111 research outputs found
Cardiac MRI characteristics in patients with borderline pulmonary hypertension: results from the ASPIRE registry
Imaging biomarkers of lung ventilation in interstitial lung disease from ¹²⁹Xe and oxygen enhanced ¹H MRI
PURPOSE: To compare imaging biomarkers from hyperpolarised 129Xe ventilation MRI and dynamic oxygen-enhanced MRI (OE-MRI) with standard pulmonary function tests (PFT) in interstitial lung disease (ILD) patients. To evaluate if biomarkers can separate ILD subtypes and detect early signs of disease resolution or progression. STUDY TYPE: Prospective longitudinal. POPULATION: Forty-one ILD (fourteen idiopathic pulmonary fibrosis (IPF), eleven hypersensitivity pneumonitis (HP), eleven drug-induced ILD (DI-ILD), five connective tissue disease related-ILD (CTD-ILD)) patients and ten healthy volunteers imaged at visit 1. Thirty-four ILD patients completed visit 2 (eleven IPF, eight HP, ten DIILD, five CTD-ILD) after 6 or 26 weeks. FIELD STRENGTH/SEQUENCE: MRI performed at 1.5 T. Inversion recovery T1 mapping, dynamic MRI acquisition with varying oxygen levels, and hyperpolarised 129Xe ventilation MRI. Subjects underwent standard spirometry and gas transfer testing. ASSESSMENT: Five 1H MRI and two 129Xe MRI ventilation metrics were compared with spirometry and gas transfer measurements. STATISTICAL TEST: To evaluate differences at visit 1 among subgroups: ANOVA or Kruskal-Wallis rank tests with correction for multiple comparisons. To assess the relationships between imaging biomarkers, PFT, age and gender, at visit 1 and for the change between visit 1 and 2: Pearson correlations and multilinear regression models. RESULTS: The global PFT tests could not distinguish ILD subtypes. Ventilated volumes were lower in ILD patients than in HVs when measured with 129Xe MRI (HV 97.4 ± 2.6, CTD-ILD: 91.0 ± 4.8 p = 0.017, DI-ILD 90.1 ± 7.4 p = 0.003, HP 92.6 ± 4.0 p = 0.013, IPF 88.1 ± 6.5 p < 0.001), but not with OE-MRI. 129Xe reported more heterogeneous ventilation in DI-ILD and IPF than in HV, and OE-MRI reported more heterogeneous ventilation in DI-ILD and IPF than in HP or CTD-ILD. The longitudinal changes reported by the imaging biomarkers did not correlate with the PFT changes between visits. DATA CONCLUSION: Neither 129Xe ventilation nor OE-MRI biomarkers investigated in this study were able to differentiate between ILD subtypes, suggesting that ventilation-only biomarkers are not indicated for this task. Limited but progressive loss of ventilated volume as measured by 129Xe-MRI may be present as the biomarker of focal disease progresses. OE-MRI biomarkers are feasible in ILD patients and do not correlate strongly with PFT. Both OE-MRI and 129Xe MRI revealed more spatially heterogeneous ventilation in DI-ILD and IPF
Simultaneous SuperDARN and Cluster observations of the growth and expansion phases of substorms
Airway microstructure in idiopathic pulmonary fibrosis: assessment at hyperpolarized 3He diffusion-weighted MRI
Background
MRI with inhaled hyperpolarized helium 3 (3He) allows for functional and structural imaging of the lungs. Hyperpolarized gas diffusion-weighted (DW) MRI provides noninvasive and quantitative assessment of microstructural acinar changes in the lungs.
Purpose
To investigate whether microstructural imaging metrics from in-vivo hyperpolarized 3He DW MRI are sensitive to longitudinal changes in a cohort of participants with idiopathic pulmonary fibrosis (IPF) and to evaluate the reproducibility of these metrics and their correlation with existing clinical measures of IPF disease severity.
Materials and Methods
In this prospective study, 18 participants with IPF underwent 3He DW MRI at 1.5 T and 11 participants underwent an identical same-day examination for reproducibility assessment. Thirteen participants returned for 6- and 12-month follow-up examinations. Pulmonary function tests, including diffusing capacity of the lungs for carbon monoxide and forced vital capacity, were performed at each examination. The apparent diffusion coefficient (ADC) and stretched exponential model–derived mean diffusive length scale (LmD) from DW MRI was compared with baseline CT fibrosis scores and pulmonary function tests by using Spearman rank correlation coefficient. Longitudinal changes in DW MRI and pulmonary function test measurements were assessed with Friedman tests and post hoc Dunn test.
Results
3He ADC and LmD were reproducible (mean Bland-Altman analysis bias, 0.002 cm2 · sec-1 and −1.5 μm, respectively). Elevated ADC and LmD regions qualitatively corresponded to fibrotic regions at CT. ADC and LmD correlated with diffusing capacity of the lungs for carbon monoxide (respectively: r = −0.56, P = .017; and r = −0.54, P = .02) and CT fibrosis score (respectively: r = 0.71, P = .001; and r = 0.65, P = .003). LmD increased by 12 μm after 12 months (P = .001) whereas mean ADC (P = .17), forced vital capacity (P = .12), and diffusing capacity of the lungs for carbon monoxide (P > .99) were not statistically different between examinations.
Conclusion
Helium 3 diffusion-weighted MRI-derived mean diffusive length scale demonstrates longitudinal changes in lungs affected by idiopathic pulmonary fibrosis
Non-invasive detection of severe PH in lung disease using magnetic resonance imaging
IntroductionSevere pulmonary hypertension (mean pulmonary artery pressure ≥35 mmHg) in chronic lung disease (PH-CLD) is associated with high mortality and morbidity. Data suggesting potential response to vasodilator therapy in patients with PH-CLD is emerging. The current diagnostic strategy utilises transthoracic Echocardiography (TTE), which can be technically challenging in some patients with advanced CLD. The aim of this study was to evaluate the diagnostic role of MRI models to diagnose severe PH in CLD.Methods167 patients with CLD referred for suspected PH who underwent baseline cardiac MRI, pulmonary function tests and right heart catheterisation were identified. In a derivation cohort (n = 67) a bi-logistic regression model was developed to identify severe PH and compared to a previously published multiparameter model (Whitfield model), which is based on interventricular septal angle, ventricular mass index and diastolic pulmonary artery area. The model was evaluated in a test cohort.ResultsThe CLD-PH MRI model [= (−13.104) + (13.059 * VMI)—(0.237 * PA RAC) + (0.083 * Systolic Septal Angle)], had high accuracy in the test cohort (area under the ROC curve (0.91) (p < 0.0001), sensitivity 92.3%, specificity 70.2%, PPV 77.4%, and NPV 89.2%. The Whitfield model also had high accuracy in the test cohort (area under the ROC curve (0.92) (p < 0.0001), sensitivity 80.8%, specificity 87.2%, PPV 87.5%, and NPV 80.4%.ConclusionThe CLD-PH MRI model and Whitfield model have high accuracy to detect severe PH in CLD, and have strong prognostic value
Detection of early sub-clinical lung disease in children with cystic fibrosis by lung ventilation imaging with hyperpolarized gas MRI
Hyperpolarised 3He ventilation-MRI, anatomical lung MRI, lung clearance index (LCI), low-dose CT and spirometry were performed on 19 children (6–16 years) with clinically stable mild cystic fibrosis (CF) (FEV1>−1.96), and 10 controls. All controls had normal spirometry, MRI and LCI. Ventilation-MRI was the most sensitive method of detecting abnormalities, present in 89% of patients with CF, compared with CT abnormalities in 68%, LCI 47% and conventional MRI 22%. Ventilation defects were present in the absence of CT abnormalities and in patients with normal physiology, including LCI. Ventilation-MRI is thus feasible in young children, highly sensitive and provides additional information about lung structure–function relationships
Assessment of the influence of lung inflation state on the quantitative parameters derived from hyperpolarized gas lung ventilation MRI in healthy volunteers.
In this study, the effect of lung volume on quantitative measures of lung ventilation was investigated using MRI with hyperpolarized 3He and 129Xe. Six volunteers were imaged with hyperpolarized 3He at five different lung volumes (residual volume (RV), RV+1L, functional residual capacity (FRC), FRC+1L and total lung capacity (TLC)), and three were also imaged with hyperpolarized 129Xe. Imaging at each of the lung volumes was repeated twice on the same day with corresponding 1H lung anatomical images. Percentage lung ventilated volume (%VV) and variation of signal intensity (heterogeneity score, Hscore) were evaluated. Increased ventilation heterogeneity, quantified by reduced %VV and increased Hscore, was observed at lower lung volumes with the least ventilation heterogeneity observed at TLC. For 3He MRI data, the coefficient of variation of %VV was less than 1.5% and less than 5.5% for Hscore at all lung volumes, whilst for 129Xe data the values were 4% and 10% respectively. Generally, %VV generated from 129Xe images was lower than that seen from 3He images. The good repeatability of 3He %VV found here supports prior publications showing that percentage lung ventilated volume is a robust method for assessing global lung ventilation. The greater ventilation heterogeneity observed at lower lung volumes indicates that there may be partial airway closure in healthy lungs and that lung volume should be carefully considered for reliable longitudinal measurements of %VV and Hscore. The results suggest that imaging patients at different lung volumes may help to elucidate obstructive disease pathophysiology and progression
Myocardial T1-mapping and extracellular volume in pulmonary arterial hypertension: A systematic review and meta-analysis
Introduction: Elevated myocardial T 1-mapping and extracellular volume (ECV) measured on cardiac MR (CMR) imaging is associated with myocardial abnormalities such as oedema or fibrosis. This meta-analysis aims to provide a summary of T 1-mapping and ECV values in pulmonary arterial hypertension (PAH) and compare their values with controls. Methods: We searched CENTRAL, MEDLINE, Embase, and Web of Science in August 2020. We included CMR studies reporting T 1-mapping or ECV values in adults with any type of PAH. We calculated the mean difference of T 1-values and ECV between PAH and controls. Results: We included 12 studies with 674 participants. T 1-values were significantly higher in PAH with the highest mean difference (MD) recorded at the RV insertion points (RVIP) (108 milliseconds (ms), 95% confidence intervals (CI) 89 to 128), followed by the RV free wall (MD 91 ms, 95% CI 56 to 126). The pooled mean T 1-value in PAH at the RVIP was 1084, 95% CI (1071 to 1097) measured using 1.5 Tesla Siemens systems. ECV was also higher in PAH with an MD of 7.5%, 95% CI (5.9 to 9.1) at the RV free wall. Conclusion: T 1 mapping values in PAH patients are on average 9% higher than healthy controls when assessed under the same conditions including the same MRI system, magnetic field strength or sequence used for acquisition. The highest T 1 and ECV values are at the RVIP. T 1 mapping and ECV values in PH are higher than the values reported in cardiomyopathies and were associated with poor RV function and RV dilatation
Pulmonary MR angiography and perfusion imaging—A review of methods and applications
The pulmonary vasculature and its role in perfusion and gas exchange is an important consideration in many conditions of the lung and heart. Currently the mainstay of imaging of the vasculature and perfusion of the lungs lies with CT and nuclear medicine perfusion scans, both of which require ionizing radiation exposure. Improvements in MRI techniques have increased the use of MRI in pulmonary vascular imaging. Here we review MRI methods for imaging the pulmonary vasculature and pulmonary perfusion, both using contrast enhanced and non-contrast enhanced methodology.
In many centres pulmonary MR angiography and dynamic contrast enhanced perfusion MRI are now well established in the routine workflow of patients particularly with pulmonary hypertension and thromboembolic disease. However, these imaging modalities offer exciting new directions for future research and clinical use in other respiratory diseases where consideration of pulmonary perfusion and gas exchange can provide insight in to pathophysiology
Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation:A Multi-center, Multi-vendor, and Multi-disease Study
Background: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters.Purpose: Develop a generalizable CNN for lung segmentation in 1H-MRI, robust to pathology, acquisition protocol, vendor, and center.Study type: Retrospective.Population: A total of 809 1H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6–85); 42% females) and 31 healthy participants (median age (range): 34 (23–76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets.Field Strength/Sequence: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1H-MRI.Assessment: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance.Statistical Tests: Kruskal–Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland–Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant.Results: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880–0.987), Average HD of 1.63 mm (0.65–5.45) and XOR of 0.079 (0.025–0.240) on the testing set and a DSC of 0.973 (0.866–0.987), Average HD of 1.11 mm (0.47–8.13) and XOR of 0.054 (0.026–0.255) on external validation data.Data Conclusion: The 3D CNN generated accurate 1H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center.Evidence Level: 4.Technical Efficacy: Stage 1.</p
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