Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros










Base de dados
Assunto principal
Intervalo de ano de publicação
1.
Technol Cancer Res Treat ; 22: 15330338231218227, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-38111330

RESUMO

Breast cancer is the most common malignancy in women, and some subtypes are associated with a poor prognosis with a lack of efficacious therapy. Moreover, immunotherapy and the use of other novel antibody‒drug conjugates have been rapidly incorporated into the standard management of advanced breast cancer. To extract more benefit from these therapies, clarifying and monitoring the tumor microenvironment (TME) status is critical, but this is difficult to accomplish based on conventional approaches. Radiomics is a method wherein radiological image features are comprehensively collected and assessed to build connections with disease diagnosis, prognosis, therapy efficacy, the TME, etc In recent years, studies focused on predicting the TME using radiomics have increasingly emerged, most of which demonstrate meaningful results and show better capability than conventional methods in some aspects. Beyond predicting tumor-infiltrating lymphocytes, immunophenotypes, cytokines, infiltrating inflammatory factors, and other stromal components, radiomic models have the potential to provide a completely new approach to deciphering the TME and facilitating tumor management by physicians.


Assuntos
Neoplasias da Mama , Feminino , Humanos , Neoplasias da Mama/diagnóstico por imagem , Microambiente Tumoral , Inteligência Artificial , Radiômica , Biomarcadores , Prognóstico , Biomarcadores Tumorais
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA
...