Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre

Tahir, Bilal; Marshall, Helen; Hughes, Paul; Brightling, Christopher E.; Collier, Guilhem; Ireland, R.H.; Wild, Jim M.

doi:10.1088/1361-6560/ab0145

Cited by 9 publications

(12 citation statements)

References 49 publications

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“…This might also be explained with the comparison of a static ventilation image acquired after a single inhalation of 129 Xe with a dynamic examination of tidal breathing using PREFUL‐MRI. It has been shown that the extent of VDP (and the reproducibility of measurements as well) with hyperpolarized gas depends on the chosen gas, the inflation state (ie, chosen breathing maneuver and applied gas volume 36 ) and the latency between inhalation and scan allowing gas uptake in delayed‐filling lung regions; for example, via collateral ventilation 37 . Kirby et al observed visually and quantitatively higher VDP obtained with 129 Xe MR imaging in comparison to 3 He MR imaging in patients with COPD but not in healthy subjects, 38 and Obert et al measured higher VDP using 19 F in comparison to 129 Xe 39 .…”

Section: Discussionmentioning

confidence: 99%

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing

Kaireit

Kern

Voskrebenzev

et al. 2020

Magnetic Resonance Imaging

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Background Regional flow volume loop ventilation‐weighted noncontrast‐enhanced proton lung MRI in free breathing has emerged as a novel technique for assessment of regional lung ventilation, but has yet not been validated with 129Xenon MRI (129Xe‐MRI), a direct visualization of ventilation in healthy volunteers, cystic fibrosis (CF), and chronic obstructive pulmonary disease (COPD) patients. Purpose To compare regional ventilation and regional flow volume loops measured by noncontrast‐enhanced ventilation‐weighted phase‐resolved functional lung MRI (PREFUL‐MRI) with 129Xe‐MRI ventilation imaging and with lung function test parameters. Study Type Retrospective study. Population Twenty patients with COPD, eight patients with CF, and six healthy volunteers. Field Strength/Sequence PREFUL and 129Xe‐MRI gradient echo sequences were acquired at 1.5T. Assessment Coronal slices of PREFUL‐MRI (free breathing) and 129Xe‐MRI (single breath‐hold) were acquired on the same day, matched by their ventrodorsal position and coregistered for evaluation. Ventilation defect percentage (VDP) was calculated based on regional ventilation (RV), regional flow volume loops (RFVL), or 129Xe‐MRI with two different threshold methods. A combined VDP was calculated for RV and RFVL. Additionally, lung function testing was performed (such as the forced expiratory volume in 1 second [FEV1]) was used. Statistical Tests The obtained parameters were compared using Wilcoxon tests, correlated using Spearman's correlation coefficient (r), and agreement between PREFUL and 129Xe‐MRI parameters was assessed using Bland–Altman analysis and Dice coefficients. Results VDP measured by PREFUL and 129Xe were significantly correlated with both thresholding techniques (r = 0.62–0.69, P < 0.05 for all) and with lung function test parameters. Combined RV and RFVL PREFUL defect maps correlated with lung function testing (eg, with FEV1 r = –0.87 P < 0.05), and showed better regional agreement to 129Xe‐MRI ventilation defects (Dice coefficient defect 0.413) with significantly higher VDP values (10.2 ± 27.3, P = 0.04) than either PREFUL defect map alone. Data Conclusion Combined RV and RFVL PREFUL defect maps likely increase sensitivity to mild airway obstruction with increased VDP values compared to 129Xe‐MRI, and correlate strongly with lung function test parameters. Level of Evidence 3 Technical Efficacy Stage 2

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Section: Discussionmentioning

confidence: 99%

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing

Kaireit

Kern

Voskrebenzev

et al. 2020

Magnetic Resonance Imaging

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“…Positive (or negative) values of indicate local lung volume expansion (or contraction) during inspiration, which is used as a surrogate for ventilation. Prior studies have shown that CTVI has good regional accuracy with Galligas PET [ 19 ] and hyperpolarized gas MRI [ 20 ], and has been incorporated to guide functional-avoidance planning [ 8 , 13 – 15 ].…”

Section: Methodsmentioning

confidence: 99%

CT ventilation image-guided helical Tomotherapy at sparing functional lungs for locally advanced lung cancer: analysis of dose-function metrics and the impact on pulmonary toxicity

Liu

Gao

et al. 2023

Radiat Oncol

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Purpose CT ventilation image (CTVI)-guided radiotherapy that selectively avoids irradiating highly-functional lung regions has potential to reduce pulmonary toxicity. Considering Helical TomoTherapy (HT) has higher modulation capabilities, we investigated the capability and characteristic of HT at sparing functional lungs for locally advanced lung cancer. Methods and materials Pretreatment 4DCT scans were carried out for 17 patients. Local lung volume expansion (or contraction) during inspiration is related to the volume change at a given lung voxel and is used as a surrogate for ventilation. The ventilation maps were generated from two sets of CT images (peak-exhale and peak-inhale) by deformable registration and a Jacobian-based algorithm. Each ventilation map was normalized to percentile images. Six plans were designed for each patient: one anatomical plan without ventilation map and five functional plans incorporating ventilation map which designed to spare varying degrees of high-functional lungs that were defined as the top 10%, 20%, 30%, 40%, and 50% of the percentile ventilation ranges, respectively. The dosimetric and evaluation factors were recorded regarding planning target volume (PTV) and other organs at risk (OARs), with particular attention to the dose delivered to total lung and functional lungs. An established dose-function-based normal tissue complication probability (NTCP) model was used to estimate risk of radiation pneumonitis (RP) for each scenario. Results Patients were divided into a benefit group (8 patients) and a non-benefit group (9 patients) based on whether the RP-risk of functional plan was lower than that of anatomical plan. The distance between high-ventilated region and PTV, as well as tumor volume had significant differences between the two groups (P < 0.05). For patients in the benefit group, the mean value of fV5, fV10, fV20, and fMLD (functional V5, V10, V20, and mean lung dose, respectively) were significantly lower starting from top 30% functional plan than in anatomical plan (P < 0.05). With expand of avoidance region in functional plans, the dose coverage of PTV is not sacrificed (P > 0.05) but at the cost of increased dose received by OARs. Conclusion Ventilation image-guided HT plans can reduce the dose received by highly-functional lung regions with a range up to top 50% ventilated area. The spatial distribution of ventilation and tumor size were critical factors to better select patients who could benefit from the functional plan.

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“… 66 Ventilation assessment using tissue expansion metrics based on the deformation fields generated by DIR or the differences in tissue density between the coregistered image pairs have shown reasonable correlation with the regional assessment of ventilation using Xenon CT 48,67 and Xenon-MRI. 68 However, variability between registration approaches has led to a poor correlation between DIR-based ventilation metrics and reference modalities at the voxel level. 69 …”

Section: Ai In Functional Quantificationmentioning

confidence: 99%

Artificial intelligence in functional imaging of the lung

Estépar

2021

The British Journal of Radiology

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Artificial intelligence (AI) is transforming the way we perform advanced imaging. From high-resolution image reconstruction to predicting functional response from clinically acquired data, AI is promising to revolutionize clinical evaluation of lung performance, pushing the boundary in pulmonary functional imaging for patients suffering from respiratory conditions. In this review, we overview the current developments and expound on some of the encouraging new frontiers. We focus on the recent advances in machine learning and deep learning that enable reconstructing images, quantitating, and predicting functional responses of the lung. Finally, we shed light on the potential opportunities and challenges ahead in adopting AI for functional lung imaging in clinical settings.

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Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre

Cited by 9 publications

References 49 publications

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing

CT ventilation image-guided helical Tomotherapy at sparing functional lungs for locally advanced lung cancer: analysis of dose-function metrics and the impact on pulmonary toxicity

Artificial intelligence in functional imaging of the lung

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Comparison of CT ventilation imaging and hyperpolarised gas MRI: effects of breathing manoeuvre

Cited by 9 publications

References 49 publications

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With 129Xenon Ventilation MRI and Lung Function Testing

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With 129Xenon Ventilation MRI and Lung Function Testing

CT ventilation image-guided helical Tomotherapy at sparing functional lungs for locally advanced lung cancer: analysis of dose-function metrics and the impact on pulmonary toxicity

Artificial intelligence in functional imaging of the lung

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Product

Resources

About

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing

Flow Volume Loop and Regional Ventilation Assessment Using Phase‐Resolved Functional Lung (PREFUL) MRI: Comparison With ¹²⁹Xenon Ventilation MRI and Lung Function Testing