Congress:
ECR25
Poster Number:
C-13257
Type:
Poster: EPOS Radiologist (scientific)
Authorblock:
C. Piccolo, M. Sarli, M. Pileri, M. Tommasiello, A. Rofena, V. Guarrasi, P. Soda, B. Beomonte Zobel; Rome/IT
Disclosures:
Claudia Piccolo:
Nothing to disclose
Marina Sarli:
Nothing to disclose
Matteo Pileri:
Nothing to disclose
Manuela Tommasiello:
Nothing to disclose
Aurora Rofena:
Nothing to disclose
Valerio Guarrasi:
Nothing to disclose
Paolo Soda:
Nothing to disclose
Bruno Beomonte Zobel:
Nothing to disclose
Keywords:
Breast, Mammography, Computer Applications-Detection, diagnosis, Cancer
This study advances breast cancer radiomics by systematically analyzing radiomic features from tumor lesions and their contours. The findings demonstrate radiomics' potential not only for diagnosis but also for tailoring treatment strategies to individual patients. Radiomic features provide clinically relevant information, enhancing risk stratification and treatment planning.
The study emphasizes the need for an integrated, multi-dimensional radiomic approach to maximize its utility in breast cancer care. Incorporating radiomic analysis into clinical practice could support personalized treatment strategies, enabling precise therapeutic decisions and improved patient outcomes.