An Adaptive Algorithm to Identify Ambiguous Prostate Capsule Boundary Lines for Three-Dimensional Reconstruction and Quantitation

Currently there are few parameters that are used to compare the efficiency of different methods of cancerous prostate surgical removal. An accurate assessment of the percentage and depth of extra-capsular soft tissue removed with the prostate by the various surgical techniques can help surgeons determine the appropriateness of surgical approaches. Additionally, an objective assessment can allow a particular surgeon to compare individual performance against a standard. In order to facilitate 3D reconstruction and objective analysis and thus provide more accurate quantitation results when analyzing specimens, it is essential to automatically identify the capsule line that separates the prostate gland tissue from its extra-capsular tissue. However the prostate capsule is sometimes unrecognizable due to the naturally occurring intrusion of muscle and connective tissue into the prostate gland. At these regions where the capsule disappears, its contour can be arbitrarily reconstructed by drawing a continuing contour line based on the natural shape of the prostate gland. Presented here is a mathematical model that can be used in deciding the missing part of the capsule. This model approximates the missing parts of the capsule where it disappears to a standard shape by using a Generalized Hough Transform (GHT) approach to detect the prostate capsule. We also present an algorithm based on a least squares curve fitting technique that uses a prostate shape equation to merge previously detected capsule parts with the curve equation to produce an approximated curve that represents the prostate capsule. We have tested our algorithms using three shapes on 13 prostate slices that are cut at different locations from the apex and the results are promisin

Development of transcriptional amplification systems to target and characterize cancer cells based on gene expression altered during prostate cancer development and treatment

Le cancer de la prostate (CaP) est le cancer dont l’incidence augmente le plus vite parmi les hommes. Selon la Société Canadienne du Cancer, en 2015, 24 000 nouveaux cas de cancer de la prostate seront diagnostiqués et 4 100 patients en décèderont. Bien que des techniques cliniques pour la détection, le diagnostique et le traitement du CaP soient disponibles et importantes dans le traitement actuel de la maladie, elles sont cependant limitées. L’exploitation de plusieurs promoteurs dont l’activité est altérée au cours du développement du cancer est un moyen pour surmonter ces limitations. L’ARN non codant PCA3 est un biomarqueur unique du CaP qui a été largement étudié et dont l’expression est 60 fois plus forte dans les cellules de CaP que dans les cellules bégnines de prostate. Le gène de l’APS (PSEBC) est un marqueur important en clinique, il reflète la réponse au traitement par privation androgénique. Ces études ont pour objectif de développer des systèmes d’amplification transcriptionnel avec les promoteurs PCA3 et PSEBC pour non seulement cibler mais aussi caractériser les cellules cancéreuses de prostate lors de la progression de la maladie. Nous avons générés plusieurs systèmes dans des adénovirus contenant différentes constructions avec le promoteur proximal PCA3 de 152 pb, le système d’amplification TSTA et le gène rapporteur de la luciférase. Nous avons testé leur spécificité pour les cellules du CaP par infection transitoire. Nous avons amélioré le système TSTA et généré le PCA3-3STA. Nous avons ensuite intégré le promoteur PCA3 avec le promoteur PSA pour générer un autre nouveau système d’amplification transcriptionnelle qui se nomme le système «Multiple Promoter Integrated Transcriptional Amplification (MP-ITSTA)». Ces systèmes ont ensuite été exploités avec un microscope à bioluminescence pour cibler des cellules de CaP provenant de biopsies liquides de patients. Dans le chapitre deux, nous avons montré que l’activité de PCA3-3STA était hautement spécifique pour les cellules de CaP. Son activité était de 98,7 à 108 fois plus fortes dans les cellules de CaP que dans les cellules primaires bégnines de prostate ou dans les cellules cancéreuses nonprostatiques. Dans des modèles murins de xénogreffes de lignées cellulaires de CaP, nous avons montré que PCA3-3STA pouvait imager de manière très sensible l’activité du promoteur PCA3. De plus, sur des modèles de cultures primaires de biopsies, nous avons montré que le système PCA3-3STA ciblait spécifiquement les cellules épithéliales de CaP sans affecter les cellules stromales. Dans le chapitre trois, nous avons ensuite développé une technique en combinat la microscopie à bioluminescence avec le système TSTA et le promoteur PSA pour cibler les cellules de CaP purifiées de sang de patients et évaluer, cellule par cellule, l’hétérogénéité de leur réponse aux anti-androgènes. Cette technique a aussi montré que la microscopie à bioluminescence est hautement quantitative et a la capacité de détecter les changements moléculaires à l’échelle de la cellule. Le quatrième chapitre présente le système MP-ITSTA. Le système intègre l’activation combinée de deux promoteurs qui contrôlent l’expression d’un seul gène rapporteur. La combinaison du promoteur PCA3 avec celui de l’APS permet d’évaluer, cellule par cellule, la réponse aux anti-androgènes de cellules de CaP prélevés à partir d’urine de patients. C’est pourquoi, les systèmes PCA3-3STA et MP-ITSTA sont des systèmes d’expression spécifiques au cancer de la prostate avec le potentiel de cibler et détecter avec précision les cellules épithéliales de CaP ainsi que leur réponse aux traitements thérapeutiques in vivo et ex vivo. Ces systèmes peuvent jouer un rôle important pour l’imagerie moléculaire, l’immunothérapie et la thérapie génique.Development Of Transcriptional Amplification Systems To Target and Interrogate Cancer Cells Based On Gene Expression Altered During Cancer Development and Treatment Prostate cancer (PCa) is the fastest rising cancer among the males. According to the Canadian Cancer Society in 2015 it was estimated that 24 000 new cases will be diagnosed with prostate cancer and 4100 patients will die from the disease. Although already available clinical techniques for the detection, prognosis and treatment of PCa play an important role in decision making, they are limited in terms of the ability of detecting PCa cells, prognosis and increasing over all survival of patients. Exploitation of several gene promoters altered during cancer development act as important tool to overcome these limitations. PCA3 noncoding long RNA is a unique PCa biomarker that has been widely studied for its sixty-fold overexpression in PCa cells, compared to benign prostate cells. PSA (PSEBC) gene is of high clinical significance as it can give an account of response to androgen deprivation treatments. These studies aim to develop Transcriptional Amplification Systems that can target as well as characterise cancer cells during disease progression using PCA3 and PSA gene promoters. Various adenovirus constructs incorporating the proximal 152 bp PCA3 promoter, the TSTA system and the Firefly luciferase reporter gene were generated and the specificity of the promoter was tested in PCa cells by transient infection. We have improved the TSTA system and generated the (PCA3-3STA). We further integrated the PCA3 promoter along with the PSA promoter to generate a new transcriptional amplification system that we named the Multiple Promoter Integrated Transcriptional Amplification (MP-ITSTA) system. These systems were further applied to target PCa cells from body fluids of patients using bioluminescence microscopy. In chapter two we show that PCA3-3STA activity was highly specific for PCa cells, ranging between 98.7 and 108.0-fold higher, respectively, than that for benign prostate or non-PCa cells. In PCa cell line mouse xenografts, PCA3-3STA was shown to image PCA3 promoter activity with high sensitivity. Moreover, when primary PCa biopsies were infected with PCA3-3STA, it managed to image PCa epithelial cells but not stromal cells. In chapter three we further developed a bioluminescence microscopy technique using the TSTA system with PSA promoter to target PCa cells from blood of patients and assess heterogeneous single cell response to antiandrogens. This technique also shows that bioluminescence microscopy is highly quantitative and has the ability to detect molecular changes at the cellular level. The fourth chapter presents the MP-ITSTA system. This system integrates the combined activation of two promoters giving a single reporter gene expression. PCA3 when combined with the PSA promoter could assess single cell response to antiandrogens in cells isolated from urine of patients. Hence, PCA3-3STA and MP-ITSTA utilizing the bioluminescence microscopy represent a prostate- and PCa-specific expression systems with the potential to target, with high accuracy, PCa epithelial cells, assess their response to therapy in vivo and ex vivo. This can play an important role for imaging, immunotherapy, or gene therapy

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

Advancements and Breakthroughs in Ultrasound Imaging

Ultrasonic imaging is a powerful diagnostic tool available to medical practitioners, engineers and researchers today. Due to the relative safety, and the non-invasive nature, ultrasonic imaging has become one of the most rapidly advancing technologies. These rapid advances are directly related to the parallel advancements in electronics, computing, and transducer technology together with sophisticated signal processing techniques. This book focuses on state of the art developments in ultrasonic imaging applications and underlying technologies presented by leading practitioners and researchers from many parts of the world

Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases

Cardiothoracic and pulmonary diseases are a significant cause of mortality and morbidity worldwide. The COVID-19 pandemic has highlighted the lack of access to clinical care, the overburdened medical system, and the potential of artificial intelligence (AI) in improving medicine. There are a variety of diseases affecting the cardiopulmonary system including lung cancers, heart disease, tuberculosis (TB), etc., in addition to COVID-19-related diseases. Screening, diagnosis, and management of cardiopulmonary diseases has become difficult owing to the limited availability of diagnostic tools and experts, particularly in resource-limited regions. Early screening, accurate diagnosis and staging of these diseases could play a crucial role in treatment and care, and potentially aid in reducing mortality. Radiographic imaging methods such as computed tomography (CT), chest X-rays (CXRs), and echo ultrasound (US) are widely used in screening and diagnosis. Research on using image-based AI and machine learning (ML) methods can help in rapid assessment, serve as surrogates for expert assessment, and reduce variability in human performance. In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases. We hope that these articles will help establish the advancements in AI

Caracterização de patologias da pele por ultrassons

A pele constitui a primeira barreira física que o corpo humano dispõe para proteção, sendo importante manter as suas características. Para a sua avaliação e diagnóstico, a técnica por ultrassons, nomeadamente a ecografia, apresenta-se como uma abordagem com utilização crescente devido ao seu carácter não invasivo, não ionizante e acessível (baixo custo), quando comparado com outras técnicas de imagiologia. O principal objetivo da presente dissertação consiste no desenvolvimento de três abordagens com vista à caracterização da pele, usando tecnologia por ultrassons. Para tal foram usadas imagens ecográficas de doentes assim como imagens obtidas a partir de fantomas criados no Laboratório de Tecnologia de Materiais Elétricos e Ultrassons, do Departamento de Engenharia Electrotécnica e de Computadores, da Faculdade de Ciências e Tecnologia da Universidade de Coimbra. Duas dessas abordagens permitem a caracterização completamente automática de imagens de forma global ou recorrendo a características texturais da imagem, eliminando possíveis ambiguidades resultantes do processo de interação com utilizadores. A metodologia desenvolvida inclui mais de 400 características texturais, 5 classificadores, seletores de características e um algoritmo de fusão de classificadores. A terceira abordagem permite a classificação de imagens de fantomas a partir do uso de apenas três parâmetros acústicos, revelando a possibilidade de desenvolvimento de técnicas de caracterização, recorrendo apenas a parâmetros acústicos, tornando a técnica ainda mais acessível. O trabalho desenvolvido mostrou que os ultrassons podem ser utilizados para distinguir pele com lesão de pele sem lesão. Utilizando características texturais das imagens é possível obter um valor F-score igual a 96,3% para imagens de pele. Mostrou-se ainda, que a utilização de apenas três parâmetros acústicos extraídos dos fantomas permite a sua classificação com um F-score igual a 89,1%. Palavras-Chave: Ultrassons, Fantomas, Parâmetros Acústicos, Processamento de Imagem Médica, Algoritmos de Classificaçã