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

Multi-Nuclear Magnetic Resonance Imaging of Obstructive Lung Disease

Obstructive lung diseases such as chronic-obstructive-lung-disease (COPD), bronchiectasis, and asthma are characterized by airflow obstruction. They affect over six million Canadians costing the economy $12 billion/year. Despite decades of research, therapies that modify obstructive-lung-disease progression and control are lacking because patient diagnosis, monitoring, and response to therapy are currently made using airflow measurements that may conceal the independent contributions of underlying pathologies. One goal of obstructive-lung-disease research is to develop ways to identify patients with specific underlying pathological phenotypes to improve patient care and outcomes. Thoracic computed-tomography (CT) and magnetic-resonance-imaging (MRI) provide ways to regionally identify the underlying pathologies associated with obstructive-lung-disease, and offer quantitative biomarkers of obstructive-lung-disease (e.g. lung-density, airway dimensions, ventilation abnormalities, and lung microstructure). As the first step to identify patients with specific underlying pathological phenotypes, it is important to understand the physiological and clinical consequences of these imaging derived measurements. Accordingly, our objective was to evaluate lung structure and function using multi-nuclear pulmonary MRI in aging and obstructive-lung-disease to provide a better understanding of MR-derived biomarkers. In older never-smokers, the majority of subjects had 3He MR ventilation abnormalities that were not responsive to bronchodilation. 3He ventilation abnormalities were related to airflow obstruction and airways resistance, but not occupational exposure or exercise limitation. We then developed and evaluated ultra-short-echo-time MRI in COPD subjects with and without bronchiectasis. This work demonstrated that ultra-short-echo-time MR-derived measurements were reproducible and significantly related to CT tissue-density measurements. In the COPD subjects with bronchiectasis, ultra-short-echo-time signal-intensity was related to airway measurements. In COPD subjects without bronchiectasis, ultra-short-echo-time signal-intensity was related to the severity of emphysema. Finally, based on the ultra-short-echo-time MR biomarkers developed in patients with COPD and bronchiectasis, patients that share some of the airway and inflammatory features common in asthmatics, we produced ultra-short-echo-time MR measurements in asthma. These measurements not only provided similar information as CT, but also information about regional ventilation deficits. These results demonstrated that ultra-short-echo-time MR biomarkers may reflect ventilation heterogeneity and/or gas-trapping in asthma. These important findings indicate that multi-nuclear pulmonary MRI has the potential to quantitatively evaluate the different pathologies of obstructive-lung-disease

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

Hyperpolarized 3He Magnetic Resonance Imaging Phenotypes of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the world. Identifying clinically relevant COPD phenotypes has the potential to reduce the global burden of COPD by helping to alleviate symptoms, slow disease progression and prevent exacerbation by stratifying patient cohorts and forming targeted treatment plans. In this regard, quantitative pulmonary imaging with hyperpolarized 3He magnetic resonance imaging (MRI) and thoracic computed tomography (CT) have emerged as ways to identify and measure biomarkers of lung structure and function. 3He MRI may be used as a tool to probe both functional and structural properties of the lung whereby static-ventilation maps allow the direct visualization of ventilated lung regions and 3He apparent diffusion coefficient maps show the lung microstructure at alveolar scales. At the same time, thoracic CT provides quantitative measurements of lung density and airway wall and lumen dimensions. Together, MRI and CT may be used to characterize the relative contributions of airways disease and emphysema on overall lung function, providing a way to phenotype underlying disease processes in a way that conventional measurements of airflow, taken at the mouth, cannot. Importantly, structure-function measurements obtained from 3He MRI and CT can be extracted from the whole-lung or from individual lung lobes, providing direct information on specific lung regions. In this thesis, my goal was to identify pulmonary imaging phenotypes to provide a better understanding of COPD pathophysiology in ex-smokers with and without airflow limitation. This thesis showed: 1) ex-smokers without airflow limitation had imaging evidence of subclinical lung and vascular disease, 2) pulmonary abnormalities in ex- smokers without airflow limitation were spatially related to airways disease and very mild emphysema, and, 3) in ex-smokers with COPD, there were distinct apical-basal lung phenotypes associated with disease severity. Collectively, these findings provide strong evidence that quantitative pulmonary imaging phenotypes may be used to characterize the underlying pathophysiology of very mild or early COPD and in patients with severe disease

This is what COPD looks like

Despite decades of research, and the growing healthcare and societal burden of chronic obstructive pulmonary disease (COPD), therapeutic COPD breakthroughs have not occurred. Sub-optimal COPD patient phenotyping, an incomplete understanding of COPD pathogenesis and a scarcity of sensitive tools that provide patient-relevant intermediate endpoints likely all play a role in the lack of new, efficacious COPD interventions. In other words, COPD patients are still diagnosed based on the presence of persistent airflow limitation measured using spirometry. Spirometry measurements reflect the global sum of all the different possible COPD pathologies and perhaps because of this, we lose sight of the different contributions of airway and parenchymal abnormalities. With recent advances in thoracic X-ray computed tomography (CT) and magnetic resonance imaging (MRI), lung structure and function abnormalities may be regionally identified and measured. These imaging endpoints may serve as biomarkers of COPD that can be used to better phenotype patients. Therefore, here we review novel CT and MRI measurements that help reveal COPD phenotypes and what COPD really \u27looks\u27 like, beyond spirometric indices. We discuss MR and CT imaging approaches for generating reproducible and sensitive measurements of COPD phenotypes related to pulmonary ventilation and perfusion as well as airway and parenchyma anatomical and morphological features. These measurements may provide a way to advance the development and testing of new COPD interventions and therapies

Quantitative lung CT analysis for the study and diagnosis of Chronic Obstructive Pulmonary Disease

The importance of medical imaging in the research of Chronic Obstructive Pulmonary Dis- ease (COPD) has risen over the last decades. COPD affects the pulmonary system through two competing mechanisms; emphysema and small airways disease. The relative contribu- tion of each component varies widely across patients whilst they can also evolve regionally in the lung. Patients can also be susceptible to exacerbations, which can dramatically ac- celerate lung function decline. Diagnosis of COPD is based on lung function tests, which measure airflow limitation. There is a growing consensus that this is inadequate in view of the complexities of COPD. Computed Tomography (CT) facilitates direct quantification of the pathological changes that lead to airflow limitation and can add to our understanding of the disease progression of COPD. There is a need to better capture lung pathophysiology whilst understanding regional aspects of disease progression. This has motivated the work presented in this thesis. Two novel methods are proposed to quantify the severity of COPD from CT by analysing the global distribution of features sampled locally in the lung. They can be exploited in the classification of lung CT images or to uncover potential trajectories of disease progression. A novel lobe segmentation algorithm is presented that is based on a probabilistic segmen- tation of the fissures whilst also constructing a groupwise fissure prior. In combination with the local sampling methods, a pipeline of analysis was developed that permits a re- gional analysis of lung disease. This was applied to study exacerbation susceptible COPD. Lastly, the applicability of performing disease progression modelling to study COPD has been shown. Two main subgroups of COPD were found, which are consistent with current clinical knowledge of COPD subtypes. This research may facilitate precise phenotypic characterisation of COPD from CT, which will increase our understanding of its natural history and associated heterogeneities. This will be instrumental in the precision medicine of COPD

Structure and Function of Asthma Evaluated Using Pulmonary Imaging

Asthma has been understood to affect the airways in a spatially heterogeneous manner for over six decades. Computational models of the asthmatic lung have suggested that airway abnormalities are diffusely and randomly distributed throughout the lung, however these mechanisms have been challenging to measure in vivo using current clinical tools. Pulmonary structure and function are still clinically characterized by the forced expiratory volume in one-second (FEV1) – a global measurement of airflow obstruction that is unable to capture the underlying regional heterogeneity that may be responsible for symptoms and disease worsening. In contrast, pulmonary magnetic resonance imaging (MRI) provides a way to visualize and quantify regional heterogeneity in vivo, and preliminary MRI studies in patients suggest that airway abnormalities in asthma are spatially persistent and not random. Despite these disruptive results, imaging has played a limited clinical role because the etiology of ventilation heterogeneity in asthma and its long-term pattern remain poorly understood. Accordingly, the objective of this thesis was to develop a deeper understanding of the pulmonary structure and function of asthma using functional MRI in conjunction with structural computed tomography (CT) and oscillometry, to provide a foundation for imaging to guide disease phenotyping, personalized treatment and prediction of disease worsening. We first evaluated the biomechanics of ventilation heterogeneity and showed that MRI and oscillometry explained biomechanical differences between asthma and other forms of airways disease. We then evaluated the long-term spatial and temporal nature of airway and ventilation abnormalities in patients with asthma. In nonidentical twins, we observed a spatially-matched CT airway and MRI ventilation abnormality that persisted for seven-years; we estimated the probability of an identical defect occurring in time and space to be 1 in 130,000. In unrelated asthmatics, ventilation defects were spatially-persistent over 6.5-years and uniquely predicted longitudinal bronchodilator reversibility. Finally, we investigated the entire CT airway tree and showed that airways were truncated in severe asthma related to thickened airway walls and worse MRI ventilation heterogeneity. Together, these results advance our understanding of asthma as a non-random disease and support the use of MRI ventilation to guide clinical phenotyping and treatment decisions

Evaluating Small Airways Disease in Asthma and COPD using the Forced Oscillation Technique and Magnetic Resonance Imaging

Obstructive lung disease, including asthma and chronic obstructive pulmonary disease (COPD), is characterized by heterogeneous ventilation. Unfortunately, the underlying structure-function relationships and the relationships between measurements of heterogeneity and patient quality-of-life in obstructive lung disease are not well understood. Hyperpolarized noble gas MRI is used to visualize and quantify ventilation distribution and the forced oscillation technique (FOT) applies a multi-frequency pressure oscillation at the mouth to measure respiratory impedance to airflow (including resistance and reactance). My objective was to use FOT, ventilation MRI and computational airway tree modeling to better understand ventilation heterogeneity in asthma and COPD. FOT-measured respiratory system impedance was correlated with MRI ventilation heterogeneity and both were related to quality-of-life in asthma and COPD. FOT-measurements and model-predictions of reactance and small-airways resistance were correlated in asthma and COPD respectively. This study is the first to demonstrate the relationships between FOT-measured impedance, MRI ventilation heterogeneity, and patient quality-of-life

A Heterogeneous Patient-Specific Biomechanical Model of the Lung for Tumor Motion Compensation and Effective Lung Radiation Therapy Planning

Radiation therapy is a main component of treatment for many lung cancer patients. However, the respiratory motion can cause inaccuracies in radiation delivery that can lead to treatment complications. In addition, the radiation-induced damage to healthy tissue limits the effectiveness of radiation treatment. Motion management methods have been developed to increase the accuracy of radiation delivery, and functional avoidance treatment planning has emerged to help reduce the chances of radiation-induced toxicity. In this work, we have developed biomechanical model-based techniques for tumor motion estimation, as well as lung functional imaging. The proposed biomechanical model accurately estimates lung and tumor motion/deformation by mimicking the physiology of respiration, while accounting for heterogeneous changes in the lung mechanics caused by COPD, a common lung cancer comorbidity. A biomechanics-based image registration algorithm is developed and is combined with an air segmentation algorithm to develop a 4DCT-based ventilation imaging technique, with potential applications in functional avoidance therapies