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Updated: Jan 13, 2026

A New Technique for Treating Low-risk Prostate Cancer—Super Active Surveillance
Published on: November 7, 2025
How to tailor the radiotherapy after radical prostatectomy in the modern era of molecular imaging, genomic testing,
1Department of Electroradiology, Poznan University of Medical Sciences, Poznan, Poland.
Abstract:
In recent years, we have observed a significant increase in the number of radical prostatectomies (RP) performed in patients at very high risk of prostate cancer. This group of patients is very heterogeneous due to the presence of multiple risk factors for recurrence, which makes decisions regarding the use of salvage radiotherapy (RT) very challenging. On the one hand, there is a subgroup of patients who can only be observed. For a more advanced subgroup of patients postoperative RT alone is effective treatment. For patients with very aggressive biology characteristics RT should be combined with systemic therapy. Unfortunately, we still do not have ideal tools to precisely assign individual patients to these subgroups. Clinicopathological factors are very helpful in this regard. So, introduction of modern molecular diagnostics, i.e., positron emission tomography (PET) using a radiotracer that binds to prostate-specific membrane antigen (PET-PSMA), allowed for a change in the general strategy for salvage RT. Information from PET scans included in the RT plan allow for increasing the effectiveness of RT. Another method for personalizing RT planning is the use of genomic testing. To date, the most clinically validated method allows for the identification of a subgroup of patients in whom combined treatment [androgen deprivation therapy (ADT) + RT] yields the greatest clinical benefits. Improvement in RT outcomes is associated with the introduction of technologically advanced RT methods, such as adaptive RT (ART), which provides the opportunity for a precise delivery of dose to a tumour bed. Another very promising development involves new predictive tests for RT which are based on genomic analysis of cancer tissue.

