FABIO JOSE AYRES

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  • Artigo Científico
    Detection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension, and texture analysis
    (2008) Rangayyan, Rangaraj M.; Prajna, Shormistha; FABIO JOSE AYRES; Desautels, J. E. Leo
    Objective Mammography is a widely used screening tool for the early detection of breast cancer. One of the commonly missed signs of breast cancer is architectural distortion. The purpose of this study is to explore the application of fractal analysis and texture measures for the detection of architectural distortion in screening mammograms taken prior to the detection of breast cancer. Materials and methods A method based on Gabor filters and phase portrait analysis was used to detect initial candidates for sites of architectural distortion. A total of 386 regions of interest (ROIs) were automatically obtained from 14 “prior mammograms”, including 21 ROIs related to architectural distortion. From the corresponding set of 14 “detection mammograms”, 398 ROIs were obtained, including 18 related to breast cancer. For each ROI, the fractal dimension and Haralick’s texture features were computed. The fractal dimension of the ROIs was calculated using the circular average power spectrum technique. Results The average fractal dimension of the normal (false-positive) ROIs was significantly higher than that of the ROIs with architectural distortion (p = 0.006). For the “prior mammograms”, the best receiver operating characteristics (ROC) performance achieved, in terms of the area under the ROC curve, was 0.80 with a Bayesian classifier using four features including fractal dimension, entropy, sum entropy, and inverse difference moment. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.79 at 8.4 false positives per image in the detection of sites of architectural distortion in the “prior mammograms”. Conclusion Fractal dimension offers a promising way to detect the presence of architectural distortion in prior mammograms.
  • Artigo Científico
    Estimation of the tissue composition of the tumour mass in neuroblastoma using segmented CT images
    (2004) FABIO JOSE AYRES; M. K. Zuffo,; Rangayyan, R. M.; Boag, G. S.; O. Filho, V.; Valente , M.
    Neuroblastoma is the most common extra-cranial, solid, malignant tumour in children. Advances in radiology have made possible the detection and staging of the disease. Nevertheless, there is no method available at present that can go beyond detection and qualitative analysis, towards quantitative assessment of the tissues composition of the primary tumour mass in neuroblastoma. Such quantitative analysis could provide important information and serve as a decision-support tool to the radiologist and the oncologist, result in better treatment and follow-up and even lead to the avoidance of delayed surgery. The problem investigated was the improvement of the analysis of the primary tumour mass, in patients with neuroblastoma, using X-ray computed tomography (CT) images. A methodology was proposed for the estimation of the tissue content of the mass: it comprised a Gaussian mixture model for estimation, from segmented CT images, of the tissue composition of the primary tumour. To demonstrate the potential of the method, the results are presented of its application to ten CT examinations of four patients. The method provides quantitative information, and it was observed that the tumour in one of the patients reduced from 523 cm3 to 81 cm3 in volume, with an increase in calcification from about 20% to about 88% of the tumour volume, in response to chemotherapy over a period of five months. Results indicate that the proposed technique may be of considerable value in assessing the response to therapy of patients with neuroblastoma.
  • Artigo Científico
    The Lysyl Oxidase Inhibitor, b-Aminopropionitrile, Diminishes the Metastatic Colonization Potential of Circulating Breast Cancer Cells
    (2009) Bondareva, Alla; Downey, Charlene M.; FABIO JOSE AYRES; Liu, Wei; Boyd, Steven K.; Hallgrimsson, Benedikt; Jirik, Frank R.
    Lysyl oxidase (LOX), an extracellular matrix remodeling enzyme, appears to have a role in promoting breast cancer cell motility and invasiveness. In addition, increased LOX expression has been correlated with decreases in both metastases-free, and overall survival in breast cancer patients. With this background, we studied the ability of b-aminopropionitrile (BAPN), an irreversible inhibitor of LOX, to regulate the metastatic colonization potential of the human breast cancer cell line, MDA MB-231. BAPN was administered daily to mice starting either 1 day prior, on the same day as, or 7 days after intracardiac injection of luciferase expressing MDA-MB-231-Luc2 cells. Development of metastases was monitored by in vivo bioluminescence imaging, and tumor-induced osteolysis was assessed by micro-computed tomography (mCT). We found that BAPN administration was able to reduce the frequency of metastases. Thus, when BAPN treatment was initiated the day before, or on the same day as the intra-cardiac injection of tumor cells, the number of metastases was decreased by 44%, and 27%, and whole-body photon emission rates (reflective of total tumor burden) were diminished by 78%, and 45%, respectively. In contrast, BAPN had no effect on the growth of established metastases. Our findings suggest that LOX activity is required during extravasation and/or initial tissue colonization by circulating MDA-MB-231 cells, lending support to the idea that LOX inhibition might be useful in metastasis prevention.
  • Artigo Científico
    Three-Dimensional Segmentation of the Tumor in Computed Tomographic Images of Neuroblastoma
    (2007) Deglint, Hanford J.; Rangayyan, Rangaraj M.; FABIO JOSE AYRES; Boag, Graham S.; Zuffo, Marcelo K.
    Segmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost Always heterogeneous in nature; furthermore, viable tumor, necrosis, and normal tissue are often intermixed. Tumor definition and diagnosis require the analysis of the spatial distribution and Hounsfield unit (HU) values of voxels in computed tomography (CT) images, coupled with a knowledge of normal anatomy. Segmentation and analysis of the tissue composition of the tumor can assist in quantitative assessment of the response to therapy and in the planning of delayed surgery for resection of the tumor. We propose methods to achieve 3-dimensional segmentation of the neuroblastic tumor. In our scheme, some of the normal structures expected in abdominal CT images are delineated and removed from further consideration; the remaining parts of the image volume are then examined for the tumor mass. Mathematical morphology, fuzzy connectivity, and other image processing tools are deployed for this purpose. Expert knowledge provided by a radiologist in the form of the expected structures and their shapes, HU values, and radiological characteristics are incorporated into the segmentation algorithm. In this preliminary study, the methods were tested with 10 CT exams of four cases from the Alberta Children’s Hospital. False-negative error rates of less than 12% were obtained in eight of the 10 exams; however, seven of the exams had false-positive error rates of more than 20% with respect to manual segmentation of the tumor by a radiologist.
  • Artigo Científico
    A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs
    (2007) Rangayyan, Rangaraj M.; FABIO JOSE AYRES; Desautels, J.E. Leo
    Mammography is the best available tool for screening for the early detection of breast cancer. Mammographic screening has been shown to be effective in reducing breast cancer mortality rates: screening programs have reduced mortality rates by 30–70%. Mammograms are difficult to interpret, especially in the screening context. The sensitivity of screening mammography is affected by image quality and the radiologist's level of expertise. Computer-aided diagnosis (CAD) technology can improve the performance of radiologists, by increasing sensitivity to rates comparable to those obtained by double reading, in a cost-effective manner. Current research is directed toward the development of digital imaging and image analysis systems that can detect mammographic features, classify them, and provide visual prompts to the radiologist. Radiologists would like the ability to change the contrast of a mammogram, either manually or with pre-selected settings. Computer techniques for detecting, classifying, and annotating diagnostic features on the images would be desirable. This paper presents an overview of digital image processing and pattern analysis techniques to address several areas in CAD of breast cancer, including: contrast enhancement, detection and analysis of calcifications, detection and analysis of masses and tumors, analysis of bilateral asymmetry, and detection of architectural distortion. Although a few commercial CAD systems have been released, the detection of subtle signs of breast cancer such as global bilateral asymmetry and focal architectural distortion remains a difficult problem. We present some of our recent works on the development of image processing and pattern analysis techniques for these applications.
  • Artigo Científico
    Gabor filters and phase portraits for the detection of architectural distortion in mammograms
    (2006) Rangayyan, Rangaraj M.; FABIO JOSE AYRES
    Segmentation of the tumor in neuroblastoma is complicated by the fact that the mass is almost Always heterogeneous in nature; furthermore, viable Architectural distortion is a subtle abnormality in mammograms, and a source of overlooking errors by radiologists. Computer-aided diagnosis (CAD) techniques can improve the performance of radiologists in detecting masses and calcifications; however, most CAD systems have not been designed to detect architectural distortion. We present a new method to detect and localise architectural distortion by analysing the oriented texture in mammograms. A bank of Gabor filters is used to obtain the orientation field of the given mammogram. The curvilinear structures (CLS) of interest (spicules and fibrous tissue) are separated from confounding structures (pectoral muscle edge, parenchymal tissue edges, breast boundary, and noise). The selected core CLS pixels and the orientation field are filtered and downsampled, to reduce noise and also to reduce the computational effort required by the subsequent methods. The downsampled orientation field is analysed to produce three phase portrait maps: node, saddle, and spiral. The node map is further analysed in order to detect the sites of architectural distortion. The method was tested with 19 mammograms containing architectural distortion. In a preliminary experiment, a sensitivity of 84% was obtained at 7.8 false positives per image.