.svg?iar=0&updated=20230109065058&hash=B8F025B8AA9A24E727DBB30EAED272C8){kind=logo}
Speaker: Mo Zhang, The First Hospital of China Medical University, China
Important Takeaways
-
Mixed Reality (MR) navigation systems provide enhanced intraoperative guidance, allowing real-time integration of imaging and 3D holographic models for precise tumour resection in robotic-assisted radical prostatectomy (RARP).
-
Improved functional outcomes: MR guidance significantly supports early continence and potency recovery by preserving the neurovascular bundles and other critical structures with greater accuracy.
-
Reduction in positive surgical margins: MR-guided RARP lowers the incidence of positive surgical margins, particularly valuable in high-risk prostate cancer cases.
-
Enhanced preoperative planning and patient communication: 3D MR models improve preoperative assessment and provide clearer visuals for surgeon-patient discussions regarding tumour location and surgical risks.
-
Future prospects: Advances in AI-driven tissue tracking and deformation simulation are expected to further enhance the accuracy and utility of MR navigation systems.
Key Highlights
Study Overview and Patient Demographics:
Dr. Zhang presented an overview of the study conducted from July 2022 to October 2023, which assessed MR-guided robotic-assisted radical prostatectomy (RARP) in 145 patients with high-risk prostate cancer. The MR-guided group was compared to a standard RARP control group. Patient characteristics were balanced between groups through propensity score matching to ensure comparability. All participants underwent a high-resolution imaging scan, with the MR model files utilized for intraoperative navigation.
Preoperative Planning and Communication:
MR technology enabled a comprehensive preoperative assessment, mapping the tumour, neurovascular bundles (NVBs), and urethral sphincter in 3D. Using MR headsets, both the surgeon and patient could view the holographic prostate model, providing a detailed explanation of tumour location, the surgical approach, and associated risks. This improved understanding of the procedure and aided patient engagement.
Intraoperative Navigation and Enhanced Precision:
During surgery, the MR model was superimposed on the patient’s anatomy in real-time, offering precise intraoperative navigation. The surgeon could more accurately locate critical areas like the bladder neck and the prostate apex, preserving the NVBs with minimal tissue disturbance. This level of precision was shown to be superior to traditional MRI cognitive guidance and proved especially beneficial in preserving the NVB complex and membranous urethra.
Surgical Outcomes and Functional Recovery:
Pathological assessments confirmed a higher rate of NVB preservation and a lower incidence of positive surgical margins in the MR-guided group than in the control group. Early recovery of continence and potency was notably better in the MR-guided patients, with continence defined stringently as requiring zero pads. Long-term functional recovery between the groups was comparable, with no significant difference noted at a median follow-up of 28 months.
Limitations and Future Directions:
Dr. Zhang addressed limitations, noting that the MR navigation model’s segmentation and registration require manual input, necessitating close cooperation between radiologists and surgeons. Additionally, intraoperative tissue deformation posed challenges in maintaining MR model accuracy. Future advancements in AI, such as deep learning-based tissue tracking and deformation simulation, are anticipated to resolve these issues and enhance the applicability of MR navigation.
Conclusion:
Dr. Zhang concluded, intraoperative navigation with the MR system in robotic-assisted radical prostatectomy (RARP) enhances surgical precision, facilitates nerve-sparing approaches, reduces positive surgical margins (PSM), and optimizes functional recovery without compromising oncological safety. However, manual segmentation, registration, and tracking require collaboration between radiologists and urologists. A significant limitation is the inaccuracy due to tissue deformation caused by surgical manipulation. Nevertheless, advancements in artificial intelligence, particularly deep learning algorithms, are expected to provide solutions for automatic identification, tissue deformation simulation, and improved tracking, further enhancing MR navigation's effectiveness in urologic surgery.
Société Internationale d'Urologie Congress, 23-26 October 2024, New Delhi, India.
