Development of computer-based algorithms for unsupervised assessment of radiotherapy contouring

INTRODUCTION: Despite the advances in radiotherapy treatment delivery, target volume delineation remains one of the greatest sources of error in the radiotherapy delivery process, which can lead to poor tumour control probability and impact clinical outcome. Contouring assessments are performed to ensure high quality of target volume definition in clinical trials but this can be subjective and labour-intensive. This project addresses the hypothesis that computational segmentation techniques, with a given prior, can be used to develop an image-based tumour delineation process for contour assessments. This thesis focuses on the exploration of the segmentation techniques to develop an automated method for generating reference delineations in the setting of advanced lung cancer. The novelty of this project is in the use of the initial clinician outline as a prior for image segmentation. METHODS: Automated segmentation processes were developed for stage II and III non-small cell lung cancer using the IDEAL-CRT clinical trial dataset. Marker-controlled watershed segmentation, two active contour approaches (edge- and region-based) and graph-cut applied on superpixels were explored. k-nearest neighbour (k-NN) classification of tumour from normal tissues based on texture features was also investigated. RESULTS: 63 cases were used for development and training. Segmentation and classification performance were evaluated on an independent test set of 16 cases. Edge-based active contour segmentation achieved highest Dice similarity coefficient of 0.80 ± 0.06, followed by graphcut at 0.76 ± 0.06, watershed at 0.72 ± 0.08 and region-based active contour at 0.71 ± 0.07, with mean computational times of 192 ± 102 sec, 834 ± 438 sec, 21 ± 5 sec and 45 ± 18 sec per case respectively. Errors in accuracy of irregularly shaped lesions and segmentation leakages at the mediastinum were observed. In the distinction of tumour and non-tumour regions, misclassification errors of 14.5% and 15.5% were achieved using 16- and 8-pixel regions of interest (ROIs) respectively. Higher misclassification errors of 24.7% and 26.9% for 16- and 8-pixel ROIs were obtained in the analysis of the tumour boundary. CONCLUSIONS: Conventional image-based segmentation techniques with the application of priors are useful in automatic segmentation of tumours, although further developments are required to improve their performance. Texture classification can be useful in distinguishing tumour from non-tumour tissue, but the segmentation task at the tumour boundary is more difficult. Future work with deep-learning segmentation approaches need to be explored.Funded by National Radiotherapy Trials Quality Assurance (RTTQA) grou

Advanced Computational Methods for Oncological Image Analysis

[Cancer is the second most common cause of death worldwide and encompasses highly variable clinical and biological scenarios. Some of the current clinical challenges are (i) early diagnosis of the disease and (ii) precision medicine, which allows for treatments targeted to specific clinical cases. The ultimate goal is to optimize the clinical workflow by combining accurate diagnosis with the most suitable therapies. Toward this, large-scale machine learning research can define associations among clinical, imaging, and multi-omics studies, making it possible to provide reliable diagnostic and prognostic biomarkers for precision oncology. Such reliable computer-assisted methods (i.e., artificial intelligence) together with clinicians’ unique knowledge can be used to properly handle typical issues in evaluation/quantification procedures (i.e., operator dependence and time-consuming tasks). These technical advances can significantly improve result repeatability in disease diagnosis and guide toward appropriate cancer care. Indeed, the need to apply machine learning and computational intelligence techniques has steadily increased to effectively perform image processing operations—such as segmentation, co-registration, classification, and dimensionality reduction—and multi-omics data integration.

[¹⁸F]fluorination of biorelevant arylboronic acid pinacol ester scaffolds synthesized by convergence techniques

Aim: The development of small molecules through convergent multicomponent reactions (MCR) has been boosted during the last decade due to the ability to synthesize, virtually without any side-products, numerous small drug-like molecules with several degrees of structural diversity.(1) The association of positron emission tomography (PET) labeling techniques in line with the “one-pot” development of biologically active compounds has the potential to become relevant not only for the evaluation and characterization of those MCR products through molecular imaging, but also to increase the library of radiotracers available. Therefore, since the [18F]fluorination of arylboronic acid pinacol ester derivatives tolerates electron-poor and electro-rich arenes and various functional groups,(2) the main goal of this research work was to achieve the 18F-radiolabeling of several different molecules synthesized through MCR. Materials and Methods: [18F]Fluorination of boronic acid pinacol esters was first extensively optimized using a benzaldehyde derivative in relation to the ideal amount of Cu(II) catalyst and precursor to be used, as well as the reaction solvent. Radiochemical conversion (RCC) yields were assessed by TLC-SG. The optimized radiolabeling conditions were subsequently applied to several structurally different MCR scaffolds comprising biologically relevant pharmacophores (e.g. β-lactam, morpholine, tetrazole, oxazole) that were synthesized to specifically contain a boronic acid pinacol ester group. Results: Radiolabeling with fluorine-18 was achieved with volumes (800 μl) and activities (≤ 2 GBq) compatible with most radiochemistry techniques and modules. In summary, an increase in the quantities of precursor or Cu(II) catalyst lead to higher conversion yields. An optimal amount of precursor (0.06 mmol) and Cu(OTf)2(py)4 (0.04 mmol) was defined for further reactions, with DMA being a preferential solvent over DMF. RCC yields from 15% to 76%, depending on the scaffold, were reproducibly achieved. Interestingly, it was noticed that the structure of the scaffolds, beyond the arylboronic acid, exerts some influence in the final RCC, with electron-withdrawing groups in the para position apparently enhancing the radiolabeling yield. Conclusion: The developed method with high RCC and reproducibility has the potential to be applied in line with MCR and also has a possibility to be incorporated in a later stage of this convergent “one-pot” synthesis strategy. Further studies are currently ongoing to apply this radiolabeling concept to fluorine-containing approved drugs whose boronic acid pinacol ester precursors can be synthesized through MCR (e.g. atorvastatin)

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

This two-volume set LNCS 12962 and 12963 constitutes the thoroughly refereed proceedings of the 7th International MICCAI Brainlesion Workshop, BrainLes 2021, as well as the RSNA-ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge, the Federated Tumor Segmentation (FeTS) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the challenge on Quantification of Uncertainties in Biomedical Image Quantification (QUBIQ). These were held jointly at the 23rd Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2020, in September 2021. The 91 revised papers presented in these volumes were selected form 151 submissions. Due to COVID-19 pandemic the conference was held virtually. This is an open access book

Spine Surgery

We are very excited to introduce this new book on spinal surgery, which follows the curriculum of the EUROSPINE basic and advanced diploma courses. The approach we take is a purely case-based one, in which each case illustrates the concepts surrounding the treatment of a given pathology, including the uncertainties and problems in decision-making. The readers will notice that in many instances a lack of evidence for a given treatment exists. So decisions taken are usually not a clearcut matter of black or white, but merely different shades of gray. Probably in a lot of cases, there is often more than one option to treat the patient. The authors were asked to convey this message to the reader, giving him a guidance as what would be accepted within the mainstream. In addition, the reader is provided with the most updated literature and evidence on the topic. Most of the authors are teachers in the courses of EUROSPINE or other national societies with often vast clinical experience and have given their own perspective and reasoning. We believe that the readers will profit very much from this variety and bandwidth of knowledge provided for them in the individual chapters. We have given the authors extensive liberty as to what they consider the best solution for their case. It is thus a representative picture of what is considered standard of care for spine pathologies in Europe. We hope that this book will be an ideal complement for trainees to the courses they take. Munich, Germany Bernhard Meyer Offenbach, Germany Michael Rauschman

Quality of life in patients receiving platinum based chemotherapy for advanced non-small cell lung cancer.

Quality of life in patients receiving platinum based chemotherapy for advanced non-small cell lung cancer. Lung cancer is the cause of 34,000 deaths in the UK each year, with a five year survival rate of only 7.5%. The current treatment for advanced Non Small Cell Lung Cancer is combination chemotherapy but this confers only a small survival advantage. Quality of Life is often proposed as a secondary outcome to most chemotherapy studies as chemotherapy remains palliative. Quality of life is measured using a series of tools, such as the EORTC QLQ 30 that although established and tested for validity are functionally based or focus on physical symptoms. The aim of this study is to explore the meaning of quality of life in this group of patients. The study utilises use comparative methods (interview n=50, QLQ EORTC 30 data, clinical observation/field notes, medical notes, nursing notes and mapping) to examine the meaning of quality of life in this patient group. This is essentially a collaboration of medical and nursing practice with the aim of understanding what quality of life means to these patients, improving the experience of patients undergoing treatment and offering appropriate psycho-social support. Content analysis has generated a core theme of patient experience as having an impact on quality of life (negotiation of the treatment calendar, value of treatment broker and interactions with professionals) the overlapping themes are Lens of diagnosis (viewed as atrocity stories), The worth of treatment (despite physical side effects and poor life expectancy, chemotherapy is a focus of hope and allows for adjustment to poor prognosis) and Suffering (psychological and social, for example exclusion from social activities and loss of independence). This study has impacted on the service to cancer patients at a central London NHS Foundation Trust

The huntingtin protein in Huntington disease

Huntingtin disease (HD) is an autosomal dominant inheritable disease that mainly affects the brain. HD is caused by expansion of a CAG repeat within exon 1 of the huntingtin gene giving rise to the expression of a mutant huntingtin protein with an elongated polyQ repeat at it's N-terminus. Mutant huntingtin is prone to aggregation and is believed to invoke toxicity, especially by the formation of N-terminal fragments. The first part of this thesis describes the selection and characterization of Llama VHH antibody fragments against N-terminal huntingtin. The second part of this thesis consists of studies on huntingtin in human (brain) tissue regarding N-terminal fragments, huntingtin aggregation and mutant versus wild-type huntingtin expression levels.Prinses Beatrix Fonds, BontiusstichtingLUMC / Geneeskunde Repositoriu

Current Issues and Recent Advances in Pacemaker Therapy

Patients with implanted pacemakers or defibrillators are frequently encountered in various healthcare settings. As these devices may be responsible for, or contribute to a variety of clinically significant issues, familiarity with their function and potential complications facilitates patient management. This book reviews several clinically relevant issues and recent advances of pacemaker therapy: implantation, device follow-up and management of complications. Innovations and research on the frontiers of this technology are also discussed as they may have wider utilization in the future. The book should provide useful information for clinicians involved in the management of patients with implanted antiarrhythmia devices and researchers working in the field of cardiac implants

EMERGING APPLICATIONS IN THE MEASUREMENT OF BODY COMPOSITION AND THEIR RELATIONSHIPS TO DISEASE RISK

Ph.D