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Review
. 2020 Oct:142:29-42.
doi: 10.1016/j.wneu.2020.06.172. Epub 2020 Jun 27.

The Future of Skull Base Surgery: A View Through Tinted Glasses

Affiliations
Review

The Future of Skull Base Surgery: A View Through Tinted Glasses

Laligam N Sekhar et al. World Neurosurg. 2020 Oct.

Abstract

In the present report, we have broadly outlined the potential advances in the field of skull base surgery, which might occur within the next 20 years based on the many areas of current research in biology and technology. Many of these advances will also be broadly applicable to other areas of neurosurgery. We have grounded our predictions for future developments in an exploration of what patients and surgeons most desire as outcomes for care. We next examined the recent developments in the field and outlined several promising areas of future improvement in skull base surgery, per se, as well as identifying the new hospital support systems needed to accommodate these changes. These include, but are not limited to, advances in imaging, Raman spectroscopy and microscopy, 3-dimensional printing and rapid prototyping, master-slave and semiautonomous robots, artificial intelligence applications in all areas of medicine, telemedicine, and green technologies in hospitals. In addition, we have reviewed the therapeutic approaches using nanotechnology, genetic engineering, antitumor antibodies, and stem cell technologies to repair damage caused by traumatic injuries, tumors, and iatrogenic injuries to the brain and cranial nerves. Additionally, we have discussed the training requirements for future skull base surgeons and stressed the need for adaptability and change. However, the essential requirements for skull base surgeons will remain unchanged, including knowledge, attention to detail, technical skill, innovation, judgment, and compassion. We believe that active involvement in these rapidly evolving technologies will enable us to shape some of the future of our discipline to address the needs of both patients and our profession.

Keywords: Artificial intelligence; Genetic engineering and antitumor antibodies; Raman spectroscopy; Skull base surgery; Stem cell technology.

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Figures

Figure 1
Figure 1
A patient with skull base chondrosarcoma. (A and B) Raman spectroscopy with an explanation of the various peaks present. (C) Hematoxylin and eosin–stained specimen. (D) Simulated Raman microscopy of fresh tissue from the patient.
Figure 2
Figure 2
The modern design of an artificial intelligence network compared with the human brain, which processes external signals and responds appropriately through the effector organs in the body.
Figure 3
Figure 3
(A) Artificial intelligence (AI) evaluation and treatment to guide a patient and primary care physician (PCP) through the diagnosis, required investigations, and appropriate referrals. (B) The AI system can also help trainees before surgery, educate and prepare the patient and employer, and, finally, provide feedback to the primary care physician and specialist. CISS, constructive interference in steady state; FIESTA, fast imaging employing steady-state acquisition; CNS, central nervous system; MRI, magnetic resonance imaging.
Figure 3
Figure 3
(A) Artificial intelligence (AI) evaluation and treatment to guide a patient and primary care physician (PCP) through the diagnosis, required investigations, and appropriate referrals. (B) The AI system can also help trainees before surgery, educate and prepare the patient and employer, and, finally, provide feedback to the primary care physician and specialist. CISS, constructive interference in steady state; FIESTA, fast imaging employing steady-state acquisition; CNS, central nervous system; MRI, magnetic resonance imaging.
Figure 4
Figure 4
The Raven II table-mounted robot for abdominal surgery in use experimentally (not approved for use in humans). It is table mountable and can accommodate 4 arms. A rapid tool changer has also been designed to change the surgical equipment.
Figure 5
Figure 5
(A) The Roboscope is shown with the actuator mechanism. (B) The bendable sheath has 6 channels at present. The top 2 (SFE 1.4 mm) are for the 2 laser endoscopes, the middle 2 (2.0 mm) are for the instruments (Inst), and the bottom 2 (1.1 mm) are for suction (S) devices. The channels can be modified to suit the surgical requirements.
Figure 6
Figure 6
(A) The Roboscope with 2 different dimensions (14 and 8 mm). (B) The Roboscope shown bent, with the 2 tools in close up.
Figure 7
Figure 7
The Karns introducer device for the Roboscope is shown with (A) the tulip closed and (B) the tulip open.
Figure 8
Figure 8
Cadaveric use of the Roboscope. (A) Introduction of the Roboscope through an opening in the skull base of a cadaver. (B) Remote manipulation of the controls. (C) The view of the structures through the laser fiberoptic endoscope (courtesy of Eric Seibel, PhD).
Figure 9
Figure 9
Concept of the artificially intelligent robotic assistant showing (A) the surgeon and robotic assistant and (B) the surgeon, a human assistant, and a robotic assistant.
Figure 10
Figure 10
Ground truth (GT) annotation for identifying instruments in a surgical field through the NeuroID dataset generated by the University of Washington team. (A) Input frame. (B) Annotations were created using the LabelMe annotation tool. (C) GT for distinguishing tool versus background (e.g., tissue, gauze). (D) GT for locating each class of instrument in pixel space.
Figure 11
Figure 11
Conceptualization of the android robotic nurse helper (NH) for a patient in isolation because of an infection. The physician (P) and nurse (N) are able to remotely view the patient and all vital signs, sense palpation using haptic sensors, and instruct the robotic nurse helper. The android robotic nurse helper is present with the patient continuously around the clock and is able to sterilize itself using ultraviolet (UV) light or other methods.

Comment in

References

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