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There are still a limited number of primary interventions for prevention of breast cancer. For women at a high risk of developing breast cancer, the most effective intervention is prophylactic mastectomy. This is a drastic surgical procedure in which the mammary epithelial cells that can give rise to breast cancer are completely removed along with the surrounding tissue. The goal of this protocol is to demonstrate the feasibility of a minimally invasive intraductal procedure that could become a new primary intervention for breast cancer prevention. This local procedure would preferentially ablate mammary epithelial cells before they can become malignant. Intraductal methods to deliver solutions directly to these epithelial cells in rodent models of breast cancer have been developed at Michigan State University and elsewhere. The rat mammary gland consists of a single ductal tree that has a simpler and more linear architecture compared to the human breast. However, chemically induced rat models of breast cancer offer valuable tools for proof-of-concept studies of new preventive interventions and scalability from mouse models to humans. Here, a procedure for intraductal delivery of an ethanol-based ablative solution containing tantalum oxide nanoparticles as X-ray contrast agent and ethyl cellulose as gelling agent into the rat mammary ductal tree is described. Delivery of aqueous reagents (e.g., cytotoxic compounds, siRNAs, AdCre) by intraductal injection has been described previously in mouse and rat models. This protocol description emphasizes methodological changes and steps that pertain uniquely to delivering an ablative solution, formulation consideration to minimize local and systemic side effects of the ablative solution, and X-ray imaging for in vivo assessment of ductal tree filling. Fluoroscopy and micro-CT techniques enable to determine the success of ablative solution delivery and the extent of ductal tree filling thanks to compatibility with the tantalum-containing contrast agent.
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http://dx.doi.org/10.3791/64042 | DOI Listing |
EBioMedicine
September 2025
Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, 264000, PR China. Electronic address:
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFEpidemiol Serv Saude
September 2025
Universidade Estadual do Norte do Paraná, Programa de Pós-Graduação em Enfermagem em Atenção Primária à Saúde Bandeirantes, PR, Brazil.
Objectives: To analyze the temporal trend and identify spatial clusters of breast cancer mortality in Paraná state between 2012 and 2021.
Methods: This was a time series study, with spatial analysis of breast cancer mortality rates in the 399 municipalities of Paraná. Data were selected from the Mortality Information System.
Cien Saude Colet
August 2025
Faculdade de Medicina da Universidade Federal de Pelotas. Pelotas RS Brasil.
The objective of this study was to analyze the characteristics of avoidable mortality in the population aged five to 69 years living in the city of Pelotas/RS, comparing it with the rest of the state of Rio Grande do Sul, from 2000 to 2021. An ecological study was conducted analyzing avoidable mortality coefficients according to sex and age, from 2000 to 2021. The data source was the Mortality Information System, and the trend analysis was performed using Prais-Winsten regression, with standardization of coefficients.
View Article and Find Full Text PDFCien Saude Colet
August 2025
Programa de Pós-Graduação em Nutrição e Saúde, Universidade Estadual do Ceará. R. Betel 1958, Itaperi. 60714-230 Fortaleza CE Brasil.
This study aimed to evaluate mortality due to female breast cancer attributable to overweight and obesity and to estimate the number of preventable deaths with a reduction in the Body Mass Index in Brazil. An ecological study was carried out with investigation of information on overweight, obesity, sociodemographic characteristics based on a national survey carried out in 2013-14; breast cancer mortality rate in 2019 using the Online Atlas of Mortality and Relative Risk Meta-Analyses. The Potential Impact Fraction analysis was carried out, considering the following counterfactual scenarios related to the reduction in BMI: Scenario A - population contingent of women that make up the prevalence of overweight and obesity now composes the prevalence of eutrophy; Scenario B - population contingent of women that make up the prevalence of overweight starts to make up the prevalence of eutrophy; Scenario C - population contingent of women that make up the prevalence of obesity becomes part of the prevalence of overweight.
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