Regional Pulmonary Function Analysis Using Image Registration and 4DCT PDF Download

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: Kaifang Du
Publisher:
ISBN:
Category : Image registration
Languages : en
Pages : 105

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Book Description
Lung function depends on the expansion and contraction of lung tissue during the respiratory cycle. The measurement of regional pulmonary function is of great interest and importance since many lung diseases can cause changes in biomechanical or material properties. It is also significant to study the radiation-induced changes in pulmonary function following radiation therapy. In this thesis, we propose a technique that uses four-dimensional (3D+time) CT imaging (4DCT), 3D non-rigid image registration to estimate regional lung function. Lung images reconstructed at different inflation levels are analyzed for dynamic lung function development during a breath cycle. We demonstrate local pulmonary function can be reproducibly measured using 4DCT in human subjects prior to RT. The image registration accuracy is validated using semi-automatic anatomic landmark picking system. The major contributions of this thesis include: 1) demonstrating the robustness and reproducibility of regional pulmonary function measurement using 4DCT in both sheep and human subjects, 2) developing approaches to improve the measurement reproducibility by dynamic lung volume matching and Jacobian normalization, 3) development and comparison four cubic metrics for reproducibility analysis, 4) research on time-varying lung ventilation in different breathing phases in both sheep and human subjects. Our contributions in this thesis are useful for diagnosis and assessment of lung diseases, useful for qualifying radiation induced changes in pulmonary function in irradiated and non-irradiated lung tissue.

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: Tessa A. Sundaram
Publisher:
ISBN: 9781109985849
Category :
Languages : en
Pages : 156

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Book Description
The lung is a highly elastic organ, composed of an intricate network of blood vessels and airways that terminate in alveoli---the site of gas exchange. Normal alveolar walls are extremely thin and highly compliant, allowing the lung to deform easily as air passes through. Various pathological processes interfere with the normal respiratory deformation of the lung, either by disrupting the alveolar architecture or affecting the resistance and makeup of the airways. Characterization of normal lung motion patterns seeks to further the understanding of the changes brought about by these diseases.

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: Youbing Yin
Publisher:
ISBN:
Category : Image registration
Languages : en
Pages : 140

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Book Description
Computational fluid dynamics (CFD) has become an attractive tool in understanding the characteristic of air flow in the human lungs. Inter-subject variations make subject-specific simulations essential for understanding structure-function relationship, assessing lung function and improving drug delivery. However, currently the subject-specific CFD analysis remains challenging due, in large part to, two issues: construction of realistic deforming airway geometry and imposition of physiological boundary conditions. To address these two issues, we develop subject-specific, dynamic lung models by utilizing two or multiple volume multi-detector row computed tomography (MDCT) data sets and image registrations in this thesis. A mass-preserving nonrigid image registration algorithm is first proposed to match a pair of three-dimensional (3D) MDCT data sets with large deformations. A novel similarity criterion, the sum of squared tissue volume difference (SSTVD), is introduced to account for changes in intensity with lung inflation. We then demonstrate the ability to develop dynamic lung models by using a pair of lung volumes to account for deformations of airway geometries and subject-specific boundary conditions. The deformation of the airway geometry is derived by the registration-derived deformation field and subject-specific boundary condition is estimated from regional ventilation in a 3D and one-dimensional (1D) coupled multi-scale framework. Improved dynamic lung models are then proposed from three lung volumes by utilizing nonlinear interpolations. The improved lung models account for nonlinear geometry motions and time-varying boundary conditions during breathing. The capability of the proposed dynamic lung model is expected to move the CFD-based interrogation of lung function to the next plateau.

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.

Author: John Frederic Murray
Publisher:
ISBN:
Category : Respiratory organs
Languages : en
Pages : 1320

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Author: William J. Mullally
Publisher:
ISBN:
Category :
Languages : en
Pages : 180

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Book Description
Abstract: This thesis arises out of the study of lung physiology and the development of new techniques to help analyze the complex and prodigious amount data which modem medical imaging can provide. This document describes work in two major directions. The first is an investigation into which airways in the human airway tree contribute to the decrease in lung function in asthmatics. This works pulls together a number of well understood methods in image analysis and image registration with image data on ventilation defects and methods for building computation models of the human airway tree. We show how to incorporate ventilation defects observed in image data into subject specific models of the human airway tree. Our study indicates that ventilation defects may be caused by closures of larger airways than previously reported. Our second effort has been to advance the field of image registration to solve image alignment problems presented in the study of acute respiratory distress syndrome (ARDS). This has led us to develop two novel image registration techniques: an approach for cost-switching in non-rigid image registration and an approach to image registration using classifiers learned from example images. Our cost-switching approach has led to the first accurate semi-automatic non-rigid registration of images of healthy lungs to those of lungs after the onset of ARDS. Our example-based approach uses multiple classifiers to achieve rigid registration when image appearance has changed dramatically and non-uniformly. We show a significant increase in registration accuracy in comparison to an approach using mutual information.

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.