Literature DB >> 31751219

Optical Coherence Tomography Guided Robotic Needle Insertion for Deep Anterior Lamellar Keratoplasty.

Mark Draelos, Gao Tang, Brenton Keller, Anthony Kuo, Kris Hauser, Joseph A Izatt.   

Abstract

OBJECTIVE: Deep anterior lamellar keratoplasty (DALK) significantly reduces the post-transplantation morbidity in patients eligible for partial-thickness cornea grafts. The popular "big bubble" technique for DALK is so challenging, however, that a significant fraction of corneal pneumodissection attempts fail for surgeons without extensive DALK-specific experience, even with previous-generation cross-sectional optical coherence tomography (OCT) guidance. We seek to develop robotic, volumetric OCT-guided technology capable of facilitating or automating the difficult needle insertion step in DALK.
METHODS: Our system provides for real-time volumetric corneal imaging, segmentation, and tracking of the needle insertion to display feedback for surgeons and to generate needle insertion plans for robotic execution. We include a non-automatic mode for cooperative needle control for stabilization and tremor attenuation, and an automatic mode in which needle insertion plans are generated based on OCT tracking results and executed under surgeon hold-to-run control by the robot arm. We evaluated and compared freehand, volumetric OCT-guided, cooperative, and automatic needle insertion approaches in terms of perforation rate and final needle depth in an ex vivo human cornea model.
RESULTS: Volumetric OCT visualization reduces cornea perforations and beneficially increases final needle depth in manual insertions by clinically significant amounts. Our automatic robotic needle insertion techniques meet or exceed surgeon performance in both needle placement and perforation rate.
CONCLUSION: Volumetric OCT is a key enabler for surgeons, although robotic techniques can reliably replicate their performance. SIGNIFICANCE: Robotic needle control and volumetric OCT promise to improve outcomes in DALK.

Entities:  

Mesh:

Year:  2019        PMID: 31751219      PMCID: PMC7365552          DOI: 10.1109/TBME.2019.2954505

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  39 in total

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Authors:  Paramjit K Bhullar; Oscar M Carrasco-Zevallos; Alexandria Dandridge; Neel D Pasricha; Brenton Keller; Liangbo Shen; Joseph A Izatt; Cynthia A Toth; Anthony N Kuo
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Authors:  Brenton Keller; Mark Draelos; Gao Tang; Sina Farsiu; Anthony N Kuo; Kris Hauser; Joseph A Izatt
Journal:  Biomed Opt Express       Date:  2018-05-21       Impact factor: 3.732

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