Part 1
Introduction
With the rapid development of technology and artificial intelligence, modern neurosurgery is continuously breaking through towards minimally invasive, precise, and efficient techniques. Neurosurgery robots, as core equipment, will play an increasingly important role.
Neurosurgery has always faced challenges such as limited surgical space and difficult positioning. Since surgeries often require operations on specific neural tissues, precision is crucial, which can be challenging for surgeons to achieve. Therefore, performing precise actions with robots under medical imaging guidance has become the preferred surgical method for many doctors. Below, Professor Xu Jiajun will provide a detailed introduction.
Part 2
Advantages of Robot-Assisted Neurosurgery
Robot-assisted neurosurgery has the following advantages: ① Robots have a dexterous structure and devices that can achieve precise positioning and maintain stable surgical posture, allowing for accurate surgery; ② Advanced robotic control technology and user-friendly human-machine interface technology can enhance surgical precision and dexterity (for instance, using robotic operations can eliminate hand tremors and improve the surgeon’s skills), making surgeries more minimally invasive; ③ Robots can work continuously without fatigue during the procedure, ensuring stability and reliability; ④ Remote surgeries can be performed; ⑤ They provide an ergonomically suitable operating environment, minimizing the operator’s fatigue, thereby improving surgical safety.
Part 3
Neurosurgery Robot Systems
In the mid-1980s, the PUMA (Programmable Universal Machine for Assembly industrial robot) was the first robot used in neurosurgery.
Surgeons input the coordinates of the lesion based on preoperative imaging and use the robot to guide the puncture needle for biopsy, initially in conjunction with a stereotactic surgical frame.
For example, the American Cartesian robot system (mpass International, Rochester, MN) and NeuroMate (Integrated Surgical Systems, Sacramento, CA) were among the first neurosurgery robots approved by the FDA for clinical use, capable of performing stereotactic surgeries.
Imaging is used for surgical planning, followed by the passive mechanical arm completing the surgery. It can lock joints and accurately deliver instruments like puncture needles and electrodes to the designated target, guiding the surgeon in performing biopsies, foreign body removal, cyst aspiration, and other operations. NeuroMate utilizes preoperative imaging data for positioning, but if brain tissue shifts occur, systemic errors significantly increase. Currently, newer versions are in clinical application. It passively delivers surgical instruments to the surgical site, functioning as a semi-automatic robot. Minerva (University of Lausanne, Lausanne, Switzerland) was the first system to provide real-time imaging guidance, enabling frameless stereotactic surgery. It is installed under a CT machine, utilizing intraoperative scans to overcome brain tissue displacement issues. Although it improved precision, its utilization was low since patients had to undergo surgery under a CT machine, leading to the cessation of Minerva’s research two years later.
Early neurosurgery robot systems were primarily used for stereotactic surgery or surgical positioning. In the mid-1990s, NASA developed the RAMS (Robot-Assisted Microsurgery System), which was the first robot to be compatible with nuclear magnetic imaging. The system is based on a six-degree-of-freedom active-passive (master-slave) control, allowing for 3-D operations, thus not limited to stereotactic surgery. RAMS performed tremor filtering and gradient operation, significantly enhancing surgical precision and dexterity. Le Roux et al. applied RAMS for carotid artery anastomosis in rats, achieving successful outcomes, although the surgical time was longer than manual surgeries.
Joskowicz L et al. introduced an imaging-guided system capable of precise automatic positioning in laparoscopic surgery. The system is a MARS micro robot suitable for mechanical guidance of puncture needles, probes, and catheters. The robot is directly fixed to the scalp clamp or skull during the procedure. It can achieve pre-determined target positioning based on preoperative CT/MRI anatomical registration and intraoperative 3D facial scans of the patient. Registration trials using this system showed a target registration error of 1.7 mm (SD=0.7 mm).
Part 4
Remote Operation Neurosurgery Robot Systems
In the past decade, the rapid advancement of multimedia and information network technology, built on effective computer graphics, has provided technical support for remote human-machine communication, making the dream of remote surgery gradually a reality. Surgeries are controlled by surgeons remotely through a remote control system, managing robots at the surgical site. Remote operation surgical robot systems involve a wide range of high-tech fields, as remote medical care requires the transmission of large amounts of medical information, including data, text, video, audio, and images, which demands high real-time performance and reliability, placing high demands on communication networks. Particularly, to control the robot system over long distances, analysis and compensation for communication delays in the remote operation environment are necessary to overcome latency issues. Several remote-operated neurosurgery robot systems are currently being researched abroad.
NeuRobot (Shinshu University School of Medicine, Matsumoto, Japan) is a remote micro neurosurgery robot developed in Japan. NeuRobot is a microsurgery system that can be operated remotely. It mainly consists of four parts: a micro manipulator (passive slave manipulator), manipulator support device, surgical operation device (active master manipulator), and a 3D display. The micro manipulator is equipped with three 1-mm end-effectors and a 3D endoscope. Each instrument has three degrees of freedom (rotation, bending, forward/backward movement) and can be controlled remotely. The surgeon can perform precise surgical operations without direct contact with the patient. This system successfully performed simulated surgeries on a cadaver’s head for lateral fissure opening and third ventricle incision. It was also successfully used in surgery for a 54-year-old male with recurrent atypical meningioma, removing the tumor without any robot-related complications, and the patient recovered smoothly after surgery. After the basic experiments of NeuRobot surgeries were completed, precise simulated surgeries on rats were conducted remotely (40 kilometers away). In recent years, although various neurosurgery robots have been developed, clinical applications of remote-controlled robotic systems capable of performing multiple surgical operations remain rare. The use of robots for microsurgery has been reported for the first time in this case.
Robot Remote Collaboration System
(Socrates; Computer Motion, Inc., Santa Barbara, CA) is one of the first remote collaboration systems approved by the FDA in the USA.
Using the Socrates system, it is possible to control the robotic arm’s movements from a distant operating room, processing dual-channel video, voice communication, and transmitting neuro-navigation data. Four integrated service digital networks provide a transmission speed of 512Kb/s. Basic research has provided long-distance communication between a university college and a community center 400 kilometers away. The supervisor can directly control the endoscope based on real-time neuro-navigation data and can communicate with the surgical site via voice and video. The system can directly control the mechanical arm (AESOP) for surgery. Six surgeries have been conducted with remote guidance, including three craniotomies for brain tumor removal, one arteriovenous malformation excision, one carotid endarterectomy, and one lumbar disc removal. All six patients recovered smoothly, with no surgical complications. The guided neurosurgeons believed that remote guidance was beneficial in all cases, especially critical in excising medial temporal gliomas and occipital arteriovenous malformations. Practical results indicate that robot remote guidance is feasible, reliable, and safe. Remote guidance has great potential in enhancing surgical care and training in neurosurgery, bringing high-level neurosurgical services to the world.
The NeuroArm (University of Calgary, Calgary, Alberta, Canada) project, funded with $30 million, includes all the operations that neurosurgeons need to perform intracranially. It is designed based on biological mimicry, allowing mechanical arms (holding surgical instruments) to simulate hand movements. NeuroArm consists of two robotic arms, each with seven degrees of freedom, plus a third arm with two cameras providing stereoscopic images. NeuroArm can perform microsurgical operations, including biopsies, microsurgery, cutting, blunt dissection, clamping, electrocautery, burning, traction, cleaning instruments, suctioning, and suturing. It can also provide haptic pressure feedback to the surgeon. The NeuroArm workstation is unique, replicating the surgical scene as closely as possible, providing auditory, visual, and tactile experiences. Robotic sensors and MRI display 3D brain tissue images on the screen. In terms of safety, NeuroArm filters out hand tremors and has a safety switch to prevent accidental movements. NeuroArm can plan surgical boundaries preoperatively, and all materials are compatible with MRI, allowing for intraoperative MRI scanning. The robotic arms are made of titanium alloy and polymer plastic, resulting in minimal distortion of MRI images. NeuroArm can perform stereotactic surgeries, accurately reaching targets through linear drive mechanisms. The NeuroArm imaging guidance system can utilize virtual reality to simulate the surgical process preoperatively. This robotic system is currently undergoing testing, with plans for clinical use within two years.
Part 5
Conclusion
Neurosurgery robots have developed rapidly in recent years, but there are still many technologies that need improvement, such as enhancing the human-machine interface; improving dexterity, as robotic movements are slower than human hands; further enhancing haptic and pressure feedback; miniaturizing temperature sensors and instrument tip sensors; and improving 3-D navigational spatial awareness. Furthermore, robots must better adapt to the deformability of brain tissue, as current imaging technologies still cannot achieve 100% real-time imaging. NASA has developed various micro-sensors that effectively address this issue. It utilizes optimal spectra, microelectrode recording, micro hemodynamics, and micro-endoscopy to collect large amounts of tissue data in real-time, determining the characteristics of the tissue. It is anticipated that in the near future, more advanced, precise, and stable neurosurgery robots will be widely applied in clinical settings.