U-Net Architectures for Prostate Cancer Radiation Therapy: A Literature Review

Abstract

Silently asymptomatic, PCa is usually diagnosed with Digital Rectal Examination (DRE) and Prostate Specific Antigen (PSA) levels. Since the first treatment of an advanced prostatic malignancy with X-rays by Imbert and Imbert in 1904, External Beam Radiation Therapy (EBRT) is now a curative option for localised and locally advanced disease and a palliative option for the metastatic low-volume disease. Even with the introduction of computers in EBRT and better imaging techniques, volume delineation is still a very time-consuming task relying on manual or semi-automatic segmentation techniques. On the other hand, the U-Net architecture was specially designed for medical image segmentation presenting promising results. This literature review gathers work using U-Net architectures for PCa segmentation in an EBRT context. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards, we outline methods, techniques and obtained outcomes as a potential foundation for an automated segmentation framework for PCa.