Clinical Scorecard: Advancing Autonomous Robotic Systems for Prostate Biopsy: A Preliminary Investigation
At a Glance
Category
Detail
Condition
Prostate cancer (PCa), a leading cause of death in men
Key Mechanisms
Needle biopsy under ultrasound guidance with robotic assistance integrating machine learning for target selection, image fusion, and motion compensation
Target Population
Men undergoing prostate biopsy for cancer detection
Care Setting
Outpatient clinics and operating rooms
Key Highlights
PROST robotic system provides level 1 autonomy, offering cognitive and manual assistance during prostate biopsy to improve accuracy regardless of physician expertise.
The system enables reaching the entire prostate through only two punctures, reducing patient trauma and procedure time.
Integration of machine learning allows real-time prostate segmentation and task replanning to enhance biopsy targeting accuracy.
Guideline-Based Recommendations
Diagnosis
Use needle biopsy as the most reliable technique to detect prostate cancer and estimate aggressiveness.
Prefer transperineal biopsy over transrectal to reduce infection risk.
Management
Employ robotic assistance systems like PROST to improve biopsy accuracy and reduce dependence on operator experience.
Utilize image fusion techniques combining pre-operative MR and real-time ultrasound for target planning.
Monitoring & Follow-up
Monitor needle positioning and prostate motion in real-time using robotic tracking and machine learning segmentation.
Risks
Minimize infection risk by using transperineal approach and reducing the number of needle insertion points.
Maintain physician control over needle insertion to ensure safety despite robotic assistance.
Patient & Prescribing Data
Men requiring prostate biopsy for cancer diagnosis
Robotic-assisted biopsy systems can standardize procedure accuracy, reduce trauma, and potentially allow outpatient setting use, improving accessibility and reducing costs.
Clinical Best Practices
Perform prostate biopsy under ultrasound guidance with image fusion to enhance target accuracy.
Use robotic systems that provide cognitive and manual assistance while maintaining physician control over needle insertion.
Limit the number of needle entry points to reduce patient trauma without compromising biopsy accuracy.
Incorporate machine learning algorithms for real-time prostate segmentation and adaptive task planning.
by Bogdan Maris, Chiara Tenga, Rudy Vicario, Luigi Palladino, Noe Murr, Michela De Piccoli, Andrea Calanca, Stefano Puliatti, Salvatore Micali, Alessandro Tafuri, Paolo Fiorini
The expert panel outlines surveillance, device management, and diagnostic stewardship strategies to address both catheter-associated and non–catheter-associated infections.
