Adaptive Control of Sclera Force and Insertion Depth for Safe Robot-Assisted Retinal Surgery

Background: As an advanced surgical technique to reduce trauma to the inner ear, robot-assisted electrode array (EA) insertion has been applied in adult cochlear implantation (CI) and was approved as a safe surgical procedure that could result in better outcomes. As the mastoid and temporal bones are generally smaller in children, which would increase the difficulty for robot-assisted manipulation, the clinical application of these systems for CI in children has not been reported. Given that the pediatric candidate is the main population, we aim to investigate the safety and reliability of robot-assisted techniques in pediatric cochlear implantation.Methods: Retrospective cohort study at a referral center in Shanghai including all patients of simultaneous bilateral CI with robotic assistance on one side (RobOtol® system, Collin ORL, Bagneux, France), and manual insertion on the other (same brand of EA and CI in both side), from December 2019 to June 2020. The surgical outcomes, radiological measurements (EA positioning, EA insertion depth, mastoidectomy size), and audiological outcomes (Behavior pure-tone audiometry) were evaluated.Results: Five infants (17.8 ± 13.5 months, ranging from 10 to 42 months) and an adult (39 years old) were enrolled in this study. Both perimodiolar and lateral wall EAs were included. The robot-assisted EA insertion was successfully performed in all cases, although the surgical zone in infants was about half the size in adults, and no difference was observed in mastoidectomy size between robot-assisted and manual insertion sides (p = 0.219). The insertion depths of EA with two techniques were similar (P = 0.583). The robot-assisted technique showed no scalar deviation, but scalar deviation occurred for one manually inserted pre-curved EA (16%). Early auditory performance was similar to both techniques.Conclusion: Robot-assisted technique for EA insertion is approved to be used safely and reliably in children, which is possible and potential for better scalar positioning and might improve long-term auditory outcome. Standard mastoidectomy size was enough for robot-assisted technique. This first study marks the arrival of the era of robotic CI for all ages.

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A MECHANICS-BASED MODEL FOR SIMULATING THE NEEDLE DEFLECTION IN TRANSVERSE ISOTROPIC TISSUE FOR A PERCUTANEOUS PUNCTURE

Journal of Mechanics in Medicine and Biology ◽

10.1142/s021951941950060x ◽

2019 ◽

Vol 19 (06) ◽

pp. 1950060 ◽

Cited By ~ 1

Author(s):

WANYU LIU ◽

ZHIYONG YANG ◽

SHAN JIANG

Keyword(s):

Needle Insertion ◽

Robot Assisted ◽

Insertion Depth ◽

Interaction Forces ◽

Percutaneous Puncture ◽

Needle Deflection ◽

Isotropic Elasticity ◽

Transverse Isotropic ◽

Radioactive Seeds ◽

Medical Needle

During the percutaneous puncture for robot-assisted brachytherapy, a medical needle is usually inserted into fiber-structured soft tissue which has transverse isotropic elasticity, such as muscle and skin, to deliver radioactive seeds that kill cancer cells. To place the radioactive seeds more accurately, it is necessary to assess the effect of the transverse isotropic elasticity on the needle deflection. A mechanics-based model for simulating the needle deflection in transverse isotropic tissue is developed in this paper. The anisotropic needle–tissue interaction forces are estimated and used as inputs to drive the model for simulating needle deflections for different insertion orientation angles. Automatic insertion experiments were performed on a single-layered porcine muscle at five different insertion orientation angles. The results show that the maximum difference in the tip deflection for the different insertion orientation angles is 2.99[Formula: see text]mm when the insertion depth is 50[Formula: see text]mm. The maximum simulated error of the needle axis deflection is 0.62[Formula: see text]mm for all insertion orientation angles. The developed model can successfully simulate the needle deflections inside transverse isotropic tissue for different insertion orientation angles. This work is useful for predicting and compensating for the deflection error for automatic needle insertion.

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FBG-based Kalman Filtering and Control of Tool Insertion Depth For Safe Robot-assisted Vitrectomy

2020 International Symposium on Medical Robotics (ISMR) ◽

10.1109/ismr48331.2020.9312931 ◽

2020 ◽

Author(s):

Ali Ebrahimi ◽

Muller Urias ◽

Niravkumar Patel ◽

Peter Gehlbach ◽

Farshid Alambeigi ◽

...

Keyword(s):

Kalman Filtering ◽

Robot Assisted ◽

Insertion Depth ◽

And Control

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Robot-Assisted Retinal Surgery: Overcoming Human Limitations

Surgical Retina - Retina Atlas ◽

10.1007/978-981-13-6214-9_11 ◽

2019 ◽

pp. 109-114 ◽

Cited By ~ 2

Author(s):

K. Xue ◽

T. L. Edwards ◽

H. C. M. Meenink ◽

M. J. Beelen ◽

G. J. L. Naus ◽

...

Keyword(s):

Robot Assisted ◽

Retinal Surgery

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Force sensing micro-forceps for robot assisted retinal surgery

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/embc.2012.6346201 ◽

2012 ◽

Cited By ~ 28

Author(s):

I. Kuru ◽

B. Gonenc ◽

M. Balicki ◽

J. Handa ◽

P. Gehlbach ◽

...

Keyword(s):

Force Sensing ◽

Robot Assisted ◽

Retinal Surgery

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Artificial intelligence, robotics and eye surgery: are we overfitted?

International Journal of Retina and Vitreous ◽

10.1186/s40942-019-0202-y ◽

2019 ◽

Vol 5 (1) ◽

Cited By ~ 1

Author(s):

Müller G. Urias ◽

Niravkumar Patel ◽

Changyan He ◽

Ali Ebrahimi ◽

Ji Woong Kim ◽

...

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Graphics Processing Units ◽

Development Effort ◽

Robot Assisted ◽

Retinal Surgery ◽

Eye Surgery ◽

Physiological Limits ◽

Stage Of Development ◽

Technological Advances

AbstractEye surgery, specifically retinal micro-surgery involves sensory and motor skill that approaches human boundaries and physiological limits for steadiness, accuracy, and the ability to detect the small forces involved. Despite assumptions as to the benefit of robots in surgery and also despite great development effort, numerous challenges to the full development and adoption of robotic assistance in surgical ophthalmology, remain. Historically, the first in-human–robot-assisted retinal surgery occurred nearly 30 years after the first experimental papers on the subject. Similarly, artificial intelligence emerged decades ago and it is only now being more fully realized in ophthalmology. The delay between conception and application has in part been due to the necessary technological advances required to implement new processing strategies. Chief among these has been the better matched processing power of specialty graphics processing units for machine learning. Transcending the classic concept of robots performing repetitive tasks, artificial intelligence and machine learning are related concepts that has proven their abilities to design concepts and solve problems. The implication of such abilities being that future machines may further intrude on the domain of heretofore “human-reserved” tasks. Although the potential of artificial intelligence/machine learning is profound, present marketing promises and hype exceeds its stage of development, analogous to the seventieth century mathematical “boom” with algebra. Nevertheless robotic systems augmented by machine learning may eventually improve robot-assisted retinal surgery and could potentially transform the discipline. This commentary analyzes advances in retinal robotic surgery, its current drawbacks and limitations, and the potential role of artificial intelligence in robotic retinal surgery.

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