Breast Cancer and Breast Reconstruction

This book has been contrived to gather recent data on a common health problem. As breast cancer imposes a heavy burden for society due to its psychological, social and economic consequences, every step to broaden our understanding is a worthy task. The aim of this book is to provide some insights on this subject through the information given on new perspectives in genetics and diagnosis, exposed in the section on oncologic issues, as well as on recent topics on surgical treatment, presented in the sections on breast conservative and breast reconstructive surgery

Software and Hardware-based Tools for Improving Ultrasound Guided Prostate Brachytherapy

Minimally invasive procedures for prostate cancer diagnosis and treatment, including biopsy and brachytherapy, rely on medical imaging such as two-dimensional (2D) and three-dimensional (3D) transrectal ultrasound (TRUS) and magnetic resonance imaging (MRI) for critical tasks such as target definition and diagnosis, treatment guidance, and treatment planning. Use of these imaging modalities introduces challenges including time-consuming manual prostate segmentation, poor needle tip visualization, and variable MR-US cognitive fusion. The objective of this thesis was to develop, validate, and implement software- and hardware-based tools specifically designed for minimally invasive prostate cancer procedures to overcome these challenges. First, a deep learning-based automatic 3D TRUS prostate segmentation algorithm was developed and evaluated using a diverse dataset of clinical images acquired during prostate biopsy and brachytherapy procedures. The algorithm significantly outperformed state-of-the-art fully 3D CNNs trained using the same dataset while a segmentation time of 0.62 s demonstrated a significant reduction compared to manual segmentation. Next, the impact of dataset size, image quality, and image type on segmentation performance using this algorithm was examined. Using smaller training datasets, segmentation accuracy was shown to plateau with as little as 1000 training images, supporting the use of deep learning approaches even when data is scarce. The development of an image quality grading scale specific to 3D TRUS images will allow for easier comparison between algorithms trained using different datasets. Third, a power Doppler (PD) US-based needle tip localization method was developed and validated in both phantom and clinical cases, demonstrating reduced tip error and variation for obstructed needles compared to conventional US. Finally, a surface-based MRI-3D TRUS deformable image registration algorithm was developed and implemented clinically, demonstrating improved registration accuracy compared to manual rigid registration and reduced variation compared to the current clinical standard of physician cognitive fusion. These generalizable and easy-to-implement tools have the potential to improve workflow efficiency and accuracy for minimally invasive prostate procedures

Patient-specific simulation environment for surgical planning and preoperative rehearsal

Surgical simulation is common practice in the fields of surgical education and training. Numerous surgical simulators are available from commercial and academic organisations for the generic modelling of surgical tasks. However, a simulation platform is still yet to be found that fulfils the key requirements expected for patient-specific surgical simulation of soft tissue, with an effective translation into clinical practice. Patient-specific modelling is possible, but to date has been time-consuming, and consequently costly, because data preparation can be technically demanding. This motivated the research developed herein, which addresses the main challenges of biomechanical modelling for patient-specific surgical simulation. A novel implementation of soft tissue deformation and estimation of the patient-specific intraoperative environment is achieved using a position-based dynamics approach. This modelling approach overcomes the limitations derived from traditional physically-based approaches, by providing a simulation for patient-specific models with visual and physical accuracy, stability and real-time interaction. As a geometrically- based method, a calibration of the simulation parameters is performed and the simulation framework is successfully validated through experimental studies. The capabilities of the simulation platform are demonstrated by the integration of different surgical planning applications that are found relevant in the context of kidney cancer surgery. The simulation of pneumoperitoneum facilitates trocar placement planning and intraoperative surgical navigation. The implementation of deformable ultrasound simulation can assist surgeons in improving their scanning technique and definition of an optimal procedural strategy. Furthermore, the simulation framework has the potential to support the development and assessment of hypotheses that cannot be tested in vivo. Specifically, the evaluation of feedback modalities, as a response to user-model interaction, demonstrates improved performance and justifies the need to integrate a feedback framework in the robot-assisted surgical setting.Open Acces

Personalised body counter calibration using anthropometric parameters

This book describes the development of a new method for personalisation of efficiency factors in partial body counting. Its achieved goal is the quantification of uncertainties in those factors due to variation in anatomy of the measured persons, and their reduction by correlation with anthropometric parameters. The method was applied to a detector system at the In Vivo Measurement Laboratory at Karlsruhe Institute of Technology using Monte Carlo simulation and computational phantoms

Dosimétrie clinique en radiothérapie moléculaire

La radiothérapie moléculaire (RTM) est une radiothérapie systémique, où le produit radiopharmaceutique se lie spécifiquement sur les tumeurs pour détruire sélectivement les cibles cancéreuses tout en préservant les organes sains. Lutathera® (177Lu-DOTATATE) est un radiopharmaceutique récemment approuvé par la FDA/EMA pour le traitement des tumeurs neuroendocrines gastro-entéro-pancréatiques (GEP-NETs). Dans la pratique clinique, les patients reçoivent une activité fixe de Lutathera®, 4 cycles de 7,4 GBq, en supposant que la pharmacocinétique du radiopharmaceutique est même entre les patients. La dosimétrie spécifique au patient permet un changement de paradigme majeur dans l'administration de la RTM, passant d'une approche "taille unique" à une véritable médecine personnalisée où l'activité administrée est évaluée spécifiquement sur la base de l'irradiation délivrée à chaque patient. Pour ce faire, il faut généralement déterminer la distribution spatiale du radiopharmaceutique dans les organes par imagerie à différents moments (imagerie quantitative), estimer le nombre total de désintégrations radioactives en intégrant l'activité dans le temps (évaluation pharmacocinétique) et calculer la dose absorbée à partir des caractéristiques physiques du radionucléide et du transport de l'énergie dans les tissus du patient. Actuellement, il n'existe pas de procédures normalisées pour effectuer la dosimétrie clinique. En outre, l'évaluation des incertitudes associées à la procédure de dosimétrie n'est pas triviale. Le projet DosiTest a été lancé pour évaluer les incertitudes associées à chacune des étapes du flux de travail de la dosimétrie clinique, via une inter-comparaison multicentrique basée sur la modélisation de Monte Carlo (MC). La première phase de la thèse a consisté à comparer les analyses dosimétriques effectuées par différents centres utilisant le même logiciel et le même protocole sur le même ensemble de données de patients dans le cadre du projet IAEA-CRP E23005 afin d'évaluer la précision de la dosimétrie clinique. À notre connaissance, c'est la première fois qu'une comparaison dosimétrique multicentrique d'un seul ensemble de données cliniques sur un patient a été entreprise en utilisant le même protocole et le même logiciel par de nombreux centres dans le monde entier. Elle a mis en évidence le besoin crucial d'établir des points de contrôle et d'effectuer des vérifications de bon sens pour éliminer les disparités significatives entre les résultats et distinguer les pratiques erronées de la variabilité inter-opérateurs acceptable. Un résultat important de ce travail a été le manque d'assurance qualité en dosimétrie de médecine nucléaire clinique et la nécessité de développer des procédures de contrôle qualité. Alors que la dosimétrie gagne en popularité en médecine nucléaire, les meilleures pratiques doivent être adoptées pour garantir la fiabilité, la traçabilité et la reproductibilité des résultats. Cela met également en avant la nécessité de dispenser une formation suffisante après l'acquisition des progiciels relativement nouveaux, au-delà de quelques jours. Ceci est clairement insuffisant dans le contexte d'un domaine émergent où l'expérience professionnelle fait souvent défaut. Ensuite, l'étude de l'exactitude de la dosimétrie clinique nécessite de générer des ensembles de données de test, afin de définir la vérité de base par rapport à laquelle les procédures de dosimétrie clinique peuvent être comparées. La deuxième section de la thèse traite de la simulation de l'imagerie TEMP scintigraphique tridimensionnelle en implémentant le mouvement du détecteur d'auto-contournement dans la boîte à outils Monte Carlo GATE. Après la validation des projections TEMP/TDM sur des modèles anthropomorphes, une série d'images réalistes de patients cliniques a été générée. La dernière partie de la thèse a établi la preuve de concept du projet DosiTest, en utilisant un ensemble de données TEMP/TDM virtuelles (simulées) à différents moments, avec différentes gamma-caméras, permettant de comparer différentes techniques dosimétriques et d'évaluer la faisabilité clinique du projet dans certains départements de médecine nucléaire.Molecular radiotherapy (MRT) is a systemic radiotherapy where the radiopharmaceutical binds specifically to tumours to selectively destroy cancer targets while sparing healthy organs. Lutathera® (177Lu-DOTATATE) is a radiopharmaceutical that was recently FDA/EMA approved for the treatment of the GastroEnteroPancreatic NeuroEndocrine Tumours (GEP-NETs). In clinical practice, patients are administered with a fixed activity of Lutathera®, assuming that radiopharmaceutical distribution is the same for all patients. Patient-specific dosimetry allows for a major paradigm shift in the administration of MRT from "one-size-fits-all" approach, to real personalised medicine where administered activity is assessed specifically on the base of the irradiation delivered to each patient. This usually requires determining the spatial distribution of the radiopharmaceutical in various organs via imaging at different times (quantitative imaging), estimating the total number of radioactive decays by integrating activity over time (pharmacokinetic assessment) and calculating the absorbed dose using the physical characteristics of the radionuclide and implementing radiation transport in patient's tissues. Currently, there are no standardised procedures to perform clinical dosimetry. In addition, the assessment of the uncertainties associated with the dosimetry procedure is not trivial. The DosiTest project (http://www.dositest.org/) was initiated to evaluate uncertainties associated with each of the steps of the clinical dosimetry workflow, via a multicentric inter-comparison based on Monte Carlo (MC) modelling. The first phase of the thesis compared dosimetry analysis performed by various centres using the same software and protocol on the same patient dataset as a part of IAEA-CRP E23005 project in order to appraise the precision of clinical dosimetry. To our knowledge, this is the first time that a multi-centric dosimetry comparison of a single clinical patient dataset has been undertaken using the same protocol and software by many centres worldwide. It highlighted the critical need to establish checkpoints and conduct sanity checks to eliminate significant disparities among results, and distinguish erroneous practice with acceptable inter-operator variability. A significant outcome of this work was the lack of quality assurance in clinical nuclear medicine dosimetry and the need for the development of quality control procedures. While dosimetry is gaining popularity in nuclear medicine, best practices should be adopted to ensure that results are reliable, traceable, and reproducible. It also brings forward the need to deliver sufficient training after the acquisition of the relatively new software packages beyond a couple of days. This is clearly insufficient in a context of an emerging field where the professional experience is quite often lacking. Next, the study of clinical dosimetry accuracy requires generating test datasets, to define the ground truth against which clinical dosimetry procedures can be benchmarked. The second section of the thesis addressed the simulation of three-dimensional scintigraphic SPECT imaging by implementing auto-contouring detector motion in the GATE Monte Carlo toolkit. Following the validation of SPECT/CT projections on anthropomorphic models, a series of realistic clinical patient images were generated. The last part of the thesis established the proof of concept of the DosiTest project, using a virtual (simulated) SPECT/CT dataset at various time points, with various gamma cameras, enabling comparison of various dosimetric techniques and to assess the clinical feasibility of the project in selected nuclear medicine departments