Harnessing artificial intelligence to bridge the neurosurgery gap in low-income and middle-income countries

The Future of Sustainable Neurosurgery: Is a Moonshot Plan for Artificial Intelligence and Robot-Assisted Surgery Possible in Japan?

Japanese neurosurgery faces challenges such as a declining number of neurosurgeons and their concentration in urban areas. Particularly in rural areas, access to neurosurgical care for patients with conditions, such as stroke, is limited, raising concerns about the collapse of regional healthcare. Robot-assisted surgical technologies have advanced in recent years, contributing to the improved precision and safety of deep brain surgery. This study proposes the "Artificial Intelligence (AI) and Robot-Assisted Surgery Moonshot Plan" for Japan, comprising 5 pillars: 1) establishment of regional medical centers, 2) development of remote surgery systems, 3) enhancement of robotic-assisted surgery training programs, 4) integration of AI technologies, and 5) promotion of industry-academia-government collaboration. In addition, strengthening the approach to spinal surgery is expected to revitalize regional medical centers, optimize the number of neurosurgeons, improve surgical skills, and promote minimally invasive surgery. This study analyzed the current status and challenges of Japanese neurosurgery through a literature review and statistical analysis. AI is used in various aspects of neurosurgery, including diagnostic support, surgical planning and navigation, treatment outcome prediction, intraoperative monitoring, robot-assisted surgery, and rehabilitation. However, challenges, such as data bias, ethical issues, costs, and regulations, remain. In Japan, issues such as the uneven distribution and decline of neurosurgeons, collapse of regional healthcare, and increase in the number of patients with spinal disorders due to aging have been highlighted. The "AI and Robot-Assisted Surgery Moonshot Plan" serves as a guide to overcome the challenges of neurosurgery in Japan and establish a sustainable medical system.

Fluorescence visualization for cancer DETECTION: EXPERIENCE and perspectives

The current review focuses on the latest advances in the improvement and application of fluorescence imaging technology. Near-infrared (NIR) fluorescence imaging is a promising new technique that uses non-specific fluorescent agents and targeted fluorescent tracers combined with a dedicated camera to better navigate and visualize tumors. Fluorescence-guided surgery (FGS) is used to perform various tasks, helping the surgeon to distinguish lymphatic vessels and nodes from surrounding tissues easily and quickly assess the perfusion of the planned resection area, including intraoperative visualization of metastases. The results of the insertion of fluorescence visualization as an auxiliary method to cancer detection and high-risk metastatic lesions in clinical practice have demonstrated enthusiastic results and huge potential. However, intraoperative fluorescence visualization must not be considered as a main diagnostic or treatment method but as an aid to the surgeon. Thus, fluorescence study does not dispense the diagnostic gold standards of benign or malignant tumors (conventional examination, biopsy, ultrasonography and computed tomography, etc.) and can be done usually during intraoperative treatment. Moreover, as fluorescence surgery and fluorescence diagnostic techniques continue to improve, it is likely that they will evolve towards targeted fluorescence imaging probes that will increasingly target a specific type of cancer cell. The most important point remains the search for highly selective messengers of fluorescent labels, which make it possible to identify tumor cells exclusively in the affected organs and indicate to surgeons the boundaries of their spread and metastasis.