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Congress: ECR25
Poster Number: C-11257
Type: Poster: EPOS Radiologist (scientific)
Authorblock: M. Swoboda, J. Deeg, D. Egle, V. Ladenhauf, M. Galijašević, S. Haushammer, B. Amort, M. Pamminger, L. Gruber; Innsbruck/AT
Disclosures:
Michael Swoboda: Nothing to disclose
Johannes Deeg: Nothing to disclose
Daniel Egle: Nothing to disclose
Valentin Ladenhauf: Nothing to disclose
Malik Galijašević: Nothing to disclose
Silke Haushammer: Nothing to disclose
Birgit Amort: Nothing to disclose
Mathias Pamminger: Nothing to disclose
Leonhard Gruber: Nothing to disclose
Keywords: Artificial Intelligence, Breast, Oncology, Elastography, Ultrasound, Diagnostic procedure, Cancer
References

1. Rubio IT, Wyld L, Marotti L et al. European guidelines for the diagnosis, treatment and follow-up of breast lesions with uncertain malignant potential (B3 lesions) developed jointly by EUSOMA, EUSOBI, ESP (BWG) and ESSO. European Journal of Surgical Oncology 2024; 50: 107292. doi:10.1016/j.ejso.2023.107292

2. Yoon GY, Cha JH, Kim HH et al. Sonographic features that can be used to differentiate between small triple-negative breast cancer and fibroadenoma. Ultrasonography 2018; 37: 149–156. doi:10.14366/usg.17036

3. Cho SH, Park SH. Mimickers of breast malignancy on breast sonography. Journal of Ultrasound in Medicine 2013; 32: 2029–2036. doi:10.7863/ultra.32.11.2029

4. Evans A, Jethwa K. Fibroepithelial lesions of the breast: improving the accuracy of imaging diagnosis and reducing unnecessary biopsy. Br JRadiol 2023; 96. doi:10.1259/bjr.20220078

5. Salati SA. Breast fibroadenomas: a review in the light of current literature. Polish Journal of Surgery 2020; 93: 40–48. doi:10.5604/01.3001.0014.5676
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