Delayed ventilation assessment using fast dynamic hyperpolarised Xenon-129 magnetic resonance imaging.

OBJECTIVES: To investigate the use of a fast dynamic hyperpolarised 129Xe ventilation magnetic resonance imaging (DXeV-MRI) method for detecting and quantifying delayed ventilation in patients with chronic obstructive pulmonary disease (COPD). METHODS: Three male participants (age range 31-43) with healthy lungs and 15 patients (M/F = 12:3, age range = 48-73) with COPD (stages II-IV) underwent spirometry tests, quantitative chest computed tomography (QCT), and DXeV-MRI at 1.5-Tesla. Regional delayed ventilation was captured by measuring the temporal signal change in each lung region of interest (ROI) in comparison to that in the trachea. In addition to its qualitative assessment through visual inspection by a clinical radiologist, delayed ventilation was quantitatively captured by calculating a covariance measurement of the lung ROI and trachea signals, and quantified using both the time delay, and the difference between the integrated areas covered by the signal-time curves of the two signals. RESULTS: Regional temporal ventilation, consistent with the expected physiological changes across a free breathing cycle, was demonstrated with DXeV-MRI in all patients. Delayed ventilation was observed in 13 of the 15 COPD patients and involved variable lung ROIs. This was in contrast to the control group, where no delayed ventilation was demonstrated (p = 0.0173). CONCLUSIONS: DXeV-MRI offers a non-invasive way of detecting and quantifying delayed ventilation in patients with COPD, and provides physiological information on regional pulmonary function during a full breathing cycle. KEY POINTS: • Dynamic xenon MRI allows for the non-invasive detection and measurement of delayed ventilation in COPD patients. • Dynamic xenon MRI during a free breathing cycle can provide unique information about pulmonary physiology and pulmonary disease pathophysiology. • With further validation, dynamic xenon MRI could offer a non-invasive way of measuring collateral ventilation which can then be used to guide lung volume reduction therapy (LVRT) for certain COPD patients.

CT-based Airway Flow Model to Assess Ventilation in Chronic Obstructive Pulmonary Disease: A Pilot Study.

Background The lack of functional information in thoracic CT remains a limitation of its use in the clinical management of chronic obstructive pulmonary disease (COPD). Purpose To compare the distribution of pulmonary ventilation assessed by a CT-based full-scale airway network (FAN) flow model with hyperpolarized xenon 129 (129Xe) MRI (hereafter, 129Xe MRI) and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging (hereafter, V-SPECT) in participants with COPD. Materials and Methods In this prospective study performed between May and August 2017, pulmonary ventilation in participants with COPD was computed by using the FAN flow model. The modeled pulmonary ventilation was compared with functional imaging data from breath-hold time-series 129Xe MRI and V-SPECT. FAN-derived ventilation images on the coronal plane and volumes of interest were compared with functional lung images. Percentage lobar ventilation estimated by the FAN model was compared with that measured at 129Xe MRI and V-SPECT. The statistical significance of ventilation distribution between FAN and functional images was demonstrated with the Spearman correlation coefficient and χ2 distance. Results For this study, nine participants (seven men [mean age, 65 years ± 5 {standard deviation}] and two women [mean age, 63 years ± 7]) with COPD that was Global Initiative for Chronic Obstructive Lung Disease stage II-IV were enrolled. FAN-modeled ventilation profile showed strong positive correlation with images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.65; P < .001). The χ2 distances of the ventilation histograms in the volumes of interest between the FAN and 129Xe MRI and FAN and V-SPECT were 0.16 ± 0.08 and 0.28 ± 0.14, respectively. The ratios of lobar ventilations in the models were linearly correlated to images from 129Xe MRI (ρ = 0.67; P < .001) and V-SPECT (ρ = 0.59; P < .001). Conclusion A CT-based full-scale airway network flow model provided regional pulmonary ventilation information for chronic obstructive pulmonary disease and correlates with hyperpolarized xenon 129 MRI and technetium 99m-diethylenetriaminepentaacetic acid aerosol SPECT ventilation imaging. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schiebler and Parraga in this issue.

Patch-based lung ventilation estimation using multi-layer supervoxels.

Patch-based approaches have received substantial attention over the recent years in medical imaging. One of their potential applications may be to provide more anatomically consistent ventilation maps estimated on dynamic lung CT. An assessment of regional lung function may act as a guide for radiotherapy, ensuring a more accurate treatment plan. This in turn, could spare well-functioning parts of the lungs. We present a novel method for lung ventilation estimation from dynamic lung CT imaging, combining a supervoxel-based image representation with deformations estimated during deformable image registration, performed between peak breathing phases. For this we propose a method that tracks changes of the intensity of previously extracted supervoxels. For the evaluation of the method we calculate correlation of the estimated ventilation maps with static ventilation images acquired from hyperpolarized Xenon129 MRI. We also investigate the influence of different image registration methods used to estimate deformations between the peak breathing phases in the dynamic CT imaging. We show that our method performs favorably to other ventilation estimation methods commonly used in the field, independently of the image registration method applied to dynamic CT. Due to the patch-based approach of our method, it may be physiologically more consistent with lung anatomy than previous methods relying on voxel-wise relationships. In our method the ventilation is estimated for supervoxels, which tend to group spatially close voxels with similar intensity values. The proposed method was evaluated on a dataset consisting of three lung cancer patients undergoing radiotherapy treatment, and this resulted in a correlation of 0.485 with XeMRI ventilation images, compared with 0.393 for the intensity-based approach, 0.231 for the Jacobian-based method and 0.386 for the Hounsfield units averaging method, on average. Within the limitation of the small number of cases analyzed, results suggest that the presented technique may be advantageous for CT-based ventilation estimation. The results showing higher values of correlation of the proposed method demonstrate the potential of our method to more accurately mimic the lung physiology.

Magnetic resonance imaging of the time course of hyperpolarized 129Xe gas exchange in the human lungs and heart.

PURPOSE: To perform magnetic resonance imaging (MRI), human lung imaging, and quantification of the gas-transfer dynamics of hyperpolarized xenon-129 (HPX) from the alveoli into the blood plasma. MATERIALS AND METHODS: HPX MRI with iterative decomposition of water and fat with echo asymmetry and least-square estimation (IDEAL) approach were used with multi-interleaved spiral k-space sampling to obtain HPX gas and dissolved phase images. IDEAL time-series images were then obtained from ten subjects including six normal subjects and four patients with pulmonary emphysema to test the feasibility of the proposed technique for capturing xenon-129 gas-transfer dynamics (XGTD). The dynamics of xenon gas diffusion over the entire lung was also investigated by measuring the signal intensity variations between three regions of interest, including the left and right lungs and the heart using Welch's t test. RESULTS: The technique enabled the acquisition of HPX gas and dissolved phase compartment images in a single breath-hold interval of 8 s. The y-intersect of the XGTD curves were also found to be statistically lower in the patients with lung emphysema than in the healthy group (p < 0.05). CONCLUSION: This time-series IDEAL technique enables the visualization and quantification of inhaled xenon from the alveoli to the left ventricle with a clinical gradient strength magnet during a single breath-hold, in healthy and diseased lungs. KEY POINTS: • The proposed hyperpolarized xenon-129 gas and dissolved magnetic resonance imaging technique can provide regional and temporal measurements of xenon-129 gas-transfer dynamics. • Quantitative measurement of xenon-129 gas-transfer dynamics from the alveolar to the heart was demonstrated in normal subjects and pulmonary emphysema. • Comparison of gas-transfer dynamics in normal subjects and pulmonary emphysema showed that the proposed technique appears sensitive to changes affecting the alveoli, pulmonary interstitium, and capillaries.

Time-series hyperpolarized xenon-129 MRI of lobar lung ventilation of COPD in comparison to V/Q-SPECT/CT and CT.

PURPOSE: To derive lobar ventilation in patients with chronic obstructive pulmonary disease (COPD) using a rapid time-series hyperpolarized xenon-129 (HPX) magnetic resonance imaging (MRI) technique and compare this to ventilation/perfusion single-photon emission computed tomography (V/Q-SPECT), correlating the results with high-resolution computed tomography (CT) and pulmonary function tests (PFTs). MATERIALS AND METHODS: Twelve COPD subjects (GOLD stages I-IV) participated in this study and underwent HPX-MRI, V/Q-SPECT/CT, high-resolution CT, and PFTs. HPX-MRI was performed using a novel time-series spiral k-space sampling approach. Relative percentage ventilations were calculated for individual lobe for comparison to the relative SPECT lobar ventilation and perfusion. The absolute HPX-MRI percentage ventilation in each lobe was compared to the absolute CT percentage emphysema score calculated using a signal threshold method. Pearson's correlation and linear regression tests were performed to compare each imaging modality. RESULTS: Strong correlations were found between the relative lobar percentage ventilation with HPX-MRI and percentage ventilation SPECT (r = 0.644; p < 0.001) and percentage perfusion SPECT (r = 0.767; p < 0.001). The absolute CT percentage emphysema and HPX percentage ventilation correlation was also statistically significant (r = 0.695, p < 0.001). The whole lung HPX percentage ventilation correlated with the PFT measurements (FEV1 with r = - 0.886, p < 0.001*, and FEV1/FVC with r = - 0.861, p < 0.001*) better than the whole lung CT percentage emphysema score (FEV1 with r = - 0.635, p = 0.027; and FEV1/FVC with r = - 0.652, p = 0.021). CONCLUSION: Lobar ventilation with HPX-MRI showed a strong correlation with lobar ventilation and perfusion measurements derived from SPECT/CT, and is better than the emphysema score obtained with high-resolution CT. KEY POINTS: • The ventilation hyperpolarized xenon-129 MRI correlates well with ventilation and perfusion with SPECT/CT with the advantage of higher temporal and spatial resolution. • The hyperpolarized xenon-129 MRI correlates with the PFT measurements better than the high-resolution CT with the advantage of avoiding the use of ionizing radiation.

Fast dynamic ventilation MRI of hyperpolarized 129 Xe using spiral imaging.

PURPOSE: To develop and optimize a rapid dynamic hyperpolarized 129 Xe ventilation (DXeV) MRI protocol and investigate the feasibility of capturing pulmonary signal-time curves in human lungs. THEORY AND METHODS: Spiral k-space trajectories were designed with the number of interleaves Nint = 1, 2, 4, and 8 corresponding to voxel sizes of 8 mm, 5 mm, 4 mm, and 2.5 mm, respectively, for field of view = 15 cm. DXeV images were acquired from a gas-flow phantom to investigate the ability of Nint = 1, 2, 4, and 8 to capture signal-time curves. A finite element model was constructed to investigate gas-flow dynamics corroborating the experimental signal-time curves. DXeV images were also carried out in six subjects (three healthy and three chronic obstructive pulmonary disease subjects). RESULTS: DXeV images and numerical modelling of signal-time curves permitted the quantification of temporal and spatial resolutions for different numbers of spiral interleaves. The two-interleaved spiral (Nint = 2) was found to be the most time-efficient to obtain DXeV images and signal-time curves of whole lungs with a temporal resolution of 624 ms for 13 slices. Signal-time curves were well matched in three healthy volunteers. The Spearman's correlations of chronic obstructive pulmonary disease subjects were statistically different from three healthy subjects (P < 0.05). CONCLUSION: The Nint = 2 spiral demonstrates the successful acquisition of DXeV images and signal-time curves in healthy subjects and chronic obstructive pulmonary disease patients. Magn Reson Med 79:2597-2606, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Chronic Obstructive Pulmonary Disease: Lobar Analysis with Hyperpolarized 129Xe MR Imaging.

Purpose To compare lobar ventilation and apparent diffusion coefficient (ADC) values obtained with hyperpolarized xenon 129 (129Xe) magnetic resonance (MR) imaging to quantitative computed tomography (CT) metrics on a lobar basis and pulmonary function test (PFT) results on a whole-lung basis in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods The study was approved by the National Research Ethics Service Committee; written informed consent was obtained from all patients. Twenty-two patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stage II-IV) underwent hyperpolarized 129Xe MR imaging at 1.5 T, quantitative CT, and PFTs. Whole-lung and lobar 129Xe MR imaging parameters were obtained by using automated segmentation of multisection hyperpolarized 129Xe MR ventilation images and hyperpolarized 129Xe MR diffusion-weighted images after coregistration to CT scans. Whole-lung and lobar quantitative CT-derived metrics for emphysema and bronchial wall thickness were calculated. Pearson correlation coefficients were used to evaluate the relationship between imaging measures and PFT results. Results Percentage ventilated volume and average ADC at lobar 129Xe MR imaging showed correlation with percentage emphysema at lobar quantitative CT (r = -0.32, P < .001 and r = 0.75, P < .0001, respectively). The average ADC at whole-lung 129Xe MR imaging showed moderate correlation with PFT results (percentage predicted transfer factor of the lung for carbon monoxide [Tlco]: r = -0.61, P < .005) and percentage predicted functional residual capacity (r = 0.47, P < .05). Whole-lung quantitative CT percentage emphysema also showed statistically significant correlation with percentage predicted Tlco (r = -0.65, P < .005). Conclusion Lobar ventilation and ADC values obtained from hyperpolarized 129Xe MR imaging demonstrated correlation with quantitative CT percentage emphysema on a lobar basis and with PFT results on a whole-lung basis. © RSNA, 2016.

MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations.

Non-local shape descriptor: a new similarity metric for deformable multi-modal registration.

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this problem and proposes a new similarity metric for multi-modal registration, the non-local shape descriptor. It aims to extract the shape of anatomical features in a non-local region. By utilizing the dense evaluation of shape descriptors, this new measure bridges the gap between intensity-based and geometric feature-based similarity criteria. Our new metric allows for accurate and reliable registration of clinical multi-modal datasets and is robust against the most considerable differences between modalities, such as non-functional intensity relations, different amounts of noise and non-uniform bias fields. The measure has been implemented in a non-rigid diffusion-regularized registration framework. It has been applied to synthetic test images and challenging clinical MRI and CT chest scans. Experimental results demonstrate its advantages over the most commonly used similarity metric - mutual information, and show improved alignment of anatomical landmarks.

Interventional radiology of pleural diseases.

Image-guided pleural procedures are important in both the diagnosis and management of pleural disease. Pleural aspiration, biopsy and drainage are all proven to be safer and more efficacious using image guidance. The aim of this article is to review common image-guided pleural techniques and the evidence base for their application in clinical practice.

Imaging of the pleura.

Pleural disease is a problem of global significance which causes significant morbidity and mortality. Pleural disease is usually first suspected on chest x-ray but further imaging, often ultrasound, is usually required as part of the diagnostic work-up. Complex imaging with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)-CT are less often performed but are routinely required in patients with mesothelioma and occasionally required in patients with pleural infection and other pleural diseases. Cross-sectional imaging may be used to suggest the diagnosis of pleural disease, quantify disease severity, guide biopsy, and even predict prognosis. This review will focus on the contributions of CT, MRI, and PET to the management of pleural disease with discussion of their relative strengths and weaknesses.