Computer-assisted and image-guided surgery for surgical lymph-nodal staging of gynecologic cancer in the era of digital and robotic surgery: a review of current evidence

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Authors: Matteo Pavone, Lise Lecointre, Nicolò Bizzarri, Anna Fagotti, Denis Querleu, Barbara Seeliger
Cited by: 1
References: 76

Abstract

Accurate lymph node staging is central to prognostic stratification and therapeutic decision-making in gynecologic oncology. Yet, conventional systematic lymphadenectomy frequently results in excessive treatment for node-negative patients, who represent the majority of cases, and is associated with significant morbidity. This review highlights how digital and imaging technologies are redefining intraoperative lymph node assessment. Real-time optical biopsies with full-field optical coherence tomography or high-frequency ultrasound, coupled with artificial intelligence-assisted image analysis, promise to enhance the precision, efficiency, and safety of nodal evaluation. Although the impact of robotic-assisted laparoscopy on oncologic outcomes compared with conventional approaches remains debated, its role as a versatile platform for the integration of digital assistance tools is steadily expanding. The convergence of these innovations is driving a shift from extensive dissections to selective, image-guided interventions to detect micrometastases intraoperatively. Ultimately, advances in intraoperative imaging and AI may make nodal excision unnecessary when a reliable negative assessment can be achieved. This paves the way for smart operating rooms where technology and surgical expertise converge to deliver safer, more efficient, and personalized oncologic care. Funding: This work was supported by French state funds managed by the ANR within the 'Programme d'investissements d'avenir' France 2030 (reference ANR-10-IAHU-02).

Fields of Study & Subjects

Endometrial and Cervical Cancer Treatments Ovarian cancer diagnosis and treatment Surgical Simulation and Training

Publication details

Journal / source
EClinicalMedicine
Publisher
Elsevier BV
Volume
97
Pages
103869–103869
Publication date
15 June 2026
Language
EN