On the use of machine learning methods for mPSD calibration in HDR brachytherapy

Artificial intelligence in interventional radiotherapy (brachytherapy): Enhancing patient-centered care and addressing patients' needs

This review explores the integration of artificial intelligence (AI) in interventional radiotherapy (IRT), emphasizing its potential to streamline workflows and enhance patient care. Through a systematic analysis of 78 relevant papers spanning from 2002 to 2024, we identified significant advancements in contouring, treatment planning, outcome prediction, and quality assurance. AI-driven approaches offer promise in reducing procedural times, personalizing treatments, and improving treatment outcomes for oncological patients. However, challenges such as clinical validation and quality assurance protocols persist. Nonetheless, AI presents a transformative opportunity to optimize IRT and meet evolving patient needs.

A novel ultrasound probe calibration method for multimodal image guidance of needle placement in cervical cancer brachytherapy

PURPOSE

Interstitial needles placement is a critical component of combined intracavitary/interstitial (IC/IS) brachytherapy (BT). To ensure precise placement of interstitial needles, we proposed a novel ultrasonic (US) probe calibration method to accurately register the US image in the magnetic resonance imaging (MRI) image and provide multimodal image guidance for needle placement.

METHODS

A wire-based calibration phantom combined with the stylus was developed for the calibration of US probe. The calibration phantom helps to quickly align the imaging plane of the US probe with the fiducial points to obtain US images of these points. The coordinates of fiducial points in US images were located automatically by feature extraction algorithms and were further corrected by the proposed correction method. Ingenious structures were designed on both sides of the calibration phantom to accurately obtain the coordinates of the fiducial points relative to the tracking device. Marker validation and pelvic phantom study were performed to evaluate the accuracy of the proposed calibration method.

RESULTS

In the marker validation, the US probe calibration method with corrected transformation achieves a registration accuracy of 0.694 ± 0.014 mm, and the uncorrected one is 0.746 ± 0.018 mm. In the pelvic phantom study, the needle tip difference was 1.096 ± 0.225 mm and trajectory difference was 1.416 ± 0.284 degrees.

CONCLUSION

The proposed US probe calibration method is helpful to achieve more accurate multimodality image guidance for needle placement.