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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

La proton thérapie est une modalité de traitement du cancer qu’utilise des faisceaux de protons. Les systèmes de planification de traitement actuels se basent sur une image de l’anatomie du patient acquise par tomodensitométrie. Le pouvoir d’arrêt des protons relatif à l’eau (Stopping Power Ratio en Anglais, SPR) est déterminé à partir des unités Hounsfield (Hounsfield Units en Anglais, HU) pour calculer la dose absorbée au patient. Les protons sont plus vulnérables que les photons aux modifications du SPR du tissu dans la direction du faisceau dues au mouvement, désalignement ou changements anatomiques. De plus, les inexactitudes survenues de la CT de planification et intrinsèques à la conversion HU-SPR contribuent énormément à l’incertitude de la portée des protons. Dans la pratique clinique, au volume de traitement s’ajoutent des marges de sécurité pour tenir en compte ces incertitudes en détriment de perdre la capacité d’épargner les tissus autour de la tumeur. L’usage de l’imagerie bi-énergie en proton thérapie a été proposé pour la première fois en 2009 pour mieux estimer le SPR du patient par rapport à l’imagerie mono-énergie. Le but de cette thèse est d’étudier la potentielle amélioration de l’estimation du SPR des protons en utilisant l’imagerie bi-énergie, pour ainsi réduire l’incertitude dans la prédiction de la portée des protons dans le patient. Cette thèse est appliquée à un nouveau système d’imagerie, l’Imaging Ring (IR), un scanner de tomodensitométrie conique (Cone-Beam CT en Anglais, CBCT) développé pour la radiothérapie guidée par l’image. L’IR est équipé d’une source de rayons X avec un système d’alternance rapide du voltage, synchronisé avec une roue contenant des filtres de différents matériaux que permet des acquisitions CBCT multi-énergie. La première contribution est une méthode pour calibrer les modèles de source et la réponse du détecteur pour être utilisés en simulations d’imagerie X. Deuxièmement, les recherches ont évalué les facteurs que peuvent avoir un impact sur les résultats du procès de décomposition bi-énergie, dès paramètres d’acquisition au post-traitement. Les deux domaines, image et basée en la projection, ont été minutieusement étudiés, avec un spéciale accent aux approches basés en la projection. Deux nouvelles bases de décomposition ont été proposées pour estimer le SPR, sans avoir besoin d’une variable intermédiaire comme le nombre atomique effectif. La dernière partie propose une estimation du SPR des fantômes de caractérisation tissulaire et d’un fantôme anthropomorphique à partir d’acquisitions avec l’IR. Il a été implémentée une correction du diffusé, et il a été proposée une routine pour interpoler linéairement les sinogrammes de basse et haute énergie des acquisitions bi-énergie pour pouvoir réaliser des décompositions en matériaux avec données réelles. Les valeurs réconstruits du SPR ont été comparées aux valeurs du SPR expérimentales déterminés avec un faisceau d’ions de carbone. / Proton therapy is a promising radiation treatment modality that uses proton beams to treat cancer. Current treatment planning systems rely on an X-ray computed tomography (CT) image of the patient's anatomy to design the treatment plan. The proton stopping-power ratio relative to water (SPR) is derived from CT numbers (HU) to compute the absorbed dose in the patient. Protons are more vulnerable than photons to changes in tissue SPR in the beam direction caused by movement, misalignment or anatomical changes. In addition, inaccuracies arising from the planning CT and intrinsic to the HU-SPR conversion greatly contribute to the proton range uncertainty. In clinical practice, safety margins are added to the treatment volume to account for these uncertainties at the expense of losing organ-sparing capabilities. The use of dual-energy (DE) in proton therapy was first suggested in 2009 to better estimate the SPR with respect to single-energy X-ray imaging. The aim of this thesis work is to investigate the potential improvement in determining proton SPR using DE to reduce the uncertainty in predicting the proton range in the patient. This PhD work is applied to a new imaging device, the Imaging Ring (IR), which is a cone-beam CT (CBCT) scanner developed for image-guided radiotherapy (IGRT). The IR is equipped with a fast kV switching X-ray source, synchronized with a filter wheel, allowing for multi-energy CBCT imaging. The first contribution of this thesis is a method to calibrate a model for the X-ray source and the detector response to be used in X-ray image simulations. It has been validated experimentally on three CBCT scanners. Secondly, the investigations have evaluated the factors that have an impact on the outcome of the DE decomposition process, from the acquisition parameters to the post-processing. Both image- and projection-based decomposition domains have been thoroughly investigated, with special emphasis on projection-based approaches. Two novel DE decomposition bases have been proposed to estimate proton SPRs, without the need for an intermediate variable such as the effective atomic number. The last part of the thesis proposes an estimation of proton SPR maps of tissue characterization and anthropomorphic phantoms through DE-CBCT acquisitions with the IR. A correction for X-ray scattering has been implemented off-line, and a routine to linearly interpolate low-energy and high-energy sinograms from sequential and fast-switching DE acquisitions has been proposed to perform DE material decomposition in the projection domain with real data. DECT-derived SPR values have been compared with experimentally-determined SPR values in a carbon-ion beam.

Made available in DSpace on 2014-07-29T15:25:15Z (GMT). No. of bitstreams: 1 Tese Larissa Silva Barbosa.pdf: 4706638 bytes, checksum: 84142955db2151a63ddb14705543d0e3 (MD5) Previous issue date: 2011-05-09 / The aim of this study was to assess body composition and anthropometry of the elderly with regard to agreement between methods, development and validation of predictive equations and cutoffs. We evaluated 132 elderly patients (52 men and 80 women) aged between 60 and 91 years, users of primary health care, not institutionalized and drawn at random in proportion to the nine health districts of Goiânia, GO. For collection of anthropometric measurements, bioelectrical impedance (BIA) and dual energy x-ray absorptiometry (DEXA), standardized procedures were used by trained examiners and equipment was calibrated regularly. Analyses were performed using STATA/SE. Descriptive analysis, tests for comparison of means, equation validation according to criteria suggested by Lohman, Bland-Altman and Lin graphic analysis and ROC (receiver operator characteristic curve) analysis were carried out. The project was approved by the Ethics Committee of the Federal University of Goias. The Durnin and Womersley equation showed the highest concordance correlation coefficient (CCC = 0.846) and the lowest mean differences (MD = - 2.335) for males. The equations of Lean et al. (for men) and Deurenberg et al. (for women) showed the highest correlation with and lowest mean differences from DEXA. Equations were proposed to estimate body fat percentage (BF%): (males: BF% = - 16.868 + 0.571TSF + 0.409WC and females: BF% = 8.634 + 0.601BMI + 0.321SISF + 0.234SSSF + 0.398TSF 0.467BSF). In both sexes, the equations are similar to DEXA in estimating BF% with high precision and accuracy. In males, the proposed body mass index (BMI) cutoff point was ≥ 25 kg/m2; the waist circumference (WC) cutoff point was ≥ 98.9 cm. In women, the BMI and WC values with the most sensitivity, specificity and accuracy were ≥ 26.6 kg/m2 and ≥ 90.5 cm. Since the currently available equations for predicting body composition of elderly have certain limitations, these newly developed and validated equations for the two sexes can be recommended for wide use. Accurate BMI and WC cutoff points for predicting BF% in older adults were also identified. / O objetivo deste estudo foi analisar a composição corporal e antropometria de idosos com relação à concordância entre métodos, desenvolvimento e validação de equações preditivas e pontos de corte. Foram avaliados 132 idosos (52 homens e 80 mulheres), com idade entre 60 e 91 anos, usuários da atenção primária à saúde, não instituicionalizados, selecionados a partir de sorteio aleatório proporcional aos nove distritos sanitários de Goiânia-GO. Para coleta de medidas antropométricas, impedância bioelétrica (BIA) e absortometria por raio-X de dupla energia (DEXA) foram utilizados procedimentos padronizados, por avaliadores devidamente treinados, com equipamentos regularmente calibrados. As análises foram realizadas no STATA/SE. Realizou-se análise descritiva, testes para comparação de médias, validação de equações segundo critérios sugeridos por Lohman, análise gráfica por Bland e Altman e por Lin e análise de Curva ROC (receiver operator characteristic curve). O projeto foi aprovado pelo Comitê de Ética em Pesquisa da Universidade Federal de Goiás. A equação de Durnin e Womersley apresentou maior coeficiente de correlação de concordância (CCC = 0,846) e menor diferenças médias (DM = - 2,335) para o sexo masculino. A equação de Lean et al. (para homens) e de Deurenberg et al. (para mulheres) apresentaram maior concordância e menores diferenças médias com DEXA. Foram propostas equações para estimativa do percentual de gordura corporal (%GC): (sexo masculino: %GC = - 16,868 + 0,571DCTR + 0,409CC e sexo feminino: %GC = 8,634 + 0,601IMC + 0,321DCSI + 0,234DCSE + 0,398DCTR 0,467DCBI). Em ambos os sexos, as equações propostas apresentaram semelhança com DEXA na estimativa do %GC, apresentando alta precisão e acurácia. No sexo masculino o ponto de corte proposto para índice de massa corporal (IMC) foi ≥ 25 Kg/m2 e para circunferência da cintura (CC) ≥ 98,9 cm. Nas mulheres os valores de IMC e CC com maior sensibilidade, especificidade e acurácia foram ≥ 26,6 Kg/m2 e ≥ 90,5 cm. As equações atualmentes disponíveis para predizer a composição corporal de idosos apresentam limitações, sendo desenvolvida e validada nova equação para ambos os sexos a qual recomenda-se sua ampla utilização. Identificou-se ainda pontos de corte acurados de IMC e CC para predizer %GC em idosos.

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