3 resultados para cancer detection

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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The most significant radiation field nonuniformity is the well-known Heel effect. This nonuniform beam effect has a negative influence on the results of computer-aided diagnosis of mammograms, which is frequently used for early cancer detection. This paper presents a method to correct all pixels in the mammography image according to the excess or lack on radiation to which these have been submitted as a result of the this effect. The current simulation method calculates the intensities at all points of the image plane. In the simulated image, the percentage of radiation received by all the points takes the center of the field as reference. In the digitized mammography, the percentages of the optical density of all the pixels of the analyzed image are also calculated. The Heel effect causes a Gaussian distribution around the anode-cathode axis and a logarithmic distribution parallel to this axis. Those characteristic distributions are used to determine the center of the radiation field as well as the cathode-anode axis, allowing for the automatic determination of the correlation between these two sets of data. The measurements obtained with our proposed method differs on average by 2.49 mm in the direction perpendicular to the anode-cathode axis and 2.02 mm parallel to the anode-cathode axis of commercial equipment. The method eliminates around 94% of the Heel effect in the radiological image and the objects will reflect their x-ray absorption. To evaluate this method, experimental data was taken from known objects, but could also be done with clinical and digital images.

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Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.

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The recovery and stability of DNA for the detection and genotyping of HPV in UCM-containing specimens, after exposure to denaturing reagents and stored for up to 2 years were evaluated. Samples were collected from 60 women who had cervical cytology specimens harboring cervical intraepithelial neoplasia (CIN) 2 or 3. All samples were stored in UCM and had been frozen at -20 degrees C following the addition of the denaturing reagent (sodium hydroxide) and the removal of the aliquot required for Hybrid Capture 2 testing for the identification of HPV DNA. The samples had been stored for 6, 12 and 24 months (20 samples for each storage time). HPV DNA extraction was performed according to a protocol designed specifically and the presence and quality of DNA was confirmed by human P-globin detection using the consensus primers G73 and G74. HPV DNA was amplified using the consensus primers PGMY09 and PGMY11, and reverse line-blot hybridization was used to detect type-specific amplicons for 37 HPV types. The DNA extracted from the denatured specimen was recovered in 57/60 (95%) of the samples. HPV DNA was detected in 56/57 (98%) of the recovered samples. Twenty-six of the 56 samples recovered (48%) were genotyped successfully. (c) 2007 Elsevier B.V. All rights reserved.