Speckle Detection in Ultrasonic Images Using Unsupervised Clustering Techniques

Research for the improvement of the quality of clinical ultrasound images has been a topic of interest for researchers and physicians. One of the challenges is the presence of speckle artifacts. This dissertation reviews the speckle phenomena in such images, and develops algorithms to better identify this artifact in sonographic images. Speckle artifact is categorized into two groups: partially developed speckles and fully developed speckles (FDS). This concept has been used, along with the classification techniques, to segment the ultrasound images into patches and classify the patches in the image as FDS or non-FDS. The proposed algorithms and the results of the experiments have been validated using simulation, phantom and real data that were created for the purposes of this study or taken from other research groups. Current speckle detection methods do not optimize statistical features and they are not based on machine learning techniques. For the first time this work introduces a novel method for searching and extracting the best features for optimizing speckle detection rate using statistical machine learning and ensemble classification. Potential applications include strain imaging by tracking speckle displacement, elastography, speckle tracking and suppression applications, and needle-tracking applications.Ph.D., Biomedical Engineering -- Drexel University, 201

Genetic Profiling in Soft Tissue Sarcoma

Soft tissue sarcomas (STS) are a heterogeneous group of highly malignant mesenchymal tumors that account for ~1% of all malignancies. Frequent heterogeneity and pleomorphism along with suboptimal diagnostic reproducibility and insufficient prognostic markers make clinical management of these tumors difficult. This thesis has applied microarray-based gene expression and copy-number profiling to STS. The studies provide clues to the genetic pathways involved in STS development and identify profiles linked to diagnosis and prognosis. The results from Study I that concerns intratumor versus intertumor heterogeneity of gene expression profiles in malignant fibrous histiocytoma (MFH) and leiomyosarcoma (LMS), suggest that intratumor heterogeneity may be particularly relevant in small tumor series and thus serve as a reminder to run larger sample sets for increased reliability. Study II established expression patterns related to the SS18-SSX fusion variants and metastatic potential in synovial sarcoma (SS). The differential expression of various developmental genes, transcription factors, histones, and metallothioneins suggests that the gene fusion variants have distinct downstream effects. In Study III, 177 STS of mixed histopathological subtypes were profiled using cDNA microarrays. Distinct gene expression patterns were identified in subtypes with specific translocations or mutations. Herein, frequent upregulation of developmental genes, from e.g. the Wingless and Hedgehog signaling pathways, was demonstrated. The more pleomorphic STS showed overexpression of genes involved in proliferation, adhesion, motility and protein degradation. Moreover, a prognostic signature partly characterized by hypoxia-related genes was identified within the pleomorphic STS. Study IV applied array-based comparative genomic hybridization in MFH and LMS, and demonstrated extensive genetic complexity with multiple recurrent gains and losses, novel amplifications and homozygous deletions. Losses in chromosomal regions 6q14 and 7q36 provided prognostic information independent of previously established risk factors. In summary, these studies demonstrate the potential of genetic profiling in STS and herein, define intratumor heterogeneity, demonstrate that gene fusion variants in SS yield different downstream effects, identify diagnostic and prognostic subsets within STS, and in the pleomorphic tumors, discern prognostically important alterations within the plethora of genetic aberrations that characterize many STS

Quantification of tumour heterogenity in MRI

Cancer is the leading cause of death that touches us all, either directly or indirectly. It is estimated that the number of newly diagnosed cases in the Netherlands will increase to 123,000 by the year 2020. General Dutch statistics are similar to those in the UK, i.e. over the last ten years, the age-standardised incidence rate1 has stabilised at around 355 females and 415 males per 100,000. Figure 1 shows the cancer incidence per gender. In the UK, the rise in lifetime risk of cancer is more than one in three and depends on many factors, including age, lifestyle and genetic makeup

Knee cartilage segmentation using multi purpose interactive approach

Interactive model incorporates expert interpretation and automated segmentation. However, cartilage has complicated structure, indistinctive tissue contrast in magnetic resonance image of knee hardens image review and existing interactive methods are sensitive to various technical problems such as bi-label segmentation problem, shortcut problem and sensitive to image noise. Moreover, redundancy issue caused by non-cartilage labelling has never been tackled. Therefore, Bi-Bezier Curve Contrast Enhancement is developed to improve visual quality of magnetic resonance image by considering brightness preservation and contrast enhancement control. Then, Multipurpose Interactive Tool is developed to handle users’ interaction through Label Insertion Point approach. Approximate NonCartilage Labelling system is developed to generate computerized non-cartilage label, while preserves cartilage for expert labelling. Both computerized and interactive labels initialize Random Walks based segmentation model. To evaluate contrast enhancement techniques, Measure of Enhancement (EME), Absolute Mean Brightness Error (AMBE) and Feature Similarity Index (FSIM) are used. The results suggest that Bi-Bezier Curve Contrast Enhancement outperforms existing methods in terms of contrast enhancement control (EME = 41.44±1.06), brightness distortion (AMBE = 14.02±1.29) and image quality (FSIM = 0.92±0.02). Besides, implementation of Approximate Non-Cartilage Labelling model has demonstrated significant efficiency improvement in segmenting normal cartilage (61s±8s, P = 3.52 x 10-5) and diseased cartilage (56s±16s, P = 1.4 x 10-4). Finally, the proposed labelling model has high Dice values (Normal: 0.94±0.022, P = 1.03 x 10-9; Abnormal: 0.92±0.051, P = 4.94 x 10-6) and is found to be beneficial to interactive model (+0.12)

Echocardiography

The book "Echocardiography - New Techniques" brings worldwide contributions from highly acclaimed clinical and imaging science investigators, and representatives from academic medical centers. Each chapter is designed and written to be accessible to those with a basic knowledge of echocardiography. Additionally, the chapters are meant to be stimulating and educational to the experts and investigators in the field of echocardiography. This book is aimed primarily at cardiology fellows on their basic echocardiography rotation, fellows in general internal medicine, radiology and emergency medicine, and experts in the arena of echocardiography. Over the last few decades, the rate of technological advancements has developed dramatically, resulting in new techniques and improved echocardiographic imaging. The authors of this book focused on presenting the most advanced techniques useful in today's research and in daily clinical practice. These advanced techniques are utilized in the detection of different cardiac pathologies in patients, in contributing to their clinical decision, as well as follow-up and outcome predictions. In addition to the advanced techniques covered, this book expounds upon several special pathologies with respect to the functions of echocardiography

Current Frontiers and Perspectives in Cell Biology

A numerous internationally renowned authors in the pages of this book present the views of the fields of cell biology and their own research results or review of current knowledge. Chapters are divided into five sections that are dedicated to cell structures and functions, genetic material, regulatory mechanisms, cellular biomedicine and new methods in cell biology. Multidisciplinary and often quite versatile approach by many authors have imposed restrictions of this classification, so it is certain that many chapters could belong to the other sections of this book. The current frontiers, on the manner in which they described in the book, can be a good inspiration to many readers for further improving, and perspectives which are highlighted can be seen in many areas of fundamental biology, biomedicine, biotechnology and other applications of knowledge of cell biology. The book will be very useful for beginners to gain insight into new area, as well as experts to find new facts and expanding horizons

Characterisation of the Tumour Microenvironment in Ovarian Cancer

The tumour microenvironment comprises the non-cancerous cells present in the tumour mass (fibroblasts, endothelial, and immune cells), as well as signalling molecules and extracellular matrix. Tumour growth, invasion, metastasis, and response to therapy are influenced by the tumour microenvironment. Therefore, characterising the cellular and molecular components of the tumour microenvironment, and understanding how they influence tumour progression, represent a crucial aim for the success of cancer therapies. High-grade serous ovarian cancer provides an excellent opportunity to systematically study the tumour microenvironment due to its clinical presentation of advanced disseminated disease and debulking surgery being standard of care. This thesis first presents a case report of a long-term survivor (>10 years) of metastatic high-grade serous ovarian cancer who exhibited concomitant regression/progression of the metastatic lesions (5 samples). We found that progressing metastases were characterized by immune cell exclusion, whereas regressing metastases were infiltrated by CD8+ and CD4+ T cells. Through a T cell - neoepitope challenge assay we demonstrated that pre- dicted neoepitopes were recognised by the CD8+ T cells obtained from blood drawn from the patient, suggesting that regressing tumours were subjected to immune attack. Immune excluded tumours presented a higher expression of immunosuppressive Wnt signalling, while infiltrated tumours showed a higher expression of the T cell chemoattractant CXCL9 and evidence of immunoediting. These findings suggest that multiple distinct tumour immune microenvironments can co-exist within a single individual and may explain in part the hetero- geneous fates of metastatic lesions often observed in the clinic post-therapy. Second, this thesis explores the prevalence of intra-patient tumour microenvironment het- erogeneity in high-grade serous ovarian cancer at diagnosis (38 samples from 8 patients), as well as the effect of chemotherapy on the tumour microenvironment (80 paired samples from 40 patients). Whole transcriptome analysis and image-based quantification of T cells from treatment-naive tumours revealed highly prevalent variability in immune signalling and distinct immune microenvironments co-existing within the same individuals at diagnosis. ConsensusTME, a method that generates consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods that predict immune cell populations using bulk RNA data was developed. ConsensusTME improved accuracy and sensitivity of T cell and leukocyte deconvolutions in ovarian cancer samples. As previously observed in the case report, Wnt signalling expression positively correlated with immune cell exclusion. To evaluate the effect of chemotherapy on the tumour microenvironment, we compared site-matched and site-unmatched tumours before and after neoadjuvant chemotherapy. Site- matched samples showed increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, unlike site-unmatched samples where heterogeneity could not be accounted for. In addition, low levels of immune activation pre-chemotherapy were found to be correlated with immune activation upon chemotherapy treatment. These results cor- roborate that the tumour-immune interface in advanced high-grade serous ovarian cancer is intrinsically heterogeneous, and that chemotherapy induces an immunogenic effect mediated by cytotoxic cells. Finally, the different deconvolution methods were benchmarked along with ConsensusTME in a pan-cancer setting by comparing deconvolution scores to DNA-based purity scores, leukocyte methylation data, and tumour infiltrating lymphocyte counts from image analysis. In so far as it has been benchmarked, unlike the other methods, ConsensusTME performs consistently among the top three methods across cancer-related benchmarks. Additionally, ConsensusTME provides a dynamic and evolvable framework that can integrate newer de- convolution tools and benchmark their performance against itself, thus generating an ever updated version. Overall, this thesis presents a systematic characterisation of the tumour microenvironment of high grade serous ovarian cancer in treatment-naive and chemotherapy treated samples, and puts forward the development of an integrative computational method for the systematic analysis of the tumour microenvironment of different tumour types using bulk RNA data.Cancer Research UK Cambridge Institute provided funding for my studentship. The Mexican National Council of Science and Technology provided funding for my studentship

Therapeutic Monoclonal Antibodies and Antibody Products, Their Optimization and Drug Design in Cancers

The book broadly deals with therapeutic monoclonal antibodies (mAbs) and various relevant topics, including different antibody formats such as Antibody–Drug Conjugates (ADC), bispecifics, nanoparticle-based mAbs and HER2+ cancers, immune checkpoint inhibitors and other closely related topics. Each paper was written by leading active research groups in their fields both from academia and industry. The book should be of interest to those scientists and researchers who develop or use biologics, biotherapeutics, biosimilars and biobetters in cancer treatment