This study evaluated the accuracy of mammary carcinoma diagnoses in female dogs through cytological exams (FNA) compared to histopathological diagnoses. The presence of neoplasia and the effectiveness of procedures at the Pathology Laboratory of the Veterinary Hospital of the FMVZ of Unesp Botucatu, were analyzed. Between 2015 and 2020, a total of 1100 mammary neoplasms were identified, of which 569 were mammary carcinomas. Fifty cytological samples were selected and analyzed to determine occurrence, age at presentation, and the most affected breeds, as well as to verify the obtained diagnoses. Mammary carcinoma constituted for 51.72% of the registered cases. A higher occurrence was observed in mixed-breed female dogs, at 40.42%, followed by Poodles at 17%. The most common age at diagnosis was 10 years, and in 65.55% of cases, the dogs had not been previously spayed. 9.31% of the animals had received contraceptives, while 14% had given birth and 14.58% had presented symptoms of pseudopregnancy at some point in their lives. In the test results, a 70% agreement between cytology and histology was observed, with a 30% disagreement between them. Statistically, a sensitivity of 79.32% and a specificity of 57.14% were reflected. Intact and older female dogs represent a significant risk of developing mammary carcinoma. Although the protocol for processing and interpreting cytological samples is well established, the results do not reach the level of excellence observed in previous studies.
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http://dx.doi.org/10.29374/2527-2179.bjvm003024 | DOI Listing |
Sci Rep
December 2024
Department of Breast Surgery, Second Affiliated Hospital of Dalian Medical University, No. 467 Zhongshan Road, Shahekou District, Dalian, China.
Early prediction of patient responses to neoadjuvant chemotherapy (NACT) is essential for the precision treatment of early breast cancer (EBC). Therefore, this study aims to noninvasively and early predict pathological complete response (pCR). We used dynamic ultrasound (US) imaging changes acquired during NACT, along with clinicopathological features, to create a nomogram and construct a machine learning model.
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View Article and Find Full Text PDFthe evolution of axillary management in breast cancer has witnessed significant changes in recent decades, leading to an overall reduction in surgical interventions. There have been notable shifts in practice, aiming to minimize morbidity while maintaining oncologic outcomes and accurate staging for newly diagnosed breast cancer patients. These advancements have been facilitated by the improved efficacy of adjuvant therapies.
View Article and Find Full Text PDFthe axillary reverse mapping (ARM) procedure aims to preserve the lymphatic drainage structures of the upper extremity during axillary surgery for breast cancer, thereby reducing the risk of lymphedema in the upper limb. Material and this prospective study included 57 patients with breast cancer who underwent SLNB and ARM. The sentinel lymph node (SLN) was identified using a radioactive tracer.
View Article and Find Full Text PDFBrief Bioinform
November 2024
School of Medicine, Institute of Biomedicine, University of Eastern Finland, Yliopistonranta 1, PO Box 1627, 70211 Kuopio, Finland.
The selection of biomarker panels in omics data, challenged by numerous molecular features and limited samples, often requires the use of machine learning methods paired with wrapper feature selection techniques, like genetic algorithms. They test various feature sets-potential biomarker solutions-to fine-tune a machine learning model's performance for supervised tasks, such as classifying cancer subtypes. This optimization process is undertaken using validation sets to evaluate and identify the most effective feature combinations.
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