Automated patient-specific transperineal ultrasound probe setups for prostate cancer patients undergoing radiotherapy.

PURPOSE

The use of ultrasound imaging is not widespread in prostate cancer radiotherapy workflows, despite several advantages (eg, allowing real-time volumetric organ tracking). This can be partially attributed to the need for a trained operator during acquisition and interpretation of the images. We introduce and evaluate an algorithm that can propose a patient-specific transperineal ultrasound probe setup, based on a CT scan and anatomical structure delineations. The use of this setup during the simulation and treatment stage could improve usability of ultrasound imaging for relatively untrained operators (radiotherapists with less than 1 yr experience with ultrasound).

METHODS

The internal perineum boundaries of three prostate cancer patients were identified based on bone masks extracted from their CT scans. After projection of these boundaries to the skin and exclusion of specific areas, this resulted in a skin area accessible for transperineal ultrasound probe placement in clinical practice. Several possible probe setups on this area were proposed by the algorithm and the optimal setup was automatically selected. In the end, this optimal setup was evaluated based on a comparison with a corresponding transperineal ultrasound volume acquired by a radiation oncologist.

RESULTS

The algorithm-proposed setups allowed visualization of 100% of the clinically required anatomical structures, including the whole prostate and seminal vesicles, as well as the adjacent edges of the bladder and rectum. In addition, these setups allowed visualization of 94% of the anatomical structures, which were also visualized by the physician during the acquisition of an actual ultrasound volume.

CONCLUSION

Provided that the ultrasound probe setup proposed by the algorithm, is properly reproduced on the patient, it allows visualization of all clinically required structures for image guided radiotherapy purposes. Future work should validate these results on a patient population and optimize the workflow to enable a relatively untrained operator to perform the procedure.