Cost of illness in benign prostatic hyperplasia: A review

The paper provides a systematic review on the cost-of-illness studies in an age-associated condition with high prevalence, benign prostatic hyperplasia (BPH), published in Medline between 2005 and 2015. Overall 11 studies were included, which were conducted in 8 countries. In the US, the annual direct medical costs per patient ranged from $255 to $5,729, while in Europe from €253 to €1,251. In 2008, in the UK total annual direct medical costs of BPH were £180.8 million at national level. In the US, overall costs of BPH management in the private sector were estimated at $3.9 billion annually, of which $500 million was attributable to productivity loss (year 1999). Due to demographic factors and possible surgical innovations in the field of urology, the costs of BPH are likely to increase in the future. Over the next decade the age of retirement is projected to rise, consequently, the indirect costs related to aging-associated conditions such as BPH are expected to soar. To promote the transparent and cost-effective management of BPH, development of rational clinical guidelines would be essential that may lead to significant improvement in quality of care as well as reduction in healthcare expenditure.

Motion correction algorithm of lung tumors for respiratory gated PET images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

The potential role of environmental exposures and genomic signaling in development of central nervous system tumors

The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.

Reduced Androgen Receptor Expression Accelerates the Onset of ERBB2 Induced Breast Tumors in Female Mice

Androgen receptor (AR) is commonly expressed in both the epithelium of normal mammary glands and in breast cancers. AR expression in breast cancers is independent of estrogen receptor alpha (ERα) status and is frequently associated with overexpression of the ERBB2 oncogene. AR signaling effects on breast cancer progression may depend on ERα and ERBB2 status. Up to 30% of human breast cancers are driven by overactive ERBB2 signaling and it is not clear whether AR expression affects any steps of tumor progression in this cohort of patients. To test this, we generated mammary specific Ar depleted mice (MARKO) by combining the floxed allele of Ar with the MMTV-cre transgene on an MMTV-NeuNT background and compared them to littermate MMTV-NeuNT, Arfl/+ control females. Heterozygous MARKO females displayed reduced levels of AR in mammary glands with mosaic AR expression in ductal epithelium. The loss of AR dramatically accelerated the onset of MMTV-NeuNT tumors in female MARKO mice. In this report we show that accelerated MMTV-NeuNT-dependent tumorigenesis is due specifically to the loss of AR, as hormonal levels, estrogen and progesterone receptors expression, and MMTV-NeuNT expression were similar between MARKO and control groups. MMTV-NeuNT induced tumors in both cohorts displayed distinct loss of AR in addition to ERα, PR, and the pioneer factor FOXA1. Erbb3 mRNA levels were significantly elevated in tumors in comparison to normal mammary glands. Thus the loss of AR in mouse mammary epithelium accelerates malignant transformation rather than the rate of tumorigenesis.

Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

Análise da imunoexpressão de Oct- 4 e C44 em lesões odontogênicas epiteliais benignas

benign epithelial odontogenic lesions are great clinical importance entities that develop in the jaws from the tissues that form teeth. It has been shown that in benign and malignant tumors, are present in a large number of tumor stem cells, which has great implications in the development of these lesions. Oct-4 and CD44 have been demos as important markers for tumoral stem cells. The objective of this study was to identify epithelial cells expressing stem cell markers by immunohistochemical expression of Oct-4 and CD44 in a series of cases of benign epithelial odontogenic lesions. The sample was comprised of 20 cases of odontogenic keratocyst (OKC), 20 cases of solid/multicystic ameloblastoma and 20 cases of adenomatoid odontogenic tumor (AOT). The expression of Oct-4 and CD44 was evaluated in epithelial lesions using the percentage of positive cells (PP) and the intensity of expression (IE), being realized the sum of these scores, resulting in Total Immunostaining Score (TIS) ranging 0 to 7. The results were submitted to the appropriate statistical test (nonparametric Kruskal-Wallis and Spearman correlation coefficient). All cases were positive for both markers and most showed high expression of both markers. The analysis of Oct-4 expression revealed no statistically significant differences (p = 0.406) among the studied lesions. Regarding the CD44 expression, there was a statistically significant difference between the cases of ameloblastoma and TOA in relation to the CCO, with the latter show more cases in the score 7 (p = 0.034). In the correlation analysis of the immunoreactivity of both markers in the three lesions studied, there was no statistically significant correlation. The results of this study identified the presence of cells with stemness characteristics arranged at various sites in the epithelial component of the studied lesions suggesting their possible role in the histogenesis and differentiation in benign epithelial odontogenic lesions, thus contributing to the development of these lesions.

Análise da imunoexpressão de Oct- 4 e C44 em lesões odontogênicas epiteliais benignas

benign epithelial odontogenic lesions are great clinical importance entities that develop in the jaws from the tissues that form teeth. It has been shown that in benign and malignant tumors, are present in a large number of tumor stem cells, which has great implications in the development of these lesions. Oct-4 and CD44 have been demos as important markers for tumoral stem cells. The objective of this study was to identify epithelial cells expressing stem cell markers by immunohistochemical expression of Oct-4 and CD44 in a series of cases of benign epithelial odontogenic lesions. The sample was comprised of 20 cases of odontogenic keratocyst (OKC), 20 cases of solid/multicystic ameloblastoma and 20 cases of adenomatoid odontogenic tumor (AOT). The expression of Oct-4 and CD44 was evaluated in epithelial lesions using the percentage of positive cells (PP) and the intensity of expression (IE), being realized the sum of these scores, resulting in Total Immunostaining Score (TIS) ranging 0 to 7. The results were submitted to the appropriate statistical test (nonparametric Kruskal-Wallis and Spearman correlation coefficient). All cases were positive for both markers and most showed high expression of both markers. The analysis of Oct-4 expression revealed no statistically significant differences (p = 0.406) among the studied lesions. Regarding the CD44 expression, there was a statistically significant difference between the cases of ameloblastoma and TOA in relation to the CCO, with the latter show more cases in the score 7 (p = 0.034). In the correlation analysis of the immunoreactivity of both markers in the three lesions studied, there was no statistically significant correlation. The results of this study identified the presence of cells with stemness characteristics arranged at various sites in the epithelial component of the studied lesions suggesting their possible role in the histogenesis and differentiation in benign epithelial odontogenic lesions, thus contributing to the development of these lesions.

Classificação de nódulos pulmonares em imagens tomográficas utilizando redes neurais artificiais em cascata

Lung cancer is the most common of malignant tumors, with 1.59 million new cases worldwide in 2012. Early detection is the main factor to determine the survival of patients affected by this disease. Furthermore, the correct classification is important to define the most appropriate therapeutic approach as well as suggest the prognosis and the clinical disease evolution. Among the exams used to detect lung cancer, computed tomography have been the most indicated. However, CT images are naturally complex and even experts medical are subject to fault detection or classification. In order to assist the detection of malignant tumors, computer-aided diagnosis systems have been developed to aid reduce the amount of false positives biopsies. In this work it was developed an automatic classification system of pulmonary nodules on CT images by using Artificial Neural Networks. Morphological, texture and intensity attributes were extracted from lung nodules cut tomographic images using elliptical regions of interest that they were subsequently segmented by Otsu method. These features were selected through statistical tests that compare populations (T test of Student and U test of Mann-Whitney); from which it originated a ranking. The features after selected, were inserted in Artificial Neural Networks (backpropagation) to compose two types of classification; one to classify nodules in malignant and benign (network 1); and another to classify two types of malignancies (network 2); featuring a cascade classifier. The best networks were associated and its performance was measured by the area under the ROC curve, where the network 1 and network 2 achieved performance equal to 0.901 and 0.892 respectively.

Effects of photodynamic therapy with topical and systemic aminolevulinic acid on ultraviolet induced tumors in hairless mice

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Development and characterization of long-circulating emulsions to target solid tumors

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Development of a novel approach for brain delivery : dendritic nanocarriers for the enhanced delivery of methotrexate to the brain tumors

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Source localization of reaction-diffusion models for brain tumors

We propose a mathematically well-founded approach for locating the source (initial state) of density functions evolved within a nonlinear reaction-diffusion model. The reconstruction of the initial source is an ill-posed inverse problem since the solution is highly unstable with respect to measurement noise. To address this instability problem, we introduce a regularization procedure based on the nonlinear Landweber method for the stable determination of the source location. This amounts to solving a sequence of well-posed forward reaction-diffusion problems. The developed framework is general, and as a special instance we consider the problem of source localization of brain tumors. We show numerically that the source of the initial densities of tumor cells are reconstructed well on both imaging data consisting of simple and complex geometric structures.

Tissue Equivalent Phantom Design for Optimization of a Coherent Scatter Imaging System

Scatter in medical imaging is typically cast off as image-related noise that detracts from meaningful diagnosis. It is therefore typically rejected or removed from medical images. However, it has been found that every material, including cancerous tissue, has a unique X-ray coherent scatter signature that can be used to identify the material or tissue. Such scatter-based tissue-identification provides the advantage of locating and identifying particular materials over conventional anatomical imaging through X-ray radiography. A coded aperture X-ray coherent scatter spectral imaging system has been developed in our group to classify different tissue types based on their unique scatter signatures. Previous experiments using our prototype have demonstrated that the depth-resolved coherent scatter spectral imaging system (CACSSI) can discriminate healthy and cancerous tissue present in the path of a non-destructive x-ray beam. A key to the successful optimization of CACSSI as a clinical imaging method is to obtain anatomically accurate phantoms of the human body. This thesis describes the development and fabrication of 3D printed anatomical scatter phantoms of the breast and lung.

The purpose of this work is to accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Tissue-equivalent anatomical phantoms were designed to assess the capability of the CACSSI system to classify different types of breast tissue (adipose, fibroglandular, malignant). These phantoms were 3D printed based on DICOM data obtained from CT scans of prone breasts. The phantoms were tested through comparison of measured scatter signatures with those of adipose and fibroglandular tissue from literature. Tumors in the phantom were modeled using a variety of biological tissue including actual surgically excised benign and malignant tissue specimens. Lung based phantoms have also been printed for future testing. Our imaging system has been able to define the location and composition of the various materials in the phantom. These phantoms were used to characterize the CACSSI system in terms of beam width and imaging technique. The result of this work showed accurate modeling and characterization of the phantoms through comparison of the tissue-equivalent form factors to those from literature. The physical construction of the phantoms, based on actual patient anatomy, was validated using mammography and computed tomography to visually compare the clinical images to those of actual patient anatomy.

Effects of photodynamic therapy with topical and systemic aminolevulinic acid on ultraviolet induced tumors in hairless mice

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Development and characterization of long-circulating emulsions to target solid tumors

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.