Enhancing COPD classification using combined quantitative computed tomography and texture-based radiomics: a CanCOLD cohort study.

Background: Recent advances in texture-based computed tomography (CT) radiomics have demonstrated its potential for classifying COPD. Methods: Participants from the Canadian Cohort Obstructive Lung Disease (CanCOLD) study were evaluated. A total of 108 features were included: eight quantitative CT (qCT), 95 texture-based radiomic and five demographic features. Machine-learning models included demographics along with texture-based radiomics and/or qCT. Combinations of five feature selection and five classification methods were evaluated; a training dataset was used for feature selection and to train the models, and a testing dataset was used for model evaluation. Models for classifying COPD status and severity were evaluated using the area under the receiver operating characteristic curve (AUC) with DeLong's test for comparison. SHapely Additive exPlanations (SHAP) analysis was used to investigate the features selected. Results: A total of 1204 participants were evaluated (n=602 no COPD; n=602 COPD). There were no differences between the groups for sex (p=0.77) or body mass index (p=0.21). For classifying COPD status, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.87) than the combination of demographics and texture-based radiomics (AUC=0.81, p<0.05) or qCT alone (AUC=0.84, p<0.05). Similarly, for classifying COPD severity, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.81) than demographics and texture-based radiomics (AUC=0.72, p<0.05) or qCT alone (AUC=0.79, p<0.05). Texture-based radiomics and qCT features were among the top five features selected (15th percentile of the CT density histogram, CT total airway count, pack-years, CT grey-level distance zone matrix zone distance entropy, CT low-attenuation clusters) for classifying COPD status. Conclusion: Texture-based radiomics and conventional qCT features in combination improve machine­learning models for classification of COPD status and severity.

CT Chest Imaging Using Normalized Join-Count: Predicting Emphysema Progression in the CanCOLD Study.

Background Pre-existing emphysema is recognized as an indicator of future worsening in patients with chronic obstructive pulmonary disease (COPD) when observed through CT imaging. However, it remains uncertain whether additional factors, such as the spatial compactness of CT emphysema, might also serve as predictors of disease progression. Purpose To evaluate the relationship between the compactness of CT emphysema voxels and emphysema progression. Materials and Methods This secondary analysis uses data from the prospective Canadian Cohort Obstructive Lung Disease (CanCOLD) study, examining CT images obtained in participants with and without COPD at baseline and a 3-year follow-up time point (November 2009 to November 2018). Measurements of forced expiratory volume in first second of expiration (FEV1) and diffusing capacity of lung for carbon monoxide (DLco) were collected. The normalized join-count (NJC) measurement from baseline CT images and lung density (LD) changes were analyzed. Emphysema progression was defined as an annualized LD change of less than half an SD below the mean of the participants without COPD with no smoking history. Multivariable linear and logistic regression models were used to assess the association between baseline CT NJC measurements and the annualized change in LD, FEV1, DLco, and emphysema progression versus nonprogression. Results A total of 524 participants (mean age, 66 years ± 10 [SD]; 293 male) (FEV1 percent predicted, 88% ± 19; FEV1/FVC, 67% ± 9; DLco percent predicted, 105% ± 25) were analyzed, 187 (36%) of whom had COPD. CT NJC was associated with the annualized change in LD (P < .001), FEV1 (P = .02), and DLco (P = .01). Additionally, CT NJC predicted emphysema progression versus nonprogression (odds ratio, 2.24; 95% CI: 1.37, 3.50; P < .001). Conclusion The spatial distribution, or "compactness," of CT emphysema voxels predicted emphysema progression in individuals with and without COPD. ClinicalTrials.gov Identifier: NCT00920348 © RSNA, 2024 Supplemental material is available for this article.

Dysanapsis Genetic Risk Predicts Lung Function Across the Lifespan.

Rationale Dysanapsis refers to a mismatch between airway tree caliber and lung size arising early in life. Dysanapsis assessed by computed tomography (CT) is evident by early adulthood and associated with chronic obstructive pulmonary disease (COPD) risk later in life. Objective By examining the genetic factors associated with CT-assessed dysanapsis, we aimed to elucidate its molecular underpinnings and physiological significance across the lifespan. Methods We performed a genome-wide association study (GWAS) of CT-assessed dysanapsis in 11,951 adults, including individuals from two population-based and two COPD-enriched studies. We applied colocalization analysis to integrate GWAS and gene expression data from whole blood and lung. Genetic variants associated with dysanapsis were combined into a genetic risk score that was applied to examine association with lung function in children from a population-based birth cohort (n=1,278) and adults from the UK Biobank (n=369,157). Measurements and Main Results CT-assessed dysanapsis was associated with genetic variants from 21 independent signals in 19 gene regions, implicating HHIP, DSP, and NPNT as potential molecular targets based on colocalization of their expression. Higher dysanapsis genetic risk score was associated with obstructive spirometry among 5 year old children and among adults in the 5th, 6th and 7th decades of life. Conclusions CT-assessed dysanapsis is associated with variation in genes previously implicated in lung development and dysanapsis genetic risk is associated with obstructive lung function from early life through older adulthood. Dysanapsis may represent an endo-phenotype link between the genetic variations associated with lung function and COPD.

Classifying Future Healthcare Utilization in COPD Using Quantitative CT Lung Imaging and Two-Step Feature Selection via Sparse Subspace Learning with the CanCOLD Study.

RATIONALE: Although numerous candidate features exist for predicting risk of higher risk of healthcare utilization in patients with chronic obstructive pulmonary disease (COPD), the process for selecting the most discriminative features remains unclear. OBJECTIVE: The objective of this study was to develop a robust feature selection method to identify the most discriminative candidate features for predicting healthcare utilization in COPD, and compare the model performance with other common feature selection methods. MATERIALS AND METHODS: In this retrospective study, demographic, lung function measurements and CT images were collected from 454 COPD participants from the Canadian Cohort Obstructive Lung Disease study from 2010-2017. A follow-up visit was completed approximately 1.5 years later and participants reported healthcare utilization. CT analysis was performed for feature extraction. A two-step hybrid feature selection method was proposed that utilized: (1) sparse subspace learning with nonnegative matrix factorization, and, (2) genetic algorithm. Seven commonly used feature selection methods were also implemented that reported the top 10 or 20 features for comparison. Performance was evaluated using accuracy. RESULTS: Of the 454 COPD participants evaluated, 161 (35%) utilized healthcare services at follow-up. The accuracy for predicting subsequent healthcare utilization for the seven commonly used feature selection methods ranged from 72%-76% with the top 10 features, and 77%-80% with the top 20 features. Relative to these methods, hybrid feature selection obtained significantly higher accuracy for predicting subsequent healthcare utilization at 82% ± 3% (p < 0.05). Selected features with the proposed method included: DLCO, FEV1, RV, FVC, TAC, LAA950, Pi-10, LAA856, LAC total hole count, outer area RB1, wall area RB1, wall area and Jacobian. CONCLUSION: The hybrid feature selection method identified the most discriminative features for classifying individuals with and without future healthcare utilization, and increased the accuracy compared to other state-of-the-art approaches.

Voltage-Controlled Magnon Transistor via Tuning Interfacial Exchange Coupling.

Magnon transistors that can effectively regulate magnon transport by an electric field are desired for magnonics, which aims to provide a Joule-heating free alternative to the conventional electronics owing to the electric neutrality of magnons (the key carriers of spin-angular momenta in the magnonics). However, also due to their electric neutrality, magnons have no access to directly interact with an electric field and it is thus difficult to manipulate magnon transport by voltages straightforwardly. Here, we demonstrated a gate voltage (V_{g}) applied on a nonmagnetic metal and magnetic insulator (MI) interface that bent the energy band of the MI and then modulated the probability for conduction electrons in the nonmagnetic metal to tunnel into the MI, which can consequently enhance or weaken the spin-magnon conversion efficiency at the interface. A voltage-controlled magnon transistor based on the magnon-mediated electric current drag (MECD) effect in a Pt-Y_{3}Fe_{5}O_{12}-Pt sandwich was then experimentally realized with V_{g} modulating the magnitude of the MECD signal. The obtained efficiency (the change ratio between the MECD voltage at ±V_{g}) reached 10%/(MV/cm) at 300 K. This prototype of magnon transistor offers an effective scheme to control magnon transport by a gate voltage.

Abnormal Exertional Breathlessness on Cardiopulmonary Cycle Exercise Testing in Relation to Self-Reported and Physiologic Responses in Chronic Airflow Limitation.

BACKGROUND: Exertional breathlessness is a cardinal symptom of cardiorespiratory disease. RESEARCH QUESTION: How does breathlessness abnormality, graded using normative reference equations during cardiopulmonary exercise testing (CPET), relate to self-reported and physiologic responses in people with chronic airflow limitation (CAL)? STUDY DESIGN AND METHODS: An analysis was done of people aged ≥ 40 years with CAL undergoing CPET in the Canadian Cohort Obstructive Lung Disease study. Breathlessness intensity ratings (Borg CR10 scale [0-10 category-ratio scale for breathlessness intensity rating]) were evaluated in relation to power output, rate of oxygen uptake, and minute ventilation at peak exercise, using normative reference equations as follows: (1) probability of breathlessness normality (probability of having an equal or greater Borg CR10 rating among healthy people; lower probability reflecting more severe breathlessness) and (2) presence of abnormal breathlessness (rating above the upper limit of normal). Associations with relevant participant-reported and physiologic outcomes were evaluated. RESULTS: We included 330 participants (44% women): mean ± SD age, 64 ± 10 years (range, 40-89 years); FEV1/FVC, 57.3% ± 8.2%; FEV1, 75.6% ± 17.9% predicted. Abnormally low exercise capacity (peak rate of oxygen uptake < lower limit of normal) was present in 26%. Relative to peak power output, rate of oxygen uptake, and minute ventilation, abnormally high breathlessness was present in 26%, 25%, and 18% of participants. For all equations, abnormally high exertional breathlessness was associated with worse lung function, exercise capacity, self-reported symptom burden, physical activity, and health-related quality of life; and greater physiologic abnormalities during CPET. INTERPRETATION: Abnormal breathlessness graded using CPET normative reference equations was associated with worse clinical, physiological, and functional outcomes in people with CAL, supporting construct validity of abnormal exertional breathlessness.

Airway tree caliber heterogeneity and airflow obstruction among older adults.

Smaller mean airway tree caliber is associated with airflow obstruction and chronic obstructive pulmonary disease (COPD). We investigated whether airway tree caliber heterogeneity was associated with airflow obstruction and COPD. Two community-based cohorts (MESA Lung, CanCOLD) and a longitudinal case-control study of COPD (SPIROMICS) performed spirometry and computed tomography measurements of airway lumen diameters at standard anatomical locations (trachea-to-subsegments) and total lung volume. Percent-predicted airway lumen diameters were calculated using sex-specific reference equations accounting for age, height, and lung volume. The association of airway tree caliber heterogeneity, quantified as the standard deviation (SD) of percent-predicted airway lumen diameters, with baseline forced expired volume in 1-second (FEV1), FEV1/forced vital capacity (FEV1/FVC) and COPD, as well as longitudinal spirometry, were assessed using regression models adjusted for age, sex, height, race-ethnicity, and mean airway tree caliber. Among 2,505 MESA Lung participants (means ± SD age: 69 ± 9 yr; 53% female, mean airway tree caliber: 99 ± 10% predicted, airway tree caliber heterogeneity: 14 ± 5%; median follow-up: 6.1 yr), participants in the highest quartile of airway tree caliber heterogeneity exhibited lower FEV1 (adjusted mean difference: -125 mL, 95%CI: -171,-79), lower FEV1/FVC (adjusted mean difference: -0.01, 95%CI: -0.02,-0.01), and higher odds of COPD (adjusted odds ratio: 1.42, 95%CI: 1.01-2.02) when compared with the lowest quartile, whereas longitudinal changes in FEV1 and FEV1/FVC did not differ significantly. Observations in CanCOLD and SPIROMICS were consistent. Among older adults, airway tree caliber heterogeneity was associated with airflow obstruction and COPD at baseline but was not associated with longitudinal changes in spirometry.NEW & NOTEWORTHY In this study, by leveraging two community-based samples and a case-control study of heavy smokers, we show that among older adults, airway tree caliber heterogeneity quantified by CT is associated with airflow obstruction and COPD independent of age, sex, height, race-ethnicity, and dysanapsis. These observations suggest that airway tree caliber heterogeneity is a structural trait associated with low baseline lung function and normal decline trajectory that is relevant to COPD.

A fully automated pipeline for the extraction of pectoralis muscle area from chest computed tomography scans.

Background: Computed tomography (CT)-derived pectoralis muscle area (PMA) measurements are prognostic in people with or at-risk of COPD, but fully automated PMA extraction has yet to be developed. Our objective was to develop and validate a PMA extraction pipeline that can automatically: 1) identify the aortic arch slice; and 2) perform pectoralis segmentation at that slice. Methods: CT images from the Canadian Cohort of Obstructive Lung Disease (CanCOLD) study were used for pipeline development. Aorta atlases were used to automatically identify the slice containing the aortic arch by group-based registration. A deep learning model was trained to segment the PMA. The pipeline was evaluated in comparison to manual segmentation. An external dataset was used to evaluate generalisability. Model performance was assessed using the Dice-Sorensen coefficient (DSC) and PMA error. Results: In total 90 participants were used for training (age 67.0±9.9 years; forced expiratory volume in 1 s (FEV1) 93±21% predicted; FEV1/forced vital capacity (FVC) 0.69±0.10; 47 men), and 32 for external testing (age 68.6±7.4 years; FEV1 65±17% predicted; FEV1/FVC 0.50±0.09; 16 men). Compared with manual segmentation, the deep learning model achieved a DSC of 0.94±0.02, 0.94±0.01 and 0.90±0.04 on the true aortic arch slice in the train, validation and external test sets, respectively. Automated aortic arch slice detection obtained distance errors of 1.2±1.3 mm and 1.6±1.5 mm on the train and test data, respectively. Fully automated PMA measurements were not different from manual segmentation (p>0.05). PMA measurements were different between people with and without COPD (p=0.01) and correlated with FEV1 % predicted (p<0.05). Conclusion: A fully automated CT PMA extraction pipeline was developed and validated for use in research and clinical practice.

[The cases of tracing the source of patients infected with Omicron variant of SARS-CoV-2 based on wastewater-based epidemiology in Shenzhen].

Wastewater-based epidemiology (WBE) is an emerging discipline, which has been applied to drug abuse tracking and infectious disease pathogen surveillance. During the COVID-19 epidemic, WBE has been applied to monitor the epidemic trend and SARS-CoV-2 variants etc. In order to detect hidden COVID-19 cases and prevent transmission in the community, wastewater surveillance system for monitoring SARS-CoV-2 RNA was developed in Shenzhen. The sewage sampling sites were set up in key places such as the port areas, urban villages and residential communities of Futian, Nanshan, Luohu and Yantian districts. From July 26 to November 30, 2022, a total of 369 sewage sampling sites were set up, covering 1.93 million people. Continuous sampling was carried out for 3 hours in the peak period of water use every day. Sewage virus enrichment and SARS-CoV-2 nucleic acid detection were carried out by polyethylene glycol precipitation method and RT-qPCR, and a positive water sample disposal process was molded. This article aims to introduce the case of source tracing of COVID-19 infected patients based on urban sewage in Shenzhen. The sewage monitoring of Honghu water treatment plant in Luohu District played an early warning role, and the source of infection was traced. In the disposal of positive water samples in Futian South Road, Futian District, the important experience of monitoring point layout was obtained. In the sewage monitoring of Nanshan village, Nanshan District, the existence of occult infection was revealed. Sharing the experience of tracing the source of COVID-19 patients to avoid the spread of COVID-19 in the community based on wastewater surveillance of SARS-CoV-2 RNA in Shenzhen, and summarizing the advantages and application prospects of sewage surveillance can provide new ideas for monitoring emerging or re-emerging pathogens that are known to exhibit gastrointestinal excretion in the future.

Physiological Characterization of Preserved Ratio Impaired Spirometry in the CanCOLD Study: Implications for Exertional Dyspnea and Exercise Intolerance.

Rationale: It is increasingly recognized that adults with preserved ratio impaired spirometry (PRISm) are prone to increased morbidity. However, the underlying pathophysiological mechanisms are unknown. Objectives: Evaluate the mechanisms of increased dyspnea and reduced exercise capacity in PRISm. Methods: We completed a cross-sectional analysis of the CanCOLD (Canadian Cohort Obstructive Lung Disease) population-based study. We compared physiological responses in 59 participants meeting PRISm spirometric criteria (post-bronchodilator FEV1 < 80% predicted and FEV1/FVC ⩾ 0.7), 264 control participants, and 170 ever-smokers with chronic obstructive pulmonary disease (COPD), at rest and during cardiopulmonary exercise testing. Measurements and Main Results: Individuals with PRISm had lower total lung, vital, and inspiratory capacities than healthy controls (all P < 0.05) and minimal small airway, pulmonary gas exchange, and radiographic parenchymal lung abnormalities. Compared with healthy controls, individuals with PRISm had higher dyspnea/[Formula: see text]o2 ratio at peak exercise (4.0 ± 2.2 vs. 2.9 ± 1.9 Borg units/L/min; P < 0.001) and lower [Formula: see text]o2peak (74 ± 22% predicted vs. 96 ± 25% predicted; P < 0.001). At standardized submaximal work rates, individuals with PRISm had greater Vt/inspiratory capacity (Vt%IC; P < 0.001), reflecting inspiratory mechanical constraint. In contrast to participants with PRISm, those with COPD had characteristic small airways dysfunction, dynamic hyperinflation, and pulmonary gas exchange abnormalities. Despite these physiological differences among the three groups, the relationship between increasing dyspnea and Vt%IC during cardiopulmonary exercise testing was similar. Resting IC significantly correlated with [Formula: see text]o2peak (r = 0.65; P < 0.001) in the entire sample, even after adjusting for airflow limitation, gas trapping, and diffusing capacity. Conclusions: In individuals with PRISm, lower exercise capacity and higher exertional dyspnea than healthy controls were mainly explained by lower resting lung volumes and earlier onset of dynamic inspiratory mechanical constraints at relatively low work rates. Clinical trial registered with www.clinicaltrials.gov (NCT00920348).

Prevalence of chronic cough, its risk factors and population attributable risk in the Burden of Obstructive Lung Disease (BOLD) study: a multinational cross-sectional study.

Background: Chronic cough is a common respiratory symptom with an impact on daily activities and quality of life. Global prevalence data are scarce and derive mainly from European and Asian countries and studies with outcomes other than chronic cough. In this study, we aimed to estimate the prevalence of chronic cough across a large number of study sites as well as to identify its main risk factors using a standardised protocol and definition. Methods: We analysed cross-sectional data from 33,983 adults (≥40 years), recruited between Jan 2, 2003 and Dec 26, 2016, in 41 sites (34 countries) from the Burden of Obstructive Lung Disease (BOLD) study. We estimated the prevalence of chronic cough for each site accounting for sampling design. To identify risk factors, we conducted multivariable logistic regression analysis within each site and then pooled estimates using random-effects meta-analysis. We also calculated the population attributable risk (PAR) associated with each of the identifed risk factors. Findings: The prevalence of chronic cough varied from 3% in India (rural Pune) to 24% in the United States of America (Lexington,KY). Chronic cough was more common among females, both current and passive smokers, those working in a dusty job, those with a history of tuberculosis, those who were obese, those with a low level of education and those with hypertension or airflow limitation. The most influential risk factors were current smoking and working in a dusty job. Interpretation: Our findings suggested that the prevalence of chronic cough varies widely across sites in different world regions. Cigarette smoking and exposure to dust in the workplace are its major risk factors. Funding: Wellcome Trust.

Normative Reference Equations for Breathlessness Intensity during Incremental Cardiopulmonary Cycle Exercise Testing.

Rationale: Cardiopulmonary exercise testing (CPET) is the gold standard to evaluate exertional breathlessness, a common and disabling symptom. However, the interpretation of breathlessness responses to CPET is limited by a scarcity of normative data. Objectives: We aimed to develop normative reference equations for breathlessness intensity (Borg 0-10 category ratio) response in men and women aged ⩾40 years during CPET, in relation to power output (watts), oxygen uptake, and minute ventilation. Methods: Analysis of ostensibly healthy people aged ⩾40 years undergoing symptom-limited incremental cycle CPET (10 W/min) in the CanCOLD (Canadian Cohort Obstructive Lung Disease) study. Participants had smoking histories <5 pack-years and normal lung function and exercise capacity. The probability of each Borg 0-10 category ratio breathlessness intensity rating by power output, oxygen uptake, and minute ventilation (as an absolute or a relative value [percentage of predicted maximum]) was predicted using ordinal multinomial logistic regression. Model performance was evaluated by fit, calibration, and discrimination (C statistic) and externally validated in an independent sample (n = 86) of healthy Canadian adults. Results: We included 156 participants (43% women) from CanCOLD; the mean age was 65 (range, 42-91) years, and the mean body mass index was 26.3 (standard deviation, 3.8) kg/m2. Reference equations were developed for women and men separately, accounting for age and/or body mass. Model performance was high across all equations, including in the validation sample (C statistic for men = 0.81-0.92, C statistic for women = 0.81-0.96). Conclusions: Normative reference equations are provided to compare exertional breathlessness intensity ratings among individuals or groups and to identify and quantify abnormal breathlessness responses (scores greater than the upper limit of normal) during CPET.

Dysanapsis is not associated with exertional dyspnoea in healthy male and female never-smokers aged 40 years and older.

In healthy adults, airway-to-lung (i.e., dysanapsis) ratio is lower and dyspnoea during exercise at a given minute ventilation (V̇E) is higher in females than in males. We investigated the relationship between dysanapsis and sex on exertional dyspnoea in healthy adults. We hypothesized that females would have a smaller airway-to-lung ratio than males and that exertional dyspnoea would be associated with airway-to-lung ratio in males and females. We analyzed data from n = 100 healthy never-smokers aged ≥40 years enrolled in the Canadian Cohort Obstructive Lung Disease (CanCOLD) study who underwent pulmonary function testing, a chest computed tomography scan, and cardiopulmonary exercise testing. The luminal area of the trachea, right main bronchus, left main bronchus, right upper lobe, bronchus intermedius, left upper lobe, and left lower lobe were 22%-37% smaller (all p < 0.001) and the airway-to-lung ratio (i.e., average large conducting airway diameter relative to total lung capacity) was lower in females than in males (0.609 ± 0.070 vs. 0.674 ± 0.082; p < 0.001). During exercise, there was a significant effect of V̇E, sex, and their interaction on dyspnoea (all p < 0.05), indicating that dyspnoea increased as a function of V̇E to a greater extent in females than in males. However, after adjusting for age and total lung capacity, there were no significant associations between airway-to-lung ratio and measures of exertional dyspnoea, regardless of sex (all r < 0.34; all p > 0.05). Our findings suggest that sex differences in airway size do not contribute to sex differences in exertional dyspnoea.

The modified Borg/6-min walk distance ratio: a method to assess exertional breathlessness and leg discomfort using the 6-min walk test.

Background: The 6-min walk test (6MWT) is widely used to assess exercise capacity across chronic health conditions, but is currently not useful to assess symptoms, as the scores do not account for the 6-min walk distance (6MWD). We aimed to 1) develop normative reference equations for breathlessness and leg discomfort intensity expressed as modified Borg (mBorg)/6MWD ratios; and 2) validate the equations in people with COPD. Methods: Analysis of people aged ≥40 years who performed two 6MWTs (on a 20-m course) in the Canadian Cohort Obstructive Lung Disease (CanCOLD) study: a healthy cohort (n=291; mean±sd age 67.5±9.4 years; 54% male) with normal 6MWD and lung function, and a COPD cohort (n=156; age 66.2±9.0 years; 56% male; forced expiratory volume in 1 s (FEV1)/forced vital capacity 56.6±8.2%; FEV1 74.4±18.6% pred). The mBorg score was calculated as the Borg 0-10 category ratio intensity rating of breathlessness or leg discomfort recorded at the end of the 6MWT +1 (range 1-11), to avoid zeros and yield ratios proportional to the symptom score and 6MWD-1. Results: Using data from the healthy cohort, sex-specific normative reference equations for breathlessness and leg discomfort mBorg/6MWD ratios were developed using multivariable linear regression, accounting for age, and body mass or body mass index. In the COPD cohort, abnormal breathlessness and leg discomfort (mBorg/6MWD>upper limit of normal) showed strong concurrent validity with worse airflow limitation, Medical Research Council breathlessness and COPD Assessment Test scores. Conclusion: Normative references for the mBorg/6MWD ratio are presented to assess breathlessness and leg discomfort responses to the 6MWT in COPD.

CT Imaging With Machine Learning for Predicting Progression to COPD in Individuals at Risk.

BACKGROUND: Identifying individuals at risk of progressing to COPD may allow for initiation of treatment to potentially slow the progression of the disease or the selection of subgroups for discovery of novel interventions. RESEARCH QUESTION: Does the addition of CT imaging features, texture-based radiomic features, and established quantitative CT scan to conventional risk factors improve the performance for predicting progression to COPD in individuals who smoke with machine learning? STUDY DESIGN AND METHODS: Participants at risk (individuals who currently or formerly smoked, without COPD) from the Canadian Cohort Obstructive Lung Disease (CanCOLD) population-based study underwent CT imaging at baseline and spirometry at baseline and follow-up. Various combinations of CT scan features, texture-based CT scan radiomics (n = 95), and established quantitative CT scan (n = 8), as well as demographic (n = 5) and spirometry (n = 3) measurements, with machine learning algorithms were evaluated to predict progression to COPD. Performance metrics included the area under the receiver operating characteristic curve (AUC) to evaluate the models. DeLong test was used to compare the performance of the models. RESULTS: Among the 294 at-risk participants who were evaluated (mean age, 65.6 ± 9.2 years; 42% female; mean pack-years, 17.9 ± 18.7), 52 participants (23.7%) in the training data set and 17 participants (23.0%) in the testing data set progressed to spirometric COPD at follow-up (2.5 ± 0.9 years from baseline). Compared with machine learning models with demographics alone (AUC, 0.649), the addition of CT imaging features to demographics (AUC, 0.730; P < .05) or CT imaging features and spirometry to demographics (AUC, 0.877; P < .05) significantly improved the performance for predicting progression to COPD. INTERPRETATION: Heterogeneous structural changes occur in the lungs of individuals at risk that can be quantified using CT imaging features, and evaluation of these features together with conventional risk factors improves performance for predicting progression to COPD.

Efficient Spin-to-Charge Conversion via Altermagnetic Spin Splitting Effect in Antiferromagnet RuO_{2}.

The relativistic spin Hall effect and inverse spin Hall effect enable the efficient generation and detection of spin current. Recently, a nonrelativistic altermagnetic spin splitting effect (ASSE) has been theoretically and experimentally reported to generate time-reversal-odd spin current with controllable spin polarization in antiferromagnet RuO_{2}. The inverse effect, electrical detection of spin current via ASSE, still remains elusive. Here we show the spin-to-charge conversion stemming from ASSE in RuO_{2} by the spin Seebeck effect measurements. Unconventionally, the spin Seebeck voltage can be detected even when the injected spin current is polarized along the directions of either the voltage channel or the thermal gradient, indicating the successful conversion of x- and z-spin polarizations into the charge current. The crystal axes-dependent conversion efficiency further demonstrates that the nontrivial spin-to-charge conversion in RuO_{2} is ascribed to ASSE, which is distinct from the magnetic or antiferromagnetic inverse spin Hall effects. Our finding not only advances the emerging research landscape of altermagnetism, but also provides a promising pathway for the spin detection.

The association of spirometric small airways obstruction with respiratory symptoms, cardiometabolic diseases, and quality of life: results from the Burden of Obstructive Lung Disease (BOLD) study.

BACKGROUND: Spirometric small airways obstruction (SAO) is common in the general population. Whether spirometric SAO is associated with respiratory symptoms, cardiometabolic diseases, and quality of life (QoL) is unknown. METHODS: Using data from the Burden of Obstructive Lung Disease study (N = 21,594), we defined spirometric SAO as the mean forced expiratory flow rate between 25 and 75% of the FVC (FEF25-75) less than the lower limit of normal (LLN) or the forced expiratory volume in 3 s to FVC ratio (FEV3/FVC) less than the LLN. We analysed data on respiratory symptoms, cardiometabolic diseases, and QoL collected using standardised questionnaires. We assessed the associations with spirometric SAO using multivariable regression models, and pooled site estimates using random effects meta-analysis. We conducted identical analyses for isolated spirometric SAO (i.e. with FEV1/FVC ≥ LLN). RESULTS: Almost a fifth of the participants had spirometric SAO (19% for FEF25-75; 17% for FEV3/FVC). Using FEF25-75, spirometric SAO was associated with dyspnoea (OR = 2.16, 95% CI 1.77-2.70), chronic cough (OR = 2.56, 95% CI 2.08-3.15), chronic phlegm (OR = 2.29, 95% CI 1.77-4.05), wheeze (OR = 2.87, 95% CI 2.50-3.40) and cardiovascular disease (OR = 1.30, 95% CI 1.11-1.52), but not hypertension or diabetes. Spirometric SAO was associated with worse physical and mental QoL. These associations were similar for FEV3/FVC. Isolated spirometric SAO (10% for FEF25-75; 6% for FEV3/FVC), was also associated with respiratory symptoms and cardiovascular disease. CONCLUSION: Spirometric SAO is associated with respiratory symptoms, cardiovascular disease, and QoL. Consideration should be given to the measurement of FEF25-75 and FEV3/FVC, in addition to traditional spirometry parameters.

Quantitative computed tomography and visual emphysema scores: association with lung function decline.

Background: Computed tomography (CT) visual emphysema score is a better predictor of mortality than single quantitative CT emphysema measurements in COPD, but there are numerous CT measurements that reflect COPD-related disease features. The purpose of this study was to determine if linear combinations of quantitative CT measurements by principal component analysis (PCA) have a greater association with forced expiratory volume in 1 s (FEV1) lower limit of normal (LLN) annualised change (ΔFEV1) than visual emphysema score in COPD. Methods: In this retrospective, longitudinal study, demographic, spirometry and CT images were acquired. CT visual emphysema score and quantitative analysis were performed; low attenuation area <950 HU (LAA950) and 12 other quantitative CT measurements were investigated. PCA was used for CT feature extraction. Multiple linear regression models for baseline FEV1 LLN and 6-year ΔFEV1 were used to determine associations with visual emphysema score and CT measurements. A total of 725 participants were analysed (n=299 never-smokers, n=242 at-risk and n=184 COPD). Results: Quantitative CT measures (LAA950 and PCA components) were independently statistically significant (p<0.05) in predicting baseline FEV1 LLN, whereas visual emphysema score was not statistically significant in any baseline model. When predicting 6-year ΔFEV1, only visual emphysema score was significant (p<0.05) in models with LAA950 and PCA combination of emphysema measurements. In the model with PCA using all CT measurements predicting 6-year ΔFEV1, visual emphysema score (p=0.021) along with one PCA component (p=0.004) were statistically significant. Conclusions: PCA with a combination of CT measurements reflecting several different COPD-related disease features independently predicted baseline lung function and increased the relative importance of quantitative CT compared with visual emphysema score for predicting lung function decline.

Factors Associated with Attrition in a Longitudinal Cohort of Older Adults in the Community.

Introduction: Retaining participants in longitudinal studies increases their power. We undertook this study in a population-based longitudinal cohort of adults with COPD to determine the factors associated with increased cohort attrition. Methods: In the longitudinal population-based Canadian Cohort of Obstructive Lung Disease (CanCOLD) study, 1561 adults > 40 years old were randomly recruited from 9 urban sites. Participants completed in-person visits at 18-month intervals and also were followed up every 3 months over the phone or by email. The cohort retention for the study and the reasons for attrition were analyzed. Hazard ratios and robust standard errors were calculated using Cox regression methods to explore the associations between participants who remained in the study and those who did not. Results: The median follow-up (years) of the study is 9.0 years. The overall mean retention was 77%. Reasons for attrition (23%) were: dropout by participant (39%), loss of contact (27%), investigator-initiated withdrawal (15%), deaths (9%), serious disease (9%), and relocation (2%). Factors independently associated with attrition were lower educational attainment, higher pack-year tobacco consumption, diagnosed cardiovascular disease, and a higher Hospital Anxiety and Depression Scale score: adjusted hazard ratios (95% confidence interval) were 1.43(1.11, 1.85); 1.01(1.00, 1.01); 1.44(1.13, 1.83); 1.06(1.02, 1.10) respectively. Conclusions: Identification and awareness of risk factors for attrition could direct targeted retention strategies in longitudinal studies. Moreover, the identification of patient characteristics associated with study dropout could address any potential bias introduced by differential dropouts.