Computed tomography-based visual assessment of chronic obstructive pulmonary disease: comparison with pulmonary function test and quantitative computed tomography

Imaging Phenotypes Assessment by Using Quantitative Parameters for CT-Defined Subtypes of Chronic Obstructive Pulmonary Disease

Purpose

To explore the quantitative imaging phenotype differences for CT-defined subtypes classified by the Fleischner Society in patients with chronic obstructive pulmonary disease (COPD).

Patients and Methods

A total of 228 COPD patients who underwent non-enhanced chest CT screening from 2018 to 2024 were included. All patients were divided into type-A (Absent emphysema that no or mild emphysema, Goddard score ≤8, regardless of bronchial wall thickening), type-E (Emphysema that significant emphysema, Goddard score >8, without bronchial wall thickening), and type-M (Mixed emphysema and bronchial wall thickening that both significant emphysema, Goddard score >8, and bronchial wall thickening ≥ grade 1 in ≥1 lung lobe). Imaging phenotype parameters included lung airspace analysis (LAA) and LAA size analysis (LAASA) in emphysema, airway wall, lung vessels and interstitial lung disease (ILD) extracted by a COPD-specific analysis software were analysis among three groups.

Results

Quantitative assessment of emphysema among three image phenotypes showed significant differences in full emphysema and full emphysema ratio based on LAA among three groups (P < 0.05). The areas of consolidation, ground-glass opacity, and reticular patterns were significantly larger in type-M than the other two types (P < 0.05). Quantitative assessment of small airways disease and small vessel parameters found smaller lumen-volume and larger wall-volume in whole lung level in the emphysema phenotype of type-M (P < 0.05) were found in the small vessel count in distance of 6 mm and 9mm from the pleura were significant differences among three groups (P < 0.05). The multivariate logistic regression analysis showed that the higher proportion of full emphysema ratio and wall-volume, a proportion of smaller lumen-volume, and a more noticeable interstitial lung alterations were associated with type-M.

Conclusion

A quantitative CT evaluation can further delineate the imaging phenotypes characteristics thereby in guiding to early diagnosis, severity assessment, and therapeutic recommendations in COPD patients.

Assessment of Emphysema on X-ray Equivalent Dose Photon-Counting Detector CT: Evaluation of Visual Scoring and Automated Quantification Algorithms

OBJECTIVES

The aim of this study was to evaluate the feasibility and efficacy of visual scoring, low-attenuation volume (LAV), and deep learning methods for estimating emphysema extent in x-ray dose photon-counting detector computed tomography (PCD-CT), aiming to explore future dose reduction potentials.

METHODS

One hundred one prospectively enrolled patients underwent noncontrast low- and chest x-ray dose CT scans in the same study using PCD-CT. Overall image quality, sharpness, and noise, as well as visual emphysema pattern (no, trace, mild, moderate, confluent, and advanced destructive emphysema; as defined by the Fleischner Society), were independently assessed by 2 experienced radiologists for low- and x-ray dose images, followed by an expert consensus read. In the second step, automated emphysema quantification was performed using an established LAV algorithm with a threshold of -950 HU and a commercially available deep learning model for automated emphysema quantification. Automated estimations of emphysema extent were converted and compared with visual scoring ratings.

RESULTS

X-ray dose scans exhibited a significantly lower computed tomography dose index than low-dose scans (low-dose: 0.66 ± 0.16 mGy, x-ray dose: 0.11 ± 0.03 mGy, P < 0.001). Interreader agreement between low- and x-ray dose for visual emphysema scoring was excellent (κ = 0.83). Visual emphysema scoring consensus showed good agreement between low-dose and x-ray dose scans (κ = 0.70), with significant and strong correlation (Spearman ρ = 0.79). Although trace emphysema was underestimated in x-ray dose scans, there was no significant difference in the detection of higher-grade (mild to advanced destructive) emphysema ( P = 0.125) between the 2 scan doses. Although predicted emphysema volumes on x-ray dose scans for the LAV method showed strong and the deep learning model excellent significant correlations with predictions on low-dose scans, both methods significantly overestimated emphysema volumes on lower quality scans ( P < 0.001), with the deep learning model being more robust. Further, deep learning emphysema severity estimations showed higher agreement (κ = 0.65) and correlation (Spearman ρ = 0.64) with visual scoring for low-dose scans than LAV predictions (κ = 0.48, Spearman ρ = 0.45).

CONCLUSIONS

The severity of emphysema can be reliably estimated using visual scoring on CT scans performed with x-ray equivalent doses on a PCD-CT. A deep learning algorithm demonstrated good agreement and strong correlation with the visual scoring method on low-dose scans. However, both the deep learning and LAV algorithms overestimated emphysema extent on x-ray dose scans. Nonetheless, x-ray equivalent radiation dose scans may revolutionize the detection and monitoring of disease in chronic obstructive pulmonary disease patients.

Artificial Intelligence-Based Emphysema Quantification in Routine Chest Computed Tomography: Correlation With Spirometry and Visual Emphysema Grading

OBJECTIVE

The aim of the study is to assess the correlation between artificial intelligence (AI)-based low attenuation volume percentage (LAV%) with forced expiratory volume in the first second to forced vital capacity (FEV1/FVC) and visual emphysema grades in routine chest computed tomography (CT). Furthermore, optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or moderate to more extensive visual emphysema grades were calculated.

METHODS

In a retrospective study of 298 consecutive patients who underwent routine chest CT and spirometry examinations, LAV% was quantified using an AI-based software with a threshold < -950 HU. The FEV1/FVC was derived from spirometry, with FEV1/FVC < 70% indicating airway obstruction. The mean time interval of CT from spirometry was 3.87 ± 4.78 days. Severity of emphysema was visually graded by an experienced chest radiologist using an established 5-grade ordinal scale (Fleischner Society classification system). Spearman correlation coefficient between LAV% and FEV1/FVC was calculated. Receiver operating characteristic determined the optimal LAV% cutoff values for predicting a FEV1/FVC < 70% or a visual emphysema grade of moderate or higher (Fleischner grade 3-5).

RESULTS

Significant correlation between LAV% and FEV1/FVC was found (ϱ = -0.477, P < 0.001). Increasing LAV% corresponded to higher visual emphysema grades. For patients with absent visual emphysema, mean LAV% was 2.98 ± 3.30, for patients with trace emphysema 3.22 ± 2.75, for patients with mild emphysema 3.90 ± 3.33, for patients with moderate emphysema 6.41 ± 3.46, for patients with confluent emphysema 9.02 ± 5.45, and for patients with destructive emphysema 16.90 ± 8.19. Optimal LAV% cutoff value for predicting a FEV1/FVC < 70 was 6.1 (area under the curve = 0.764, sensitivity = 0.773, specificity = 0.665), while for predicting a visual emphysema grade of moderate or higher, it was 4.7 (area under the curve = 0.802, sensitivity = 0.766, specificity = 0.742). Furthermore, correlation between visual emphysema grading and FEV1/FVC was found. In patients with FEV1/FVC < 70% a high proportion of subjects had emphysema grade 3 (moderate) or higher, whereas in patients with FEV1/FVC ≥ 70%, a larger proportion had emphysema grade 3 (moderate) or lower. The sensitivity for visual emphysema grading predicting a FEV1/FVC < 70% was 56.3% with an optimal cutoff point at a visual grade of 4 (confluent), demonstrating a lower sensitivity compared with LAV% (77.3%).

CONCLUSIONS

A significant correlation between AI-based LAV% and FEV1/FVC as well as visual CT emphysema grades can be found in routine chest CT suggesting that AI-based LAV% measurement might be integrated as an add-on functional parameter in the evaluation of chest CT in the future.

Association between arachidonate lipoxygenase 15,c.-292 C > T gene polymorphism and non-cystic fibrosis bronchiectasis in children: a pilot study on the effects on airway lipoxin A4 and disease phenotype

BACKGROUND

Persistent airway inflammation is a central feature of bronchiectasis. Arachidonate 15-lipoxygenase (ALOX-15) controls production of endogenous lipid mediators, including lipoxins that regulate airway inflammation. Mutations at various positions in ALOX-15 gene can influence airway disease development. We investigated association between ALOX-15,c.-292 C > T gene polymorphism and bronchiectasis unrelated to cystic fibrosis in Egyptian children. Also, lipoxin A4 (LXA4) level in bronchoalveolar lavage (BAL) was studied in relation to polymorphism genotypes and disease phenotypes determined by clinical, pulmonary functions, and radiological severity parameters.

METHODS

This was an exploratory study that included 60 participants. Thirty children with non-cystic fibrosis bronchiectasis (NCFB) were compared with 30 age and sex-matched controls. ALOX-15,c.-292 C > T polymorphism was genotyped using TaqMan-based Real-time PCR. LXA4 was measured in BAL using ELISA method.

RESULTS

There was no significant difference between patients and controls regarding ALOX-15,c.-292 C > T polymorphism genotypes and alleles (OR = 1.75; 95% CI (0.53-5.7), P = 0.35) (OR = 1; 95% CI (0.48-2), p = 1). BAL LXA4 level was significantly lower in patients, median (IQR) of 576.9 (147.6-1510) ng/ml compared to controls, median (IQR) of 1675 (536.8-2542) (p = 0.002). Patients with severe bronchiectasis had a significantly lower LXA4 level (p < 0.001). There were significant correlations with exacerbations frequency (r=-0.54, p = 0.002) and FEV1% predicted (r = 0.64, p = 0.001). Heterozygous CT genotype carriers showed higher LXA4 levels compared to other genotypes(p = 0.005).

CONCLUSIONS

Low airway LXA4 in children with NCFB is associated with severe disease phenotype and lung function deterioration. CT genotype of ALOX-15,c.-292 C > T polymorphism might be a protective genetic factor against bronchiectasis development and/or progression due to enhanced LXA4 production.

The role of chest computed tomography in the evaluation and management of chronic obstructive pulmonary disease

PURPOSE OF REVIEW

The purpose of this review is to compile recent data on the clinical associations of computed tomography (CT) scan findings in the literature and potential avenues for implementation into clinical practice.

RECENT FINDINGS

Airways dysanapsis, emphysema, chronic bronchitis, and pulmonary vascular metrics have all recently been associated with poor chronic obstructive pulmonary disease (COPD) outcomes when controlled for clinically relevant covariables, including risk of mortality in the case of emphysema and chronic bronchitis. Other authors suggest that CT scan may provide insight into both lung parenchymal damage and other clinically important comorbidities in COPD.

SUMMARY

CT scan findings in COPD relate to clinical outcomes. There is a continued need to develop processes to best implement the results of these studies into clinical practice.

Quantitative Computed Tomography Analysis of the Longitudinal Change Between Centrilobular and Paraseptal Emphysema Subtypes: A Retrospective Study

OBJECTIVE

This study aimed to investigate the difference between the extent of centrilobular emphysema (CLE) and paraseptal emphysema (PSE) on follow-up chest CT scans and their relationship to the cross-sectional area (CSA) of small pulmonary vessels.

METHODS

Sixty-two patients (36 CLE and 26 PSE) who underwent 2 chest CT scans were enrolled in this study. The percentage of low attenuation volume (%LAV) and total CSA of the small pulmonary vessels <5 mm 2 (%CSA < 5) were measured at the 2 time points. Analysis of the initial %CSA < 5 and the change in the %LAV and %CSA < 5 on follow-up imaging was performed.

RESULTS

The initial %CSA < 5 was not significantly different between the CLE and the PSE groups (CLE, 0.66 vs. PSE, 0.71; P = 0.78). There was no significant difference in the longitudinal change in the %LAV between the 2 groups (CLE, -0.048% vs. PSE, 0.005%; P = 0.26). The longitudinal change in the %CSA < 5 in patients with PSE significantly decreased compared with those with CLE (CLE, 0.025% vs. PSE, -0.018%; P = 0.02).

CONCLUSIONS

The longitudinal change in the %CSA < 5 was significantly different for patients with CLE and PSE, demonstrating an important pathophysiological difference between the subtypes.

The Role of Pulmonary Function Testing in the Diagnosis and Management of COPD

Pulmonary function testing (PFT) has a long and rich history in the definition, diagnosis, and management of COPD. For decades, spirometry has been regarded as the standard for diagnosing COPD; however, numerous studies have shown that COPD symptoms, pathology, and associated poor outcomes can occur, despite normal spirometry. Diffusing capacity and imaging studies have called into question the need for spirometry to put the "O" (obstruction) in COPD. The role of exercise testing and the ability of PFTs to phenotype COPD are reviewed. Although PFTs play an important role in diagnosis, treatment decisions are primarily determined by symptom intensity and exacerbation history. Although a seminal study positioned FEV1 as the primary predictor of survival, numerous studies have shown that tests other than spirometry are superior predictors of mortality. In years past, using spirometry to screen for COPD was promulgated; however, this only seems appropriate for individuals who are symptomatic and at risk for developing COPD.

Identification of frequent acute exacerbations phenotype in COPD patients based on imaging and clinical characteristics

BACKGROUND

Chronic obstructive pulmonary disease (COPD) is a common disease with high morbidity, with acute exacerbations manifesting as a worsening of respiratory symptoms. This study aimed to identify the frequent acute exacerbation phenotype in patients with COPD based on imaging and clinical characteristics.

METHODS

Patients with COPD (n = 201) were monitored for acute exacerbations one year after their initial hospital admission and further divided into frequent and non-frequent exacerbation groups according to the frequency and severity of acute exacerbations. All patients underwent high resolution CT scans and low attenuation area less than -950Hu (LAA-950) in the whole lung was measured. Differences in visual subtypes, LAA-950, and clinical basic characteristics were compared between groups. The clinical factors influencing frequent exacerbation were determined using binary logistic regression. Finally, based on imaging and clinical factors, the receiver operating characteristic curve was used to identify the phenotype of COPD with frequent acute exacerbations.

RESULTS

Patients with frequent exacerbations had a larger LAA-950 than those non-frequent exacerbations patients (p＜0.001). Frequent acute exacerbations were associated with worsening visual subtypes. Multivariate binary logistic regression illustrated that age, smoking status, BMI, FEV1 pred, and LAA-950 were associated with frequent exacerbations of COPD. The area under the receiver operating characteristic curve for predicting frequent exacerbations based on age, smoking status, BMI, FEV1 pred, and LAA-950 was 0.907 (p＜0.001).

CONCLUSION

The combination of imaging and clinical characteristics reached high diagnostic efficacy in the identification of frequent acute exacerbations in patients with COPD.

Outcomes for the Arthroscopic Treatment of Femoroacetabular Impingement Syndrome With Acetabular Retroversion: A 3D Computed Tomography Analysis

BACKGROUND

Increased attention has been directed toward the acetabular morphology in the management of patients with femoroacetabular impingement syndrome (FAIS). Whether acetabular version influences patient-reported outcomes remains poorly understood.

PURPOSE

To use computed tomography (CT)-based 3-dimensional (3D) bone models to (1) quantify acetabular version in patients with FAIS, (2) compare acetabular version on 3D bone models with current plain radiographic parameters, and (3) explore the relationship between the magnitude of acetabular version and minimum 2-year clinical outcomes after hip arthroscopy.

STUDY DESIGN

Cohort study; Level of evidence, 3.

METHODS

Three-dimensional models of the pelvis and femur were generated by semiautomated segmentation and aligned to a standard coordinate system. Acetabular version was quantified at the 3-o'clock position, and 3 groups were identified: acetabular retroversion (AR; <15°), normal acetabular version (NV; 15°-25°), and acetabular anteversion (AA; >25°). Patient demographic characteristics, plain radiographic parameters, and clinical outcomes were analyzed, including the Hip Outcome Score-Activities of Daily Living, Hip Outcome Score-Sports Subscale, modified Harris Hip Score (mHHS), International Hip Outcome Tool (iHOT-12), and visual analog scale (VAS) for pain and satisfaction.

RESULTS

Preoperative CT scans were acquired in 105 consecutive patients before hip arthroscopy for FAIS, of which 84 (80.0%) completed minimum 2-year patient-reported outcomes. The mean ± SD age and body mass index of patients were 33.9 ± 12.6 years and 26.0 ± 5.4, respectively; 70.2% were female. The number of patients and the mean central acetabular version within each group were as follows: AR (n = 12; 11.3°± 2.7°), NV (n = 56; 20.7°± 2.9°), and AA (n = 16; 28.5°± 2.7°). Posterior wall sign was the only plain radiographic parameter that was significantly more observed in the AR group than in the other 2 groups. At minimum 2-year follow-up, significant between-group differences in the mHHS, iHOT-12, and VAS for pain and satisfaction (P < .05) were appreciated, while post hoc analysis with Bonferroni correction (P < .0167) found lower scores on the mHHS, iHOT-12, and VAS for pain and satisfaction in patients with AR as compared with NV. Lower scores on the VAS for satisfaction were reported in patients with AR when compared with AA (P = .006) but not on the mHHS (P = .023), iHOT-12 (P = .032), or VAS for pain (P = .072).

CONCLUSION

Traditional plain radiographic indices to describe AR, including crossover sign and ischial spine sign, were not reliable in defining AR according to 3D models derived from CT scans. Only the posterior wall sign was observed in a higher proportion in the AR group. Patients with AR demonstrated inferior outcomes when compared with patients with NV and AA after hip arthroscopy for FAIS.

Strain Analysis in Patients at High-Risk for COPD Using Four-Dimensional Dynamic-Ventilation CT

Purpose

To quantitatively identify abnormal lung motion in chronic obstructive pulmonary disease (COPD) using strain analysis, and further clarify the potential differences of deformation in COPD with different severity of airflow limitation.

Materials and Methods

Totally, 53 patients at high-risk for COPD were enrolled in this study. All CT examinations were performed on a 320-row MDCT scanner, and strain measurement based on dynamic-ventilation CT data was performed with a computational fluid dynamics analysis software (Micro Vec V3.6.2). The strain-related parameters derived from the whole expiration phase (PSmax-all, PSmean-all, Speedmax-all ), the first 2s of expiration phase (PSmax2s, PSmean2s, Speedmax2s ) were divided respectively by the changes in lung volume to adjust for the degree of expiration. Spearman rank correlation analysis was used to evaluate associations between the strain-related parameters and various spirometric parameters. Comparisons of the strain-related parameters between COPD and non-COPD patients, between GOLD I (mild airflow restriction) and GOLD II-IV (moderate to severe airflow restriction) were made using the Mann-Whitney U-test. Receiver-operating characteristic (ROC) analysis was performed to evaluate the diagnostic performance of the strain-related parameters for COPD. P <0.05 was considered statistically significant.

Results

Strain-related parameters demonstrated positive correlations with spirometric parameters (ρ=0.275~0.687, P<0.05), suggesting that heterogeneity in lung motion was related to abnormal spirometric results. Strain-related parameters can quantitatively distinguish COPD from non-COPD patients with moderate diagnostic significance with the AUC values ranged from 0.821 to 0.894. Furthermore, parameters of the whole expiration phase (PSmax-all, Speedmax-all) demonstrated significant differences (P=0.005; P=0.04) between COPD patients with mild and moderate to severe airflow limitation.

Conclusion

Strain-related parameters derived from dynamic-ventilation CT data covering the whole lung associated with lung function changes in COPD, reflecting the severity of airflow limitation in some degree, even though its utility in severe COPD patients remains to be investigated.

Diagnostic efficacy of visual subtypes and low attenuation area based on HRCT in the diagnosis of COPD

Background

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease. Current gold standard criteria, pulmonary function tests (PFTs) may result in underdiagnosis of potential COPD patients. Therefore, we hypothesize that the combination of high-resolution computed tomography (HRCT) and clinical basic characteristics will enable the identification of more COPD patients.

Methods

A total of 284 patients with respiratory symptoms who were current or former smokers were included in the study, and were further divided into 5 groups of GOLD grade I–IV and non-COPD according to PFTs. All patients underwent inspiratory HRCT scanning and low attenuation area (LAA) was measured. Then they were divided into seven visual subtypes according to the Fleischner Society classification system. Non-parametric tests were used for exploring differences in basic characteristics and PFTs between different groups of enrolled patients and visual subtypes. Binary logistic regression was to find the influencing factors that affected the patients’ outcome (non-COPD vs GOLD I-IV). The area under the receiver operating characteristic curve (AUC-ROC) was to explore the diagnostic efficacy of LAA, visual subtypes, and combined basic characteristics related to COPD for COPD diagnosis. Finally, based on the cut-off values of ROC analysis, exploring HRCT features in patients who do not meet the diagnostic criteria but clinically suspected COPD.

Results

With the worsening severity of COPD, the visual subtypes gradually progressed (p < 0.01). There was a significant difference in LAA between GOLD II–IV and non-COPD (p < 0.0001). The diagnostic efficacy of LAA, visual subtypes, and LAA combined with visual subtypes for COPD were 0.742, 0.682 and 0.730 respectively. The diagnostic efficacy increased to 0.923–0.943 when basic characteristics were added (all p < 0.001). Based on the cut-off value of ROC analysis, LAA greater than 5.6, worsening of visual subtypes, combined with positive basic characteristics can help identify some potential COPD patients.

Conclusion

The heterogeneous phenotype of COPD requires a combination of multiple evaluation methods. The diagnostic efficacy of combining LAA, visual subtypes, and basic characteristics achieves good consistency with current diagnostic criteria.