Purpose To optimize 3D radial ultrashort echo time MRI for high resolution whole-lung imaging. Methods 3D radial ultrashort echo time was implemented on a 3T scanner to investigate the effects of: (1) limited field-of-view excitation, (2) variable density readouts, and (3) radial oversampling. Improvements in noise performance and spatial resolution were assessed through simulation and phantom studies. Their effects on lung and airway visualization in five healthy male human subjects (mean age 32 years) were compared qualitatively through blinded ordinal scoring by two cardiothoracic radiologists using a nonparametric Friedman test (P < 0.05). Relative signal difference between endobronchial air and adjacent lung tissue, normalized to nearby vessel, was used as a surrogate for lung tissue signal. Quantitative measures were compared using the paired Student's t-test (P < 0.05). Finally, clinical feasibility was investigated in a patient with interstitial fibrosis. Results Simulation and phantom studies showed up to 67% improvement in SNR and reduced blurring for short T2* species using all three optimizations. In vivo images showed decreased artifacts and improved lung tissue and airway visualization both qualitatively and quantitatively. Conclusion The use of limited field-of-view excitation, variable readout gradients, and radial oversampling significantly improve the technical quality of 3D radial ultrashort echo time lung images.
BACKGROUND.The link between mucus plugs and airflow obstruction has not been established in chronic severe asthma, and the role of eosinophils and their products in mucus plug formation is unknown. METHODS.In clinical studies, we developed and applied a bronchopulmonary segment-based scoring system to quantify mucus plugs on multidetector computed tomography (MDCT) lung scans from 146 subjects with asthma and 22 controls, and analyzed relationships among mucus plug scores, forced expiratory volume in 1 second (FEV1), and airway eosinophils. Additionally, we used airway mucus gel models to explore whether oxidants generated by eosinophil peroxidase (EPO) oxidize cysteine thiol groups to promote mucus plug formation. RESULTS.Mucus plugs occurred in at least 1 of 20 lung segments in 58% of subjects with asthma and in only 4.5% of controls, and the plugs in subjects with asthma persisted in the same segment for years. A high mucus score (plugs in ≥ 4 segments) occurred in 67% of subjects with asthma with FEV1 of less than 60% of predicted volume, 19% with FEV1 of 60%-80%, and 6% with FEV1 greater than 80% (P < 0.001) and was associated with marked increases in sputum eosinophils and EPO. EPO catalyzed oxidation of thiocyanate and bromide by H 2 O 2 to generate oxidants that crosslink cysteine thiol groups and stiffen thiolated hydrogels. CONCLUSION.Mucus plugs are a plausible mechanism of chronic airflow obstruction in severe asthma, and EPO-generated oxidants may mediate mucus plug formation. We propose an approach for quantifying airway mucus plugging using MDCT lung scans and suggest that treating mucus plugs may improve airflow in chronic severe asthma. TRIAL REGISTRATION. Clinicaltrials.gov NCT01718197, NCT01606826, NCT01750411, NCT01761058, NCT01761630, NCT01759186, NCT01716494, and NCT01760915.FUNDING. NIH grants P01 HL107201, R01 HL080414, U10 HL109146, U10 HL109164, U10 HL109172, U10 HL109086, U10 HL109250, U10 HL109168, U10 HL109257, U10 HL109152, and P01 HL107202 and National Center for Advancing Translational Sciences grants UL1TR0000427, UL1TR000448, and KL2TR000428.
Background-To prospectively apply an automated, quantitative 3-D approach to imaging and airway analysis to assess airway remodeling in asthma.
Rationale: Reducing asthma exacerbation frequency is an important criterion for approval of asthma therapies, but the clinical features of exacerbation-prone asthma (EPA) remain incompletely defined.Objectives: To describe the clinical, physiologic, inflammatory, and comorbidity factors associated with EPA.Methods: Baseline data from the NHLBI Severe Asthma Research Program (SARP)-3 were analyzed. An exacerbation was defined as a burst of systemic corticosteroids lasting 3 days or more. Patients were classified by their number of exacerbations in the past year: none, few (one to two), or exacerbation prone (>3). Replication of a multivariable model was performed with data from the SARP-1 1 2 cohort.Measurements and Main Results: Of 709 subjects in the SARP-3 cohort, 294 (41%) had no exacerbations and 173 (24%) were exacerbation prone in the prior year. Several factors normally associated with severity (asthma duration, age, sex, race, and socioeconomic status) did not associate with exacerbation frequency in SARP-3; bronchodilator responsiveness also discriminated exacerbation proneness from asthma severity. In the SARP-3 multivariable model, blood eosinophils, body mass index, and bronchodilator responsiveness were positively associated with exacerbation frequency (rate ratios [95% confidence interval],
Background Severe asthma subjects have increased physiologically measured air trapping. However, a similar study using CT measures of air trapping has not been performed. This study was designed to address two hypotheses: 1) air trapping, measured by multi-detector CT quantitative methodology, would be a predictor of a more severe asthma phenotype; and 2) historical, clinical, allergic, or inflammatory risk factors could be identified via multivariate analysis. Methods Multi-detector CT scanning of a subset of the Severe Asthma Research Program subjects was performed at functional residual capacity. Air trapping was defined as 9.66% or more of the lung tissue less than −850 HU. Subjects who were defined as air trappers were then compared to non-trappers on clinical and demographic factors using both univariate and multivariate statistical analysis. Results Air trappers were significantly more likely to have a history of asthma-related hospitalizations, ICU visits and/or mechanical ventilation. Duration of asthma (OR 1.42, 95% CI 1.08–1.87), history of pneumonia (OR 8.55, 95% CI 2.07–35.26), high levels of airway neutrophils (OR 8.67, 95% CI 2.05–36.57), air flow obstruction (FEV1/FVC) (OR 1.61, 95% CI 1.21–2.14) and atopy (OR 11.54, 95% CI 1.97–67.70), were identified as independent risk factors associated with the air trapping phenotype. Conclusions Quantitative CT determined air trapping in asthmatic subjects identifies a group of individuals with a high risk of severe disease. Several independent risk factors for the presence of this phenotype were identified, perhaps most interestingly history of pneumonia, neutrophilic inflammation, and atopy.
The noninvasive assessment of lung function using imaging is increasingly of interest for the study of lung diseases, including chronic obstructive pulmonary disease (COPD) and asthma. Hyperpolarized gas MRI (HP MRI) has demonstrated the ability to detect changes in ventilation, perfusion, and lung microstructure that appear to be associated with both normal lung development and disease progression. The physical characteristics of HP gases and their application to MRI are presented with an emphasis on current applications. Clinical investigations using HP MRI to study asthma, COPD, cystic fibrosis, pediatric chronic lung disease, and lung transplant are reviewed. Recent advances in polarization, pulse sequence development for imaging with Xe-129, and prototype low magnetic field systems dedicated to lung imaging are highlighted as areas of future development for this rapidly evolving technology.
During the past several years there has been extensive development and application of hyperpolarized helium-3 (HP 3 He) magnetic resonance imaging (MRI) in clinical respiratory indications such as asthma, chronic obstructive pulmonary disease, cystic fibrosis, radiation-induced lung injury, and transplantation. This review focuses on the state-of-the-art of HP 3 He MRI and its application to clinical pulmonary research. This is not an overview of the physics of the method, as this topic has been covered previously. We focus here on the potential of this imaging method and its challenges in demonstrating new types of information that has the potential to influence clinical research and decision making in pulmonary medicine. Particular attention is given to functional imaging approaches related to ventilation and diffusion-weighted imaging with applications in chronic obstructive pulmonary disease, cystic fibrosis, asthma, and radiationinduced lung injury. The strengths and challenges of the application of 3 He MRI in these indications are discussed along with a comparison to established and emerging imaging techniques.
Objectives This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. Methods An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. Results Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. Discussion This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
334 Leonard St
Brooklyn, NY 11211
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.