The purpose of this project was to explore the performance of methods for estimating stopping power ratio (SPR) from Hounsfield units (HU) using dual energy CT scans, rather than the standard single energy CT scans, with the aim of finding a method which could outperform the current single energy stoichiometric method. Such a method could reduce the margin currently added to the target volume during treatment which is defined as 3.5 % of the range to the target volume + 1 mm . Three such methods, by Taasti, Zhu, and, Lalonde and Bouchard, were chosen and implemented in MATLAB. A phantom containing 10 tissue-like inserts was scanned and used as a basis for the SPR estimation. To investigate the variation of the SPR from day-to-day the phantom was scanned once a day for 12 days. The resulting SPR of all methods, including the stoichiometric method, were compared with theoretical SPR values which were calculated using known elemental weight fractions of the inserts and mean excitation energies from the National Institute of Standards and Technology (NIST). It was found that the best performing method was the Taasti method which had, at best, an average percentage difference from the theoretical values of only 2.5 %. The Zhu method had, at best, 4.8 % and Lalonde-Bouchard 15.6% including bone tissue or 6.3 % excluding bone. The best average percentage difference of the stoichiometric method was 3.1 %. As the Taasti method was the best performing method and shows much promise, future work should focus on further improving its performance by testing more scanning protocols and kernels to find the ones yielding the best performance. This should then be supplemented with testing different pairs of energies for the dual energy scans. The fact that the Zhu and Lalonde-Bouchard method performed poorly could indicate problems with the implementation of those methods in this project. Investigating and solving those problems is also an important goal for future projects. Lastly the Lalonde-Bouchard method should be tested with more than two energy spectra.

La radiothérapie est une modalité importante dans le traitement de néoplasie telle que le cancer pulmonaire. Cependant, les poumons sont susceptibles à des toxicités radio-induites comme la pneumonie radique et la fibrose pulmonaire radique. Plusieurs patients souffrant du cancer pulmonaire ont aussi des comorbidités tel la maladie obstructive pulmonaire chronique, qui affecte déjà leur fonction respiratoire. Actuellement, la planification de la radiothérapie tient compte de l’anatomie mais non de la fonction différentielle des poumons. La planification de la radiothérapie guidée par la fonction aurait pour but d’inclure cette fonction différentielle dans le processus de planification, évitant l’irradiation du parenchyme sain et améliorant le profil de toxicités du traitement. Différentes techniques d’imagerie fonctionnelle sont présentement à l’étude. La tomodensitométrie à double-énergie (DECT, dual-energy computed tomography) est une technique qui utilises des rayons-X d’énergie différente, permettant une meilleure différentiation du matériel. L’article présenté dans ce mémoire étudie une technique préalablement décrite de décomposition de matériaux qui utilise des cartographies d’iodine dérivées des images de DECT avec contraste. Nous avons réalisé une étude longitudinale de la perfusion pulmonaire, un indicateur de la fonction respiratoire. Des patients avec un cancer pulmonaire traités avec radiothérapie stéréotaxique ou conventionnelle ont été recrutés de façon prospective et ont eu un DECT avec contraste avant le début des traitements et 6 et 12 mois post-traitement. Des réponses fonctionnelles normalisées ont été calculées à 6 et 12 mois pour 3 catégories de dose d’irradiation : moins de 5 Gray, 5-20 Gray et plus de 20 Gray. Aux analyses statistiques, nous avons observé une corrélation de cette réponse avec la dose de radiation reçue. Les régions qui ont reçu le plus de dose ont démontré une plus grande baisse de fonction. La réponse fonctionnelle normalisée est également corrélée avec le temps écoulé post-radiothérapie. Nous avons conclu que la cartographie d’iodine dérivée du DECT permet d’évaluer l’effet de la dose de radiation sur les changements fonctionnels du parenchyme pulmonaire post-radiothérapie. Ainsi, le DECT permet d'évaluer les changements de fonction pulmonaire post-radiothérapie et pourrait être utilisé pour évaluer les dommages post-radiques. / Radiotherapy is an important modality in the treatment of malignancies such as lung cancer. However, the lungs are susceptible to radiation-induced lung injury such as radiation pneumonitis and radiation fibrosis. In addition, many lung cancer patients also suffer from comorbidities such as chronic obstructive lung disease, which affect their baseline respiratory function. Current standard of care for radiotherapy planning considers the anatomy but not the differential function of the lungs. Function-guided radiotherapy planning would seek to include the differential function of the lungs, avoiding the irradiation of healthy parenchyma, therefore improving the toxicity profile of the treatment. Currently, different functional imaging techniques are being studied for this purpose. Dual-energy computed tomography (DECT) is a technique which uses two X-rays of different energy, allowing improved material differentiation. The article presented in this thesis studies the use of a previously described 2-material decomposition technique using iodine maps derived from contrast-enhanced DECT images. This allows for the longitudinal evaluation of lung perfusion, a surrogate for respiratory function. Lung cancer patients who were treated with stereotactic radiotherapy or conventional radiotherapy were prospectively enrolled and underwent a contrast-enhanced DECT before the treatment and at 6 and 12 months post-treatment. Normalized functional responses were calculated at 6 and 12 months for three dose ranges: less than 5 Gray, 5-20 Gray and more than 20 Gray. This normalized functional response was found to correlate with the dose received. The regions receiving the most radiation dose demonstrate the greatest decrease in function. It was also found be correlated with the time elapsed after radiotherapy. We concluded that DECT-derived iodine maps can be used to evaluate the dose-response effect of radiation on lungs. DECT can therefore be an interesting technique to study post-treatment pulmonary parenchymal changes and can be used to assess post-radiation damage.

A Tomografia Computadorizada de Energia Dupla (DECT em inglês) é um dos campos das imagens tomográficas que mais evoluiu nos últimos anos. O DECT usa dois espectros para irradiar pacientes e é capaz de diferenciar tecidos com base na sua composição elementar. Apesar de serem semelhantes aos dispositivos padrão de tomografia, para essa modalidade é necessário o desenvolvimento de ferramentas específicas que permitam o estudo de suas propriedades de imagem. O objetivo deste trabalho era construir um sistema simulado de Tomografia Computadorizada (TC) com a capacidade de produzir imagens semelhantes às obtidas em dispositivos DECT reais. O TC simulado também permitiria explorar as propriedades das imagens de materiais de teste antes de sua construção física. Este trabalho presenta a simulação do processo de aquisição de imagens de um dispositivo DECT que funciona a partir da troca rápida de kV, o GE Discovery CT 750 HD. A geometria simulada foi baseada num dispositivo atualmente disponível no InRad (Instituto de Radiologia da Faculdade de Medicina da Universidade de São Paulo). As simulações foram realizadas usando o código Monte Carlo PENELOPE/penEasy para simular o transporte de radiação através dos materiais e detectores. Também é apresentada uma comparação entre as imagens obtidas no dispositivo real e nas simulações. Para isso, foi preparado um objeto simulador cilíndrico contendo concentrações de materiais equivalentes a iodo e cálcio. As imagens de tal objeto simulador foram adquiridas no equipamento GE Discovery CT 750 HD. Um objeto simulador equivalente foi modelado e as suas imagens foram simuladas com o código PENELOPE/penEasy. As imagens foram adquiridas e reconstruídas de acordo com as possibilidades do equipamento clínico de tomografia. Imagens de concentração de material e imagens monoenergéticas foram obtidas a partir do dispositivo CT clínico e das simulações. O algoritmo BMD (Basis Material Decomposition em Inglês) baseado nas projeções foi implementado usando os coeficientes de atenuação mássicos da água e do iodo. Consequentemente, imagens de concentração dos materiais água e iodo foram obtidas. A concentração medida nos cilindros de iodo foi equivalente às esperadas tanto no dispositivo real quanto nas imagens simuladas. Foram observados artefatos de endurecimento de feixe nas imagens de concentração de material. Imagens monoenergéticas foram obtidas para diferentes energias. Tais imagens foram obtidas a partir da superposição das imagens de concentração de água e iodo, que foram ponderadas pelos seus respectivos coeficientes de atenuação mássicos. Verificou-se que para as imagens monoenergéticas simuladas e reais em altas energias a imagem de concentração da água é a componente dominante, produzindo imagens que apresentaram as cavidades de iodo como menos atenuantes do que a água. Por outro lado, para energias baixas, a componente dominante nas imagens monoenergéticas foi a imagem de concentração do iodo. O CNR foi analisado nas imagens monoenergéticas como função da energia. As curvas do CNR dos dispositivos simulado e real exibiram semelhanças em sua forma, mas com escala diferente devido à diferença no ruído. Foi possível concluir que o modelo DECT simulado apresenta resultados qualitativos semelhantes aos obtidos no dispositivo real. O sistema de TC simulado permite explorar as características das imagens com diferentes materiais e composições. Ele também pode ser usado como uma ferramenta didática para melhorar a compreensão da diferenciação de materiais em tomografia espectral e DECT. / Dual Energy (DE) Computed Tomography (CT) is one of the fields of tomographic images that has evolved rapidly during the last years. DECT uses two X-ray spectra to irradiate patients It is capable to differentiate materials based on its elementary composition. Despite being similar to standard CT devices, DECT devices require the development of specific tools that allow the study of their image properties. The objective of this work was to build a modelled CT system capable of producing images similar to those obtained in real DECT devices. The modelled CT would also allow exploring the image properties of test materials before their physical construction. This work presents the simulation of the acquisition process of a DECT device that works with rapid kV switching, the GE Discovery CT 750 HD. The simulated geometry was based on a device currently available at the InRad (Institute of Radiology of the Faculty of Medicine of the University of São Paulo). The simulations were carried out using the PENELOPE/penEasy Monte Carlo code, which simulates radiation transport through the materials and detectors. A comparison between the images obtained in the real device and from simulations is also presented. To do so, a real phantom was prepared to be imaged and an equivalent system was simulated. The phantom contained inserts with concentrations of iodine and calcium. The images were acquired and reconstructed according to the possibilities of the real CT device. Standard, material concentration and virtual monoenergetic images were acquired[L1] from both, the real CT device and simulations. The Projection-Based BMD method was implemented using the mass attenuation coefficients of water and iodine. Then, material concentration images of water and iodine were obtained. The iodine concentrations estimated from the images agreed with the expected values in both real device and simulated images. Beam hardening artefacts were observed in the simulated material concentration images. Monoenergetic images were obtained for different energies. Such images were obtained as a superposition of the concentration images of water and iodine, weighed by their respective mass attenuation coefficient. It was verified that in the simulated and real device images, at high energies, the water concentration image predominated in the monoenergetic images, producing images that presented the iodine cavities as less attenuating than water. In contrast, at low energies, the predominant component of the monoenergetic images was the iodine concentration image. Contrast Noise Ratio (CNR) was analysed in the monochromatic images as a function of energy. Simulated and real device CNR curves exhibited similarities in their shape but with a different scale due to their difference in noise. It was possible to conclude that the simulated DECT model presented qualitative results similar to the obtained in the real device. The modelled CT system permits exploring the image features with different materials and compositions. It could also be used as a didactic tool to improve the understanding of material differentiation in spectral or DECT.

No description available.

A Tomografia Computadorizada de Energia Dupla (DECT em inglês) é um dos campos das imagens tomográficas que mais evoluiu nos últimos anos. O DECT usa dois espectros para irradiar pacientes e é capaz de diferenciar tecidos com base na sua composição elementar. Apesar de serem semelhantes aos dispositivos padrão de tomografia, para essa modalidade é necessário o desenvolvimento de ferramentas específicas que permitam o estudo de suas propriedades de imagem. O objetivo deste trabalho era construir um sistema simulado de Tomografia Computadorizada (TC) com a capacidade de produzir imagens semelhantes às obtidas em dispositivos DECT reais. O TC simulado também permitiria explorar as propriedades das imagens de materiais de teste antes de sua construção física. Este trabalho presenta a simulação do processo de aquisição de imagens de um dispositivo DECT que funciona a partir da troca rápida de kV, o GE Discovery CT 750 HD. A geometria simulada foi baseada num dispositivo atualmente disponível no InRad (Instituto de Radiologia da Faculdade de Medicina da Universidade de São Paulo). As simulações foram realizadas usando o código Monte Carlo PENELOPE/penEasy para simular o transporte de radiação através dos materiais e detectores. Também é apresentada uma comparação entre as imagens obtidas no dispositivo real e nas simulações. Para isso, foi preparado um objeto simulador cilíndrico contendo concentrações de materiais equivalentes a iodo e cálcio. As imagens de tal objeto simulador foram adquiridas no equipamento GE Discovery CT 750 HD. Um objeto simulador equivalente foi modelado e as suas imagens foram simuladas com o código PENELOPE/penEasy. As imagens foram adquiridas e reconstruídas de acordo com as possibilidades do equipamento clínico de tomografia. Imagens de concentração de material e imagens monoenergéticas foram obtidas a partir do dispositivo CT clínico e das simulações. O algoritmo BMD (Basis Material Decomposition em Inglês) baseado nas projeções foi implementado usando os coeficientes de atenuação mássicos da água e do iodo. Consequentemente, imagens de concentração dos materiais água e iodo foram obtidas. A concentração medida nos cilindros de iodo foi equivalente às esperadas tanto no dispositivo real quanto nas imagens simuladas. Foram observados artefatos de endurecimento de feixe nas imagens de concentração de material. Imagens monoenergéticas foram obtidas para diferentes energias. Tais imagens foram obtidas a partir da superposição das imagens de concentração de água e iodo, que foram ponderadas pelos seus respectivos coeficientes de atenuação mássicos. Verificou-se que para as imagens monoenergéticas simuladas e reais em altas energias a imagem de concentração da água é a componente dominante, produzindo imagens que apresentaram as cavidades de iodo como menos atenuantes do que a água. Por outro lado, para energias baixas, a componente dominante nas imagens monoenergéticas foi a imagem de concentração do iodo. O CNR foi analisado nas imagens monoenergéticas como função da energia. As curvas do CNR dos dispositivos simulado e real exibiram semelhanças em sua forma, mas com escala diferente devido à diferença no ruído. Foi possível concluir que o modelo DECT simulado apresenta resultados qualitativos semelhantes aos obtidos no dispositivo real. O sistema de TC simulado permite explorar as características das imagens com diferentes materiais e composições. Ele também pode ser usado como uma ferramenta didática para melhorar a compreensão da diferenciação de materiais em tomografia espectral e DECT. / Dual Energy (DE) Computed Tomography (CT) is one of the fields of tomographic images that has evolved rapidly during the last years. DECT uses two X-ray spectra to irradiate patients It is capable to differentiate materials based on its elementary composition. Despite being similar to standard CT devices, DECT devices require the development of specific tools that allow the study of their image properties. The objective of this work was to build a modelled CT system capable of producing images similar to those obtained in real DECT devices. The modelled CT would also allow exploring the image properties of test materials before their physical construction. This work presents the simulation of the acquisition process of a DECT device that works with rapid kV switching, the GE Discovery CT 750 HD. The simulated geometry was based on a device currently available at the InRad (Institute of Radiology of the Faculty of Medicine of the University of São Paulo). The simulations were carried out using the PENELOPE/penEasy Monte Carlo code, which simulates radiation transport through the materials and detectors. A comparison between the images obtained in the real device and from simulations is also presented. To do so, a real phantom was prepared to be imaged and an equivalent system was simulated. The phantom contained inserts with concentrations of iodine and calcium. The images were acquired and reconstructed according to the possibilities of the real CT device. Standard, material concentration and virtual monoenergetic images were acquired[L1] from both, the real CT device and simulations. The Projection-Based BMD method was implemented using the mass attenuation coefficients of water and iodine. Then, material concentration images of water and iodine were obtained. The iodine concentrations estimated from the images agreed with the expected values in both real device and simulated images. Beam hardening artefacts were observed in the simulated material concentration images. Monoenergetic images were obtained for different energies. Such images were obtained as a superposition of the concentration images of water and iodine, weighed by their respective mass attenuation coefficient. It was verified that in the simulated and real device images, at high energies, the water concentration image predominated in the monoenergetic images, producing images that presented the iodine cavities as less attenuating than water. In contrast, at low energies, the predominant component of the monoenergetic images was the iodine concentration image. Contrast Noise Ratio (CNR) was analysed in the monochromatic images as a function of energy. Simulated and real device CNR curves exhibited similarities in their shape but with a different scale due to their difference in noise. It was possible to conclude that the simulated DECT model presented qualitative results similar to the obtained in the real device. The modelled CT system permits exploring the image features with different materials and compositions. It could also be used as a didactic tool to improve the understanding of material differentiation in spectral or DECT.

Derzeitige Reichweiteunsicherheiten in der Protonentherapie verhindern das vollständige Ausschöpfen ihrer physikalischen Vorteile. Ein wesentlicher Anteil ist dabei auf die Vorhersage der Reichweite mittels Röntgen-Computertomographie (CT) zurückzuführen. Um die CT-bezogene Unsicherheit zu verringern, wird die Zwei-Spektren-Computertomographie (DECT) als vielversprechend angesehen. Innerhalb dieser Arbeit wurde die Anwendbarkeit von DECT in der Protonentherapie untersucht. Zunächst wurde ein CT-Scanprotokoll für die Strahlentherapie hinsichtlich Bildqualität und Konstanz der CT-Zahlen für verschiedene Körperregionen und -größen optimiert. Anschließend wurde die patientenindividuelle DECT- basierte Reichweitevorhersage kalibriert und ihre Genauigkeit in zwei Experimenten mit bekannter Referenz unter Verwendung eines anthropomorphen Phantoms und von homogenen biologischen Geweben verifiziert. Die klinische Relevanz von DECT wurde in einer retrospektiven Analyse von Krebspatienten mit Tumoren im Kopf, Becken oder Thorax nachgewiesen. Die systematischen Reichweiteunterschiede zwischen DECT und dem klinischen Standardverfahren konnten durch die Optimierung der Standardmethode basierend auf zusätzlichen mit DECT erworbenen Patienteninformationen reduziert werden. Somit wurde DECT erstmalig klinisch genutzt, um die Reichweiteberechnung zu verbessern. Die patientenindividuelle DECT-basierte Reichweitevorhersage kann zusätzlich Gewebevariabilitäten innerhalb eines und zwischen Patienten berücksichtigen, wie für Kopftumorpatienten gezeigt wurde. Dies legt den Grundstein für eine genauere Reichweiteberechnung und eröffnet neue Möglichkeiten für die Reduktion klinischer Sicherheitssäume, in denen die CT-bezogenen Unsicherheiten berücksichtigt sind.:1 Introduction 2 Physical Principles of Computed Tomography 2.1 Image Acquisition 2.2 Image Reconstruction 2.3 Dual-Energy Computed Tomography 3 Physical Principles of Proton Therapy 3.1 Treatment Techniques 3.2 Uncertainties in Proton Therapy 4 Principles of Stopping-Power Prediction from Computed Tomography 4.1 Single-Energy Computed Tomography 4.2 Dual-Energy Computed Tomography 5 Experimental Calibration of Stopping-Power Prediction 5.1 Scan Protocol Optimisation in Computed Tomography 5.2 Characterisation of Pseudo-Monoenergetic CT Calculation 5.3 Determination of Proton Stopping Power 5.4 Calibration of Stopping-Power Prediction Methods 6 Experimental Verification of Stopping-Power Prediction 6.1 Anthropomorphic Head Phantom 6.2 Homogeneous Biological Tissue Samples 7 Clinical Translation and Validation of Dual-Energy Computed Tomography 7.1 Feasibility of Dual-Spiral Dual-Energy CT 7.2 Range Prediction in Cerebral and Pelvic Tumour Patients 7.3 Tissue Variability in Brain-Tumour Patients 7.4 Feasibility of 4D Dual-Spiral Dual-Energy CT 7.5 DECT-Based Refinement of the Hounsfield Look-Up Table 8 Summary 9 Zusammenfassung / Range uncertainty in proton therapy currently hampers the full exploitation of its physical advantages. A substantial amount of this uncertainty arises from proton range prediction based on X-ray computed tomography (CT). Dual-energy CT (DECT) has often been suggested as a promising imaging modality to reduce this CT-related range uncertainty. Within this thesis, the translation of DECT into application in proton therapy was evaluated. First, a CT scan protocol was optimised for radiotherapy considering the image quality and CT number stability for various body regions and sizes. The patient-specific DECT-based range prediction was then calibrated and its accuracy validated in two ground-truth experiments using an anthropomorphic phantom and homogeneous biological tissues. Subsequently, the clinical relevance of DECT was demonstrated in a retrospective cohort analysis of cerebral, pelvic and thoracic tumour patients. The systematic range deviations between the DECT and state-of-the-art approach were then reduced by adapting the standard method utilizing additional patient information obtained from DECT. Hence, DECT was clinically applied for the first time to refine proton range calculation. As a further step, the use of patient-specific DECT-based range prediction also considers intra- and inter-patient tissue variabilities as quantified in brain-tumour patients. A future implementation will be an important cornerstone to improve proton range calculation and might open up the possibility to reduce clinical safety margins accounting for the CT-related range uncertainty.:1 Introduction 2 Physical Principles of Computed Tomography 2.1 Image Acquisition 2.2 Image Reconstruction 2.3 Dual-Energy Computed Tomography 3 Physical Principles of Proton Therapy 3.1 Treatment Techniques 3.2 Uncertainties in Proton Therapy 4 Principles of Stopping-Power Prediction from Computed Tomography 4.1 Single-Energy Computed Tomography 4.2 Dual-Energy Computed Tomography 5 Experimental Calibration of Stopping-Power Prediction 5.1 Scan Protocol Optimisation in Computed Tomography 5.2 Characterisation of Pseudo-Monoenergetic CT Calculation 5.3 Determination of Proton Stopping Power 5.4 Calibration of Stopping-Power Prediction Methods 6 Experimental Verification of Stopping-Power Prediction 6.1 Anthropomorphic Head Phantom 6.2 Homogeneous Biological Tissue Samples 7 Clinical Translation and Validation of Dual-Energy Computed Tomography 7.1 Feasibility of Dual-Spiral Dual-Energy CT 7.2 Range Prediction in Cerebral and Pelvic Tumour Patients 7.3 Tissue Variability in Brain-Tumour Patients 7.4 Feasibility of 4D Dual-Spiral Dual-Energy CT 7.5 DECT-Based Refinement of the Hounsfield Look-Up Table 8 Summary 9 Zusammenfassung

No description available.