Publications by authors named "J L Raya-Povedano"
Breast cancer (BCa) is a highly prevalent pathological condition (̴30% in women) with limited and subtype-dependent prognosis and therapeutic options. Therefore, BCa management might benefit from the identification of novel molecular elements with clinical potential. Since splicing process is gaining a great relevance in cancer, this work analysed the expression of multiple Spliceosome Components (SCs = 17) and Splicing Factors (SFs = 26) and found a drastic dysregulation in BCa (n = 69) vs.
View Article and Find Full Text PDFPurpose: This work aims to compare the interval cancer rate and interval cancer characteristics between women screened with digital breast tomosynthesis (DBT) + digital mammography (DM) and those screened with DM alone.
Methods: The interval cancer rate and interval cancer characteristics of the study population included in the Córdoba Breast Tomosynthesis Screening Trial (CBTST) were compared to a contemporary control population screened with DM. The tumour characteristics of screen-detected and interval cancers were also compared.
Article Synopsis
- The study looked at how having an MRI before surgery affects the chances of needing a mastectomy or having to have more surgery for women with ductal carcinoma in situ (DCIS), a type of breast cancer.
- They compared two groups of patients: one that had MRIs before surgery and one that didn't, looking closely at various factors that could affect the results.
- The results showed that women who had the MRI were more likely to have a mastectomy but were less likely to need additional surgeries afterwards.
Objectives: To evaluate the impact of using an artificial intelligence (AI) system as support for human double reading in a real-life scenario of a breast cancer screening program with digital mammography (DM) or digital breast tomosynthesis (DBT).
Material And Methods: We analyzed the performance of double reading screening with mammography and tomosynthesis after implementarion of AI as decision support. The study group consisted of a consecutive cohort of 1 year screening between March 2021 and March 2022 where double reading was performed with concurrent AI support that automatically detects and highlights lesions suspicious of breast cancer in mammography and tomosynthesis.