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Chest CT provides a way to quantify pulmonary airway and vascular tree measurements. In patients with COPD, CT airway measurement differences in females are concomitant with worse quality-of-life and other outcomes. CT total airway count (TAC), airway lumen area (LA), and wall thickness (WT) also differ in females with long-COVID. Our objective was to evaluate CT airway and pulmonary vascular and quality-of-life measurements in females with COPD as compared to ex-smokers and patients with long-COVID. Chest CT was acquired 3-months post-COVID-19 infection in females with long-COVID for comparison with the same inspiratory CT in female ex-smokers and COPD patients. TAC, LA, WT, and pulmonary vascular measurements were quantified. Linear regression models were adjusted for confounders including age, height, body-mass-index, lung volume, pack-years and asthma diagnosis. Twenty-one females (53 ± 14 years) with long-COVID, 17 female ex-smokers (69 ± 9 years) and 13 female COPD (67 ± 6 years) patients were evaluated. In the absence of differences in quality-of-life scores, females with long-COVID reported significantly different LA ( p  = 0.006) compared to ex-smokers but not COPD ( p  = 0.7); WT% was also different compared to COPD ( p  = 0.009) but not ex-smokers ( p  = 0.5). In addition, there was significantly greater pulmonary small vessel volume (BV 5 ) in long-COVID as compared to female ex-smokers ( p  = 0.045) and COPD ( p  = 0.003) patients and different large (BV 10 ) vessel volume as compared to COPD ( p  = 0.03). In females with long-COVID and highly abnormal quality-of-life scores, there was CT evidence of airway remodelling, similar to ex-smokers and patients with COPD, but there was no evidence of pulmonary vascular remodelling. Clinical Trial Registration: www.clinicaltrials.gov NCT05014516 and NCT02279329.

Rationale and Objectives: Hyperpolarized 129 Xe MRI quantifies ventilation-defect-percent (VDP), the ratio of 129 Xe signal-void to the anatomic 1 H MRI thoracic-cavity-volume. VDP is associated with airway inflammation and disease control and serves as a treatable trait in therapy studies. Semi-automated VDP pipelines require time-intensive observer interactions. Current convolutional neural network (CNN) approaches for quantifying VDP lack external validation, which limits multicenter utilization. Our objective was to develop an automated and externally validated deep-learning pipeline to quantify pulmonary 129 Xe MRI VDP., Materials and Methods: 1 H and 129 Xe MRI data from the primary site (Site1) were used to train and test a CNN segmentation and registration pipeline, while two independent sites (Site2 and Site3) provided external validation. Semi-automated and CNN-based registration error was measured using mean-absolute-error (MAE) while segmentation error was measured using generalized-Dice-similarity coefficient (gDSC). CNN and semi-automated VDP were compared using linear regression and Bland-Altman analysis., Results: Training/testing used data from 205 participants (healthy volunteers, asthma, COPD, long-COVID; mean age=54 ± 16y; 119 females) from Site1. External validation used data from 71 participants. CNN and semi-automated 1 H and 129 Xe registrations agreed (MAE=0.3°, R 2 =0.95 rotation; 1.1%, R 2 =0.79 scaling; 0.2/0.5px, R 2 =0.96/0.95, x/y-translation; all p < .001). Thoracic-cavity and ventilation segmentations were also spatially corresponding (gDSC=0.92 and 0.88, respectively). CNN VDP correlated with semi-automated VDP (Site1 R 2 /ρ = .97/.95, bias=-0.5%; Site2 R 2 /ρ = .85/.93, bias=-0.9%; Site3 R 2 /ρ = .95/.89, bias=-0.8%, all p < .001)., Conclusion: An externally validated CNN registration/segmentation model demonstrated strong agreement with low error compared to the semi-automated method. CNN and semi-automated registrations, thoracic-cavity-volume and ventilation-volume segmentations were highly correlated with high gDSC for the datasets., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Rationale and Objectives: It remains difficult to predict longitudinal outcomes in long-COVID, even with chest CT and functional MRI. 129 Xe MRI reflects airway dysfunction, measured using ventilation defect percent (VDP) and in long-COVID patients, MRI VDP was abnormal, suggestive of airways disease. While MRI VDP and quality-of-life improved 15-month post-COVID infection, both remained abnormal. To better understand the relationship of airways disease and quality-of-life improvements in patients with long-COVID, we extracted 129 Xe ventilation MRI textures and generated machine-learning models in an effort to predict improved quality-of-life, 15-month post-infection., Materials and Methods: Long-COVID patients provided written-informed consent to 3-month and 15-month post-infection visits. Pyradiomics was used to extract 129 Xe ventilation MRI texture features, which were ranked using a Random-Forest classifier. Top-ranking features were used in classification models to dichotomize patients based on St. George's Respiratory Questionnaire (SGRQ) score improvement greater than the minimal-clinically-important-difference (MCID). Classification performance was evaluated using the area under the receiver-operator-characteristic-curve (AUC), sensitivity, and specificity., Results: 120 texture features were extracted from 129 Xe ventilation MRI in 44 long-COVID participants (54 ± 14 years), including 30 (52 ± 12 years) with ΔSGRQ≥MCID and 14 (58 ± 18 years) with ΔSGRQ129 Xe MRI ventilation textures explained improved SGRQ-scores 12 months later, and outperformed clinical models. Their unique spatial-intensity information helps build our understanding about long-COVID airway dysfunction., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Grace Parraga reports financial support was provided by Ontario Ministry of Health and Long-Term Care. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Financial/Nonfinancial Disclosures None declared.

Purpose: Our objective was to train machine-learning algorithms on hyperpolarized He 3 magnetic resonance imaging (MRI) datasets to generate models of accelerated lung function decline in participants with and without chronic-obstructive-pulmonary-disease. We hypothesized that hyperpolarized gas MRI ventilation, machine-learning, and multivariate modeling could be combined to predict clinically-relevant changes in forced expiratory volume in 1 s ( FEV 1 ) across 3 years., Approach: Hyperpolarized He 3 MRI was acquired using a coronal Cartesian fast gradient recalled echo sequence with a partial echo and segmented using a k-means clustering algorithm. A maximum entropy mask was used to generate a region-of-interest for texture feature extraction using a custom-developed algorithm and the PyRadiomics platform. The principal component and Boruta analyses were used for feature selection. Ensemble-based and single machine-learning classifiers were evaluated using area-under-the-receiver-operator-curve and sensitivity-specificity analysis., Results: We evaluated 88 ex-smoker participants with 31 ± 7 months follow-up data, 57 of whom (22 females/35 males, 70 ± 9 years) had negligible changes in FEV 1 and 31 participants (7 females/24 males, 68 ± 9 years) with worsening FEV 1 ≥ 60    mL / year . In addition, 3/88 ex-smokers reported a change in smoking status. We generated machine-learning models to predict FEV 1 decline using demographics, spirometry, and texture features, with the later yielding the highest classification accuracy of 81%. The combined model (trained on all available measurements) achieved the overall best classification accuracy of 82%; however, it was not significantly different from the model trained on MRI texture features alone., Conclusion: For the first time, we have employed hyperpolarized He 3 MRI ventilation texture features and machine-learning to identify ex-smokers with accelerated decline in FEV 1 with 82% accuracy., (© 2024 The Authors.)

Rationale and Objectives: Ex-smokers without spirometry or CT evidence of chronic obstructive pulmonary disease (COPD) but with mildly abnormal diffusing capacity of the lungs for carbon monoxide (DL CO ) are at higher risk of developing COPD. It remains difficult to make clinical management decisions for such ex-smokers without other objective assessments consistent with COPD. Hence, our objective was to develop a machine-learning and CT texture-analysis pipeline to dichotomize ex-smokers with normal and abnormal DL CO (DL CO ≥75% pred and DL CO <75% pred )., Materials and Methods: In this retrospective study, 71 ex-smokers (50-85yrs) without COPD underwent spirometry, plethysmography, thoracic CT, and 3 He MRI to generate ventilation defect percent (VDP) and apparent diffusion coefficients (ADC). PyRadiomics was utilized to extract 496 CT texture-features; Boruta and principal component analysis were used for feature selection and various models were investigated for classification. Machine-learning classifiers were evaluated using area under the receiver operator characteristic curve (AUC), sensitivity, specificity, and F1-measure., Results: Of 71 ex-smokers without COPD, 29 with mildly abnormal DL CO had significantly different MRI ADC (p < .001), residual-volume to total-lung-capacity ratio (p = .003), St. George's Respiratory Questionnaire (p = .029), and six-minute-walk distance (6MWD) (p < .001), but similar relative area of the lung < -950 Hounsfield-units (RA 950 ) (p = .9) compared to 42 ex-smokers with normal DL CO . Logistic-regression machine-learning mixed-model trained on selected texture-features achieved the best classification accuracy of 87%. All clinical and imaging measurements were outperformed by high-high-pass filter high-gray-level-run-emphasis texture-feature (AUC=0.81), which correlated with DL CO (ρ = -0.29, p = .02), MRI ADC (ρ = 0.23, p = .048), and 6MWD (ρ = -0.25, p = .02)., Conclusion: In ex-smokers with no CT evidence of emphysema, machine-learning models exclusively trained on CT texture-features accurately classified ex-smokers with abnormal diffusing capacity, outperforming conventional quantitative CT measurements., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Grace Parraga reports a relationship with Natural Sciences and Engineering Research Council of Canada that includes: funding grants. Grace Parraga reports a relationship with Canadian Institutes of Health Research that includes: funding grants. Maksym Sharma reports a relationship with Natural Sciences and Engineering Research Council of Canada that includes: funding grants. Miranda Kirby reports a relationship with Natural Sciences and Engineering Research Council of Canada that includes: funding grants., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Recent years have witnessed major advances in lung imaging in patients with COPD. These include significant refinements in images obtained by computed tomography (CT) scans together with the introduction of new techniques and software that aim for obtaining the best image whilst using the lowest possible radiation dose. Magnetic resonance imaging (MRI) has also emerged as a useful radiation-free tool in assessing structural and more importantly functional derangements in patients with well-established COPD and smokers without COPD, even before the existence of overt changes in resting physiological lung function tests. Together, CT and MRI now allow objective quantification and assessment of structural changes within the airways, lung parenchyma and pulmonary vessels. Furthermore, CT and MRI can now provide objective assessments of regional lung ventilation and perfusion, and multinuclear MRI provides further insight into gas exchange; this can help in structured decisions regarding treatment plans. These advances in chest imaging techniques have brought new insights into our understanding of disease pathophysiology and characterising different disease phenotypes. The present review discusses, in detail, the advances in lung imaging in patients with COPD and how structural and functional imaging are linked with common resting physiological tests and important clinical outcomes., Competing Interests: Conflict of interest: A.F. Elbehairy has nothing to disclose. H. Marshall reports research funding from GlaxoSmithKline and meeting expenses from AstraZeneca. J.H. Naish has a part-time appointment with Bioxydyn Ltd. J.M. Wild is funded by the UKRI, NIHR, MRC and NIHR Sheffield Biomedical Research Centre, has investigator-led research funding from GlaxoSmithKline and AstraZeneca, and has provided consultancy for Vertex, Boehringer Ingelheim and AstraZeneca. G. Parraga acknowledges study funding from GlaxoSmithKline and AstraZeneca, honoraria from GlaxoSmithKline, AstraZeneca and Polarean, and travel support from GlaxoSmithKline and Polarean. A. Horsley reports personal fees from Vertex Pharmaceuticals and Mylan Pharmaceuticals, consulting fees from Vertex Pharmaceuticals, Boehringer Ingelheim and Roche Genentech, grants from JP Moulton Charitable Trust, EPSRC, CF Trust, Cystic Fibrosis Foundation and NIHR, and leadership roles with the Translational Research Collaboration and CF Trust Clinical Trials Accelerator Platform, outside the submitted work. J. Vestbo reports personal fees from ALK-Abelló, AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline and Teva, outside the submitted work. A. Horsley and J. Vestbo are supported by the NIHR Manchester Biomedical Research Centre and Clinical Research Facility., (Copyright ©The authors 2024. For reproduction rights and permissions contact permissions@ersnet.org.)

The respiratory consequences of acute COVID-19 infection and related symptoms tend to resolve 4 weeks post-infection. However, for some patients, new, recurrent, or persisting symptoms remain beyond the acute phase and persist for months, post-infection. The symptoms that remain have been referred to as long-COVID. A number of research sites employed 129 Xe magnetic resonance imaging (MRI) during the pandemic and evaluated patients post-infection, months after hospitalization or home-based care as a way to better understand the consequences of infection on 129 Xe MR gas-exchange and ventilation imaging. A systematic review and comprehensive search were employed using MEDLINE via PubMed (April 2023) using the National Library of Medicine's Medical Subject Headings and key words: post-COVID-19, MRI, 129 Xe, long-COVID, COVID pneumonia, and post-acute COVID-19 syndrome. Fifteen peer-reviewed manuscripts were identified including four editorials, a single letter to the editor, one review article, and nine original research manuscripts (2020-2023). MRI and MR spectroscopy results are summarized from these prospective, controlled studies, which involved small sample sizes ranging from 9 to 76 participants. Key findings included: 1) 129 Xe MRI gas-exchange and ventilation abnormalities, 3 months post-COVID-19 infection, and 2) a combination of MRI gas-exchange and ventilation abnormalities alongside persistent symptoms in patients hospitalized and not hospitalized for COVID-19, 1-year post-infection. The persistence of respiratory symptoms and 129 Xe MRI abnormalities in the context of normal or nearly normal pulmonary function test results and chest computed tomography (CT) was consistent. Longitudinal improvements were observed in long-term follow-up of long-COVID patients but mean 129 Xe gas-exchange, ventilation heterogeneity values and symptoms remained abnormal, 1-year post-infection. Pulmonary functional MRI using inhaled hyperpolarized 129 Xe gas has played a role in detecting gas-exchange and ventilation abnormalities providing complementary information that may help develop our understanding of the root causes of long-COVID. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 5., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Pulmonary imaging measurements using magnetic resonance imaging (MRI) and computed tomography (CT) have the potential to deepen our understanding of chronic obstructive pulmonary disease (COPD) by measuring airway and parenchymal pathologic information that cannot be provided by spirometry. Currently, MRI and CT measurements are not included in mortality risk predictions, diagnosis, or COPD staging. We evaluated baseline pulmonary function, MRI and CT measurements alongside imaging texture-features to predict 10-year all-cause mortality in ex-smokers with ( n  = 93; 31 females; 70 ± 9years) and without ( n  = 69; 29 females, 69 ± 9years) COPD. CT airway and vessel measurements, helium-3 ( 3 He) MRI ventilation defect percent (VDP) and apparent diffusion coefficients (ADC) were quantified. MRI and CT texture-features were extracted using PyRadiomics (version2.2.0). Associations between 10-year all-cause mortality and all clinical and imaging measurements were evaluated using multivariable regression model odds-ratios. Machine-learning predictive models for 10-year all-cause mortality were evaluated using area-under-receiver-operator-characteristic-curve (AUC), sensitivity and specificity analyses. DL CO (% pred ) (HR = 0.955, 95%CI: 0.934-0.976, p  < 0.001), MRI ADC (HR = 1.843, 95%CI: 1.260-2.871, p  < 0.001), and CT informational-measure-of-correlation (HR = 3.546, 95% CI: 1.660-7.573, p  = 0.001) were the strongest predictors of 10-year mortality. A machine-learning model trained on clinical, imaging, and imaging textures was the best predictive model (AUC = 0.82, sensitivity = 83%, specificity = 84%) and outperformed the solely clinical model (AUC = 0.76, sensitivity = 77%, specificity = 79%). In ex-smokers, regardless of COPD status, addition of CT and MR imaging texture measurements to clinical models provided unique prognostic information of mortality risk that can allow for better clinical management. Clinical Trial Registration: www.clinicaltrials.gov NCT02279329.

Rationale and Objectives: The minimal clinically important difference (MCID) and upper limit of normal (ULN) for MRI ventilation defect percent (VDP) were previously reported for hyperpolarized 3 He gas MRI. Hyperpolarized 129 Xe VDP is more sensitive to airway dysfunction than 3 He, therefore the objective of this study was to determine the ULN and MCID for 129 Xe MRI VDP in healthy and asthma participants., Materials and Methods: We retrospectively evaluated healthy and asthma participants who underwent spirometry and 129 XeMRI on a single visit; participants with asthma completed the asthma control questionnaire (ACQ-7). The MCID was estimated using distribution- (smallest detectable difference [SDD]) and anchor-based (ACQ-7) methods. Two observers measured VDP (semiautomated k-means-cluster segmentation algorithm) in 10 participants with asthma, five-times each in random order, to determine SDD. The ULN was estimated based on the 95% confidence interval of the relationships between VDP and age., Results: Mean VDP was 1.6 ± 1.2% for healthy (n = 27) and 13.7 ± 12.9% for asthma participants (n = 55). ACQ-7 and VDP were correlated (r = .37, p = .006; VDP = 3.5·ACQ + 4.9). The anchor-based MCID was 1.75% while the mean SDD and distribution-based MCID was 2.25%. VDP was correlated with age for healthy participants (p = .56, p =.003; VDP = .04·Age-.01). The ULN for all healthy participants was 2.0%. By age tertiles, the ULN was 1.3% ages 18-39 years, 2.5% for 40-59 years and 3.8% for 60-79 years., Conclusion: The 129 Xe MRI VDP MCID was estimated in participants with asthma; the ULN was estimated in healthy participants across a range of ages, both of which provide a way to interpret VDP measurements in clinical investigations., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Computed tomography (CT) total-airway-count (TAC) and airway wall-thickness differ across chronic obstructive pulmonary disease (COPD) severities, but longitudinal insights are lacking. The aim of this study was to evaluate longitudinal CT airway measurements over three-years in ex-smokers. In this prospective convenience sample study, ex-smokers with ( n  = 50; 13 female; age = 70 ± 9 years; pack-years = 43 ± 26) and without ( n  = 40; 17 female; age = 69 ± 10 years; pack-years = 31 ± 17) COPD completed CT, 3 He magnetic resonance imaging (MRI), and pulmonary function tests at baseline and three-year follow-up. CT TAC, airway wall-area (WA), lumen-area (LA), and wall-area percent (WA%) were generated. Emphysema was quantified as the relative-area-of-the-lung with attenuation < -950 Hounsfield-units (RA 950 ). MRI ventilation-defect-percent (VDP) was also quantified. Differences over time were evaluated using paired-samples t tests. Multivariable prediction models using the backwards approach were generated. After three-years, forced-expiratory-volume in 1-second (FEV 1 ) was not different in ex-smokers with ( p  = 0.4) and without ( p  = 0.5) COPD, whereas RA 950 was ( p  < 0.001, p  = 0.02, respectively). In ex-smokers without COPD, there was no change in TAC ( p  = 0.2); however, LA ( p  = 0.009) and WA% ( p  = 0.01) were significantly different. In ex-smokers with COPD, TAC ( p  < 0.001), WA ( p  = 0.04), LA ( p  < 0.001), and WA% ( p  < 0.001) were significantly different. In all ex-smokers, TAC was related to VDP (baseline: ρ = -0.30, p  = 0.005; follow-up: ρ = -0.33, p  = 0.002). In significant multivariable models, baseline airway wall-thickness was predictive of TAC worsening. After three-years, in the absence of FEV 1 worsening, TAC diminished only in ex-smokers with COPD and airway walls were thinner in all ex-smokers. These longitudinal findings suggest that the evaluation of CT airway remodeling may be a useful clinical tool for predicting disease progression and managing COPD. Clinical trial registration: www.clinicaltrials.gov NCT02279329.

Reduced lung diffusing capacity for carbon monoxide (DL CO ) at rest and increased ventilation ( ⩒ E )-carbon dioxide output ( ⩒ CO 2 ) during exercise are frequent findings in dyspneic smokers with largely preserved FEV 1 . It remains unclear whether low DL CO and high ⩒ E - ⩒ CO 2 are mere reflections of alveolar destruction (i.e. emphysema) or impaired pulmonary perfusion in non-emphysematous tissue contributes to these functional abnormalities. Sixty-four smokers (41 males, FEV 1 = 84 ± 13%predicted) underwent pulmonary function tests, an incremental exercise test, and quantitative chest computed tomography. Total pulmonary vascular volume (TPVV) was calculated for the entire segmented vascular tree (VIDA Vision™). Using the median % low attenuation area (-950 HU), participants were dichotomized into "Trace" or "Mild" emphysema (E), each group classified into preserved versus reduced DL CO . Within each emphysema subgroup, participants with abnormally low DL CO showed lower TPVV, higher ⩒ E - ⩒ CO 2 , and exertional dyspnea than those with preserved DL CO ( p  < 0.05). TPVV ( r  = 0.34; p  = 0.01), but not emphysema ( r = -0.05; p  = 0.67), correlated with lower DL CO after adjusting for age and height. Despite lower emphysema burden, Trace-E participants with reduced DL CO had lower TPVV, higher dyspnea, and lower peak work rate than the Mild-E with preserved DL CO ( p  < 0.05). Interestingly, TPVV (but not emphysema) correlated inversely with both dyspnea-work rate ( r = -0.36, p  = 0.004) and dyspnea- ⩒ E slopes ( r = -0.40, p  = 0.001). Reduced pulmonary vascular volume adjusted by emphysema extent is associated with low DL CO and heightened exertional ventilation in dyspneic smokers with minor emphysema. Impaired perfusion of non-emphysematous regions of the lungs has greater functional and clinical consequences than hitherto assumed in these subjects.

Competing Interests: Disclosures of conflicts of interest: G.P. Associate editor, Radiology. M.S. No relevant relationships.

Background: We previously showed in patients with poorly controlled eosinophilic asthma that a single dose of benralizumab resulted in significantly improved Asthma Control Questionnaire (ACQ-6) score and 129 Xe MRI ventilation defect percent (VDP) 28 days postinjection, and 129 Xe MRI VDP and CT airway mucus occlusions were shown to independently predict this early ACQ-6 response to benralizumab., Research Question: Do early VDP responses at 28 days persist, and do FEV 1 , fractional exhaled nitric oxide, and mucus plug score improve during a 2.5 year treatment period?, Study Design and Methods: Participants with poorly controlled eosinophilic asthma completed spirometry, ACQ-6, and MRI, 28 days, 1 year, and 2.5 years after initiation of treatment with benralizumab; chest CT was acquired at enrollment and 2.5 years later., Results: Of 29 participants evaluated at 28 days post-benralizumab, 16 participants returned for follow-up while on therapy at 1 year, and 13 participants were evaluable while on therapy at 2.5 years post-benralizumab initiation. As compared with 28 days post-benralizumab, ACQ-6 score (2.0 ± 1.4) significantly improved after 1 year (0.5 ± 0.6, P = .02; 95% CI, 0.1-1.1) and 2.5 years (0.5 ± 0.5, P = .03; 95% CI, 0.1-1.1). The mean VDP change at 2.5 years (-4% ± 3%) was greater than the minimal clinically important difference, but not significantly different from VDP measured 28 days post-benralizumab. Mucus score (3 ± 4) was significantly improved at 2.5 years (1 ± 1, P = .03; 95% CI, 0.3-5.5). In six of eight participants with previous occlusions, mucus plugs vanished or substantially diminished 2.5 years later. VDP (P < .001) and mucus score (P < .001) measured at baseline, but not fractional exhaled nitric oxide or FEV 1 , independently predicted ACQ-6 score after 2.5 years., Interpretation: In poorly controlled eosinophilic asthma, early MRI VDP responses at 28 days post-benralizumab persisted 2.5 years later, alongside significantly improved mucus scores and asthma control., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background The association between common carotid artery intima-media thickness (CCA-IMT) and incident carotid plaque has not been characterized fully. We therefore aimed to precisely quantify the relationship between CCA-IMT and carotid plaque development. Methods and Results We undertook an individual participant data meta-analysis of 20 prospective studies from the Proof-ATHERO (Prospective Studies of Atherosclerosis) consortium that recorded baseline CCA-IMT and incident carotid plaque involving 21 494 individuals without a history of cardiovascular disease and without preexisting carotid plaque at baseline. Mean baseline age was 56 years (SD, 9 years), 55% were women, and mean baseline CCA-IMT was 0.71 mm (SD, 0.17 mm). Over a median follow-up of 5.9 years (5th-95th percentile, 1.9-19.0 years), 8278 individuals developed first-ever carotid plaque. We combined study-specific odds ratios (ORs) for incident carotid plaque using random-effects meta-analysis. Baseline CCA-IMT was approximately log-linearly associated with the odds of developing carotid plaque. The age-, sex-, and trial arm-adjusted OR for carotid plaque per SD higher baseline CCA-IMT was 1.40 (95% CI, 1.31-1.50; I 2 =63.9%). The corresponding OR that was further adjusted for ethnicity, smoking, diabetes, body mass index, systolic blood pressure, low- and high-density lipoprotein cholesterol, and lipid-lowering and antihypertensive medication was 1.34 (95% CI, 1.24-1.45; I 2 =59.4%; 14 studies; 16 297 participants; 6381 incident plaques). We observed no significant effect modification across clinically relevant subgroups. Sensitivity analysis restricted to studies defining plaque as focal thickening yielded a comparable OR (1.38 [95% CI, 1.29-1.47]; I 2 =57.1%; 14 studies; 17 352 participants; 6991 incident plaques). Conclusions Our large-scale individual participant data meta-analysis demonstrated that CCA-IMT is associated with the long-term risk of developing first-ever carotid plaque, independent of traditional cardiovascular risk factors.

Introduction: Children with a history of bronchopulmonary dysplasia (BPD) may have lower physical activity levels, but evidence to date is mixed. This study compared physical activity levels between children born extremely preterm with and without history of BPD, and examined their associations with pulmonary magnetic resonance imaging (MRI) and pulmonary function test (PFT) indices., Methods: This multicentre cross-sectional study included children aged 7-9 years born extremely preterm, with and without BPD. Children wore a pedometer for 1 week, then completed the Physical Activity Questionnaire (PAQ), pulmonary MRI, and PFT. Spearman correlations and multivariable linear regression modeling were performed., Results: Of 45 children, 28 had a history of moderate-severe BPD. There were no differences in any physical activity outcomes by BPD status. Higher average daily step count and higher average daily moderate-to-vigorous physical activity (MVPA) were each correlated with greater forced vital capacity (r = 0.41 and 0.58), greater MRI lung proton density at full expiration (r = 0.42 and 0.49), and lower lung clearance index (r = -0.50 and -0.41). After adjusting for MRI total proton density and BPD status, a 5% increase in forced expiratory volume at 1 s was associated with 738 (95% CI: 208, 1268) more steps per day and 0.1 (0.0, 0.2) more hours of MVPA, respectively., Conclusion: School-aged children born extremely preterm have similar physical activity levels to their peers, regardless of history of BPD. MRI and PFT measures suggestive of gas trapping and/or airflow obstruction are associated with lower physical activity levels., (© 2023 The Authors. Pediatric Pulmonology published by Wiley Periodicals LLC.)

Multi-b diffusion-weighted hyperpolarized gas MRI measures pulmonary airspace enlargement using apparent diffusion coefficients (ADC) and mean linear intercepts ( L m ). Rapid single-breath acquisitions may facilitate clinical translation, and, hence, we aimed to develop single-breath three-dimensional multi-b diffusion-weighted 129 Xe MRI using k-space undersampling. We evaluated multi-b (0, 12, 20, 30 s/cm 2 ) diffusion-weighted 129 Xe ADC/morphometry estimates using a fully sampled and retrospectively undersampled k-space with two acceleration-factors (AF = 2 and 3) in never-smokers and ex-smokers with chronic obstructive pulmonary disease (COPD) or alpha-one anti-trypsin deficiency (AATD). For the three sampling cases, mean ADC/ L m values were not significantly different (all p > 0.5); ADC/ L m values were significantly different for the COPD subgroup (0.08 cm 2 s -1 /580 µm, AF = 3; all p < 0.001) as compared to never-smokers (0.05 cm 2 s -1 /300 µm, AF = 3). For never-smokers, mean differences of 7%/7% and 10%/7% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and L m values, respectively. For the COPD subgroup, mean differences of 3%/4% and 11%/10% were observed between fully sampled and retrospectively undersampled (AF = 2/AF = 3) ADC and L m , respectively. There was no relationship between acceleration factor with ADC or L m ( p = 0.9); voxel-wise ADC/ L m measured using AF = 2 and AF = 3 were significantly and strongly related to fully-sampled values (all p < 0.0001). Multi-b diffusion-weighted 129 Xe MRI is feasible using two different acceleration methods to measure pulmonary airspace enlargement using L m and ADC in COPD participants and never-smokers.

129 Xe MRI red blood cell to alveolar tissue plasma ratio (RBC:TP) abnormalities have been observed in ever-hospitalised and never-hospitalised people with postacute COVID-19 syndrome (PACS). But, it is not known if such abnormalities resolve when symptoms and quality-of-life scores improve. We evaluated 21 participants with PACS, 7±4 months (baseline) and 14±4 months (follow-up) postinfection. Significantly improved diffusing capacity of the lung for carbon monoxide (DL CO , Δ=14% pred ;95%CI 7 to 21, p<0.001), postexertional dyspnoea (Δ=-0.7; 95%CI=-0.2 to -1.2, p=0.019), St George's Respiratory Questionnaire-score (SGRQ Δ=-6; 95% CI=-1 to -11, p=0.044) but not RBC:TP (Δ=0.03; 95% CI=0.01 to 0.05, p=0.051) were observed at 14 months. DL CO correlated with RBC:TP (r=0.60, 95% CI=0.22 to 0.82, p=0.004) at 7 months. While DL CO and SGRQ measurements improved, these values did not normalise 14 months post-infection. ClinicalTrials.gov NCT04584671., Competing Interests: Competing interests: SS has received honoraria for speaking engagements from AstraZeneca, Novartis and Polarean, personal fees from Arrowhead Pharma and received study funding from Cyclomedia, none of which was related to this work. JN has received honoraria from AstraZeneca, Horizon Therapeutics and Vertex outside the submitted work. GP has received research support and consulting fees from Novartis and AstraZeneca and personal fees for speaking engagements from AstraZeneca and Polarean Imaging. AMM, MJM, HKK, MA, MSA, ID and AO have no conflicts to declare., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background In individuals with postacute COVID-19 syndrome (PACS) and normal pulmonary function, xenon 129 ( 129 Xe) MRI ventilation defects, abnormal quality-of-life scores, and exercise limitation were reported 3 months after infection; the longitudinal trajectory remains unclear. Purpose To measure and compare pulmonary function, exercise capacity, quality of life, and 129 Xe MRI ventilation defect percent (VDP) in individuals with PACS evaluated 3 and 15 months after COVID-19 infection. Materials and Methods In this prospective study, participants with PACS aged 18-80 years were enrolled between July 2020 and August 2021 from two quaternary care centers. 129 Xe MRI VDP, diffusing capacity of lung for carbon monoxide (Dlco), spirometry, oscillometry, 6-minute walk distance (6MWD), and St George Respiratory Questionnaire (SGRQ) scores were evaluated 3 months and 15 months after COVID-19 infection. Differences between time points were evaluated using the paired t test. Multivariable models were generated to explain exercise capacity and quality-of-life improvement. Odds ratios (ORs) were used to evaluate potential treatment influences. Results Overall, 53 participants (mean age, 55 years ± 18 [SD]; 27 women) attended both 3- and 15-month visits and were included in the analysis. The mean values for 129 Xe MRI VDP (5.8% and 4.2%; P = .003), forced expiratory volume in the 1st second of expiration percent predicted (84% and 90%; P = .001), Dlco percent predicted (86% and 99%; P = .002), and SGRQ score (35 and 25; P < .001) improved between the 3- and 15-month visit. VDP measured 3 months after COVID-19 infection predicted the change in 6MWD (β = -0.643, P = .006), while treatment with respiratory medication at 3 months predicted an improved quality-of-life score at 15 months (OR, 4.0; 95% CI: 1.2, 13.8; P = .03). Conclusion Pulmonary function, gas exchange, exercise capacity, quality of life, and 129 Xe MRI ventilation defect percent (VDP) improved in participants with postacute COVID-19 syndrome at 15 months compared with 3 months after infection. VDP measured at 3 months after infection correlated with improved exercise capacity, while treatment with respiratory medication was associated with an improved quality-of-life score 15 months after infection. ClinicalTrials.gov registration no. NCT05014516 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vogel-Claussen in this issue.

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

This study aimed to evaluate symptoms of sleep-disordered breathing (SDB) among children born extremely preterm, with and without a history of bronchopulmonary dysplasia (BPD), including associations between sleep and respiratory symptoms, physical activity, pulmonary function, and pulmonary magnetic resonance imaging (MRI). This multi-center cross-sectional study enrolled children aged 7-9 years born extremely preterm with and without BPD. Participants completed the Pediatric Sleep Questionnaire (PSQ), the modified Epworth sleepiness scale, a respiratory symptom questionnaire, pedometer measurements, pulmonary function testing, and pulmonary MRI. Spearman's correlations and univariate and multivariable linear regression modelling were performed. Twenty-eight of 45 children included had a history of moderate-to-severe BPD. The prevalence of sleep-related symptoms was low, with the exception of hyperactivity and inattention. There were no differences in mean (SD) scores on sleep questionnaires in children with and without BPD (PSQ: 0.21 (0.13) vs 0.16 (0.14), p = 0.3; modified Epworth: 2.4 (2.4) vs 1.8 (2.8), p = 0.4). Multiple regression analyses examining difference in sleep scores between groups, adjusting for gestational age and intraventricular hemorrhage, found no statistical difference (p > 0.05). Greater daytime sleepiness was moderately correlated with FEV1%-predicted (r =  - 0.52); no other moderate-strong associations were identified.  Conclusions: There was no evidence of clinically important differences in sleep symptoms between children with and without BPD, suggesting that sleep symptoms may be related to prematurity-related factors other than a BPD diagnosis, including airflow limitation. Further research is necessary to explore the relationship between sleep symptoms, airway obstruction, and neurobehavioral symptoms among premature-born children.  Trial registration: NCT02921308. Date of registration: October 3, 2016. What is Known: • Presence of bronchopulmonary dysplasia (BPD) may further contribute to the development of SDB, though its impact is not well-studied. • Premature-born children have a greater risk of lung structural and functional differences, including sleep-disordered breathing (SDB). What is New: • There was no difference in sleep symptoms between children with and without BPD, suggesting that sleep symptoms are related to other prematurity-related factors, such as airflow limitation. • Greater daytime sleepiness was correlated with lower FEV1 in our population, which reflects greater airflow limitation., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)