<div> <div> <p>Purpose: Preclinical studies have demonstrated that cancer cells may produce innate immune signals such as type-I interferons following radiation damage, which derives from activation of the cGAS-STING pathway following detection of cytosolic dsDNA. Limited studies have explored how these mechanisms vary from the conditions of the radiation exposure. High- linear energy transfer (LET) radiation induces more DNA double-strand breaks (DSB) per dose than low-LET radiation, thus is expected to be more immunogenic. However, DNA damage in hypoxic cells is more probable to undergo chemical repair due to limitations in oxygen fixation, thus is expected to be more immunosuppressive. Our goal is to study and model the dose response characteristics of IFNβ and Trex1 in vitro following exposure of radiations with varying LET and to develop techniques for further study in vivo.<br></p><p><br></p> <p>Methods: Reference data from Vanpouille-Box (2017) on STING dose response was applied to develop empirical models of cytosolic dsDNA and Trex1 regulation as a function of dose and quantity of DNA DSB, the latter of which is dependent on particle LET and oxygenation and is calculated using Monte Carlo Damage Simulation (MCDS) software. These models were used as preliminary data to guide in vitro experiments using Merkel cell carcinoma cells. The dose response of pro-inflammatory IFNβ and exonuclease Trex1, an anti-inflammatory suppressor of cGAS-STING, was measured post-irradiation. MCDS was again used to model fast neutron relative biological effectiveness for DSB induction (RBEDSB) and compared to laboratory measurements of the RBE for IFNβ production (RBEIFNβ). RBEIFNβ models were applied to radiation transport simulations to quantify the potential secretion of IFNβ in representative clinical beams. To enable intra-tumor radiation targeting of tumor hypoxia, mice were seeded with syngeneic tumors and imaged longitudinally with PCT- spectroscopy to determine local variations hemoglobin concentration (Hb) and oxygen saturation (SaO2) over time. Hypoxia classification was based on SaO2 levels in voxels containing hemoglobin relative to a “hypoxia threshold” of SaO2 < 0.2.</p><p><br></p> <p>Results: Based on analysis of published data, our preliminary models of cytosolic DNA and Trex1 dose responses demonstrate dose enhancements from high-LET radiation, such as that at the distal edge of a Bragg peak, and suppression from cellular hypoxia. This manifests as an RBE-dependent ‘shift’ in STING response. Laboratory measurements in MCC13 cells show peak IFNβ production at 6.1 Gy following fast neutron irradiation and 14.5 Gy following x-rays (RBEIFNβ = 2.4). However, IFNβ signal amplitudes were not significantly different between these radiation types. Trex1 signal increased linearly with dose, with fourfold higher upregulation per dose for fast neutrons. Modeling of RBE in clinical beams suggests that ion sources may induce spatially localized IFNβ near their end of range, which is potentially advantageous for initiation of tumor-specific immune activity. Uncharged sources stimulate IFNβ more uniformly with depth. Longitudinal PCT-S scanning is able to localize and distinguish chronic and acute hypoxia in vivo. Changes in the hypoxic classification from tumor growth and following anti-angiogenic therapy are distinguishable.<br> </p><p> </p><div> <div> <div> <p>Conclusion: Radiation-induced immunogenicity can be induced differentially based on radiation quality and is expected to be affected by cellular oxygenation. High-LET radiation, such as fast neutrons, drives greater IFNβ innate immune response per dose than low-LET radiation, such as x-rays, which may enhance abscopal effects when used in combination with immune-stimulating agents. However, anti-inflammatory signaling is greater per dose for fast neutrons, and it remains unclear if high-LET radiations are therapeutically advantageous over low-LET radiation for pro-inflammatory tumor signaling. High resolution in vivo imaging of tumor hypoxia is feasible with photoacoustic techniques, which can potentially be leveraged to study selective immunogenicity enhancement of the hypoxic niche following radiation therapy. <br></p> </div> </div> </div> <p> </p> </div></div>

The field of radiation oncology (RO) involves the use of highly advanced techniques to treat cancer and safely spare healthy organs. The discipline has experienced rapid growth in the past 25 years, with technological advancement as the driving force. Available data and an instrument to effectively measure the accessibility of innovation in the field were lacking. The purpose of this study was to investigate the accessibility of innovative services in RO in the United States and assess possible diffusion patterns. Two hundred and forty medical physicists practicing in RO in the United States completed a custom Internet-based survey. The diffusion of innovation theory was used as the theoretical framework for the study. A quantitative cross-sectional analysis was performed to assess how innovation scores may vary depending on individual and organizational factors. ANOVA, Spearman correlation, and multiple linear regression were used to analyze the data. University affiliation, urbanicity, appreciation, and motivation were found to be statistically significant factors affecting accessibility to innovative services. Statistically significant barriers preventing innovation were lack of evidence, increased complexity, staffing constraints, lack of interest from others, lack of interoperability, and lack of reimbursement. Medical physicists are in a leadership position to influence the adoption of innovative services in RO. Encouraging the utilization of innovative and Food and Drug Administration-approved techniques may improve cancer outcomes and consequently have a positive social change effect on public health.

No description available.

The objective of this work is to develop an on-line planning and delivery technique for palliative radiotherapy of spinal metastases using a linear accelerator capable of cone-beam CT (CBCT) imaging. This technique integrates all preparation and delivery steps into a single session equivalent to an initial treatment session. The key technical challenges pertaining to the development and implementation of this novel treatment technique are related to CBCT image performance, efficient system integration, development of on-line planning tools and design of novel quality assurance (QA) phantoms and processes. Hardware and software image corrections were first implemented to make CBCT images suitable for target definition and planning. These corrections reduced CBCT non-uniformity and improved CBCT-number accuracy. The on-line treatment technique workflow and the integration of all the subsystems involved in the process were assessed on a customized spine phantom constructed for the study. The challenges related to the routine QA of the highly integrated on-line treatment technique were addressed with the construction and validation of an integral test phantom. This phantom, which contains point detectors (diodes) allows for real-time QA of the entire image guidance, planning and treatment process in terms of dose delivery accuracy. The integral test phantom was also effective for the QA of high-dose, high-precision spinal radiosurgery. Simulation of the on-line treatment technique on patient data showed that the planning step was the one of the most time consuming tasks due predominantly to manual target definition. A semi-automatic method for detection and identification of vertebrae on CBCT images was developed and validated to streamline vertebra segmentation and improve the on-line treatment efficiency. With a single patient setup at the treatment unit, patient motion during the on-line process represents the main source of geometric uncertainty for dose delivery. Spine intra-fraction motion was assessed on CBCT for a group of 49 patients treated with a palliative intent. The use of surface marker tracking as a surrogate for spine motion was also evaluated. Finally, the complete on-line planning and delivery technique was implemented in a research ethics board (REB) approved clinical study at the Princess Margaret Hospital and 7 patients have been successfully treated at the time of this report with this novel treatment approach.

<p>The online adaptive radiation therapy for prostate cancer based on re-optimization has been shown to provide better daily target coverage through the treatment course, especially in treatment sessions with large anatomical deformation. However, the clinical implementation of such technique is still limited primarily due to two major challenges: the low efficiency of re-optimization and the lack of online quality assurance technique to verify delivery accuracy. This project aims at developing new techniques and understandings to address these two challenges. </p><p>The study was based on retrospective study on patient data following IRB-approved protocol, including both planning Computer Tomography (CT) and daily Cone-Beam Computer Tomography (CBCT) images. The project is divided in to three parts. The first two parts address primarily the efficiency challenge; and the third part of this project aims at validating the deliverability of the online re-optimized plans and developing an online delivery monitoring system. </p><p><bold>I. Overall implementation scheme.</bold> In this part, an evidence-based scheme, named Adaptive Image-Guided Radiation Therapy (AIGRT), was developed to integrate the re-optimization technique with the current IGRT technique. The AIGRT process first searches for a best plan for the daily target from a plan pool, which consists the original CT plan and all previous re-optimized plans. If successful, the selected plan is used for the daily treatment with translational shifts. Otherwise, the AIGRT invokes re-optimization process of the CT plan for the anatomy-of-the-day, which is added to the plan pool afterwards as a candidate plan for future fractions. The AIGRT scheme is evaluated by comparisons with daily re-optimization and online repositioning techniques based on daily target coverage, Organ-at-Risk (OAR) sparing and implementation efficiency. Simulated treatment courses for 18 patients with re-optimization alone, re-positioning alone and AIGRT shows that AIGRT offers reliable daily target coverage that is highly comparable to re-optimization everyday and significantly improves compared to re-positioning. AIGRT is also seen to provide improved organs-at-risk (OARs) sparing compared to re-positioning. Apart from dosimetric benefits, AIGRT in addition offers an efficient scheme to integrate re-optimization to current re-positioning-based IGRT workflow.</p><p><bold>II. Strategies for automatic re-optimization.</bold> This part aims at improving the efficiency of re-optimization through automation and strategic selections of optimization parameters. It investigates the strategies for performing fast (~2 min) automatic online re-optimization with a clinical treatment planning system; and explores the performance with different input parameters settings: the DVH objective settings, starting stage and iteration number (in the context of real time planning). Simulated treatments of 10 patients were re-optimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting re-optimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analysed by statistical modelling, and compared both in terms of dosimetry and delivery efficiency. The results show that all fast online re-optimized plans provide consistent coverage and conformity to the daily target. For OAR sparing however, different planning parameters led to different optimization results. The 3 input parameters, i.e. DVH objectives, starting stages and iteration numbers, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the original plan fluence map as the starting stage reduced OAR dose at the mid-dose region, but increased 17% more monitor units. Only < 2cc differences in OAR V50% / V70Gy / V76Gy were observed between 100 and 50 iterations. Based on these results, it is feasible to perform automatic online re-optimization in ~2 min using a clinical treatment planning system. Selecting optimal sets of input parameters is the key to achieving high quality re-optimized plans, and should be based on the individual patient's daily anatomy, delivery efficiency and time allowed for plan adaptation. </p><p><bold>III. Delivery accuracy evaluation and monitoring.</bold> This part of the project aims at validating the deliverability of the online re-optimized plans and developing an online delivery monitoring system. This system is based on input from Dynamic Machine Information (DMI), which continuously reports actual multi-leaf collimator (MLC) positions and machine monitor units (MUs) at 50ms intervals. Based on these DMI inputs, the QA system performed three levels of monitoring/verification on the plan delivery process: (1) Following each input, actual and expected fluence maps delivered up to the current MLC position were dynamically updated using corresponding MLC positions in the DMI. The difference between actual and expected fluence maps creates a fluence error map (FEM), which is used to assess the delivery accuracy. (2) At each control point, actual MLC positions were verified against the treatment plan for potential errors in data transfer between the treatment planning system (TPS) and the MLC controller. (3) After treatment, delivered dose was reconstructed in the treatment planning system based on DMI data during delivery, and compared to planned dose. FEMs from 210 prostate IMRT beams were evaluated for error magnitude and patterns. In addition, systematic MLC errors of ±0.5 and ±1 mm for both banks were simulated to understand error patterns in resulted FEMs. Applying clinical IMRT QA standard to the online re-optimized plans suggests the deliverability of online re-optimized plans are similar to regular IMRT plans. Applying the proposed QA system to online re-optimized plans also reveals excellent delivery accuracy: over 99% leaf position differences are < 0.5 mm, and the majority of pixels in FEMs are < 0.5 MU with errors exceeding 0.5 MU primarily located on the edge of the fields. All clinical FEMs observed in this study have positive errors on the left edges, and negative errors on the right. Analysis on a typical FEM reveals positive correlation between the magnitude of fluence errors and the corresponding leaf speed. FEMs of simulated erroneous delivery exhibit distinct patterns for different MLC error magnitudes and directions, indicating the proposed QA system is highly specific in detecting the source of errors. Based on these results, it can be concluded that the proposed online delivery monitoring system is very sensitive to leaf position errors, highly specific of the error types, and therefore meets the purpose for online delivery accuracy verification. Post-treatment dosimetric verification shows minimal difference between planned and actual delivered DVH, further confirming that the online re-optimized plans can be accurately delivered.</p><p>In summary, this project addressed two most important challenges for clinical implementation of online ART, efficiency and quality assurance, through innovative system design, technique development and validation with clinical data. The efficiencies of the overall treatment scheme and the re-optimization process have been improved significantly; and the proposed online quality assurance system is found to be effective in catching and differentiating leaf motion errors.</p> / Dissertation

The objective of this work is to develop an on-line planning and delivery technique for palliative radiotherapy of spinal metastases using a linear accelerator capable of cone-beam CT (CBCT) imaging. This technique integrates all preparation and delivery steps into a single session equivalent to an initial treatment session. The key technical challenges pertaining to the development and implementation of this novel treatment technique are related to CBCT image performance, efficient system integration, development of on-line planning tools and design of novel quality assurance (QA) phantoms and processes. Hardware and software image corrections were first implemented to make CBCT images suitable for target definition and planning. These corrections reduced CBCT non-uniformity and improved CBCT-number accuracy. The on-line treatment technique workflow and the integration of all the subsystems involved in the process were assessed on a customized spine phantom constructed for the study. The challenges related to the routine QA of the highly integrated on-line treatment technique were addressed with the construction and validation of an integral test phantom. This phantom, which contains point detectors (diodes) allows for real-time QA of the entire image guidance, planning and treatment process in terms of dose delivery accuracy. The integral test phantom was also effective for the QA of high-dose, high-precision spinal radiosurgery. Simulation of the on-line treatment technique on patient data showed that the planning step was the one of the most time consuming tasks due predominantly to manual target definition. A semi-automatic method for detection and identification of vertebrae on CBCT images was developed and validated to streamline vertebra segmentation and improve the on-line treatment efficiency. With a single patient setup at the treatment unit, patient motion during the on-line process represents the main source of geometric uncertainty for dose delivery. Spine intra-fraction motion was assessed on CBCT for a group of 49 patients treated with a palliative intent. The use of surface marker tracking as a surrogate for spine motion was also evaluated. Finally, the complete on-line planning and delivery technique was implemented in a research ethics board (REB) approved clinical study at the Princess Margaret Hospital and 7 patients have been successfully treated at the time of this report with this novel treatment approach.

Radiation therapy (RT) plays a crucial role in the management of cancer, however, current standards of care have yet to account for patient specific radiation sensitivity. Raman spectroscopy (RS) is a promising technique for radiobiological studies as a way to measure radiation responses in biological samples and could provide a method for monitoring and predicting radiation response in patients. The work in this dissertation gives way to significant advances in the implementation of RS for applications in radiation oncology. Specifically, instrumentation improvements for clinical implementation of RS were achieved through the investigation and development of Raman microfluidic systems. Unique magnesium fluoride based microfluidic systems were engineered and evaluated for applications in radiobiological studies. These systems were found to yield superior spectral quality over traditional microfluidic designs. Furthermore, in order to assert RS as a key technique for clinical monitoring and prediction of radiation responses, human non-small cell lung cancer (NSCLC) and breast adenocarcinoma tumour xenograft models were investigated for Raman signatures of radiation response. These studies found that RS can identify unique and distinct signatures of radiation response in tumours, that can be tracked over time. In particular, NSCLC tumours were found to have key radiation induced modulations in cell cycle and metabolic linked spectral features- including glycogen. Breast adenocarcinoma tumours were found to exhibit distinct fluctuations in spectral features linked to cell cycle as well as protein content. In the case of NSCLC, radiation response signatures were found to be linked to tumour regression and hypoxic status of the tumour- a key factor that dictates radiation resistance in the disease. This work provides the first application of RS to measure radiation response signatures of tumours irradiated \textit{in vivo}. These results show that RS is a versatile technique that can offer insight into radiation induced molecular changes that are unique to the type of cancer and can be monitored over several days following radiation exposure. Together with improved instrumentation for radiobiological studies using microfluidics, the work presented in this dissertation further emphasizes the key role RS can have in radiation oncology and personalization of RT. / Graduate / 2019-08-21

De nos jours, plus de 50% des patients porteurs de tumeur bénéficient d’un traitement de radiothérapie. Malgré de récentes avancées technologiques augmentant de la précision des traitements, la radiothérapie encéphalique induit toujours des effets secondaires invalidants et irréversibles. Ce constat justifie le développement de nouvelles techniques de radiothérapie. Des études précliniques réalisées sur l’irradiation FLASH ont montré la possibilité de maintenir un effet anti-tumoral tout en réduisant drastiquement les effets secondaires sur le tissu sain. Cet effet a été appelé « l’effet FLASH ». Cette technologie consistant à délivrer des doses à des débits supérieurs à 40 Gy/s a généré un intérêt important pour l’augmentation de l’index thérapeutique de la radiothérapie.Ce travail de thèse vise à étudier l’effet anti-tumoral de l’irradiation FLASH sur des modèles précliniques de glioblastome, tout en évaluant ses effets sur le tissu cérébral sain. Des modèles murins de glioblastome sous-cutané, orthotopique et transgénique ont été développés et irradiés grâce à un prototype d’accélérateur linéaire d’électrons délivrant une irradiation FLASH ou conventionnelle. De plus, des modèles murins d’irradiation encéphalique ont été mis au point afin d’investiguer les effets cellulaires et les altérations fonctionnelles induites par l’irradiation FLASH. La division cellulaire et la structure neuronale dans l’hippocampe ont été évaluées, ainsi que des aspects plus physiopathologiques comme la neuroinflammation ou l’astrogliose. Un panel de tests cognitifs a également été utilisé afin d’étudier les altérations cognitives induites par l’irradiation encéphalique. Enfin, les évènements physico-chimiques engendrés par l’irradiation FLASH et plus particulièrement le rôle de la consommation de dioxygène lors de l’irradiation, ont été analysés afin d’élucider les mécanismes qui supportent l’effet FLASH.Dans tous les modèles étudiés, l’irradiation FLASH a présenté un effet anti-tumoral au minimum similaire à celui de l’irradiation conventionnelle. Les modèles d’irradiation encéphalique ont montré une innocuité de l’irradiation FLASH sur le tissu cérébral sain, avec une absence de déficits cognitifs pour des débits de dose supérieurs à 100 Gy/s, couplée à une absence d’altération de la division cellulaire et de la structure neuronale dans l’hippocampe, une absence de neuroinflammation et d’astrogliose. De plus, des résultats similaires ont été observés avec l’utilisation de rayons X délivrés à ultra-haut débit par un rayonnement synchrotron. Sur le plan mécanistique, la réversion des effets protecteurs de l’irradiation FLASH par l’induction d’une hyperoxie, l’absence d’effet de l’anoxie sur l’effet anti-tumoral et la production de moins de radicaux libres souligne le rôle primaire du dioxygène dans l’effet FLASH.L’ensemble de ces résultats illustre la possibilité d’augmenter l’index thérapeutique de la radiothérapie en utilisant l’irradiation FLASH. En effet, cette nouvelle technologie permet de préserver le tissu sain contre les toxicités radio-induites lorsque l’irradiation est délivrée à des débits supérieurs à 100 Gy/s, tout en gardant un effet anti-tumoral équivalent à l’irradiation conventionnelle. D’après ces résultats précliniques et un transfert clinique dans un futur proche, l’irradiation FLASH pourrait devenir une technique de choix dans le traitement des tumeurs par radiothérapie. / Nowadays, more than 50% of cancer patients can benefit from a radiation-therapy treatment. Despite important technological advance and dose delivery precision, encephalic radiation-therapy still induces large and irreversible side effects in pediatric and adult cancer patients, justifying the urge to develop new radiation-therapy techniques. Preclinical studies on FLASH irradiation (FLASH-RT) showed a possibility to efficiently treat the tumors, without inducing drastic side-effects on the normal tissue, by increasing the dose-rate over 40 Gy/s. This so called “FLASH effect” set off an important interest in this new irradiation technology to increase the therapeutic ratio of radiation-therapy.This PhD work aimed at investigating the antitumor effect of FLASH-RT on brain tumor models along with the assessment of the ultra-high dose-rate irradiation effects on the normal brain tissue. In this context, subcutaneous, orthotopic and transgenic glioblastoma murine models were used to investigate the curative effect of FLASH irradiation delivered with an experimental LINAC available at the CHUV, and able to deliver both conventional and FLASH irradiation. Moreover, murine models of whole brain irradiation were developed to investigate the radiation-induced cellular and functional alterations at early and late time-points post-FLASH-RT. These models were used to decipher the cellular effectors involved in the brain’s radiation response including hippocampal cell-division and neuronal responses but also more physio pathological aspects as radiation-induced reactive astrogliosis and neuroinflammation. A panel of well-defined cognitive tests was also developed to investigate the radiation-induced cognitive alterations. Eventually, the physio-chemical primary events induced by FLASH-RT, and particularly the role of dioxygen consumption, were investigated to decipher the mechanisms that underlie the FLASH effect.In all investigated tumor models, FLASH-RT displayed an efficient antitumor effect at least similar to the conventional irradiation. The whole brain irradiation models showed an innocuousness of FLASH-RT on the normal brain tissue, with an absence of cognitive deficit several months after irradiation at dose-rates above 100 Gy/s, coupled with a preservation of hippocampal cell division and neuronal structure. This protection was also observed at the physio pathological level with an absence of astrogliosis and neuroinflammation. Moreover, these results were reproduced with ultra-high dose-rate X-Rays delivered with a synchrotron light source. On the mechanistic side, the reversion of the protective effects of FLASH-RT by hyperoxia, and the absence of effect of anoxia on the antitumor effect, along with a decreased ROS production underlies the primary role of dioxygen consumption during ultra-high dose-rate irradiation.Altogether, these unique results depict the possibility to increase the therapeutic index of radiation-therapy by the use of FLASH-RT. Indeed, this new irradiation technology preserves the normal brain tissue from radiation-induced toxicities by increasing the dose-rate over 100 Gy/s, while keeping an antitumor effect equivalent to the conventional dose-rate irradiation. According to these preclinical results and an upcoming clinical translation, FLASH-RT might become a major contributor to the cancer treatment by radiation therapy.

One major objective in radiation oncology is the personalisation of cancer treatment. The implementation of this concept requires the identification of biomarkers, which precisely predict therapy outcome. Besides molecular characterisation of tumours, a new approach known as radiomics aims to characterise tumours using imaging data. In the context of the presented thesis, radiomics was established at OncoRay to improve the performance of imaging-based risk models. Two software-based frameworks were developed for image feature computation and risk model construction. A novel data-driven approach for the correction of intensity non-uniformity in magnetic resonance imaging data was evolved to improve image quality prior to feature computation. Further, different feature selection methods and machine learning algorithms for time-to-event survival data were evaluated to identify suitable algorithms for radiomics risk modelling. An improved model performance could be demonstrated using computed tomography data, which were acquired during the course of treatment. Subsequently tumour sub-volumes were analysed and it was shown that the tumour rim contains the most relevant prognostic information compared to the corresponding core. The incorporation of such spatial diversity information is a promising way to improve the performance of risk models.:1. Introduction 2. Theoretical background 2.1. Basic physical principles of image modalities 2.1.1. Computed tomography 2.1.2. Magnetic resonance imaging 2.2. Basic principles of survival analyses 2.2.1. Semi-parametric survival models 2.2.2. Full-parametric survival models 2.3. Radiomics risk modelling 2.3.1. Feature computation framework 2.3.2. Risk modelling framework 2.4. Performance assessments 2.5. Feature selection methods and machine learning algorithms 2.5.1. Feature selection methods 2.5.2. Machine learning algorithms 3. A physical correction model for automatic correction of intensity non-uniformity in magnetic resonance imaging 3.1. Intensity non-uniformity correction methods 3.2. Physical correction model 3.2.1. Correction strategy and model definition 3.2.2. Model parameter constraints 3.3. Experiments 3.3.1. Phantom and simulated brain data set 3.3.2. Clinical brain data set 3.3.3. Abdominal data set 3.4. Summary and discussion 4. Comparison of feature selection methods and machine learning algorithms for radiomics time-to-event survival models 4.1. Motivation 4.2. Patient cohort and experimental design 4.2.1. Characteristics of patient cohort 4.2.2. Experimental design 4.3. Results of feature selection methods and machine learning algorithms evaluation 4.4. Summary and discussion 5. Characterisation of tumour phenotype using computed tomography imaging during treatment 5.1. Motivation 5.2. Patient cohort and experimental design 5.2.1. Characteristics of patient cohort 5.2.2. Experimental design 5.3. Results of computed tomography imaging during treatment 5.4. Summary and discussion 6. Tumour phenotype characterisation using tumour sub-volumes 6.1. Motivation 6.2. Patient cohort and experimental design 6.2.1. Characteristics of patient cohorts 6.2.2. Experimental design 6.3. Results of tumour sub-volumes evaluation 6.4. Summary and discussion 7. Summary and further perspectives 8. Zusammenfassung

Boron neutron capture therapy (BNCT) has the potential to specifically destroy tumor cells without damaging the tissues infiltrated by the tumor. BNCT is a binary treatment method based on the combination of two agents that have no effect when applied individually: 10B and thermal neutrons. Exclusively, the combination of both produces an effect, whose extent depends on the amount of 10B in the tumor but also on the organs at risk. It is not yet possible to determine the 10B concentration in a specific tissue using non-invasive methods. At present, it is only possible to measure the 10B concentration in blood and to estimate the boron concentration in tissues based on the assumption that there is a fixed uptake of 10B from the blood into tissues. On this imprecise assumption, BNCT can hardly be developed further. A therapeutic approach, combining the boron carrier for therapeutic purposes with an imaging tool, might allow us to determine the 10B concentration in a specific tissue using a non-invasive method. This review provides an overview of the current clinical protocols and preclinical experiments and results on how innovative drug development for boron delivery systems can also incorporate concurrent imaging. The last section focuses on the importance of proteomics for further optimization of BNCT, a highly precise and personalized therapeutic approach.