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1.
Am J Respir Crit Care Med ; 2022 Aug 16.
Article in English | MEDLINE | ID: mdl-35972833

ABSTRACT

RATIONALE: Preterm birth is associated with low lung function in childhood, but little is known about the lung microstructure in childhood. OBJECTIVES: We assessed the differential associations between the historical diagnosis of bronchopulmonary dysplasia (BPD) and current lung function phenotypes on lung ventilation and microstructure in preterm-born children using hyperpolarised 129Xe ventilation and diffusion-weighted MRI, and multiple breath washout (MBW). METHODS: Data were available from 63 children (aged 9-13 years) including 44 born preterm (≤34 weeks' gestation) and 19 term-born controls (≥37 weeks' gestation). Preterm-born children were classified, using spirometry, into prematurity-associated obstructive lung disease (POLD, FEV1<LLN, FEV1/FVC<LLN); prematurity-associated preserved ratio of impaired spirometry (pPRISm, FEV1<LLN, FEV1/FVC≥LLN); preterm- and term-born controls; and into those with and without BPD. Ventilation heterogeneity metrics were derived from 129Xe ventilation MRI and SF6 MBW. Alveolar microstructural dimensions were derived from 129Xe diffusion-weighted MRI. RESULTS: 129Xe ventilation defect percentage and ventilation heterogeneity index were significantly increased in preterm-born children with POLD. In contrast, mean 129Xe apparent diffusion coefficient (ADC), 129Xe ADC interquartile range (IQR) and 129Xe mean alveolar dimension IQR were significantly increased in preterm-born children with BPD, suggesting changes of alveolar dimensions. MBW metrics were all significantly increased in the POLD group when compared to preterm- and term-born controls. Linear regression confirmed the differential effects of obstructive disease on ventilation defects and BPD on lung microstructure. CONCLUSION: We show that ventilation abnormalities are associated with prematurity-associated obstructive lung disease, and BPD in infancy is associated with abnormal lung microstructure.

2.
Front Cardiovasc Med ; 9: 956811, 2022.
Article in English | MEDLINE | ID: mdl-35911553

ABSTRACT

Background: There has been a rapid increase in the number of Artificial Intelligence (AI) studies of cardiac MRI (CMR) segmentation aiming to automate image analysis. However, advancement and clinical translation in this field depend on researchers presenting their work in a transparent and reproducible manner. This systematic review aimed to evaluate the quality of reporting in AI studies involving CMR segmentation. Methods: MEDLINE and EMBASE were searched for AI CMR segmentation studies in April 2022. Any fully automated AI method for segmentation of cardiac chambers, myocardium or scar on CMR was considered for inclusion. For each study, compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) was assessed. The CLAIM criteria were grouped into study, dataset, model and performance description domains. Results: 209 studies published between 2012 and 2022 were included in the analysis. Studies were mainly published in technical journals (58%), with the majority (57%) published since 2019. Studies were from 37 different countries, with most from China (26%), the United States (18%) and the United Kingdom (11%). Short axis CMR images were most frequently used (70%), with the left ventricle the most commonly segmented cardiac structure (49%). Median compliance of studies with CLAIM was 67% (IQR 59-73%). Median compliance was highest for the model description domain (100%, IQR 80-100%) and lower for the study (71%, IQR 63-86%), dataset (63%, IQR 50-67%) and performance (60%, IQR 50-70%) description domains. Conclusion: This systematic review highlights important gaps in the literature of CMR studies using AI. We identified key items missing-most strikingly poor description of patients included in the training and validation of AI models and inadequate model failure analysis-that limit the transparency, reproducibility and hence validity of published AI studies. This review may support closer adherence to established frameworks for reporting standards and presents recommendations for improving the quality of reporting in this field. Systematic Review Registration: [www.crd.york.ac.uk/prospero/], identifier [CRD42022279214].

3.
Magn Reson Imaging ; 92: 140-149, 2022 10.
Article in English | MEDLINE | ID: mdl-35777684

ABSTRACT

PURPOSE: To develop an end-to-end deep learning (DL) framework to segment ventilation defects on pulmonary hyperpolarized MRI. MATERIALS AND METHODS: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease (COPD) study is a nested longitudinal case-control study in older smokers. Between February 2016 and July 2017, 56 participants (age, mean ± SD, 74 ± 8 years; 34 men) underwent same breath-hold proton (1H) and helium (3He) MRI, which were annotated for non-ventilated, hypo-ventilated, and normal-ventilated lungs. In this retrospective DL study, 820 1H and 3He slices from 42/56 (75%) participants were randomly selected for training, with the remaining 14/56 (25%) for test. Full lung masks were segmented using a traditional U-Net on 1H MRI and were imported into a cascaded U-Net, which were used to segment ventilation defects on 3He MRI. Models were trained with conventional data augmentation (DA) and generative adversarial networks (GAN)-DA. RESULTS: Conventional-DA improved 1H and 3He MRI segmentation over the non-DA model (P = 0.007 to 0.03) but GAN-DA did not yield further improvement. The cascaded U-Net improved non-ventilated lung segmentation (P < 0.005). Dice similarity coefficients (DSC) between manually and DL-segmented full lung, non-ventilated, hypo-ventilated, and normal-ventilated regions were 0.965 ± 0.010, 0.840 ± 0.057, 0.715 ± 0.175, and 0.883 ± 0.060, respectively. We observed no statistically significant difference in DCSs between participants with and without COPD (P = 0.41, 0.06, and 0.18 for non-ventilated, hypo-ventilated, and normal-ventilated regions, respectively). CONCLUSION: The proposed cascaded U-Net framework generated fully-automated segmentation of ventilation defects on 3He MRI among older smokers with and without COPD that is consistent with our reference method.


Subject(s)
Atherosclerosis , Pulmonary Disease, Chronic Obstructive , Aged , Aged, 80 and over , Atherosclerosis/diagnostic imaging , Case-Control Studies , Helium , Humans , Lung/diagnostic imaging , Magnetic Resonance Imaging/methods , Male , Protons , Pulmonary Disease, Chronic Obstructive/diagnostic imaging , Retrospective Studies
4.
Radiology ; : 221361, 2022 Jun 28.
Article in English | MEDLINE | ID: mdl-35762895
5.
Sci Rep ; 12(1): 10566, 2022 Jun 22.
Article in English | MEDLINE | ID: mdl-35732795

ABSTRACT

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and quantification of regional lung ventilation with high spatial resolution. Segmentation of the ventilated lung is required to calculate clinically relevant biomarkers. Recent research in deep learning (DL) has shown promising results for numerous segmentation problems. Here, we evaluate several 3D convolutional neural networks to segment ventilated lung regions on hyperpolarized gas MRI scans. The dataset consists of 759 helium-3 (3He) or xenon-129 (129Xe) volumetric scans and corresponding expert segmentations from 341 healthy subjects and patients with a wide range of pathologies. We evaluated segmentation performance for several DL experimental methods via overlap, distance and error metrics and compared them to conventional segmentation methods, namely, spatial fuzzy c-means (SFCM) and K-means clustering. We observed that training on combined 3He and 129Xe MRI scans using a 3D nn-UNet outperformed other DL methods, achieving a mean ± SD Dice coefficient of 0.963 ± 0.018, average boundary Hausdorff distance of 1.505 ± 0.969 mm, Hausdorff 95th percentile of 5.754 ± 6.621 mm and relative error of 0.075 ± 0.039. Moreover, limited differences in performance were observed between 129Xe and 3He scans in the testing set. Combined training on 129Xe and 3He yielded statistically significant improvements over the conventional methods (p < 0.0001). In addition, we observed very strong correlation and agreement between DL and expert segmentations, with Pearson correlation of 0.99 (p < 0.0001) and Bland-Altman bias of - 0.8%. The DL approach evaluated provides accurate, robust and rapid segmentations of ventilated lung regions and successfully excludes non-lung regions such as the airways and artefacts. This approach is expected to eliminate the need for, or significantly reduce, subsequent time-consuming manual editing.


Subject(s)
Deep Learning , Humans , Lung/diagnostic imaging , Lung Volume Measurements , Magnetic Resonance Imaging/methods , Male
6.
Radiology ; : 220069, 2022 May 24.
Article in English | MEDLINE | ID: mdl-35608443

ABSTRACT

Background Post-Covid-19 condition describes symptoms following COVID-19 infection after four weeks. Symptoms are wide-ranging but breathlessness is common. Purpose The purpose of this study was to determine whether the previously described lung abnormalities on Hp-XeMRI in post-hospitalised COVID-19 participants are also present in non-hospitalised participants with Post-Covid-19 condition. Methods In this prospective study, non-hospitalised Post-Covid-19 condition (NHLC) and post-hospitalised COVID-19 (PHC) participants were enrolled from 06/2020 to 08/2021. Participants had chest CT, hyperpolarized pulmonary 129Xenon MRI (Hp-XeMRI), pulmonary function tests, 1-minute sit-to-stand test and breathlessness questionnaires. Control subjects underwent HP-XeMRI only. CT scans were analysed for post COVID interstitial lung disease severity using a previously published scoring system, and Full-scale Airway Network (FAN) modelling. Analysis used group and pair-wise comparisons between participants and controls, and correlations between participant clinical and imaging data. Results A total of 11 NHLC (4:7 Male: Female, 44 ± 11 years, [37-50], (mean ± SD, [95% CI]) and 12 PHC (10:2, Male: Female, 58 ± 10 years, [52-64]) participants were included, with a significant difference in age between groups, p = 0.05. NHLC participants were 287 ± 79, [240-334] and PHC 143 ± 72, [105-190] days from infection, respectively. NHLC and PHC participants had normal or near normal CT scans (0.3/25 ± 0.6, [0-0.63] and 7/25 ± 5, [4-10], respectively). Gas transfer (DLco (%)) was different between NHLC and PHC participants (76 ± 8%, [73-83] vs 86 ± 8%, [80-91] respectively, p = 0.04) but there was no evidence of other differences in lung function. Red Blood Cell:Tissue Plasma (RBC:TP) mean was different between volunteers vs PHC (0.45 ± 0.07, [0.43-0.47] vs (0.31 ± 0.10, [0.24-0.37], respectively, p = 0.02) and volunteers vs NHLC (0.37 ± 0.10, [0.31-0.44], p = 0.03) participants, but not between NHLC and PHC participants (p = 0.26). FAN results did not correlate with DLco or Hp- XeMRI. Conclusion NHLC and PHC subjects showed Hp-XeMRI RBC:TP abnormalities, with NHLC participants demonstrating lower DLco than PHC participants despite having normal CT scans. See also the editorial by Parraga and Matheson.

7.
ERJ Open Res ; 8(2)2022 Apr.
Article in English | MEDLINE | ID: mdl-35586449

ABSTRACT

Background: Pulmonary hypertension (PH) in patients with chronic lung disease (CLD) predicts reduced functional status, clinical worsening and increased mortality, with patients with severe PH-CLD (≥35 mmHg) having a significantly worse prognosis than mild to moderate PH-CLD (21-34 mmHg). The aim of this cross-sectional study was to assess the association between computed tomography (CT)-derived quantitative pulmonary vessel volume, PH severity and disease aetiology in CLD. Methods: Treatment-naïve patients with CLD who underwent CT pulmonary angiography, lung function testing and right heart catheterisation were identified from the ASPIRE registry between October 2012 and July 2018. Quantitative assessments of total pulmonary vessel and small pulmonary vessel volume were performed. Results: 90 patients had PH-CLD including 44 associated with COPD/emphysema and 46 with interstitial lung disease (ILD). Patients with severe PH-CLD (n=40) had lower small pulmonary vessel volume compared to patients with mild to moderate PH-CLD (n=50). Patients with PH-ILD had significantly reduced small pulmonary blood vessel volume, compared to PH-COPD/emphysema. Higher mortality was identified in patients with lower small pulmonary vessel volume. Conclusion: Patients with severe PH-CLD, regardless of aetiology, have lower small pulmonary vessel volume compared to patients with mild-moderate PH-CLD, and this is associated with a higher mortality. Whether pulmonary vessel changes quantified by CT are a marker of remodelling of the distal pulmonary vasculature requires further study.

8.
Respir Physiol Neurobiol ; 302: 103919, 2022 08.
Article in English | MEDLINE | ID: mdl-35562095

ABSTRACT

BACKGROUND: Indices of ventilation heterogeneity (VH) from multiple breath washout (MBW) have been shown to correlate well with VH indices derived from hyperpolarised gas ventilation MRI. Here we report the prediction of ventilation distributions from MBW data using a mathematical model, and the comparison of these predictions with imaging data. METHODS: We developed computer simulations of the ventilation distribution in the lungs to model MBW measurement with 3 parameters: σV, determining the extent of VH; V0, the lung volume; and VD, the dead-space volume. These were inferred for each individual from supine MBW data recorded from 25 patients with cystic fibrosis (CF) using approximate Bayesian computation. The fitted models were used to predict the distribution of gas imaged by 3He ventilation MRI measurements collected from the same visit. RESULTS: The MRI indices measured (I1/3, the fraction of pixels below one-third of the mean intensity and ICV, the coefficient of variation of pixel intensity) correlated strongly with those predicted by the MBW model fits (r=0.93,0.88 respectively). There was also good agreement between predicted and measured MRI indices (mean bias ± limits of agreement: I1/3:-0.003±0.118 and ICV:-0.004±0.298). Fitted model parameters were robust to truncation of MBW data. CONCLUSION: We have shown that the ventilation distribution in the lung can be inferred from an MBW signal, and verified this using ventilation MRI. The Bayesian method employed extracts this information with fewer breath cycles than required for LCI, reducing acquisition time required, and gives uncertainty bounds, which are important for clinical decision making.


Subject(s)
Cystic Fibrosis , Bayes Theorem , Breath Tests/methods , Cystic Fibrosis/diagnostic imaging , Humans , Lung/diagnostic imaging , Magnetic Resonance Imaging , Male , Respiratory Function Tests/methods
9.
Pulm Circ ; 12(2): e12054, 2022 Apr.
Article in English | MEDLINE | ID: mdl-35514781

ABSTRACT

For sensitive diagnosis and monitoring of pulmonary disease, ionizing radiation-free imaging methods are of great importance. A noncontrast and free-breathing proton magnetic resonance imaging (MRI) technique for assessment of pulmonary perfusion is phase-resolved functional lung (PREFUL) MRI. Since there is no validation of PREFUL MRI across different centers and scanners, the purpose of this study was to compare perfusion-weighted PREFUL MRI with the well-established dynamic contrast-enhanced (DCE) MRI across two centers on scanners from two different vendors. Sixteen patients with cystic fibrosis (CF) (Center 1: 10 patients; Center 2: 6 patients) underwent PREFUL and DCE MRI at 1.5T in the same imaging session. Normalized perfusion-weighted values and perfusion defect percentage (QDP) values were calculated for the whole lung and three central slices (dorsal, central, ventral of the carina). Obtained parameters were compared using Pearson correlation, Spearman correlation, Bland-Altman analysis, Wilcoxon signed-rank test, and Wilcoxon rank-sum test. Moderate-to-strong correlations between normalized perfusion-weighted PREFUL and DCE values were found (posterior slice: r = 0.69, p < 0.01). Spatial overlap of PREFUL and DCE QDP maps showed an agreement of 79.4% for the whole lung. Further, spatial overlap values of Center 1 were not significantly different to those of Center 2 for the three central slices (p > 0.07). The feasibility of PREFUL MRI across two different centers and two different vendors was shown in patients with CF and obtained results were in agreement with DCE MRI.

10.
Eur Heart J ; 43(26): 2511-2522, 2022 Jul 07.
Article in English | MEDLINE | ID: mdl-35512290

ABSTRACT

AIMS: Non-invasive imaging is routinely used to estimate left ventricular (LV) filling pressure (LVFP) in heart failure (HF). Cardiovascular magnetic resonance (CMR) is emerging as an important imaging tool for sub-phenotyping HF. However, currently, LVFP cannot be estimated from CMR. This study sought to investigate (i) if CMR can estimate LVFP in patients with suspected HF and (ii) if CMR-modelled LVFP has prognostic power. METHODS AND RESULTS: Suspected HF patients underwent right heart catheterization (RHC), CMR and transthoracic echocardiography (TTE) (validation cohort only) within 24 h of each other. Right heart catheterization measured pulmonary capillary wedge pressure (PCWP) was used as a reference for LVFP. At follow-up, death was considered as the primary endpoint. We enrolled 835 patients (mean age: 65 ± 13 years, 40% male). In the derivation cohort (n = 708, 85%), two CMR metrics were associated with RHC PCWP:LV mass and left atrial volume. When applied to the validation cohort (n = 127, 15%), the correlation coefficient between RHC PCWP and CMR-modelled PCWP was 0.55 (95% confidence interval: 0.41-0.66, P < 0.0001). Cardiovascular magnetic resonance-modelled PCWP was superior to TTE in classifying patients as normal or raised filling pressures (76 vs. 25%). Cardiovascular magnetic resonance-modelled PCWP was associated with an increased risk of death (hazard ratio: 1.77, P < 0.001). At Kaplan-Meier analysis, CMR-modelled PCWP was comparable to RHC PCWP (≥15 mmHg) to predict survival at 7-year follow-up (35 vs. 37%, χ2 = 0.41, P = 0.52). CONCLUSION: A physiological CMR model can estimate LVFP in patients with suspected HF. In addition, CMR-modelled LVFP has a prognostic role.


Subject(s)
Cardiac Catheterization , Heart Failure , Aged , Cardiac Catheterization/methods , Female , Humans , Magnetic Resonance Spectroscopy , Male , Middle Aged , Prognosis , Pulmonary Wedge Pressure/physiology , Stroke Volume/physiology , Ventricular Function, Left
11.
Heart ; 108(17): 1392-1400, 2022 Aug 11.
Article in English | MEDLINE | ID: mdl-35512982

ABSTRACT

OBJECTIVES: To determine the prognostic value of patterns of right ventricular adaptation in patients with pulmonary arterial hypertension (PAH), assessed using cardiac magnetic resonance (CMR) imaging at baseline and follow-up. METHODS: Patients attending the Sheffield Pulmonary Vascular Disease Unit with suspected pulmonary hypertension were recruited into the ASPIRE (Assessing the Spectrum of Pulmonary hypertension Identified at a REferral Centre) Registry. With exclusion of congenital heart disease, consecutive patients with PAH were followed up until the date of census or death. Right ventricular end-systolic volume index adjusted for age and sex and ventricular mass index were used to categorise patients into four different volume/mass groups: low-volume-low-mass, low-volume-high-mass, high-volume-low-mass and high-volume-high-mass. The prognostic value of the groups was assessed with one-way analysis of variance and Kaplan-Meier plots. Transition of the groups was studied. RESULTS: A total of 505 patients with PAH were identified, 239 (47.3%) of whom have died at follow-up (median 4.85 years, IQR 4.05). The mean age of the patients was 59±16 and 161 (32.7%) were male. Low-volume-low-mass was associated with CMR and right heart catheterisation metrics predictive of improved prognosis. There were 124 patients who underwent follow-up CMR (median 1.11 years, IQR 0.78). At both baseline and follow-up, the high-volume-low-mass group had worse prognosis than the low-volume-low-mass group (p<0.001). With PAH therapy, 73.5% of low-volume-low-mass patients remained in this group, whereas only 17.4% of high-volume-low-mass patients transitioned into low-volume-low-mass. CONCLUSIONS: Right ventricular adaptation assessed using CMR has prognostic value in patients with PAH. Patients with maladaptive remodelling (high-volume-low-mass) are at high risk of treatment failure.


Subject(s)
Hypertension, Pulmonary , Pulmonary Arterial Hypertension , Ventricular Dysfunction, Right , Familial Primary Pulmonary Hypertension , Female , Humans , Hypertension, Pulmonary/complications , Hypertension, Pulmonary/diagnostic imaging , Male , Predictive Value of Tests , Prognosis , Pulmonary Arterial Hypertension/diagnostic imaging , Stroke Volume , Ventricular Dysfunction, Right/complications , Ventricular Dysfunction, Right/etiology , Ventricular Function, Right , Ventricular Remodeling
12.
Front Cardiovasc Med ; 9: 797561, 2022.
Article in English | MEDLINE | ID: mdl-35402574

ABSTRACT

Background: Current European Society of Cardiology and European Respiratory Society guidelines recommend regular risk stratification with an aim of treating patients with pulmonary arterial hypertension (PAH) to improve or maintain low-risk status (<5% 1-year mortality). Methods: Consecutive patients with PAH who underwent cardiac magnetic resonance imaging (cMRI) were identified from the Assessing the Spectrum of Pulmonary hypertension Identified at a Referral centre (ASPIRE) registry. Kaplan-Meier survival curves, locally weighted scatterplot smoothing regression and multi-variable logistic regression analysis were performed. Results: In 311 consecutive, treatment-naïve patients with PAH undergoing cMRI including 121 undergoing follow-up cMRI, measures of right ventricular (RV) function including right ventricular ejection fraction (RVEF) and RV end systolic volume and right atrial (RA) area had prognostic value. However, only RV metrics were able to identify a low-risk status. Age (p < 0.01) and RVEF (p < 0.01) but not RA area were independent predictors of 1-year mortality. Conclusion: This study highlights the need for guidelines to include measures of RV function rather than RA area alone to aid the risk stratification of patients with PAH.

13.
J Cardiovasc Magn Reson ; 24(1): 25, 2022 04 07.
Article in English | MEDLINE | ID: mdl-35387651

ABSTRACT

BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may allow more reliable measurement of RA areas to improve clinical assessments. The aim of this study was to automate cardiovascular magnetic resonance (CMR) RA area measurements and evaluate the clinical utility by assessing repeatability, correlation with invasive haemodynamics and prognostic value. METHODS: A deep learning RA area CMR contouring model was trained in a multicentre cohort of 365 patients with pulmonary hypertension, left ventricular pathology and healthy subjects. Inter-study repeatability (intraclass correlation coefficient (ICC)) and agreement of contours (DICE similarity coefficient (DSC)) were assessed in a prospective cohort (n = 36). Clinical testing and mortality prediction was performed in n = 400 patients that were not used in the training nor prospective cohort, and the correlation of automatic and manual RA measurements with invasive haemodynamics assessed in n = 212/400. Radiologist quality control (QC) was performed in the ASPIRE registry, n = 3795 patients. The primary QC observer evaluated all the segmentations and recorded them as satisfactory, suboptimal or failure. A second QC observer analysed a random subcohort to assess QC agreement (n = 1018). RESULTS: All deep learning RA measurements showed higher interstudy repeatability (ICC 0.91 to 0.95) compared to manual RA measurements (1st observer ICC 0.82 to 0.88, 2nd observer ICC 0.88 to 0.91). DSC showed high agreement comparing automatic artificial intelligence and manual CMR readers. Maximal RA area mean and standard deviation (SD) DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 is 92.4 ± 3.5 cm2, 91.2 ± 4.5 cm2 and 93.2 ± 3.2 cm2, respectively. Minimal RA area mean and SD DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 was 89.8 ± 3.9 cm2, 87.0 ± 5.8 cm2 and 91.8 ± 4.8 cm2. Automatic RA area measurements all showed moderate correlation with invasive parameters (r = 0.45 to 0.66), manual (r = 0.36 to 0.57). Maximal RA area could accurately predict elevated mean RA pressure low and high-risk thresholds (area under the receiver operating characteristic curve artificial intelligence = 0.82/0.87 vs manual = 0.78/0.83), and predicted mortality similar to manual measurements, both p < 0.01. In the QC evaluation, artificial intelligence segmentations were suboptimal at 108/3795 and a low failure rate of 16/3795. In a subcohort (n = 1018), agreement by two QC observers was excellent, kappa 0.84. CONCLUSION: Automatic artificial intelligence CMR derived RA size and function are accurate, have excellent repeatability, moderate associations with invasive haemodynamics and predict mortality.


Subject(s)
Artificial Intelligence , Hypertension, Pulmonary , Heart Ventricles , Humans , Magnetic Resonance Spectroscopy , Predictive Value of Tests , Prospective Studies , Reproducibility of Results
14.
Magn Reson Med ; 88(1): 83-105, 2022 07.
Article in English | MEDLINE | ID: mdl-35253919

ABSTRACT

Hyperpolarized (HP) xenon-129 (129 Xe) brain MRI is a promising imaging modality currently under extensive development. HP 129 Xe is nontoxic, capable of dissolving in pulmonary blood, and is extremely sensitive to the local environment. After dissolution in the pulmonary blood, HP 129 Xe travels with the blood flow to the brain and can be used for functional imaging such as perfusion imaging, hemodynamic response detection, and blood-brain barrier permeability assessment. HP 129 Xe MRI imaging of the brain has been performed in animals, healthy human subjects, and in patients with Alzheimer's disease and stroke. In this review, the overall progress in the field of HP 129 Xe brain imaging is discussed, along with various imaging approaches and pulse sequences used to optimize HP 129 Xe brain MRI. In addition, current challenges and limitations of HP 129 Xe brain imaging are discussed, as well as possible methods for their mitigation. Finally, potential pathways for further development are also discussed. HP 129 Xe MRI of the brain has the potential to become a valuable novel perfusion imaging technique and has the potential to be used in the clinical setting in the future.


Subject(s)
Lung , Xenon Isotopes , Animals , Brain/diagnostic imaging , Brain/metabolism , Humans , Magnetic Resonance Imaging/methods , Neuroimaging , Xenon Isotopes/metabolism
15.
Respir Res ; 23(1): 26, 2022 Feb 10.
Article in English | MEDLINE | ID: mdl-35144620

ABSTRACT

RATIONALE: The long-acting ß2-agonist/long-acting muscarinic antagonist combination indacaterol/glycopyrronium (IND/GLY) elicits bronchodilation, improves symptoms, and reduces exacerbations in COPD. Magnetic resonance imaging (MRI) of the lung with hyperpolarized gas and gadolinium contrast enhancement enables assessment of whole lung functional responses to IND/GLY. OBJECTIVES: The primary objective was assessment of effect of IND/GLY on global ventilated lung volume (%VV) versus placebo in COPD. Lung function, regional ventilation and perfusion in response to IND/GLY were also measured. METHODS: This double-blind, randomized, placebo-controlled, crossover study assessed %VV and pulmonary perfusion in patients with moderate-to-severe COPD after 8 days of once-daily IND/GLY treatment (110/50 µg) followed by 8 days of placebo, or vice versa, using inhaled hyperpolarized 3He gas and gadolinium contrast-enhanced MRI, respectively. Lung function measures including spirometry were performed for each treatment after 8 days. MEASUREMENTS AND MAIN RESULTS: Of 31 patients randomized, 29 completed both treatment periods. IND/GLY increased global %VV versus placebo (61.73% vs. 56.73%, respectively, least squares means treatment difference: 5.00% [90% CI 1.40 to 8.60]; P = 0.025). IND/GLY improved whole lung index of ventilation volume to perfusion volume (V/Q) ratio versus placebo; 94% (90% CI 83 to 105) versus 86% (90% CI 75 to 97; P = 0.047), respectively. IND/GLY showed a trend to improve diffusing capacity for carbon monoxide (DLCO) (+ 0.66 mL/min/mmHg; P = 0.082). By Day 8, forced expiratory volume in 1 s (FEV1) was increased by 0.32 L versus placebo (90% CI 0.26 to 0.38; P < 0.0001), substantiating earlier findings and providing evidence of assay sensitivity for this trial. CONCLUSIONS: IND/GLY improved lung ventilation assessed by 3He MRI after 1 week of treatment. This observation may provide mechanistic support for the symptomatic clinical benefit shown with IND/GLY in COPD. Clinical trial registered with www.clinicaltrials.gov (NCT02634983).


Subject(s)
Bronchoconstriction/drug effects , Forced Expiratory Volume/drug effects , Glycopyrrolate/analogs & derivatives , Indans/administration & dosage , Lung/physiopathology , Pulmonary Disease, Chronic Obstructive/drug therapy , Quinolones/administration & dosage , Vital Capacity/drug effects , Aged , Cross-Over Studies , Double-Blind Method , Drug Combinations , Female , Follow-Up Studies , Glycopyrrolate/administration & dosage , Humans , Male , Middle Aged , Pulmonary Disease, Chronic Obstructive/physiopathology , Respiratory Function Tests , Retrospective Studies , Treatment Outcome
16.
ERJ Open Res ; 8(1)2022 Jan.
Article in English | MEDLINE | ID: mdl-35083317

ABSTRACT

BACKGROUND: Patients with pulmonary hypertension (PH) and lung disease may pose a diagnostic dilemma between idiopathic pulmonary arterial hypertension (IPAH) and PH associated with lung disease (PH-CLD). The prognostic impact of common computed tomography (CT) parenchymal features is unknown. METHODS: 660 IPAH and PH-CLD patients assessed between 2001 and 2019 were included. Reports for all CT scans 1 year prior to diagnosis were analysed for common lung parenchymal patterns. Cox regression and Kaplan-Meier analysis were performed. RESULTS: At univariate analysis of the whole cohort, centrilobular ground-glass (CGG) changes (hazard ratio, HR 0.29) and ground-glass opacification (HR 0.53) predicted improved survival, while honeycombing (HR 2.79), emphysema (HR 2.09) and fibrosis (HR 2.38) predicted worse survival (all p<0.001). Fibrosis was an independent predictor after adjusting for baseline demographics, PH severity and diffusing capacity of the lung for carbon monoxide (HR 1.37, p<0.05). Patients with a clinical diagnosis of IPAH who had an absence of reported parenchymal lung disease (IPAH-noLD) demonstrated superior survival to patients diagnosed with either IPAH who had coexistent CT lung disease or PH-CLD (2-year survival of 85%, 60% and 46%, respectively, p<0.05). CGG changes were present in 23.3% of IPAH-noLD and 5.8% of PH-CLD patients. There was no significant difference in survival between IPAH-noLD patients with or without CGG changes. PH-CLD patients with fibrosis had worse survival than those with emphysema. INTERPRETATION: Routine clinical reports of CT lung parenchymal disease identify groups of patients with IPAH and PH-CLD with significantly different prognoses. Isolated CGG changes are not uncommon in IPAH but are not associated with worse survival.

17.
ERJ Open Res ; 7(3)2021 Jul.
Article in English | MEDLINE | ID: mdl-34589542

ABSTRACT

BACKGROUND: Hyperpolarised gas magnetic resonance imaging (MRI) can be used to assess ventilation patterns. Previous studies have shown the image-derived metric of ventilation defect per cent (VDP) to correlate with forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) and FEV1 in asthma. OBJECTIVES: The aim of this study was to explore the utility of hyperpolarised xenon-129 (129Xe) ventilation MRI in clinical care and examine its relationship with spirometry and other clinical metrics in people seen in a severe asthma service. METHODS: 26 people referred from a severe asthma clinic for MRI scanning were assessed by contemporaneous 129Xe MRI and spirometry. A subgroup of 18 patients also underwent reversibility testing with spirometry and MRI. Quantitative MRI measures of ventilation were calculated, VDP and the ventilation heterogeneity index (VHI), and compared to spirometry, Asthma Control Questionnaire 7 (ACQ7) and blood eosinophil count. Images were reviewed by a multidisciplinary team. RESULTS: VDP and VHI correlated with FEV1, FEV1/FVC and forced expiratory flow between 25% and 75% of FVC but not with ACQ7 or blood eosinophil count. Discordance of MRI imaging and symptoms and/or pulmonary function tests also occurred, prompting diagnostic re-evaluation in some cases. CONCLUSION: Hyperpolarised gas MRI provides a complementary method of assessment in people with difficult to manage asthma in a clinical setting. When used as a tool supporting clinical care in a severe asthma service, occurrences of discordance between symptoms, spirometry and MRI scanning indicate how MRI scanning may add to a management pathway.

18.
BMJ Open Respir Res ; 8(1)2021 09.
Article in English | MEDLINE | ID: mdl-34556492

ABSTRACT

INTRODUCTION: The COVID-19 pandemic has led to over 100 million cases worldwide. The UK has had over 4 million cases, 400 000 hospital admissions and 100 000 deaths. Many patients with COVID-19 suffer long-term symptoms, predominantly breathlessness and fatigue whether hospitalised or not. Early data suggest potentially severe long-term consequence of COVID-19 is development of long COVID-19-related interstitial lung disease (LC-ILD). METHODS AND ANALYSIS: The UK Interstitial Lung Disease Consortium (UKILD) will undertake longitudinal observational studies of patients with suspected ILD following COVID-19. The primary objective is to determine ILD prevalence at 12 months following infection and whether clinically severe infection correlates with severity of ILD. Secondary objectives will determine the clinical, genetic, epigenetic and biochemical factors that determine the trajectory of recovery or progression of ILD. Data will be obtained through linkage to the Post-Hospitalisation COVID platform study and community studies. Additional substudies will conduct deep phenotyping. The Xenon MRI investigation of Alveolar dysfunction Substudy will conduct longitudinal xenon alveolar gas transfer and proton perfusion MRI. The POST COVID-19 interstitial lung DiseasE substudy will conduct clinically indicated bronchoalveolar lavage with matched whole blood sampling. Assessments include exploratory single cell RNA and lung microbiomics analysis, gene expression and epigenetic assessment. ETHICS AND DISSEMINATION: All contributing studies have been granted appropriate ethical approvals. Results from this study will be disseminated through peer-reviewed journals. CONCLUSION: This study will ensure the extent and consequences of LC-ILD are established and enable strategies to mitigate progression of LC-ILD.


Subject(s)
COVID-19/complications , Lung Diseases, Interstitial , Humans , Longitudinal Studies , Lung Diseases, Interstitial/epidemiology , Observational Studies as Topic , Pandemics , Prospective Studies , United Kingdom/epidemiology
19.
Comput Med Imaging Graph ; 93: 101982, 2021 10.
Article in English | MEDLINE | ID: mdl-34481237

ABSTRACT

Multi-atlas segmentation of cardiac regions and total infarct scar (MA-SOCRATIS) is an unsupervised automatic pipeline to segment left ventricular myocardium and scar from late gadolinium enhanced MR images (LGE-MRI) of the heart. We implement two different pipelines for myocardial and scar segmentation from short axis LGE-MRI. Myocardial segmentation has two steps; initial segmentation and re-estimation. The initial segmentation step makes a first estimate of myocardium boundaries by using multi-atlas segmentation techniques. The re-estimation step refines the myocardial segmentation by a combination of k-means clustering and a geometric median shape variation technique. An active contour technique determines the unhealthy and healthy myocardial wall. The scar segmentation pipeline is a combination of a Rician-Gaussian mixture model and full width at half maximum (FWHM) thresholding, to determine the intensity pixels in scar regions. Following this step a watershed method with an automatic seed-points framework segments the final scar region. MA-SOCRATIS was evaluated using two different datasets. In both datasets ground truths were based on manual segmentation of short axis images from LGE-MRI scans. The first dataset included 40 patients from the MS-CMRSeg 2019 challenge dataset (STACOM at MICCAI 2019). The second is a collection of 20 patients with scar regions that are challenging to segment. MA-SOCRATIS achieved robust and accurate performance in automatic segmentation of myocardium and scar regions without the need of training or tuning in both cohorts, compared with state-of-the-art techniques (intra-observer and inter observer myocardium segmentation: 81.9% and 70% average Dice value, and scar (intra-observer and inter observer segmentation: 70.5% and 70.5% average Dice value).


Subject(s)
Heart Ventricles , Myocardial Infarction , Cicatrix/diagnostic imaging , Cicatrix/pathology , Gadolinium , Heart Ventricles/diagnostic imaging , Heart Ventricles/pathology , Humans , Imaging, Three-Dimensional , Magnetic Resonance Imaging , Myocardial Infarction/diagnostic imaging
20.
Magn Reson Med ; 86(6): 2966-2986, 2021 12.
Article in English | MEDLINE | ID: mdl-34478584

ABSTRACT

Hyperpolarized (HP) 129 Xe MRI uniquely images pulmonary ventilation, gas exchange, and terminal airway morphology rapidly and safely, providing novel information not possible using conventional imaging modalities or pulmonary function tests. As such, there is mounting interest in expanding the use of biomarkers derived from HP 129 Xe MRI as outcome measures in multi-site clinical trials across a range of pulmonary disorders. Until recently, HP 129 Xe MRI techniques have been developed largely independently at a limited number of academic centers, without harmonizing acquisition strategies. To promote uniformity and adoption of HP 129 Xe MRI more widely in translational research, multi-site trials, and ultimately clinical practice, this position paper from the 129 Xe MRI Clinical Trials Consortium (https://cpir.cchmc.org/XeMRICTC) recommends standard protocols to harmonize methods for image acquisition in HP 129 Xe MRI. Recommendations are described for the most common HP gas MRI techniques-calibration, ventilation, alveolar-airspace size, and gas exchange-across MRI scanner manufacturers most used for this application. Moreover, recommendations are described for 129 Xe dose volumes and breath-hold standardization to further foster consistency of imaging studies. The intention is that sites with HP 129 Xe MRI capabilities can readily implement these methods to obtain consistent high-quality images that provide regional insight into lung structure and function. While this document represents consensus at a snapshot in time, a roadmap for technical developments is provided that will further increase image quality and efficiency. These standardized dosing and imaging protocols will facilitate the wider adoption of HP 129 Xe MRI for multi-site pulmonary research.


Subject(s)
Lung , Xenon Isotopes , Lung/diagnostic imaging , Magnetic Resonance Imaging , Multicenter Studies as Topic , Pulmonary Ventilation , Respiration
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