males. The difference was more profound in adenocarcinoma patients than in non-adenocarcinoma patients (0.70 ± 2.30 vs. 0.21 ± 0.28, P = 0.037). CONCLUSION: Female lung cancer patients are more susceptible to smoking-induced emphysema than males. The SEI may be an effective indicator for evaluating smoking-induced emphysema.

Topologic Parametric Response Mapping Identifies Tissue Subtypes Associated with Emphysema Progression.

RATIONALE AND OBJECTIVES: Small airways disease (SAD) and emphysema are significant components of chronic obstructive pulmonary disease (COPD), a heterogenous disease where predicting progression is difficult. SAD, a principal cause of airflow obstruction in mild COPD, has been identified as a precursor to emphysema. Parametric Response Mapping (PRM) of chest computed tomography (CT) can help distinguish SAD from emphysema. Specifically, topologic PRM can define local patterns of both diseases to characterize how and in whom COPD progresses. We aimed to determine if distribution of CT-based PRM of functional SAD (fSAD) is associated with emphysema progression. MATERIALS AND METHODS: We analyzed paired inspiratory-expiratory chest CT scans at baseline and 5-year follow up in 1495 COPDGene subjects using topological analyses of PRM classifications. By spatially aligning temporal scans, we mapped local emphysema at year five to baseline lobar PRM-derived topological readouts. K-means clustering was applied to all observations. Subjects were subtyped based on predominant PRM cluster assignments and assessed using non-parametric statistical tests to determine differences in PRM values, pulmonary function metrics, and clinical measures. RESULTS: We identified distinct lobar imaging patterns and classified subjects into three radiologic subtypes: emphysema-dominant (ED), fSAD-dominant (FD), and fSAD-transition (FT: transition from healthy lung to fSAD). Relative to year five emphysema, FT showed rapid local emphysema progression (-57.5% ± 1.1) compared to FD (-49.9% ± 0.5) and ED (-33.1% ± 0.4). FT consisted primarily of at-risk subjects (roughly 60%) with normal spirometry. CONCLUSION: The FT subtype of COPD may allow earlier identification of individuals without spirometrically-defined COPD at-risk for developing emphysema.

Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality.

OBJECTIVES: The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality. MATERIALS AND METHODS: This retrospective study investigated LDCTs obtained from asymptomatic individuals aged 60 years or older during health checkups between February 2009 and December 2016. These LDCTs were reconstructed using a 1- or 1.25-mm slice thickness alongside high-frequency kernels. A deep learning algorithm, capable of generating CT images that resemble standard-dose and low-frequency kernel images, was applied to these LDCTs. To quantify emphysema, the lung volume percentage with an attenuation value less than or equal to -950 Hounsfield units (LAA-950) was gauged before and after kernel adaptation. Low-dose chest CTs with LAA-950 exceeding 6% were deemed emphysema-positive according to the Fleischner Society statement. Survival data were sourced from the National Registry Database at the close of 2021. The risk of nonaccidental death, excluding causes such as injury or poisoning, was explored according to the emphysema quantification results using multivariate Cox proportional hazards models. RESULTS: The study comprised 5178 participants (mean age ± SD, 66 ± 3 years; 3110 males). The median LAA-950 (18.2% vs 2.6%) and the proportion of LDCTs with LAA-950 exceeding 6% (96.3% vs 39.3%) saw a significant decline after kernel adaptation. There was no association between emphysema quantification before kernel adaptation and the risk of nonaccidental death. Nevertheless, after kernel adaptation, higher LAA-950 (hazards ratio for 1% increase, 1.01; P = 0.045) and LAA-950 exceeding 6% (hazards ratio, 1.36; P = 0.008) emerged as independent predictors of nonaccidental death, upon adjusting for age, sex, and smoking status. CONCLUSIONS: The application of deep learning for kernel adaptation proves instrumental in quantifying pulmonary emphysema on LDCTs, establishing itself as a potential predictive tool for long-term nonaccidental mortality in asymptomatic individuals.

Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction.

OBJECTIVES: Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method. MATERIALS AND METHODS: Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis. RESULTS: SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r = - 0.69 vs. r = - 0.49/r = - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r = - 0.77 vs. r = - 0.69/r = - 0.65, p = 0.03/p = 0.002), and in the random sample (r = - 0.39 vs. r = - 0.26/r = - 0.25, p = 0.001/p = 0.007). CONCLUSION: The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores. CLINICAL RELEVANCE STATEMENT: The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores. KEY POINTS: • A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.

Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT.

OBJECTIVES: To compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND METHODS: Fifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level. RESULTS: Almost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2. CONCLUSION: UHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: • The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. • UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). • Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.