Ultrashort Echo-Time Magnetic Resonance Imaging Is a Sensitive Method for the Evaluation of Early Cystic Fibrosis Lung Disease

Roach, David J.; Crémillieux, Yannick; Fleck, Robert; Brody, Alan S.; Serai, Suraj D.; Szczesniak, Rhonda; Kerlakian, Stephanie; Clancy, John; Woods, Jason C.

doi:10.1513/annalsats.201603-203oc

Cited by 82 publications

(73 citation statements)

References 58 publications

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“…Inter-observer and intra-observer agreement of the common CT scores has shown to be good to excellent [128,129]. Comparable reproducibility has also been found for MRI using CT or MR-specific adapted scoring systems in small numbers of studies [144,148]. For semiautomatic evaluation of bronchi dimension excellent inter-observer agreement has been found particularly for the bronchial lumen [151].…”

Section: Clinical Valuementioning

confidence: 83%

See 1 more Smart Citation

Pathogenesis, imaging and clinical characteristics of CF and non-CF bronchiectasis

Schäfer

Griese²,

Chandrasekaran

et al. 2018

BMC Pulm Med

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Bronchiectasis is a common feature of severe inherited and acquired pulmonary disease conditions. Among inherited diseases, cystic fibrosis (CF) is the major disorder associated with bronchiectasis, while acquired conditions frequently featuring bronchiectasis include post-infective bronchiectasis and chronic obstructive pulmonary disease (COPD). Mechanistically, bronchiectasis is driven by a complex interplay of inflammation and infection with neutrophilic inflammation playing a predominant role. The clinical characterization and management of bronchiectasis should involve a precise diagnostic workup, tailored therapeutic strategies and pulmonary imaging that has become an essential tool for the diagnosis and follow-up of bronchiectasis. Prospective future studies are required to optimize the diagnostic and therapeutic management of bronchiectasis, particularly in heterogeneous non-CF bronchiectasis populations.

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Section: Clinical Valuementioning

confidence: 83%

“…MRI has no side effects by radiation enabling long-term surveillance of lung damage. The overall diagnostic performance by scores evaluation of MRI in direct comparison to CT is good to excellent [144][145][146] (Fig. 4).…”

Section: Imaging Characteristics Of Bronchiectasismentioning

confidence: 98%

Pathogenesis, imaging and clinical characteristics of CF and non-CF bronchiectasis

Schäfer

Griese²,

Chandrasekaran

et al. 2018

BMC Pulm Med

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“…A recent study demonstrated that the UTE signal–intensity measurements of the lung are reproducible and significantly correlated with computed tomography (CT) measures of emphysema and pulmonary function testing in human subjects with chronic obstructive pulmonary disease . Moreover, UTE proton MRI has been recently shown to have favorable comparison to CT findings of lung structural changes in subjects with evidence of cystic fibrosis (CF) …”

mentioning

confidence: 99%

Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI

Zha

Fain

Schiebler

et al. 2019

Magnetic Resonance Imaging

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Background Ultrashort echo time (UTE) proton MRI has gained popularity for assessing lung structure and function in pulmonary imaging; however, the development of rapid biomarker extraction and regional quantification has lagged behind due to labor‐intensive lung segmentation. Purpose To evaluate a deep learning (DL) approach for automated lung segmentation to extract image‐based biomarkers from functional lung imaging using 3D radial UTE oxygen‐enhanced (OE) MRI. Study Type Retrospective study aimed to evaluate a technical development. Population Forty‐five human subjects, including 16 healthy volunteers, 5 asthma, and 24 patients with cystic fibrosis. Field Strength/Sequence 1.5T MRI, 3D radial UTE (TE = 0.08 msec) sequence. Assessment Two 3D radial UTE volumes were acquired sequentially under normoxic (21% O2) and hyperoxic (100% O2) conditions. Automated segmentation of the lungs using 2D convolutional encoder‐decoder based DL method, and the subsequent functional quantification via adaptive K‐means were compared with the results obtained from the reference method, supervised region growing. Statistical Tests Relative to the reference method, the performance of DL on volumetric quantification was assessed using Dice coefficient with 95% confidence interval (CI) for accuracy, two‐sided Wilcoxon signed‐rank test for computation time, and Bland–Altman analysis on the functional measure derived from the OE images. Results The DL method produced strong agreement with supervised region growing for the right (Dice: 0.97; 95% CI = [0.96, 0.97]; P < 0.001) and left lungs (Dice: 0.96; 95% CI = [0.96, 0.97]; P < 0.001). The DL method averaged 46 seconds to generate the automatic segmentations in contrast to 1.93 hours using the reference method (P < 0.001). Bland–Altman analysis showed nonsignificant intermethod differences of volumetric (P ≥ 0.12) and functional measurements (P ≥ 0.34) in the left and right lungs. Data Conclusion DL provides rapid, automated, and robust lung segmentation for quantification of regional lung function using UTE proton MRI. Level of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1169–1181.

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“…Recently, ultrashort echo time (UTE) MRI with 3D radial k ‐space trajectories has shown promise in overcoming these obstacles. However, experience with 3D radial UTE chest MR is limited to animal models and small human studies, mostly in adults . Moreover, 3D radial acquisitions suffer from inherent inefficiencies in fully populating k ‐space, leading to trade‐offs between longer scan times and data undersampling with lesser resolution …”

mentioning

confidence: 99%

“…However, experience with 3D radial UTE chest MR is limited to animal models and small human studies, mostly in adults. [15][16][17][18][19][20][21][22][23] Moreover, 3D radial acquisitions suffer from inherent inefficiencies in fully populating k-space, leading to trade-offs between longer scan times and data undersampling with lesser resolution. 24 UTE imaging utilizing conical k-space sampling permits greater scan efficiency than do radial acquisitions.…”

mentioning

confidence: 99%

Free‐breathing pediatric chest MRI: Performance of self‐navigated golden‐angle ordered conical ultrashort echo time acquisition

Zucker

Cheng

Haldipur

et al. 2017

Magnetic Resonance Imaging

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Ultrashort Echo-Time Magnetic Resonance Imaging Is a Sensitive Method for the Evaluation of Early Cystic Fibrosis Lung Disease

Cited by 82 publications

References 58 publications

Pathogenesis, imaging and clinical characteristics of CF and non-CF bronchiectasis

Pathogenesis, imaging and clinical characteristics of CF and non-CF bronchiectasis

Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI

Free‐breathing pediatric chest MRI: Performance of self‐navigated golden‐angle ordered conical ultrashort echo time acquisition

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