Evaluation of image registration algorithms for 3D phase‐resolved functional lung ventilation magnetic resonance imaging in healthy volunteers and chronic obstructive pulmonary disease patients

Klimeš, Filip; Voskrebenzev, Andreas; Gutberlet, Marcel; Grimm, Robert; Wacker, Frank; Vogel‐Claussen, Jens

doi:10.1002/nbm.4860

Cited by 4 publications

(1 citation statement)

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“…3D imaging can extract more features and surrounding information that might be helpful for more precise lung parenchyma segmentation. Previously, other authors on segmenting of 3D morphological images in functional 3D pulmonary imaging [ 35 ]. The choice of using of 2D or 3D approach depends on the application.…”

Section: Discussionmentioning

confidence: 99%

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images

et al. 2023

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Purpose To improve automated lung segmentation on 2D lung MR images using balanced augmentation and artificially-generated consolidations for training of a convolutional neural network (CNN). Materials and methods From 233 healthy volunteers and 100 patients, 1891 coronal MR images were acquired. Of these, 1666 images without consolidations were used to build a binary semantic CNN for lung segmentation and 225 images (187 without consolidations, 38 with consolidations) were used for testing. To increase CNN performance of segmenting lung parenchyma with consolidations, balanced augmentation was performed and artificially-generated consolidations were added to all training images. The proposed CNN (CNNBal/Cons) was compared to two other CNNs: CNNUnbal/NoCons—without balanced augmentation and artificially-generated consolidations and CNNBal/NoCons—with balanced augmentation but without artificially-generated consolidations. Segmentation results were assessed using Sørensen-Dice coefficient (SDC) and Hausdorff distance coefficient. Results Regarding the 187 MR test images without consolidations, the mean SDC of CNNUnbal/NoCons (92.1 ± 6% (mean ± standard deviation)) was significantly lower compared to CNNBal/NoCons (94.0 ± 5.3%, P = 0.0013) and CNNBal/Cons (94.3 ± 4.1%, P = 0.0001). No significant difference was found between SDC of CNNBal/Cons and CNNBal/NoCons (P = 0.54). For the 38 MR test images with consolidations, SDC of CNNUnbal/NoCons (89.0 ± 7.1%) was not significantly different compared to CNNBal/NoCons (90.2 ± 9.4%, P = 0.53). SDC of CNNBal/Cons (94.3 ± 3.7%) was significantly higher compared to CNNBal/NoCons (P = 0.0146) and CNNUnbal/NoCons (P = 0.001). Conclusions Expanding training datasets via balanced augmentation and artificially-generated consolidations improved the accuracy of CNNBal/Cons, especially in datasets with parenchymal consolidations. This is an important step towards a robust automated postprocessing of lung MRI datasets in clinical routine.

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Section: Discussionmentioning

confidence: 99%

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images

et al. 2023

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Free‐Breathing Functional Pulmonary Proton MRI: A Novel Approach Using Voxel‐Wise Lung Ventilation (VOLVE) Assessment in Healthy Volunteers and Patients With Chronic Obstructive Pulmonary Disease

Peggs,

Brooke,

Bolton

et al. 2024

Magnetic Resonance Imaging

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BackgroundIn respiratory medicine, there is a need for sensitive measures of regional lung function that can be performed using standard imaging technology, without the need for inhaled or intravenous contrast agents.PurposeTo describe VOxel‐wise Lung VEntilation (VOLVE), a new method for quantifying regional lung ventilation (V) and perfusion (Q) using free‐breathing proton MRI, and to evaluate VOLVE in healthy never‐smokers, healthy people with smoking history, and people with chronic obstructive pulmonary disease (COPD).Study TypeProspective pilot.PopulationTwelve healthy never‐smoker participants (age 30.3 ± 12.5 years, five male), four healthy participants with smoking history (>10 pack‐years) (age 42.5 ± 18.3 years, one male), and 12 participants with COPD (age 62.8 ± 11.1 years, seven male).Field Strength/SequenceSingle‐slice free‐breathing two‐dimensional fast field echo sequence at 3 T.AssessmentA novel postprocessing was developed to evaluate the MR signal changes in the lung parenchyma using a linear regression‐based approach, which makes use of all the data in the time series for maximum sensitivity. V/Q‐weighted maps were produced by computing the cross‐correlation, lag and gradient between the respiratory/cardiac phase time course and lung parenchyma signal time courses. A comparison of histogram median and skewness values and spirometry was performed.Statistical TestsKruskal–Wallis tests with Dunn's multiple comparison tests to compare VOLVE metrics between groups; Spearman correlation to assess the correlation between MRI and spirometry‐derived parameters; and Bland–Altman analysis and coefficient of variation to evaluate repeatability were used. A P‐value <0.05 was considered significant.ResultsSignificant differences between the groups were found for ventilation between healthy never‐smoker and COPD groups (median XCCV, LagV, and GradV) and perfusion (median XCCQ, LagQ, and GradQ). Minimal bias and no significant differences between intravisit scans were found (P range = 0.12–0.97).Data ConclusionThis preliminary study showed that VOLVE has potential to provide metrics of function quantification.Level of Evidence2Technical EfficacyStage 1

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Effect of CFTR modulator therapy with elexacaftor/tezacaftor/ivacaftor on pulmonary ventilation derived by 3D phase-resolved functional lung MRI in cystic fibrosis patients

Klimeš,

Voskrebenzev,

Gutberlet

et al. 2023

Eur Radiol

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Objectives To investigate whether 3D phase-resolved functional lung (PREFUL)-MRI parameters are suitable to measure response to elexacaftor/tezacaftor/ivacaftor (ETI) therapy and their association with clinical outcomes in cystic fibrosis (CF) patients. Methods Twenty-three patients with CF (mean age: 21; age range: 14–46) underwent MRI examination at baseline and 8–16 weeks after initiation of ETI. Morphological and 3D PREFUL scans assessed pulmonary ventilation. Morphological images were evaluated using a semi-quantitative scoring system, and 3D PREFUL scans were evaluated by ventilation defect percentage (VDP) values derived from regional ventilation (RVent) and cross-correlation maps. Improved ventilation volume (IVV) normalized to body surface area (BSA) between baseline and post-treatment visit was computed. Forced expiratory volume in 1 second (FEV1) and mid-expiratory flow at 25% of forced vital capacity (MEF25), as well as lung clearance index (LCI), were assessed. Treatment effects were analyzed using paired Wilcoxon signed-rank tests. Treatment changes and post-treatment agreement between 3D PREFUL and clinical parameters were evaluated by Spearman’s correlation. Results After ETI therapy, all 3D PREFUL ventilation markers (all p < 0.0056) improved significantly, except for the mean RVent parameter. The BSA normalized IVVRVent was significantly correlated to relative treatment changes of MEF25 and mucus plugging score (all |r| > 0.48, all p < 0.0219). In post-treatment analyses, 3D PREFUL VDP values significantly correlated with spirometry, LCI, MRI global, morphology, and perfusion scores (all |r| > 0.44, all p < 0.0348). Conclusions 3D PREFUL MRI is a very promising tool to monitor CFTR modulator–induced regional dynamic ventilation changes in CF patients. Clinical relevance statement 3D PREFUL MRI is sensitive to monitor CFTR modulator–induced regional ventilation changes in CF patients. Improved ventilation volume correlates with the relative change of mucus plugging, suggesting that reduced endobronchial mucus is predominantly responsible for regional ventilation improvement. Key Points • 3D PREFUL MRI–derived ventilation maps show significantly reduced ventilation defects in CF patients after ETI therapy. • Significant post-treatment correlations of 3D PREFUL ventilation measures especially with LCI, FEV1 %pred, and global MRI score suggest that 3D PREFUL MRI is sensitive to measure improved regional ventilation of the lung parenchyma due to reduced inflammation induced by ETI therapy in CF patients. • 3D PREFUL MRI–derived improved ventilation volume (IVV) correlated with MRI mucus plugging score changes suggesting that reduced endobronchial mucus is predominantly responsible for regional ventilation improvement 8–16 weeks after ETI therapy.

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Evaluation of image registration algorithms for 3D phase‐resolved functional lung ventilation magnetic resonance imaging in healthy volunteers and chronic obstructive pulmonary disease patients

Cited by 4 publications

References 40 publications

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images

Free‐Breathing Functional Pulmonary Proton MRI: A Novel Approach Using Voxel‐Wise Lung Ventilation (VOLVE) Assessment in Healthy Volunteers and Patients With Chronic Obstructive Pulmonary Disease

Effect of CFTR modulator therapy with elexacaftor/tezacaftor/ivacaftor on pulmonary ventilation derived by 3D phase-resolved functional lung MRI in cystic fibrosis patients

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