Prevalence of human papillomavirus in archival samples obtained from patients with cervical pre-malignant and malignant lesions from Northeast Brazil

<p>Abstract</p> <p>Background</p> <p>Human Papillomavirus (HPV) is considered as a necessary, but not sufficient, cause of cervical cancer. In this study, we aimed to assess the prevalence of HPV in a series of pre-malignant and malignant cervical lesion cases, to identify the virus genotypes, and to assess their distribution pattern according to lesion type, age range, and other considered variables. The samples were submitted to histopathological revision examination and analysed by polymerase chain reaction (PCR) for the presence of HPV DNA, followed by HPV typing by dot blot hybridisation.</p> <p>Findings</p> <p>Of the analysed samples, 53.7% showed pre-malignant cervical lesions, and 46.3% presented with cervical cancer. Most cancer samples (84.1%) were classified as invasive carcinoma. The mean age of these cancer patients was 47.3 years. The overall HPV prevalence was 82.4% in patients with pre-malignant lesions and 92.0% in the cancer patients. HPV 16 was the most prevalent type, followed by HPV 18 and 58, including both single and double infections. Double infection was detected in 11.6% of the samples, and the most common combination was HPV 16+18.</p> <p>Conclusions</p> <p>Cervical cancer appears to occur in women in a lower age range in the studied area, compared to the situation in other Brazilian regions. Furthermore, among the patients with CIN 3 and those with cancer, we observed a higher proportion of married women, women with more than one sexual partner, smokers, and individuals with less than an elementary education, relative to their counterparts.</p> <p>Findings</p> <p>The overall HPV prevalence was 82.4% in patients with pre-malignant lesions and 92.0% in the cervical cancer patients from Northeast Brazil. HPV 16 was the most prevalent type, followed by HPV 18 and 58. The most common double infection was HPV 16+18. Cervical cancer appears to occur in women in a lower age range in the Northeast Brazil. Among the patients with CIN 3 and those with cancer, we observed a higher proportion of married women, women with more than one sexual partner, smokers, and individuals with less than an elementary education, relative to their counterparts.</p

Implementação e avaliação de um sistema de gerenciamento de imagens médicas com suporte à recuperação baseada em conteúdo Implementation and evaluation of a medical image management system with content-based retrieval support

OBJETIVO: Neste artigo são descritas a implementação e avaliação de um sistema de gerenciamento de imagens médicas com suporte à recuperação baseada em conteúdo (PACS-CBIR), integrando módulos voltados para a aquisição, armazenamento e distribuição de imagens, e a recuperação de informação textual por palavras-chave e de imagens por similaridade. MATERIAIS E MÉTODOS: O sistema foi implementado com tecnologias para Internet, utilizando-se programas livres, plataforma Linux e linguagem de programação C++, PHP e Java. Há um módulo de gerenciamento de imagens compatível com o padrão DICOM e outros dois módulos de busca, um baseado em informações textuais e outro na similaridade de atributos de textura de imagens. RESULTADOS: Os resultados obtidos indicaram que as imagens são gerenciadas e armazenadas corretamente e que o tempo de retorno das imagens, sempre menor do que 15 segundos, foi considerado bom pelos usuários. As avaliações da recuperação por similaridade demonstraram que o extrator escolhido possibilitou a separação das imagens por região anatômica. CONCLUSÃO: Com os resultados obtidos pode-se concluir que é viável a implementação de um PACS-CBIR. O sistema apresentou-se compatível com as funcionalidades do DICOM e integrável ao sistema de informação local. A funcionalidade de recuperação de imagens similares pode ser melhorada com a inclusão de outros descritores.<br>OBJECTIVE: The present paper describes the implementation and evaluation of a medical images management system with content-based retrieval support (PACS-CBIR) integrating modules focused on images acquisition, storage and distribution, and text retrieval by keyword and images retrieval by similarity. MATERIALS AND METHODS: Internet-compatible technologies were utilized for the system implementation with freeware, and C++, PHP and Java languages on a Linux platform. There is a DICOM-compatible image management module and two query modules, one of them based on text and the other on similarity of image texture attributes. RESULTS: Results demonstrate an appropriate images management and storage, and that the images retrieval time, always < 15 sec, was found to be good by users. The evaluation of retrieval by similarity has demonstrated that the selected images extractor allowed the sorting of images according to anatomical areas. CONCLUSION: Based on these results, one can conclude that the PACS-CBIR implementation is feasible. The system has demonstrated to be DICOM-compatible, and that it can be integrated with the local information system. The similar images retrieval functionality can be enhanced by the introduction of further descriptors

Content-based Retrieval of Mammograms Using Visual Features Related to Breast Density Patterns

This paper describes part of content-based image retrieval (CBIR) system that has been developed for mammograms. Details are presented of methods implemented to derive measures of similarity based upon structural characteristics and distributions of density of the fibroglandular tissue, as well as the anatomical size and shape of the breast region as seen on the mammogram. Well-known features related to shape, size, and texture (statistics of the gray-level histogram, Haralick’s texture features, and moment-based features) were applied, as well as less-explored features based in the Radon domain and granulometric measures. The Kohonen self-organizing map (SOM) neural network was used to perform the retrieval operation. Performance evaluation was done using precision and recall curves obtained from comparison between the query and retrieved images. The proposed methodology was tested with 1,080 mammograms, including craniocaudal and mediolateral-oblique views. Precision rates obtained are in the range from 79% to 83% considering the total image set. Considering the first 50% of the retrieved mages, the precision rates are in the range from 78% to 83%; the rates are in the range from 79% to 86% considering the first 25% of the retrieved images. Results obtained indicate the potential of the implemented methodology to serve as a part of a CBIR system for mammography