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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
Purpose Breast cancer (BC) remains a global health challenge, demanding innovations in imaging to enhance early detection, precise characterization, and tailored treatment strategies. This aligns with the paradigm of personalized medicine (PM), delivering the right treatment to the right patient at the right time [1–4].Contrast-enhanced mammography (CEM) has emerged as a promising second-level imaging technique, offering a cost-effective alternative to contrast-enhanced breast Magnetic Resonance (MR) [5–7]. By leveraging tumor neo-angiogenesis through intravenous iodinated contrast, CEM highlights hypervascularized regions, including neoplastic lesions...
Read more Methods and materials This retrospective, single-center study (September 2021–June 2023) included 134 women with histologically confirmed breast cancer undergoing contrast-enhanced mammography (CEM) at the Fondazione Policlinico Universitario Campus Bio-Medico, Rome. Inclusion criteria were BI-RADS 4 or 5 findings on conventional imaging, age >18 years, and ability to undergo CEM after informed consent. Exclusion criteria included pregnancy, iodinated contrast allergy, renal failure, and breast prostheses.CEM was performed using a digital mammography unit with dual-energy imaging following intravenous iodinated contrast injection (Omnipaque 350 mg/mL, 1.5...
Read more Results Univariate Analysis: Radiomic Features and Prognostic FactorsThis study highlights the potential of radiomics in breast cancer care by analyzing features from both tumor lesions and their contours. Radiomic features were shown to provide clinically relevant information for diagnosis, risk stratification, and treatment planning. Importantly, the findings emphasize the need for an integrated, multi-dimensional radiomic approach to maximize its utility in personalized treatment strategies and improve patient outcomes.Lesion Contour Features: Strong Correlations with Prognostic FactorsRadiomic features extracted from lesion contours demonstrated...
Read more Conclusion 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...
Read more References [1] Rotili, A.; Trimboli, R.M.; Penco, S.; Pesapane, F.; Tantrige, P.; Cassano, E.; Sardanelli, F. Double reading of diffusion-weighted magnetic resonance imaging for breast cancer detection. Breast Cancer Res. Treat. 2020, 180, 111–120.[2] Pesapane, F.; Rotili, A.; Penco, S.; Nicosia, L.; Cassano, E. Digital Twins in Radiology. J. Clin. Med. 2022, 11, 6553.[3] European Society of Radiology. Medical imaging in personalised medicine: A white paper of the research committee of the European Society of Radiology (ESR). Insights Imaging 2015, 6,...
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