Evolution, current challenges, and future possibilities in the objective assessment of aesthetic outcome of breast cancer locoregional treatment

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Jaime S. Cardoso (Author) FEUP; Wilson Silva (Author) FEUP; Maria João Cardoso (Author) Other

Journal

Title: Breast

Vol. 49

Pages: 123-130

ISSN: 0960-9776

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 3 Citations

Scopus - 5 Citations

Other information

Authenticus ID: P-00R-EA2

DOI: 10.1016/j.breast.2019.11.006

Abstract (EN): The Breast Cancer overall survival rate has raised impressively in the last 20 years mainly due to improved screening and effectiveness of treatments. This increase in survival paralleled the awareness over the long-lasting impact of the side effects of treatments on patient quality of life, emphasizing the motto "a longer but better life for breast cancer patients". In breast cancer more strikingly than in other cancers, besides the side effects of systemic treatments, there is the visible impact of surgery and radiotherapy on patients' body image. This has sparked interest on the development of tools for the aesthetic evaluation of Breast Cancer locoregional treatments, which evolved from manual, subjective approaches to computerized, automated solutions. However, although studied for almost four decades, past solutions were not mature enough to become a standard. Recent advancements in machine learning have inspired trends toward deep-learning-based medical image analysis, also bringing new promises to the field of aesthetic assessment of locoregional treatments. In this paper, a review and discussion of the previous state-of-the-art methods in the field is conducted and the extracted knowledge is used to understand the evolution and current challenges. The aim of this paper is to delve into the current opportunities as well as motivate and guide future research in the aesthetic assessment of Breast Cancer locoregional treatments. (C) 2019 Elsevier Ltd.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8