A cross-cutting approach for tracking architectural distortion locii on digital breast tomosynthesis slices

Autor(es)

de Oliveira, Helder C. R. ^[1] ; Mencattini, Arianna ^[2] ; Casti, Paola ^[2] ; Catani, Juliana H. ^[3] ; de Barros, Nestor ^[3] ; Gonzaga, Adilson ^[1] ; Martinelli, Eugenio ^[2] ; da Costa Vieira, Marcelo A. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Sao Carlos Sch Engn, Sao Carlos, SP - Brazil

^[2] Univ Roma Tor Vergata, Rome - Italy

^[3] Univ Sao Paulo, Med Sch, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Biomedical Signal Processing and Control; v. 50, p. 92-102, APR 2019.
• Citações Web of Science: 1

Resumo

Background and objective: Full-field digital mammography (FFDM) is the predominant breast cancer screening exam used. However, with the emergence of digital breast tomosynthesis (DBT) the radiologists could improve early recognition of breast cancer signs. In this scenario, the detection of architectural distortion (AD) is still a challenging task. ADs are very subtle contraction of the breast parenchyma that could represent the earliest manifestation of cancer, assessing at present 50% of missed cases. Methods: This paper proposes a new paradigm to detect AD in DBT exams by a cross-cutting approach exploiting the 3-dimensionality of the imaging modality. After locating AD candidates in each DBT slice, the suspicious spots are tracked in cross-slice direction and then characterized in terms of neighboring texture. In this approach, which mimics radiologist's scrolling down over zoomed slices, we reduce the amount of uninformative signs collected in DBT exams by preserving the large variability of AD appearance. Results: Using 37 sets of DBT slices containing at least one AD locus indicated by a radiologist, the proposed methodology reaches an AUC of 0.84, with only one false negative exam at sensitivity of 0.9. Conclusions: The results show that the proposed algorithm can be a promising tool for the automatic detection of AD locii. Future work will address the extension of the dataset of DBT slices as well the improvement of algorithm performance toward the application in the clinical practice. (C) 2019 Published by Elsevier Ltd. (AU)

• Processo FAPESP: 15/20812-5 - Descritores de texturas robustos à rotação, variação de iluminação e cores
• Beneficiário: Adilson Gonzaga
• Modalidade de apoio: Auxílio à Pesquisa - Regular