Recently, the 15th Shanghai Urologic Oncology Academic Conference—hosted by the Shanghai Anti-Cancer Association under the theme “Precision Integration · Intelligent Leadership”—brought together leading scholars from around the world to explore advances in urologic oncology.On this occasion, Urology Frontier invited Guo Jianming, Professor of Urology at Zhongshan Hospital, Fudan University, to provide an in-depth analysis of the clinical value and future trends of three frontier technologies—holographic medical imaging, artificial intelligence (AI), and robotic surgery—in the diagnosis and treatment of urologic tumors.
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Urology Frontier
Q: Could you introduce the main application scenarios and clinical value of holographic medical imaging in prostate cancer diagnosis and treatment?
Professor Guo Jianming: Holographic medical imaging is akin to a “battle map.” Its value must be understood in the context of prostate anatomy. The prostate lies deep in the pelvic floor and is closely adjacent to the urinary sphincter responsible for continence and the neurovascular bundles critical for sexual function. This anatomy creates a fundamental dilemma in radical prostatectomy: how to achieve complete tumor removal while maximally preserving urinary and sexual function.
For renal tumors, expanding the resection margin can achieve nearly 100% negative margins. In contrast, excessive resection in prostate surgery can easily lead to severe complications such as urinary incontinence and erectile dysfunction. Even at internationally advanced centers, the positive surgical margin rate in prostate cancer remains around 20%, meaning nearly one in five patients may face residual tumor risk.
Holographic medical imaging was developed precisely to address this challenge. It helps surgeons strike a precise balance between oncologic radicality and functional preservation, with three main application scenarios:
- Protection of Critical Structures Three-dimensional holographic reconstruction clearly visualizes continence-related structures (such as the urethral sphincter) and sexual function–related structures (such as erectile nerves), guiding surgical planning and trajectories to reduce postoperative incontinence and sexual dysfunction.
- Nerve Function Preservation Precise localization of key nerves enables selective preservation during surgery, maximizing quality of life while maintaining oncologic control.
- Optimization of Positive Margin Rates Accurate preoperative assessment of tumor location and invasion extent allows tailored resection, avoiding blind over-resection while reducing positive margins. It should be emphasized that a ~20% positive margin rate is not necessarily alarming; with adjuvant radiotherapy or endocrine therapy, many patients still achieve excellent tumor control.
Importantly, national authorities are actively advancing clinical standards and reimbursement policies for holographic imaging, with formal implementation expected as early as next year. This will accelerate the shift from experience-based decision-making to precision-guided navigation in prostate cancer care, improving radical resection rates, functional preservation, and patient quality of life simultaneously.
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Urology Frontier
Q: In early 2025, your team published a study on AI-based evaluation of renal CT images and pathology reports in Nature Communications. How do you view the future application of AI in this field?
Professor Guo Jianming: Artificial intelligence is fundamentally reshaping urologic practice, with particularly striking impact in renal cancer. In our multicenter study, we built a large-scale model using more than 13,000 preoperative CT datasets. The work was published in Nature Communications and recognized as a Best Abstract in Renal Cancer at the 39th Annual Congress of the European Association of Urology.
Clinically, this AI technology addresses three key challenges:
First, enabling “virtual biopsy.” Preoperative assessment requires determination of benign versus malignant disease, tumor grade and invasiveness, and prognosis. Conventional imaging struggles with certain differentials (e.g., clear cell vs. non–clear cell carcinoma). Our model achieved a benign-disease classification accuracy of 89.8%, offering substantial value for primary hospitals and less experienced radiologists when combined with clinical judgment—helping avoid unnecessary surgery.
Second, improving grading and invasiveness assessment. Trained on over 10,000 cases, our model improves accuracy in risk stratification and invasiveness prediction by 17% versus international benchmarks, with prognostic accuracy approaching 90%, enabling individualized risk assessment.
Third, advancing intelligent pathology reporting. Our Renal Masses pathology model automatically identifies nine renal cancer subtypes—including rare entities—with 97% classification accuracy. Its grading performance approaches that of subspecialty renal pathologists, helping address workforce shortages, reduce human error, and improve standardization.
Looking ahead, with multimodal data fusion and dynamic monitoring, AI will increasingly empower the entire renal cancer pathway—from precise preoperative diagnosis and intraoperative planning to postoperative surveillance—driving care toward greater precision, personalization, and intelligence.
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Urology Frontier
Q: Your department has recently introduced a new domestically developed robotic surgical system. How do you envision the interaction between domestic robotics, AI, and holographic imaging in advancing precision urologic oncology?
Professor Guo Jianming: Robotic surgery has become a powerful tool for complex precision tasks. Its stable platform and wristed instruments reduce tremor during radical prostatectomy, improving continence preservation and neurovascular bundle protection. In nephron-sparing surgery, robotics shortens warm ischemia time and reduces complications.
Although China has fewer robotic systems than the United States, clinical demand is far greater, accelerating innovation. Domestic systems now match imported devices in operability, flexibility, and latency, and have advanced in 5G-enabled remote surgery, image fusion, and navigation.
The key advantage of domestic platforms is open architecture, enabling deep integration with holographic imaging, fluorescence labeling, and intelligent navigation—across image fusion, guidance, fluorescence-assisted identification, and remote surgery, consultation, and education. Combined with substantially lower costs, this openness improves accessibility and scalability.
We are confident that through integrated innovation, domestic robotic platforms can achieve “curve overtaking,” pushing urologic oncology toward a future that is both more precise and more intelligent.
Author Biography
Professor Guo Jianming is a leading urologic oncologist at Zhongshan Hospital, Fudan University, specializing in precision diagnosis and treatment of urologic malignancies, with a particular focus on holographic medical imaging, artificial intelligence–assisted diagnosis, and robotic surgery.
