Introduction: Breast cancer is the most common tumour in women. It accounts for nearly 29% of all female cancers and represents the first cause of oncologic death; genetic and environmental factors are involved. Early detection is mandatory. Digital tomography represents the gold standard for early diagnosis. Tomosintesys 3D (DBT), ultrasound (US) and breast MRI are used to help diagnosis, in patient who have dense breast. Recent studies have elaborated mathematical algorithms able to create radiomics features, which represent the intrinsically characteristics of the tumour, using morphological imaging parameters of lesion. Aim of this study is to apply these MRI features in order to classify benign and malignant lesions, and their histological type. Methods and materials: We retrospectively included patients who came to the UOC of Senology of Sassari AOU between January 2018 and September 2018 and underwent a breast MRI C.E. after a digital tomography, DBT and echography, were included. Results: 51 patients were enrolled. A radiomics analysis was performed on enhanced MRI breast imaging. Discussion: This study demonstrate a potential role of radiomic in order to distinguish not just between malignant and benign lesion, but also between different histological pattern, confirming their high potential in early diagnosis and therapy.
Radiomics in breast cancer / Crivelli, P.; Ledda, R. E.; Piga, G.; Lampus, M. L.; Sotgiu, M. A.; Sanna, E.; Soro, D.; Conti, M.. - In: PHARMACOLOGYONLINE. - ISSN 1827-8620. - 1:Special Issue(2020), pp. 46-51.
Radiomics in breast cancer
Ledda R. E.;
2020-01-01
Abstract
Introduction: Breast cancer is the most common tumour in women. It accounts for nearly 29% of all female cancers and represents the first cause of oncologic death; genetic and environmental factors are involved. Early detection is mandatory. Digital tomography represents the gold standard for early diagnosis. Tomosintesys 3D (DBT), ultrasound (US) and breast MRI are used to help diagnosis, in patient who have dense breast. Recent studies have elaborated mathematical algorithms able to create radiomics features, which represent the intrinsically characteristics of the tumour, using morphological imaging parameters of lesion. Aim of this study is to apply these MRI features in order to classify benign and malignant lesions, and their histological type. Methods and materials: We retrospectively included patients who came to the UOC of Senology of Sassari AOU between January 2018 and September 2018 and underwent a breast MRI C.E. after a digital tomography, DBT and echography, were included. Results: 51 patients were enrolled. A radiomics analysis was performed on enhanced MRI breast imaging. Discussion: This study demonstrate a potential role of radiomic in order to distinguish not just between malignant and benign lesion, but also between different histological pattern, confirming their high potential in early diagnosis and therapy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.