Objective Breast cancer is a critical public health issue and a leading cause of cancer-related deaths among women worldwide. Its early diagnosis and detection can effectively help in increasing the chances of survival rate. For this reason, the diagnosis and classification of breast cancer using Deep learning algorithms have attracted a lot of attention. Therefore, our study aimed to design a computational approach based on deep convolutional neural networks for an efficient classification of breast cancer histopathological images by using our own created dataset. We collected overall 328 digital slides, from 116 of surgical breast specimens diagnosed with invasive breast carcinoma of non-specific type, and referred to the histopathology department of the National Institute of Oncology in Rabat, Morocco. We used two models of deep neural network architectures in order to accurately classify the images into one of three categories: normal tissue-benign lesions, in situ carcinoma or invasive carcinoma. Results Both Resnet50 and Xception models achieved comparable results, with a small advantage to Xception extracted features. We reported high degrees of overall correct classification accuracy (88%), and sensitivity (95%) for detection of carcinoma cases, which is important for diagnostic pathology workflow in order to assist pathologists for diagnosing breast cancer with precision. The results of the present study showed that the designed classification model has a good generalization performance in predicting diagnosis of breast cancer, in spite of the limited size of the data. To our knowledge, this approach can be highly compared with other common methods in the automated analysis of breast cancer images reported in literature.
Adult hepatoblastoma is a rare tumor whose etiology and mechanisms of development are still incompletely understood. Imaging and biological tests such as AFP and liver enzymes are non-specific. Histologically, there are 2 histological variants: pure epithelial with 5 types (pure fetal, embryonal, small cell undifferentiated, cholangioblastic, and macrotrabecular), a mixed epithelial and a mesenchymal variant with or without a teratoid contingent. The main differential diagnosis concerns hepatocellular carcinoma. The treatment of hepatoblastoma in adults is not yet standardized and surgery remains the mainstay of treatment. In this report we aim to describe the clinical, pathological, and immunohistochemical features of this rare entity in adult patients and discuss the elements allowing its distinction from hepatocellular carcinoma (HCC).
Metastasis of renal clear cell carcinoma (RCC) to the breast is exceptional. Breast metastases of extra-mammary tumors are rare and usually involve melanoma, lymphoma or leukemia. We report the case of a patient with breast metastasis of renal clear cell carcinoma occurring 18 years after nephrectomy. A history of RCC should always raise suspicion about breast metastasis, a situation that remains exceptional and whose diagnosis relies on anatomopathology.
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