Pulmonary Image Segmentation and Registration Algorithms: Towards Regional Evaluation of Obstructive Lung Disease

Pulmonary imaging, including pulmonary magnetic resonance imaging (MRI) and computed tomography (CT), provides a way to sensitively and regionally measure spatially heterogeneous lung structural-functional abnormalities. These unique imaging biomarkers offer the potential for better understanding pulmonary disease mechanisms, monitoring disease progression and response to therapy, and developing novel treatments for improved patient care. To generate these regional lung structure-function measurements and enable broad clinical applications of quantitative pulmonary MRI and CT biomarkers, as a first step, accurate, reproducible and rapid lung segmentation and registration methods are required. In this regard, we first developed a 1H MRI lung segmentation algorithm that employs complementary hyperpolarized 3He MRI functional information for improved lung segmentation. The 1H-3He MRI joint segmentation algorithm was formulated as a coupled continuous min-cut model and solved through convex relaxation, for which a dual coupled continuous max-flow model was proposed and a max-flow-based efficient numerical solver was developed. Experimental results on a clinical dataset of 25 chronic obstructive pulmonary disease (COPD) patients ranging in disease severity demonstrated that the algorithm provided rapid lung segmentation with high accuracy, reproducibility and diminished user interaction. We then developed a general 1H MRI left-right lung segmentation approach by exploring the left-to-right lung volume proportion prior. The challenging volume proportion-constrained multi-region segmentation problem was approximated through convex relaxation and equivalently represented by a max-flow model with bounded flow conservation conditions. This gave rise to a multiplier-based high performance numerical implementation based on convex optimization theories. In 20 patients with mild- to-moderate and severe asthma, the approach demonstrated high agreement with manual segmentation, excellent reproducibility and computational efficiency. Finally, we developed a CT-3He MRI deformable registration approach that coupled the complementary CT-1H MRI registration. The joint registration problem was solved by exploring optical-flow techniques, primal-dual analyses and convex optimization theories. In a diverse group of patients with asthma and COPD, the registration approach demonstrated lower target registration error than single registration and provided fast regional lung structure-function measurements that were strongly correlated with a reference method. Collectively, these lung segmentation and registration algorithms demonstrated accuracy, reproducibility and workflow efficiency that all may be clinically-acceptable. All of this is consistent with the need for broad and large-scale clinical applications of pulmonary MRI and CT

Texture Analysis and Machine Learning to Predict Pulmonary Ventilation from Thoracic Computed Tomography

Chronic obstructive pulmonary disease (COPD) leads to persistent airflow limitation, causing a large burden to patients and the health care system. Thoracic CT provides an opportunity to observe the structural pathophysiology of COPD, whereas hyperpolarized gas MRI provides images of the consequential ventilation heterogeneity. However, hyperpolarized gas MRI is currently limited to research centres, due to the high cost of gas and polarization equipment. Therefore, I developed a pipeline using texture analysis and machine learning methods to create predicted ventilation maps based on non-contrast enhanced, single-volume thoracic CT. In a COPD cohort, predicted ventilation maps were qualitatively and quantitatively related to ground-truth MRI ventilation, and both maps were related to important patient lung function and quality-of-life measures. This study is the first to demonstrate the feasibility of predicting hyperpolarized MRI-based ventilation from single-volume, breath-hold thoracic CT, which has potential to translate pulmonary ventilation information to widely available thoracic CT imaging

Pulmonary Structure and Function in Chronic Obstructive Pulmonary Disease Evaluated using Hyperpolarized Noble Gas Magnetic Resonance Imaging

Chronic obstructive pulmonary disease (COPD) is the 4th leading cause of death worldwide and accounts for the highest rate of hospital admissions in Canada. The need for sensitive regional and surrogate measurements of lung structure and function in COPD continues to motivate the development of non-radiation based and sensitive imaging approaches, such as hyperpolarized helium-3 (3He) and xenon-129 (129Xe) magnetic resonance imaging (MRI). The static ventilation images acquired using these approaches allows us to directly visualize lung regions accessed by the hyperpolarized gas during a breath-hold, as well as quantify the regions without signal referred to as the percentage of the thoracic cavity occupied by ventilation defects (VDP). The lung micro-structure can also be probed using diffusion-weighted imaging which takes advantage of the rapid diffusion of 3He and 129Xe atoms to generate surrogate measurements of alveolar size, referred to as the apparent diffusion coefficient (ADC). Here we evaluated COPD lung structure and function using hyperpolarized gas MRI measurements longitudinally, following treatment and in early disease. In COPD ex-smokers, we demonstrated 3He VDP and ADC worsened significantly in only 2 years although there was no change in age-matched healthy volunteers, suggestive of disease progression. We also evaluated COPD ex-smokers pre- and post-bronchodilator and showed regional improvements in gas distribution following bronchodilator therapy regardless of spirometry-based responder classification; the ADC measured in these same COPD ex-smokers also revealed significant reductions in regional gas trapping post-bronchodilator. Although 3He MRI has been more widely used, the limited global quantities necessitates the transition to hyperpolarized 129Xe, and therefore we directly compared 3He and 129Xe MRI in the same COPD ex-smokers and showed significantly greater gas distribution abnormalities for 129Xe compared to 3He MRI that were spatially and significantly related to lung regions with elevated ADC. Finally, we demonstrated that ex-smokers with normal spirometry but abnormal diffusion capacity of the lung for carbon monoxide (DLCO) had significantly worse symptoms, exercise capacity and 3He ADC than ex-smokers with normal DLCO. These important findings indicate that hyperpolarized gas MRI can be used to improve our understanding of lung structural and functional changes in COPD

Three-Dimensional Computed Tomography Measurements of Pulmonary Artery Volumes: Development and Application

Chronic obstructive pulmonary disease (COPD) is a major contributor to hospitalizations and healthcare costs in North America. While the hallmark of COPD is airflow limitation, it is also associated with abnormalities of the cardiovascular system. Enlargement of the pulmonary artery (PA) is a morphological marker of pulmonary hypertension, and was previously shown to predict acute exacerbations using a one-dimensional (1D) diameter measurement of the main PA. We hypothesized that a three-dimensional (3D) quantification of PA size would be more sensitive than 1D methods and encompass morphological changes along the entire central PA. Hence, we developed a 3D measurement of the main (MPA), left (LPA) and right (RPA) pulmonary arteries as well as total PA volume (TPA) volume from thoracic x-ray computed tomography (CT) imaging. Three observers performed five repeated measurements for 15 ex-smokers. There was a strong agreement (r2 = 0.76) between PA volume and PA diameter measurements, which was used as the gold standard. Intra-rater measurement reproducibility was evaluated by calculating the coefficient of variation (CV) using five rounds of measurements and revealed excellent agreement (CV \u3c 8%) between measurements. Inter-rater measurement variability was also evaluated using intraclass correlation analysis which revealed strong agreement (ICCMPA=0.98) between observers. In an application of this tool, we sought to explore the relationship between PA volumes and lung structure-function as determined by spirometry, hyperpolarized helium-3 magnetic resonance imaging (MRI) and CT in 124 ex-smokers, with (n=68) and without (n=56) airflow limitation, and in a control group of 35 healthy never-smokers. We observed significantly greater MPA (p=.014), RPA (p=.001) and TPA (p=.003) volumes in ex-smokers with airflow limitation when compared to ex-smokers without airflow limitation. We also observed significantly greater PA volumes in both ex-smoker subgroups when compared with the never-smoker control group. Modest but significant correlations were observed for PA volumes and measurements of lung structure and function. However, this was not observed when analyzing ex-smokers with airflow limitation alone, suggesting that pulmonary artery enlargement may occur secondary to COPD in our subject group. Multivariate zero-inflated Poisson regression analysis revealed TPA volume to be a significant (p=.03) predictor of acute exacerbations of COPD. In conclusion, we developed a reproducible technique for quantifying the volume of the PA. We showed that pulmonary artery enlargement may be secondary to COPD in our subject group. We also showed that total pulmonary artery volume was a significant predictor of COPD exacerbations and could be considered as a biomarker for predicting the occurrence of exacerbation events. Automated measurements of pulmonary artery abnormalities once developed, can be used to further evaluate healthy volunteers and patients with COPD

Pulmonary Imaging to Better Understand Asthma

Asthma is characterized using the spirometry measurement of the forced expiratory volume in one second (FEV1). Simple and inexpensive, FEV1 provides a global estimate of lung function but this metric cannot regionally identify airways responsible for airflow limitation, asthma symptoms or control. Work that brought about an understanding that airway abnormalities are heterogeneously distributed within the lung in asthma patients has motivated the development of pulmonary imaging approaches, such as hyperpolarized helium-3 (3He) and xenon-129 (129Xe) magnetic resonance imaging (MRI). These methods provide a way to visualize and quantify lung regions accessed by gas during a breath-hold, as well as those not accessed, referred to as “ventilation defects.” Despite the strong foundation for the use of MRI in asthma clinical care, clinical translation has been inhibited in part due to the current limited clinical and physiological understanding of ventilation defects. Accordingly, our objective was to better understand the structural determinants and clinical consequences of MRI ventilation defects observed in asthma and to provide a foundation for imaging to guide clinical decisions and asthma therapy. We evaluated the effect of gas properties on ventilation defects. In asthmatics, we compared hyperpolarized 3He and 129Xe MRI before and after bronchodilator administration and showed greater gas distribution abnormalities using 129Xe compared to 3He before bronchodilation. The temporal behavior of asthma ventilation defects was then investigated by generating personalized temporal-spatial pulmonary function maps from 3He MR images acquired on three occasions. Persistent and intermittent defects were visualized and quantified using this tool and were recognized as potential intermediate endpoints or targets for treatment. We then evaluated clinical and emerging computed tomography-derived airway morphology measurements in asthmatics with and without defects. Ventilation defects were observed in two-thirds of well-controlled asthmatics who had worse lung function, increased airway inflammation, airway hyperresponsiveness and greater airway wall thickness than asthmatics without ventilation defects. Acknowledging that asthma control is the primary goal of asthma treatment, we investigated the relationship, and established a link between worse ventilation and poor control. These findings provide a better understanding of asthma ventilation defects and strongly support their potential as a novel treatment target

Quantitative Evaluation of Pulmonary Emphysema Using Magnetic Resonance Imaging and x-ray Computed Tomography

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality affecting at least 600 million people worldwide. The most widely used clinical measurements of lung function such as spirometry and plethysmography are generally accepted for diagnosis and monitoring of the disease. However, these tests provide only global measures of lung function and they are insensitive to early disease changes. Imaging tools that are currently available have the potential to provide regional information about lung structure and function but at present are mainly used for qualitative assessment of disease and disease progression. In this thesis, we focused on the application of quantitative measurements of lung structure derived from 1H magnetic resonance imaging (MRI) and high resolution computed tomography (CT) in subjects diagnosed with COPD by a physician. Our results showed that significant and moderately strong relationship exists between 1H signal intensity (SI) and 3He apparent diffusion coefficient (ADC), as well as between 1H SI and CT measurements of emphysema. This suggests that these imaging methods may be quantifying the same tissue changes in COPD, and that pulmonary 1H SI may be used effectively to monitor emphysema as a complement to CT and noble gas MRI. Additionally, our results showed that objective multi-threshold analysis of CT images for emphysema scoring that takes into account the frequency distribution of each Hounsfield unit (HU) threshold was effective in correctly classifying the patient into COPD and healthy subgroups. Finally, we found a significant correlation between whole lung average subjective and objective emphysema scores with high inter-observer agreement. It is concluded that 1H MRI and high resolution CT can be used to quantitatively evaluate lung tissue alterations in COPD subjects

Imaging Biomarkers of Pulmonary Structure and Function

Asthma and chronic obstructive pulmonary disease (COPD) are characterized by airflow limitations resulting from airway obstruction and/or tissue destruction. The diagnosis and monitoring of these pulmonary diseases is primarily performed using spirometry, specifically the forced expiratory volume in one second (FEV1), which measures global airflow obstruction and provides no regional information of the different underlying disease pathologies. The limitations of spirometry and current therapies for lung disease patients have motivated the development of pulmonary imaging approaches, such as computed tomography (CT) and magnetic resonance imaging (MRI). Inhaled hyperpolarized noble gas MRI, specifically using helium-3 (3He) and xenon-129 (129Xe) gases, provides a way to quantify pulmonary ventilation by visualizing lung regions accessed by gas during a breath-hold, and alternatively, regions that are not accessed - coined “ventilation defects.” Despite the strong foundation and many advantages hyperpolarized 3He MRI has to offer research and patient care, clinical translation has been inhibited in part due to the cost and need for specialized equipment, including multinuclear-MR hardware and polarizers, and personnel. Accordingly, our objective was to develop and evaluate imaging biomarkers of pulmonary structure and function using MRI and CT without the use of exogenous contrast agents or specialized equipment. First, we developed and compared CT parametric response maps (PRM) with 3He MR ventilation images in measuring gas-trapping and emphysema in ex-smokers with and without COPD. We observed that in mild-moderate COPD, 3He MR ventilation abnormalities were related to PRM gas-trapping whereas in severe COPD, ventilation abnormalities correlated with both PRM gas-trapping and PRM emphysema. We then developed and compared pulmonary ventilation abnormalities derived from Fourier decomposition of free-breathing proton (1H) MRI (FDMRI) with 3He MRI in subjects with COPD and bronchiectasis. This work demonstrated that FDMRI and 3He MRI ventilation defects were strongly related in COPD, but not in bronchiectasis subjects. In COPD only, FDMRI ventilation defects were spatially related with 3He MRI ventilation defects and emphysema. Based on the FDMRI biomarkers developed in patients with COPD and bronchiectasis, we then evaluated ventilation heterogeneity in patients with severe asthma, both pre- and post-salbutamol as well as post-methacholine challenge, using FDMRI and 3He MRI. FDMRI free-breathing ventilation abnormalities were correlated with but under-estimated 3He MRI static ventilation defects. Finally, based on the previously developed free-breathing MRI approach, we developed a whole-lung free-breathing pulmonary 1H MRI technique to measure regional specific-ventilation and evaluated both asthmatics and healthy volunteers. These measurements not only provided similar information as specific-ventilation measured using plethysmography, but also information about regional ventilation defects that were correlated with 3He MRI ventilation abnormalities. These results demonstrated that whole-lung free-breathing 1H MRI biomarker of specific-ventilation may reflect ventilation heterogeneity and/or gas-trapping in asthma. These important findings indicate that imaging biomarkers of pulmonary structure and function using MRI and CT have the potential to regionally reveal the different pathologies in COPD and asthma without the use of exogenous contrast agents. The development and validation of these clinically meaningful imaging biomarkers are critically required to accelerate pulmonary imaging translation from the research workbench to being a part of the clinical workflow, with the overall goal to improve patient outcomes

Optimal graph based segmentation using flow lines with application to airway wall segmentation

This paper introduces a novel optimal graph construction method that is applicable to multi-dimensional, multi-surface segmentation problems. Such problems are often solved by refining an initial coarse surface within the space given by graph columns. Conventional columns are not well suited for surfaces with high curvature or complex shapes but the proposed columns, based on properly generated flow lines, which are non-intersecting, guarantee solutions that do not self-intersect and are better able to handle such surfaces. The method is applied to segment human airway walls in computed tomography images. Comparison with manual annotations on 649 cross-sectional images from 15 different subjects shows significantly smaller contour distances and larger area of overlap than are obtained with recently published graph based methods. Airway abnormality measurements obtained with the method on 480 scan pairs from a lung cancer screening trial are reproducible and correlate significantly with lung function

Bronchoscopic lung volume reduction for Emphysema: physiological and radiological correlations

Introduction: Patient selection in lung volume reduction (LVR) plays a pivotal role in achieving meaningful clinical outcomes. Currently, LVR patients are selected based on three established criteria: heterogeneity index, percentage of low attenuation area (%LAA), and fissure integrity score. Quantitative computed tomography (QCT) has been developed to quantify lung physiological indices at the lobar level and could potentially revolutionise patient selection in LVR procedures. We developed an in-house QCT software, LungSeg, and used its radiological indices for the purposes of this thesis. The aim of this thesis is to discover potential physiological and radiological indices that could serve as predictors for superior LVR outcomes for better patient selection. Methods: This thesis took two studies and analysed them using LungSeg. The first study was the long-term coil study, a randomised controlled study that had the control group crossing over to the treatment arm at 12 months. At 12 months post-procedure the baseline measurements were assessed against the 12-months post-procedural measurements. The second study was the short-term valve study which was another randomised controlled study that compared the primary and secondary endpoints between the control and the valve-treated group at three months post-procedure. Results: In the long-term coil study, we found that the best statistically significant combination of predictors for change in target lobar volume at inspiration was found to be the combination of baseline target LV at inspiration, -950HU EI at inspiration, and TLCabs with a model adjusted R2 of 0.407 (p = 0.0001). In a subsequent multivariate analysis using ≥45% LAA on the -950HU at Inspiration, the R2 of the same prediction model did improve to 0.493 (P-value = 0.002). Meanwhile, the best statistically significant combination of predictors for change in target lobar volume at inspiration following valve treatment was found to be the combination of baseline target LV at inspiration, target lobar fissure integrity and baseline FEV1abs with a model adjusted R2 of 0.193 (p = 0.105). Conclusion: Using QCT, we have improved the proposed patient selection algorithm for LVR procedures based on the best QCT and lung function predictors.Open Acces