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Artificial intelligence-powered intraoperative nerve
monitoring: a visionary method to reduce facial
nerve palsy in parotid surgery: an editorial
Tooba Ali, MBBSa, Hibah Abid Imam, MBBSa, Biya Maqsood, MBBSa, Ifra Jawed, MBBSa, Iman Khan, MBBSa,
Md Ariful Haque, MBBS, MD, MPHb,c,d,*
Due to the facial nerve’s critical involvement in facial expression,
sensation, and overall patient’s quality of life, maintaining facial
nerve function after parotid surgery is of the utmost importance.
Despite the growing use of intraoperative facial nerve monitoring
during Parotid gland surgery and advancements in preoperative
radiological assessments, facial nerve injury (FNI) continues to be
the most serious consequence of parotid gland surgery (PGS).
Twenty to sixty-five percent of patients undergoing parotidectomy
experience temporary facial nerve dysfunction
[1]
,whereas0–7% of
patients experience permanent facial nerve dysfunction
[1]
.The
facial nerve regulates the muscles that move the face and is closely
connected to the parotid gland. Consequently, there is a risk of
injury to the facial nerve from any surgical procedure in this loca-
tion, which would have major functional and cosmetic con-
sequences. Parotid surgical problems that result from facial nerve
dysfunction can have both short-term and long-term effects. Acute
facial paralysis can cause significant physical changes, psychologi-
cal distress, difficulties swallowing, speaking, and closing one’s
eyes. Failure to maintain facial nerve function over time can result
in contractures, reduced facial symmetry, and synkinesis
(uncontrollable simultaneous movements of various facial muscles).
Intraoperative monitoring, rigorous surgical methods, and thor-
ough anatomical knowledge are necessary to maintain facial nerve
integrity during parotid surgery. Therefore, ensuring the greatest
outcome for patients after parotid surgery is still of utmost
importance to adhere to patient-centred care principles and
enhance their general quality of life. Conventional intraoperative
nerve monitoring, which makes use of methods such as nerve sti-
mulation and electromyography, is essential for procedures such as
thyroid and parotidectomy. By enabling real-time monitoring of
vital nerves, it improves patient outcomes by lowering the chance of
nerve damage and surgical consequences, like facial weakness or
vocal cord dysfunction, and enabling surgeons to make prompt
adjustments to their technique. Most of the early papers on using
facial nerve monitoring in parotid surgery were descriptive, giving a
general summary of the technique and its possible advantages
[2]
.
Since then, research has concentrated on case or historical controls
in retrospective or prospective case series to assess the safety and
effectiveness of nerve monitoring devices during parotid surgery.
Numerous investigations have demonstrated that postoperative
rates of facial paresis can be similar for patients undergoing
intraoperative facial nerve monitoring and those who do not
[3]
.
During parotid surgery, intraoperative facial nerve monitoring has
many benefits. One benefit is that surgeons can prevent iatrogenic
facial nerve injury by using real-time feedback on the location and
functional state of the facial nerve
[4]
. On the other hand, traditional
intraoperative nerve monitoring methods are also limited, as they
offer indirect feedback through muscle responses, which may not
reflect nerve integrity reliably
[5]
. Furthermore, traditional nerve
monitoring methods involve invasive nerve stimulation, posing
injury risks, and may not be suitable for cases with inaccessible
nerves or patients with preexisting neurological conditions
[6]
.Ina
HIGHLIGHTS
The study aims to:
•Improve intraoperative nerve monitoring (IONM): To
continuously monitor the location and health of the
patient’s unique facial nerve network during surgery, a
dynamic model of the patient’s nerve network is developed
using artificial intelligence algorithms.
•Prediction and prevention of nerve injury: By utilizing
artificial intelligence, the research aims to reduce the
danger of nerve injury by predicting possible problem
regions based on the anatomy of each particular patient
and taking preventative action.
•Enhancement of patient outcomes: In the end, the research
aims to increase surgical safety and precision, reduce the
incidence of postoperative Bell’s palsy, and improve patient
outcomes, including quality of life.
a
Dow University of Health Sciences, Mission Road, Karachi, Pakistan,
b
Department
of Public Health, Atish Dipankar University of Science and Technology,
c
Voice of
Doctors Research School, Dhaka, Bangladesh and
d
Department of Orthopedic
Surgery, Yan’an Hospital Affiliated to Kunming Medical University, Kunming, Yunnan,
China
Hypothesis: By offering real-time monitoring, predictive capabilities, and the ability to
leverage large datasets to improve surgical precision and patient outcomes,
integrating AI-driven intraoperative nerve monitoring during parotid surgery will
significantly reduce the incidence of facial nerve palsy.
Sponsorships or competing interests that may be relevant to content are disclosed at
the end of this article.
Published online 15 December 2023
*Corresponding author. Address: Department of Public Health, Atish Dipanka r
University of Science and Technology, Dhaka, Bangladesh, Voice of Doctors
Research School, Dhaka, Bangladesh, Department of Orthopedic Surgery, Yan’an
Hospital Affiliated to Kunming Medical University, Kunming 1213, Yunnan, China.
Tel.: +880 189 477 3747. E-mail arifulhaque58@gmail.com (Md A. Haque).
Received 10 October 2023; Accepted 2 December 2023
Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. This is an
open access article distributed under the terms of the Creative Commons
Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is
permissible to download and share the work provided it is properly cited. The work
cannot be changed in any way or used commercially without permission from the
journal.
Annals of Medicine & Surgery (2024) 86:635–637
http://dx.doi.org/10.1097/MS9.0000000000001612
’
Editorial
635
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recent study, authors examined the literature to develop standar-
dized facial nerve monitoring (FNM) procedures for parotid sur-
gery. These included general anaesthesia, FNM setup, application
of stimulus currents, interpretation of electrophysiologic signals,
prediction of the outcome of the facial expression, and pre-and
postoperative assessment of facial expressions. Additionally, the
scientists suggested a dynamic nerve network model that can
forecast how tumour removal will affect a person’sfacial
expressions
[7]
. During surgery, the dynamic nerve network model
allows for accurate mapping of the facial neural structures, changes
in the nerve routes, and real-time nerve health monitoring. This
approach draws inspiration from well-established techniques in
nerve monitoring and intraoperative imaging
[8]
. In recent years, the
integration of artificial intelligence (AI) into the field of medicine has
burgeoned, offering myriad benefits that are revolutionizing
healthcare. AI’s rapid integration into medicine has led to round-
the-clock access to medical information via chatbots, early disease
detection through electronic health record analysis, and improved
surgical precision with AI-driven systems. This synergy between AI
and human expertise reshapes healthcare for increased efficiency,
patient-centred care, and effectiveness. However, with the combi-
nation of human medical expertise and AI-based nerve monitoring,
the postoperative complications of facial nerve palsy (Bell’spalsy)
can be reduced to a great extent. In particular, the search to avoid
postoperative Bell’s palsy has been made easier because of the
introduction of AI into parotid surgery. AI shows enormous pro-
mise for reducing this risk because it analyzes data in real-time and
recognizes patterns
[1]
. Gathering high-resolution imaging data is
the first step in AI-enhanced nerve monitoring during parotid sur-
gery. The facial nerves of the patient can be precisely mapped
anatomically using cutting-edge imaging methods like high-fre-
quency ultrasound or intraoperative MRI. Following AI algo-
rithms’processing of this data, a detailed and dynamic model of the
nerve network unique to the patient’s anatomy can be produced.
The monitoring systems powered by AI used during surgery con-
tinuously monitor the position and condition of the facial nerves
and notify the surgical team of any abnormalities. With this in-the-
moment input, surgeons can fine-tune their procedures and prevent
accidental nerve damage. Additionally, based on the patient’s
particular nerve arrangement, AI can anticipate possible issue
locations, enabling preventative interventions. In this situation, AI’s
benefits go beyond real-time surveillance. Machine learning algo-
rithms can analyze large datasets of surgical outcomes, which can
spot trends that human surgeons would miss. This information can
influence best practices, which can also help surgical procedures
continue to advance. AI has a dual effect on nerve monitoring
during parotid surgery: first, it lowers the risk of postoperative
Bell’s palsy, improving patient outcomes, and second, it increases
the precision and safety of these delicate procedures
[9]
.WithAI
keeping an eye on the vital nerves, surgeons may securely man-
oeuvre the complicated anatomy of the parotid gland. Patients gain
from lower dangers and a better possibility that their facial nerve
function would remain intact following surgery. Medical AI and
IONM integration can perform with expert-level accuracy and
provide efficient care at scale
[10]
. AI is making breakthroughs in
healthcare systems, from databases to intraoperative video analysis.
Surgeons are in a strong position to contribute to the forthcoming
phase of AI, which focuses on producing evidence-based, real-time
clinical decision assistance to enhance patient care and surgeon
workflow
[11]
. AI is becoming increasingly crucial for surgical
decision-making to address various information sources, including
patient risk factors, anatomy, disease, natural history, patient
values, and cost, and help surgeons and patients predict the out-
comes of surgical decisions more accurately
[12]
. AI-assisted surgery
could direct a surgeon’s tool during an operation and use infor-
mation from previous procedures to impact the development of
new surgical techniques. By giving surgeons real-time feedback on
their performance, it has the potential to enhance surgical results
significantly. The risk of complications during surgery can be
minimized with this feedback, which can assist surgeons to perform
more precise motions. Artificial intelligence can learn complicated,
non-linear relationships between input variables and outcome
labels by practicing on vast amounts of electronically recorded
data. The technology can then make predictions using fresh, unused
data. The competence of surgeons and the quality of patient care
can both be enhanced by these accurate, interpretable, and risk-
sensitive predictions
[13]
. On the contrary, there may indeed be
hazards associated with using AI-based monitoring in surgical
settings, such as parotid surgery, as our editorial discusses. The
possibility of “false positives,”in which an artificial intelligence
system mistakenly detects an abnormality or situation that does not
genuinely exist, is a serious worry. This can lead to erroneous
information, resulting in needless procedures or changes to the
surgical technique. Furthermore, there is a greater risk associated
with an over-reliance on technology, whereby surgeons may have
an unhealthy level of confidence in the AI system, which could
result in complacency or a diminished value placed on their clinical
competence. To reduce these dangers, it’s imperative to strike a
balance between using AI to improve decision assistance and pre-
serving the vital role that a surgeon’s judgment plays.
Conclusion
In conclusion, incorporating AI into parotid surgery is a game-
changing strategy for the future of healthcare because it lowers
the danger of facial nerve damage and improves overall patient
outcomes. However, there are several factors to consider when
assessing the viability and scalability of deploying AI systems in a
broader healthcare setting. The capacity to use AI systems in
various healthcare environments and patient demographics is
essential to scalability. Ensuring AI systems can adjust to the
fluctuations in surgical techniques, patient demographics, and
healthcare infrastructure can be challenging. Scalability is also
significantly influenced by the accessibility of resources and the
incorporation of AI into current healthcare frameworks.
Evaluating the viability of integrating AI smoothly into standard
clinical operations is necessary to ensure practicality. Instead of
upending current procedures, AI should improve productivity
and decision-making. Practical AI integration requires addressing
user training, interoperability with current systems, and reducing
the impact on overall healthcare operations. Even while our
article emphasizes the potential advantages of AI in parotid sur-
gery, given the revolutionary nature of this technology, the
broader scalability and applicability of AI in healthcare necessi-
tate a thorough study of these complex issues. The goal of future
research and development must be to simplify the use of AI such
that it is both scalable and valuable for a variety of healthcare
settings.
Editorial. Annals of Medicine & Surgery (2024) Annals of Medicine & Surgery
636
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Future research directions
Although our work acknowledges the developing nature of this
subject and cites numerous crucial areas for future research, it
also looks forward to a hopeful future for AI in parotid surgery.
To improve AI algorithms’accuracy and predictive power,
ongoing optimization should be a top priority. This ongoing
development is essential to maximize these algorithms’perfor-
mance in real-world data and surgical results. Furthermore,
research is required to harmonize data collection techniques and
combine various datasets. Using this method will make it possible
to create reliable AI models that can be used for various surgical
circumstances and patient populations. Future studies should
address issues with patient permission, data privacy, and the
responsible use of AI in surgery by examining the creation of
precise ethical norms and solid regulatory frameworks as AI
becomes more incorporated into healthcare. To guarantee that
surgeons and other medical practitioners are competent in AI
tools, user-friendly interfaces and extensive training programs
must be prioritized. Comprehensive cost-benefit assessments will
be necessary to ascertain whether incorporating AI into parotid
surgery is economically feasible in the long run.
To conclude, comprehensive clinical validation research is
required to determine the effectiveness and safety of AI-assisted
parotid surgery in actual clinical settings. This research must
include prospective trials and comparison assessments with tra-
ditional procedures. To sum up, these avenues for future study
represent a thorough plan to further the field of artificial intelli-
gence in parotid surgery and encourage its possible use in general
healthcare settings.
Ethics approval
This type of article doesn’t need any ethical approval.
Consent
No patients were included.
Source of funding
Authors have not received any funds.
Author contribution
All authors have equally contributed to the manuscript and have
approved the final manuscript to be published.
Conflicts of interest disclosure
The authors declare that they have no financial conflicts of
interest with regard to the content of this report.
Research registration unique identifying number
(UIN)
This is not a clinical trial.
Guarantor
Tooba Ali.
Data availability statement
Not applicable.
Provenance and peer review
Not commissioned, externally peer-reviewed.
Permission to reproduce material from other sources
All articles are cited and references are given. This study has not
taken any material that needs permission.
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Editorial. Annals of Medicine & Surgery (2024)
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