CT Image Registration-based Lung Mechanics in COPD PDF Download

Author: Sandeep Bodduluri
Publisher:
ISBN:
Category : Lungs
Languages : en
Pages : 143

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Book Description
Chronic obstructive pulmonary disease (COPD) is a growing health concern associated with high morbidity and mortality, and is currently the third-ranked cause of death in the United States. COPD is characterized by airflow limitation that is not fully reversible and includes chronic bronchitis, functional small airway disease, and emphysema. The interrelationship between emphysema and airway disease in COPD makes it a highly complex and heterogeneous disorder. Appropriate diagnosis of COPD is vital to administer targeted therapy strategies that can improve patient's quality of life and reduce the frequency of COPD associated exacerbations. Although spirometry or pulmonary function tests are currently the gold standard for the diagnosis and staging of the disease, their lack of reproducibility and minimal information on regional characterization of the lung tissue destruction makes it hard to rely on to phenotype COPD population and predict disease progression. Quantification of COPD, as done by computed tomography (CT) methods has seen significant advancements, helping us understand the complex pathophysiology of this disease. The prospective and established techniques that are derived from CT imaging such as densitometry, texture, airway, and pulmonary vasculature-based analyses have been successful in regional characterization of emphysema related lung tissue destruction and airway disease related morphological changes in COPD patients. Although, these measures enriched our diagnostic and treating capability of COPD, they lack information on patient specific alterations in lung mechanics and regional parenchymal stresses. This valuable information can be achieved through the use of image registration protocols. Our main goal of this research work is to examine and evaluate the role of lung mechanical measures derived from CT image registration techniques in COPD diagnosis, phenotyping, and progression.

Author: Kai Ding
Publisher:
ISBN:
Category : Lungs
Languages : en
Pages : 158

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Book Description
The main function of the respiratory system is gas exchange. Since many disease or injury conditions can cause biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung function and mechanics. In this thesis, we present a technique that uses multiple respiratory-gated CT images of the lung acquired at different levels of inflation with both breath-hold static scans and retrospectively reconstructed 4D dynamic scans, along with non-rigid 3D image registration, to make local estimates of lung tissue function and mechanics. We validate our technique using anatomical landmarks and functional Xe-CT estimated specific ventilation. The major contributions of this thesis include: 1) developing the registration derived regional expansion estimation approach in breath-hold static scans and dynamic 4DCT scans, 2) developing a method to quantify lobar sliding from image registration derived displacement field, 3) developing a method for measurement of radiation-induced pulmonary function change following a course of radiation therapy, 4) developing and validating different ventilation measures in 4DCT. The ability of our technique to estimate regional lung mechanics and function as a surrogate of the Xe-CT ventilation imaging for the entire lung from quickly and easily obtained respiratory-gated images, is a significant contribution to functional lung imaging because of the potential increase in resolution, and large reductions in imaging time, radiation, and contrast agent exposure. Our technique may be useful to detect and follow the progression of lung disease such as COPD, may be useful as a planning tool during RT planning, may be useful for tracking the progression of toxicity to nearby normal tissue during RT, and can be used to evaluate the effectiveness of a treatment post-therapy.

Author: Yoshiharu Ohno
Publisher: Springer Nature
ISBN: 3030435393
Category : Medical
Languages : en
Pages : 363

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Book Description
This book reviews the basics of pulmonary functional imaging using new CT and MR techniques and describes the clinical applications of these techniques in detail. The intention is to equip readers with a full understanding of pulmonary functional imaging that will allow optimal application of all relevant techniques in the assessment of a variety of diseases, including COPD, asthma, cystic fibrosis, pulmonary thromboembolism, pulmonary hypertension, lung cancer and pulmonary nodule. Pulmonary functional imaging has been promoted as a research and diagnostic tool that has the capability to overcome the limitations of morphological assessments as well as functional evaluation based on traditional nuclear medicine studies. The recent advances in CT and MRI and in medical image processing and analysis have given further impetus to pulmonary functional imaging and provide the basis for future expansion of its use in clinical applications. In documenting the utility of state-of-the-art pulmonary functional imaging in diagnostic radiology and pulmonary medicine, this book will be of high value for chest radiologists, pulmonologists, pulmonary surgeons, and radiation technologists.

Author: Jens Petersen
Publisher: Springer
ISBN: 9783030624682
Category : Computers
Languages : en
Pages : 166

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Book Description
This book constitutes the proceedings of the Second International Workshop on Thoracic Image Analysis, TIA 2020, held in Lima, Peru, in October 2020. Due to COVID-19 pandemic the conference was held virtually. COVID-19 infection has brought a lot of attention to lung imaging and the role of CT imaging in the diagnostic workflow of COVID-19 suspects is an important topic. The 14 full papers presented deal with all aspects of image analysis of thoracic data, including: image acquisition and reconstruction, segmentation, registration, quantification, visualization, validation, population-based modeling, biophysical modeling (computational anatomy), deep learning, image analysis in small animals, outcome-based research and novel infectious disease applications.

Author: Alexander Schmidt-Richberg
Publisher: Springer Science & Business Media
ISBN: 3658016620
Category : Computers
Languages : en
Pages : 179

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Book Description
Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.

Author: Hamed Minaeizaeim
Publisher:
ISBN:
Category : Diagnostic imaging
Languages : en
Pages : 170

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Book Description
Respiratory disease places an exceptionally high economic and social burden on society. Due to limitations of pulmonary function tests, most lung abnormalities are diagnosed using imaging techniques such as computed tomography and chest X-ray. In the clinical setting, in order to diagnose, prognose and evaluate lung diseases and overcome limitations of each imaging technique, multiple images may be taken at different volumes or postures. To improve interpretation, these images need to be accurately mapped together to relate information in one to another. Although a number of image registration techniques have been developed, either based on image intensity or landmarks, these techniques are not robust when significant changes in lung volume or postural changes occur, as the lung is highly deformable. Furthermore, they are not typically constrained to physical tissue deformation, so their results can be non-physical. In this thesis, a physics-based lung image registration using finite element method was developed and incorporated into an existing intensity based free form registration. When we breathe, the shape of the lung changes non-uniformly, as most of the lung is constrained by the chest wall but the diaphragm moves more freely. This deformation plays an important role in the physiology and mechanics of breathing. However, no biophysical accurate model has been published on the effect of the pleural cavity shape changes during breathing or posture changes. In this study, quantitative measurement of how the shape of pleural cavity for the left lung changes between two different postures and volumes were made. Then, cavity shape changes were incorporated in a biophysically based model of lung tissue deformation. Both left and right lungs deform significantly during the breathing cycle and both lungs have similar physical structure, and so likely material properties. In this study, the left lung was selected as it has more complex deformation than the right lung due to the location of the heart, which has been proposed to interact with the lung and influence its deformation. The model was assessed in healthy subjects imaged at functional residual capacity and total lung capacity in supine posture and ten healthy subjects imaged at total lung capacity in supine and prone postures. The biophysical model of the lung was used to develop a physics-based lung registration that can map the material points between a source and target image. This method can register lung images despite different postures and volumes. Furthermore, a hybrid method combining the biophysical model and free form deformation were developed to create a robust registration methodology that can rely on both the physics of the lung and image intensity. This novel registration technique was examined in two case studies of clinical interest. The first is in an adult population where multiple high-resolution computed tomography (CT) images are available, a cohort with idiopathic pulmonary fibrosis to register multiple CT images in the same subjects at different time points. Idiopathic pulmonary fibrosis can be difficult to assess as patients may find it difficult to breath to reproducible volumes at repeat visits, in this study we show how registration can help to quantitatively evaluate progression of disease features in imaging by mapping data to a consistent lung volume. The second case focuses on a more challenging population, a cohort of children with cystic fibrosis, for whom both high-resolution computed tomography and X-ray images are acquired to monitor disease status. These images are typically analysed qualitatively or quantitatively without applying registration. In this study, a biophysically based model of the left lung was created using a CT image acquired in the supine position. Then, deformation of lung tissue in the upright position was computed and areas with abnormalities mapped to an X-ray image. A machine learning method was then employed to automatically differentiate between normal and abnormal areas in X-ray. The methodologies presented a tool for mapping abnormal regions between images to identify locations where abnormalities potentially change, and for multimodal and multidimensional registration.

Author: Jens Petersen
Publisher: Springer Nature
ISBN: 3030624692
Category : Computers
Languages : en
Pages : 170

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Book Description
This book constitutes the proceedings of the Second International Workshop on Thoracic Image Analysis, TIA 2020, held in Lima, Peru, in October 2020. Due to COVID-19 pandemic the conference was held virtually. COVID-19 infection has brought a lot of attention to lung imaging and the role of CT imaging in the diagnostic workflow of COVID-19 suspects is an important topic. The 14 full papers presented deal with all aspects of image analysis of thoracic data, including: image acquisition and reconstruction, segmentation, registration, quantification, visualization, validation, population-based modeling, biophysical modeling (computational anatomy), deep learning, image analysis in small animals, outcome-based research and novel infectious disease applications.

Author: Kaifang Du
Publisher:
ISBN:
Category : Image registration
Languages : en
Pages : 196

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Book Description
Current radiation therapy (RT) planning for limiting lung toxicity is based on a uniform lung function with little consideration to the spatial and temporal pattern of lung function. Establishment of relationships between radiation dose and changes in pulmonary function can help predict and reduce the RT-induced pulmonary toxicity. Baseline measurement uncertainty of pulmonary function across scans needs to be assessed, and there is a great interest to compensate the pulmonary function for respiratory effort variations. Respiratory-gated 4DCT imaging and image registration can be used to estimate the regional lung volume change by a transformation-based ventilation metric which is computed directly from the deformation field, or a intensity-based metric which is based on CT density change in the registered image pair.

Author: Yang Wook Kim
Publisher:
ISBN:
Category : Image registration
Languages : en
Pages : 68

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Book Description
Image registration is a useful technique to measure the change between two or more images. Lung CT image registration is widely used an non-invasive method to measure the lung function changes. Non-invasive lung function measurement accuracy highly depends on lung CT image registration accuracy. Improving the registration accuracy is an important issue. In this thesis, we propose incorporating information of the anatomical structure of the lung (fissures) as an additional cost function of the lung CT image registration. The intensity-based similarity measurement method (sum of the squared tissue volume differences) is also used to complement lung tissue information matching. However, since fissures are hard to segment, a sheet-likeness filter is applied to detect fissure-like structures. Sheet-likeness is used as an additional cost function of the intensity-based registration. The registration accuracy is verified by the visual assessment and landmark error measurement. The landmark error measurement can show an improvement of the proposed algorithm.

Author: Hans-Ulrich Kauczor
Publisher: Springer Science & Business Media
ISBN: 354034618X
Category : Medical
Languages : en
Pages : 315

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Book Description
During the past decade significant developments have been achieved in the field of magnetic resonance imaging (MRI), enabling MRI to enter the clinical arena of chest imaging. Standard protocols can now be implemented on up-to-date scanners, allowing MRI to be used as a first-line imaging modality for various lung diseases, including cystic fibrosis, pulmonary hypertension and even lung cancer. The diagnostic benefits stem from the ability of MRI to visualize changes in lung structure while simultaneously imaging different aspects of lung function, such as perfusion, respiratory motion, ventilation and gas exchange. On this basis, novel quantitative surrogates for lung function can be obtained. This book provides a comprehensive overview of how to use MRI for imaging of lung disease. Special emphasis is placed on benign diseases requiring regular monitoring, given that it is patients with these diseases who derive the greatest benefit from the avoidance of ionizing radiation.