Relationship between biodosimetric parameters and treatment volumes in three types of prostate radiotherapy

Brachytherapy (BT) and external beam radiotherapy (EBRT) apply different dose rates, overall treatment times, energies and fractionation. However, the overall impact of these variables on the biological dose of blood is neglected. As the size of the irradiated volume influences the biological effect as well, we studied chromosome aberrations (CAs) as biodosimetric parameters, and explored the relationship of isodose surface volumes (ISVs: V1%, V1Gy, V10%, V10Gy, V100%, V150%) and CAs of both irradiation modalities. We performed extended dicentrics assay of lymphocytes from 102 prostate radiotherapy patients three-monthly for a year. Aberration frequency was the highest after EBRT treatment. It increased after the therapy and did not decrease significantly during the first follow-up year. We showed that various types of CAs 9 months after LDR BT, 3 months after HDR BT and in a long time-range (even up to 1 year) after EBRT positively correlated with ISVs. Regression analysis confirmed these relationships in the case of HDR BT and EBRT. The observed differences in the time points and aberration types are discussed. The ISVs irradiated by EBRT showed stronger correlation and regression relationships with CAs than the ISVs of brachytherapy.

Gastrointestinal and genitourinary toxicity profiles of metformin versus placebo in men with prostate cancer receiving prostate radiotherapy: interim toxicity results of a double-blinded, multicenter, phase II randomized controlled trial

Androgen deprivation therapy (ADT) used for prostate cancer (PCa) management is associated with metabolic and anthropometric toxicity. Metformin given concurrent to ADT is hypothesized to counteract these changes. This planned interim analysis reports the gastrointestinal and genitourinary toxicity profiles of PCa patients receiving ADT and prostate/pelvic radiotherapy plus metformin versus placebo as part of a phase 2 randomized controlled trial. Men with intermediate or high-risk PCa were randomized 1:1 to metformin versus placebo. Both groups were given ADT for 18–36 months with minimum 2-month neoadjuvant phase prior to radiotherapy. Acute gastrointestinal and genitourinary toxicities were quantified using CTCAE v4.0. Differences in ≥ grade 2 toxicities by treatment were assessed by chi-squared test. 83 patients were enrolled with 44 patients randomized to placebo and 39 randomized to metformin. There were no significant differences at any time point in ≥ grade 2 gastrointestinal toxicities or overall gastrointestinal toxicity. Overall ≥ grade 2 gastrointestinal toxicity was low prior to radiotherapy (7.9% (placebo) vs. 3.1% (metformin), p = 0.39) and at the end of radiotherapy (2.8% (placebo) vs 3.1% (metformin), p = 0.64). There were no differences in overall ≥ grade 2 genitourinary toxicity between treatment arms (19.0% (placebo) vs. 9.4% (metformin), p = 0.30). Metformin added to radiotherapy and ADT did not increase rates of ≥ grade 2 gastrointestinal or genitourinary toxicity and is generally safe and well-tolerated.

A feasibility study on the development and use of a deep learning model to automate real-time monitoring of tumor position and assessment of interfraction fiducial marker migration in prostate radiotherapy patients

Purpose The aim of this study was to assess the feasibility of the development and training of a deep learning object detection model for automating the assessment of fiducial marker migration and tracking of the prostate in radiotherapy patients. Methods and Materials A fiducial marker detection model was trained on the YOLO v2 detection framework using approximately 20,000 pelvis kV projection images with fiducial markers labelled. The ability of the trained model to detect marker positions was validated by tracking the motion of markers in a respiratory phantom and comparing detection data with the expected displacement from a reference position. Marker migration was then assessed in 14 prostate radiotherapy patients using the detector for comparison with previously conducted studies. This was done by determining variations in intermarker distance between the first and subsequent fractions in each patient. Results On completion of training, a detection model was developed that operated at a 96% detection efficacy and with a root mean square error of 0.3 pixels. By determining the displacement from a reference position in a respiratory phantom, experimentally and with the detector it was found that the detector was able to compute displacements with a mean accuracy of 97.8% when compared to the actual values. Interfraction marker migration was measured in 14 patients and the average and maximum ± standard deviation marker migration were found to be 2.0±0.9 mm and 2.3±0.9 mm, respectively. Conclusion This study demonstrates the benefits of pairing deep learning object detection, and image-guided radiotherapy and how a workflow to automate the assessment of organ motion and seed migration during prostate radiotherapy can be developed. The high detection efficacy and low error make the advantages of using a pre-trained model to automate the assessment of the target volume positional variation and the migration of fiducial markers between fractions.