Your browser doesn't support javascript.
loading
Personalized breast cancer screening with selective addition of digital breast tomosynthesis through artificial intelligence.
Dahlblom, Victor; Tingberg, Anders; Zackrisson, Sophia; Dustler, Magnus.
Afiliación
  • Dahlblom V; Lund University, Department of Translational Medicine, Diagnostic Radiology, Malmö, Sweden.
  • Tingberg A; Skåne University Hospital, Department of Medical Imaging and Physiology, Malmö, Sweden.
  • Zackrisson S; Lund University, Department of Translational Medicine, Medical Radiation Physics, Malmö, Sweden.
  • Dustler M; Skåne University Hospital, Radiation Physics, Malmö, Sweden.
J Med Imaging (Bellingham) ; 10(Suppl 2): S22408, 2023 Feb.
Article en En | MEDLINE | ID: mdl-37274777
Purpose: Breast cancer screening is predominantly performed using digital mammography (DM), but digital breast tomosynthesis (DBT) has higher sensitivity. DBT demands more resources than DM, and it might be more feasible to reserve DBT for women with a clear benefit from the technique. We explore if artificial intelligence (AI) can select women who would benefit from DBT imaging. Approach: We used data from Malmö Breast Tomosynthesis Screening Trial, where all women prospectively were examined with separately double read DM and DBT. We retrospectively analyzed DM examinations (n=14768) with a breast cancer detection system and used the provided risk score (1 to 10) for risk stratification. We tested how different score thresholds for adding DBT to an initial DM affects the number of detected cancers, additional DBT examinations needed, detection rate, and false positives. Results: If using a threshold of 9.0, 25 (26%) more cancers would be detected compared to using DM alone. Of the 41 cancers only detected on DBT, 61% would be detected, with only 1797 (12%) of the women examined with both DM and DBT. The detection rate for the added DBT would be 14/1000 women, whereas the false-positive recalls would be increased with 58 (21%). Conclusion: Using DBT only for selected high gain cases could be an alternative to complete DBT screening. AI can analyze initial DM images to identify high gain cases where DBT can be added during the same visit. There might be logistical challenges, and further studies in a prospective setting are necessary.
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Revista: J Med Imaging (Bellingham) Año: 2023 Tipo del documento: Article País de afiliación: Suecia Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies / Screening_studies Idioma: En Revista: J Med Imaging (Bellingham) Año: 2023 Tipo del documento: Article País de afiliación: Suecia Pais de publicación: Estados Unidos