In-house Implementation and Validation of the Mid-Position CT approach for the Treatment Planning of Respiration-induced Moving Tumours in Radiotherapy for Lung and Upper abdomen cancer

Tese mestrado integrado, Engenharia Biomédica e Biofísica (Engenharia Clínica e Instrumentação Médica) Universidade de Lisboa, Faculdade de Ciências, 2022A Radioterapia é uma das modalidades principais para tratamentos de foro oncológico que visa destruir a ação proliferativa das células cancerígenas e reduzir o volume tumoral. A sua ação terapêutica através do uso de radiação ionizante tem, subjacente, a máxima de irradiar o tumor com uma elevada dose, ao mesmo tempo que os órgãos de risco (OARs) adjacentes, são tanto quanto possível protegidos. Quando um tumor se localiza no pulmão ou abdómen superior, como no fígado ou pâncreas, o seu movimento devido à respiração pode alcançar até 4 cm, especialmente na direção crânio-caudal, aumentando as incertezas relativas à posição do tumor. No Centro Clínico Champalimaud (CCC), o planeamento convencional dos tratamentos de radioterapia faz uso de uma tomografia computadorizada (CT) que é adquirida aquando da respiração livre do doente e que, por isso, apresenta geralmente artefactos que podem ser uma fonte de erro durante o planeamento. Nos casos em que o movimento do tumor é considerável, é ainda adquirida uma tomografia computadorizada quadrimensional (4DCT) que consiste entre 8 e 10 CTs que representam fases do ciclo respiratório. Posteriormente, a 4DCT é utilizada para delinear o volume interno do alvo (ITV) que engloba toda a extensão do movimento do tumor. Apesar da estratégia do ITV garantir uma adequada cobertura do volume-alvo, os OARs ficam expostos a doses de radiação desnecessárias e a um maior risco de toxicidade. Este efeito é ainda mais preocupante em tratamentos hipofracionados, onde doses mais elevadas são administradas num número reduzido de frações. Nos últimos anos têm sido desenvolvidas estratégias que visam tornar os tratamentos de radioterapia mais eficazes. Uma delas é a reconstrução de uma CT que representa a posição média do doente ao longo do ciclo respiratório (Mid-P CT). Esta estratégia resulta em volumes de tratamento menores do que a estratégia do ITV, possibilitando o aumento da dose e maior controlo tumoral local. O primeiro passo para a reconstrução do Mid-P CT é o registo deformável de imagens (DIR) entre uma das fases da respiração (uma CT da 4DCT), definida como a fase de referência, e as restantes fases. Deste processo resultam campos vetoriais deformáveis (DVF) que contém informação do deslocamento dos tecidos. Os DVFs são subsequentemente utilizados para transformar cada uma das fases da respiração para a posição média. O método do Mid-P foi implementado com sucesso no Instituto do Cancro Holandês (NKI) em 2008. Apesar dos bons resultados clínicos, o número de centros de radioterapia que utiliza esta técnica é muito reduzido. Tal deve-se, por um lado, à inexistência de soluções comerciais com esta funcionalidade e, por outro, ao esforço necessário alocar para implementar e validar soluções desenvolvidas internamente. O presente projeto teve como principal objetivo implementar a estratégia do Mid-P no CCC (Portugal). Para tal, foi otimizado um módulo – RunMidP – desenvolvido para o software 3D Slicer, que calcula o Mid-P CT e estima a amplitude do movimento do tumor e OARs com base nos DVFs. Considerando que a precisão do módulo e a qualidade de imagem do Mid-P CT devem atender os requisitos para o planeamento em radioterapia, foram realizados testes para validar o módulo. Sempre que possível, a sua performance foi comparada com outras aplicações desenvolvidas para a implementação da técnica do Mid-P, nomeadamente com um protótipo desenvolvido pela empresa Mirada Medical Ltd. (Reino Unido) – Mirada – e com o software desenvolvido no NKI (Holanda) – Wimp. Os testes foram divididos em três estudos diferentes, cada um com um conjunto de dados diferente. No primeiro estudo (estudo A), foram utilizadas 4DCT de 2 fantomas digitais, cuja função respiratória e cardíaca foi modelada de forma simplificada, e de 18 doentes com tumores localizados no pulmão (N = 8), no fígado (N = 6) e no pâncreas (N = 4). Neste estudo, foram comparados dois algoritmos DIR disponíveis no software 3D Slicer, o Plastimatch e o Elastix, em termos da precisão do registo e da qualidade de imagem do Mid-P CT reconstruído. Foi ainda avaliado a capacidade dos softwares RunMidP e Mirada representarem corretamente a posição média do doente e as diferenças das amplitudes do movimento do tumor estimadas pelos dois softwares. No estudo B, foram realizados testes de verificação semelhantes aos supre mencionados, em imagens sintéticas provenientes de 16 doentes, desta vez com a vantagem de se conhecer o “verdadeiro” Mid-P CT e as “verdadeiras” amplitudes do movimento do tumor. Estes foram comparados com os resultados obtidos com os softwares RunMidP e Mirada. Ainda, as unidades de Hounsfield (HU) no Mid-P CT reconstruído por RunMidP e Mirada foram comparadas com as HU na fase de referência, de modo a verificar se os Mid P CTs produziriam diferenças dosimétricas relevantes. No último estudo (estudo C), a qualidade de imagem do Mid-P CT foi avaliada quantitativamente e qualitativamente. Durante a análise qualitativa, foi pedido a dois médicos especialistas que avaliassem a viabilidade dos Mid-P CTs, reconstruídos pelos três softwares (RunMidP, Mirada e Wimp), para o planeamento dos tratamentos. O tempo da reconstrução do Mid-P CT a partir da 4DCT foi de cerca de 1h. Ambos os algoritmos, Plastimach e Elastix, demonstraram ser adequados para DIR de imagens do pulmão e abdómen superior, com diferenças estatisticamente não significativas (p > 0.05) em termos da precisão do registo. Contudo, o Mid-P CT reconstruído com Elastix apresentou uma melhoria na qualidade de imagem, sendo assim o algoritmo DIR escolhido para ser implementado no RunMidP. Em termos de métricas aplicadas a contornos definidos manualmente, tais como a distância de Hausdorf (HD) e coeficiente de Dice (DSC), o erro do registo de imagem foi menor que 1 mm, dentro do contorno do tumor, e 2 mm no pulmão. Os Mid-P CTs reconstruídos com o RunMidP e Mirada apresentaram maiores diferenças, relativamente ao “verdadeiro” Mid-P CT, na região do diafragma e zonas de maior homogeneidade como, por exemplo, no ar presente no intestino. Contudo, para a maioria dos doentes do estudo B, o Mid-P CT reconstruído com o software Mirada apresentou maior índice de similaridade estrutural (SSIM) relativamente ao “verdadeiro” Mid-P CT. Estes resultados podem estar na origem do uso de diferentes algoritmos DIR, mas deveram-se principalmente a uma falha na aplicação das transformações deformáveis pelo módulo RunMiP que foi corrigida posteriormente. Ainda, as diferenças entre as amplitudes estimadas e previstas foram menores que 1 mm para 37 tumores (78,9%), que resultam em diferenças menores que 0.3mm quando convertidas em margens de planeamento. Para além disso, as diferenças nos valores de HU dos Mid-P CTs comparativamente à fase de referência foram, em média, de 1 HU no tumor e OARs. Foram também observadas melhorias na qualidade de imagem do Mid-P CT, nomeadamente um aumento da relação sinal-ruído (SNR) e diminuição dos artefactos. Estes resultados estão de acordo com a avaliação dos médicos que, em geral, consideraram que os Mid-P CTs reconstruídos pelos três softwares são adequados para o planeamento dos tratamentos. No entanto, os Mid-P CTs reconstruídos com dados 4DCT provenientes do CCC apresentaram classificações inferiores aos reconstruídos com dados 4DCT do NKI. Em suma, as modificações do algoritmo DIR Plastimach para Elastix e a correção do método para aplicar as transformações deformáveis, permitiram uma melhoria na qualidade de imagem do Mid P CT e melhor performance do algoritmo, respetivamente. O módulo RunMidP, neste projeto otimizado e validado, apresenta um forte potencial para a reconstrução e implementação da estratégia do Mid-P na clínica, com performance comparável a outras aplicações existentes (Mirada e Wimp). Atenção especial deve ser dada aos dados 4DCT de input que parecem afetar a qualidade de imagem final do Mid-P CT. No futuro, valerá a pena otimizar os parâmetros de aquisição e reconstrução da 4DCT de modo a melhorar a qualidade de imagem e, ainda, o módulo RunMidP pode potencialmente ser otimizado no que respeita ao tempo de reconstrução do Mid-P CT e à precisão do DIR.Radiotherapy for tumours in the thorax and upper abdomen is challenging since they move notably with breathing. To cover the whole extent of tumour motion, relatively large margins are added to treatment volumes, posing a higher risk of toxicity for surrounding organs-at-risk (OARs). The Mid Position (Mid-P) method accounts for breathing motion by using deformable image registration (DIR) to transform all phases of a 4DCT scan to a time-weighted average 3DCT scan (Mid-P CT). The Mid-P strategy results in smaller treatment volumes, potentially boosting the delivery of hypofractionated treatments. To bring the Mid-P approach to the Champalimaud Clinical Centre (CCC), an in-house Mid position software module – RunMidP – was optimized. The module reconstructs the Mid-P CT and estimates breathing motion amplitudes of tumours and relevant OARs. In addition, this project presents a set of experiments to evaluate the performance of the Mid-P method and its feasibility for clinical implementation. The experiments were conducted throughout three different studies using 4DCT data from 18 phantoms and 23 patients. In Study A, the accuracy and image quality of two DIR algorithms (Plastimatch and Elastix) were assessed using quantitative metrics applied on either warped images or manually delineated contours. The reproduction of the patient’s mean position by the Mid-P CT and the estimation of motion amplitudes were compared to a soon-to-be Mid-P commercial software developed by Mirada Medical Ltd. In Study B,similar experiments were performed, this time using a more rigorous reference – “true” Mid-P CT scans and “true” motion estimations. In Study C, the image quality of Mid P CT scans was assessed quantitatively and qualitatively. Both Plastimatch and Elastix registration showed comparable registration accuracy, although Elastix showed superior image quality of reconstructed Mid-P CTs. Based on contour metrics, the registration error was less than 2 mm. In-house Mid-P CTs showed a slightly lower match to ground truth Mid-P CTs than the ones reconstructed by the Mirada prototype due to differences in DIR methods and small shifts to the original image geometry. Higher image differences were found in the diaphragm lung interface, where the patient's anatomy moves faster due to breathing, and in homogeneous regions such as the air regions in the bowel. On the other hand, differences (estimated-predicted) in motion amplitudes smaller than 1 mm were observed in 37 moving tumours (78.7%), showing a good performance of the Mid-P algorithm. Regarding the image quality, improvements in the signal-to-noise ratio and removal of image artefacts in Mid-P CTs are great advantages for using them as the planning CT. Clinicians also gave a good assessment of the suitability of Mid-P CT scans for treatment planning. No significant differences were found in the performance of the RunMidP compared to other Mid-Position packages, although worse scores were given to the CCC dataset than the dataset from another hospital. The in-house Mid-position algorithm shows promising results regarding the use of the software module in radiotherapy for lung and upper abdomen cancer. Further exploration must be given to improve the registration accuracy, image quality of the input data, and speed up the reconstruction of the Mid-P CT scan

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 326)

This bibliography lists 108 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during July, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

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

AUGMENTED REALITY AND INTRAOPERATIVE C-ARM CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED ROBOTIC SURGERY

Minimally-invasive robotic-assisted surgery is a rapidly-growing alternative to traditionally open and laparoscopic procedures; nevertheless, challenges remain. Standard of care derives surgical strategies from preoperative volumetric data (i.e., computed tomography (CT) and magnetic resonance (MR) images) that benefit from the ability of multiple modalities to delineate different anatomical boundaries. However, preoperative images may not reflect a possibly highly deformed perioperative setup or intraoperative deformation. Additionally, in current clinical practice, the correspondence of preoperative plans to the surgical scene is conducted as a mental exercise; thus, the accuracy of this practice is highly dependent on the surgeon’s experience and therefore subject to inconsistencies. In order to address these fundamental limitations in minimally-invasive robotic surgery, this dissertation combines a high-end robotic C-arm imaging system and a modern robotic surgical platform as an integrated intraoperative image-guided system. We performed deformable registration of preoperative plans to a perioperative cone-beam computed tomography (CBCT), acquired after the patient is positioned for intervention. From the registered surgical plans, we overlaid critical information onto the primary intraoperative visual source, the robotic endoscope, by using augmented reality. Guidance afforded by this system not only uses augmented reality to fuse virtual medical information, but also provides tool localization and other dynamic intraoperative updated behavior in order to present enhanced depth feedback and information to the surgeon. These techniques in guided robotic surgery required a streamlined approach to creating intuitive and effective human-machine interferences, especially in visualization. Our software design principles create an inherently information-driven modular architecture incorporating robotics and intraoperative imaging through augmented reality. The system's performance is evaluated using phantoms and preclinical in-vivo experiments for multiple applications, including transoral robotic surgery, robot-assisted thoracic interventions, and cocheostomy for cochlear implantation. The resulting functionality, proposed architecture, and implemented methodologies can be further generalized to other C-arm-based image guidance for additional extensions in robotic surgery

Novel Techniques for Tissue Imaging and Characterization Using Biomedical Ultrasound

The use of ultrasound technology in the biomedical field has been widely increased in recent decades. Ultrasound modalities are considered more safe and cost effective than others that use ionizing radiation. Moreover, the use of high-frequency ultrasound provides means of high-resolution and precise tissue assessment. Consequently, ultrasound elastic waves have been widely used to develop non-invasive techniques for tissue assessment. In this work, ultrasound waves have been used to develop non-invasive techniques for tissue imaging and characterization in three different applications.;Currently, there is a lack of imaging modalities to accurately predict minute structures and defects in the jawbone. In particular, the inability of 2D radiographic images to detect bony periodontal defects resulted from infection of the periodontium. They also may carry known risks of cancer generation or may be limited in accurate diagnosis scope. Ultrasonic guided waves are sensitive to changes in microstructural properties, while high-frequency ultrasound has been used to reconstruct high-resolution images for tissue. The use of these ultrasound techniques may provide means for early diagnosis of marrow ischemic disorders via detecting focal osteoporotic marrow defect, chronic nonsuppurative osteomyelitis, and cavitations in the mandible (jawbone). The first part of this work investigates the feasibility of using guided waves and high frequency ultrasound for non-invasive human jawbone assessment. The experimental design and the signal/image processing procedures for each technique are developed, and multiple in vitro studies are carried out using dentate and non-dentate mandibles. Results from both the ultrasonic guided waves analysis and the high frequency 3D echodentographic imaging suggest that these techniques show great potential in providing non-invasive methods to characterize the jawbone and detect periodontal diseases at earlier stages.;The second part of this work describes indirect technique for characterization via reconstructing high-resolution microscopic images. The availability of well-defined genetic strains and the ability to create transgenic and knockout mice makes mouse models extremely significant tools in different kinds of research. For example, noninvasive measurement of cardiovascular function in mouse hearts has become a valuable need when studying the development or treatment of various diseases. This work describes the development and testing of a single-element ultrasound imaging system that can reconstruct high-resolution brightness mode (B-mode) images for mouse hearts and blood vessels that can be used for quantitative measurements in vitro. Signal processing algorithms are applied on the received ultrasound signals including filtering, focusing, and envelope detection prior to image reconstruction. Additionally, image enhancement techniques and speckle reduction are adopted to improve the image resolution and quality. The system performance is evaluated using both phantom and in vitro studies using isolated mouse hearts and blood vessels from APOE-KO and its wild type control. This imaging system shall provide a basis for early and accurate detection of different kinds of diseases such as atherosclerosis in mouse model.;The last part of this work is initialized by the increasing need for a non-invasive method to assess vascular wall mechanics. Endothelial dysfunction is considered a key factor in the development of atherosclerosis. Flow-mediated vasodilatation (FMD) measurement in brachial and other conduit arteries has become a common method to assess the endothelial function in vivo. In spite of the direct relationship that could be between the arterial wall multi-component strains and the FMD response, direct measurement of wall strain tensor due to FMD has not yet been reported in the literature. In this work, a noninvasive direct ultrasound-based strain tensor measuring (STM) technique is presented to assess changes in the mechanical parameters of the vascular wall during post-occlusion reactive hyperemia and/or FMD, including local velocities and displacements, diameter change, local strain tensor and strain rates. The STM technique utilizes sequences of B-mode ultrasound images as its input with no extra hardware requirement. The accuracy of the STM algorithm is assessed using phantom, and in vivo studies using human subjects during pre- and post-occlusion. Good correlations are found between the post-occlusion responses of diameter change and local wall strains. Results indicate the validity and versatility of the STM algorithm, and describe how parameters other than the diameter change are sensitive to reactive hyperemia following occlusion. This work suggests that parameters such as local strains and strain rates within the arterial wall are promising metrics for the assessment of endothelial function, which can then be used for accurate assessment of atherosclerosis

Wearable devices for microwave head diagnostic systems

Although current head imaging technologies such as magnetic resonance imaging (MRI) and computed tomography (CT) are capable of providing accurate diagnosis of brain injuries such as stroke and brain tumour, they have several limitations including high cost, long scanning time, bulky and mostly stationary. On the other hand, radar-based microwave imaging technology can offer a low cost, non-invasive and non-ionisation method to complement these existing imaging techniques. Moreover, a compact and wearable device for microwave head imaging is required to facilitate frequent or real-time monitoring of a patient by providing more comfort to the patient. Therefore, a wearable head imaging device would be a significant advantage compared to the existing wideband microwave head sensing devices which typically utilise rigid antenna structure. Furthermore, the wearable device can be integrated into different microwave imaging setups such as real-time wearable head imaging systems, portable systems and conventional stationary imaging tools for use in hospitals and clinics. This thesis presents the design and development of wearable devices utilising flexible antenna arrays and compact radio frequency (RF) switching circuits for wideband microwave head imaging applications. The design and characterisation of sensing antennas using flexible materials for the wearable head imaging device are presented in the first stage of this study. There are two main variations of monopole antennas that have been developed in this research, namely trapezoidal and elliptical configurations. The antennas have been fabricated using different flexible substrate materials such as flexible FR-4, polyethylene terephthalate (PET) and textile. Wideband performances of the antennas have been achieved by optimising their co-planar waveguide feeding line structures. Importantly, the efficiencies of the fabricated antennas have been tested using a realistic human head phantom by evaluating their impedance matching performances when operating in close proximity to the head phantom. The second stage of the study presents the development of wearable antenna arrays using the proposed flexible antennas. The first prototype has been built using an array of 12 flexible antennas and a conformal absorbing material backed with a conductive sheet to suppress the back lobe radiation of the monopole antennas. Additionally, the absorber also acts as a mounting base to hold the antennas where the wearable device can be comfortably worn like a hat during the measurement and monitoring processes. The effect of mutual coupling between adjacent antennas in the array has been investigated and optimised. However, the use of the absorbing material makes the device slightly rigid where it can only be fitted on a specific head size. Thus, a second prototype has been developed by using a head band to realise a stretchable configuration that can be mounted on different sizes of human heads. Furthermore, due to the stretchable characteristic of the prototype, the antennas can be firmly held in their positions when measurements are made. In addition, fully textile based sensing antennas are employed in this prototype making it perfectly suitable for monitoring purposes. Low cost and compact switching circuits to provide switching mechanism for the wearable antenna array are presented in the third stage of this study. The switching circuit is integrated with the antenna array to form a novel wearable microwave head imaging device eliminating the use of external bulky switching network. The switching circuit has been built using off-the-shelf components where it can be controlled wirelessly over Bluetooth connection. Then, a new integrated switching circuit prototype has been fabricated using 6-layer printed circuit board (PCB) technology. For the purpose of impedance matching for the radio-frequency (RF) routing lines on the circuit, a wideband Microstrip-to-Microstrip transition is utilised. The final stage of this study investigates the efficacy and sensitivity of the proposed wearable devices by performing experiments on developed realistic human head phantoms. Initially, a human head phantom has been fabricated using food-based ingredients such as tap water, sugar, salt, and agar. Subsequently, lamb’s brains have been used to improve the head phantom employed in the experiments to better mimic the heterogeneous human brain. In terms of imaging process, an interpolation technique developed using experimental data has been proposed to assist the localisation of a haemorrhage stroke location using the confocal delay-and-sum algorithm. This new technique is able to provide sensible accuracy of the location of the blood clot inside the brain. The wearable antenna arrays using flexible antennas and their integrations with compact and low cost switching circuits reported in this thesis make valuable contribution to microwave head imaging field. It is expected that a low-cost, compact and wearable radar-based microwave head imaging can be fully realised in the future for wide range of applications including static scanning setup in hospitals, portable equipment in ambulances and as a standalone wearable head monitoring system for remote and real-time monitoring purposes

Quantitative Magnetic Resonance Imaging Techniques for the Measurement of Organ Fat and Body Composition - Validation and Initial Clinical Utility

Ectopic fat is defined by excess deposition of triglycerides in non-adipose tissues that normally contain only small amounts of fat. Measuring the distribution of ectopic fat is important for understanding the pathogenesis of diseases such as obesity and type 2 diabetes mellitus (T2DM) and understanding variation in treatment response amongst patients. Body composition (the proportion of fat and lean mass in the body) is thought to influence both the development of T2DM and outcomes for treatments such as weight-loss surgery. It can also affect clinical outcomes in chronic diseases and malignancy. Quantitative magnetic resonance imaging (qMRI) enables objective measurements of tissue characteristics to be made directly from acquired data. In this thesis, a qMRI protocol based on chemical shift-encoded (CSE)-MRI, specifically the derived proton density fat fraction (PDFF) measurements, was validated against phantoms, and in volunteers and patients with obesity. A new, semi-automated tool for measurement of body composition from CSE-MRI images was developed and validated. CSE-MRI was used to quantify ectopic organ fat depots and body composition in diseases including obesity, T2DM and cancer. Specifically, differences in organ fat between patients with and without remission of T2DM after bariatric surgery was explored. Body composition was investigated in T2DM remission and it was also compared between patients with colorectal and lung cancer undergoing whole body MRI staging. Data from the pilot phase of a study investigating a new duodenal surfacing procedural treatment for T2DM (Revita-2) is presented, demonstrating the utility of hepatic fat content measured using PDFF as an endpoint in an international, multi-centre clinical trial. Finally, I describe the development of a novel technique for quantification of bone mineral density (BMD) using CSE-MRI techniques. The methodology and tools described in this thesis could be used to measure ectopic fat and body composition in future studies and have the potential for integration into clinical care pathways

Evaluation of deformable image registration for improved 4D CT-derived ventilation for image guided radiotherapy

Recent treatment planning studies have demonstrated the use of physiologic images in radiation therapy treatment planning to identify regions for functional avoidance. This image-guided radiotherapy (IGRT) strategy may reduce the injury and/or functional loss following thoracic radiotherapy. 4D computed tomography (CT), developed for radiotherapy treatment planning, is a relatively new imaging technique that allows the acquisition of a time-varying sequence of 3D CT images of the patient\u27s lungs through the respiratory cycle. Guerrero et al. developed a method to calculate ventilation imaging from 4D CT, which is potentially better suited and more broadly available for IGRT than the current standard imaging methods. The key to extracting function information from 4D CT is the construction of a volumetric deformation field that accurately tracks the motion of the patient\u27s lungs during the respiratory cycle. The spatial accuracy of the displacement field directly impacts the ventilation images; higher spatial registration accuracy will result in less ventilation image artifacts and physiologic inaccuracies. Presently, a consistent methodology for spatial accuracy evaluation of the DIR transformation is lacking. Evaluation of the 4D CT-derived ventilation images will be performed to assess correlation with global measurements of lung ventilation, as well as regional correlation of the distribution of ventilation with the current clinical standard SPECT. This requires a novel framework for both the detailed assessment of an image registration algorithm\u27s performance characteristics as well as quality assurance for spatial accuracy assessment in routine application. Finally, we hypothesize that hypo-ventilated regions, identified on 4D CT ventilation images, will correlate with hypo-perfused regions in lung cancer patients who have obstructive lesions. A prospective imaging trial of patients with locally advanced non-small-cell lung cancer will allow this hypothesis to be tested. These advances are intended to contribute to the validation and clinical implementation of CT-based ventilation imaging in prospective clinical trials, in which the impact of this imaging method on patient outcomes may be tested

Deep Learning for Medical Imaging in a Biased Environment

Deep learning (DL) based applications have successfully solved numerous problems in machine perception. In radiology, DL-based image analysis systems are rapidly evolving and show progress in guiding treatment decisions, diagnosing, localizing disease on medical images, and improving radiologists\u27 workflow. However, many DL-based radiological systems fail to generalize when deployed in new hospital settings, and the causes of these failures are not always clear. Although significant effort continues to be invested in applying DL algorithms to radiological data, many open questions and issues that arise from incomplete datasets remain. To bridge the gap, we first review the current state of artificial intelligence applied to radiology data, followed by juxtaposing the use of classical computer vision features (i.e., hand-crafted features) with the recent advances caused by deep learning. However, using DL is not an excuse for a lack of rigorous study design, which we demonstrate by proposing sanity tests that determine when a DL system is right for the wrong reasons. Having established the appropriate way to assess DL systems, we then turn to improve their efficacy and generalizability by leveraging prior information about human physiology and data derived from dual energy computed tomography scans. In this dissertation, we address the gaps in the radiology literature by introducing new tools, testing strategies, and methods to mitigate the influence of dataset biases