Evidence map›Paper›PMID 38930758›Full record

ArticleMicromachines2024

Design and Evaluation of an Eye Mountable AutoDALK Robot for Deep Anterior Lamellar Keratoplasty.

Justin D Opfermann, Yaning Wang, James Kaluna, Kensei Suzuki, William Gensheimer, Axel Krieger, Jin U Kang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Justin D OpfermannDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0002-1079-3986
Yaning WangLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA.
James KalunaDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Kensei SuzukiDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
William GensheimerOphthalmology Section, White River Junction Veterans Affairs Medical Center, White River Junction, VT 05009, USA.
Axel KriegerDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.ORCID 0000-0001-8169-075X
Jin U KangLaboratory for Computational Sensing and Robotics, Johns Hopkins University, Baltimore, MD 21218, USA.

Funding

Artificial intelligence Optical Coherence Tomography Guided Deep Anterior Lamellar Keratoplasty (AUTO-DALK)R01EY032127 · NEI · JOHNS HOPKINS UNIVERSITY · PI KANG, JIN U · 2021 to 2024
$1.6M
NIH HHS 5R01EY032127-03A1
6 · The paper itself

Abstract

Partial-thickness corneal transplants using a deep anterior lamellar keratoplasty (DALK) approach has demonstrated better patient outcomes than a full-thickness cornea transplant. However, despite better clinical outcomes from the DALK procedure, adoption of the technique has been limited because the accurate insertion of the needle into the deep stroma remains technically challenging. In this work, we present a novel hands-free eye mountable robot for automatic needle placement in the cornea, AutoDALK, that has the potential to simplify this critical step in the DALK procedure. The system integrates dual light-weight linear piezo motors, an OCT A-scan distance sensor, and a vacuum trephine-inspired design to enable the safe, consistent, and controllable insertion of a needle into the cornea for the pneumodissection of the anterior cornea from the deep posterior cornea and Descemet's membrane. AutoDALK was designed with feedback from expert corneal surgeons and performance was evaluated by finite element analysis simulation, benchtop testing, and ex vivo experiments to demonstrate the feasibility of the system for clinical applications. The mean open-loop positional deviation was 9.39 µm, while the system repeatability and accuracy were 39.48 µm and 43.18 µm, respectively. The maximum combined thrust of the system was found to be 1.72 N, which exceeds the clinical penetration force of the cornea. In a head-to-head ex vivo comparison against an expert surgeon using a freehand approach, AutoDALK achieved more consistent needle depth, which resulted in fewer perforations of Descemet's membrane and significantly deeper pneumodissection of the stromal tissue. The results of this study indicate that robotic needle insertion has the potential to simplify the most challenging task of the DALK procedure, enable more consistent surgical outcomes for patients, and standardize partial-thickness corneal transplants as the gold standard of care if demonstrated to be more safe and more effective than penetrating keratoplasty.

Indexed as

body mountable roboticsdeep anterior lamellar keratoplastymicro-roboticsoptical coherence tomographypiezoelectric

Identifiers

PMID38930758
PMCPMC11205909

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.