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56. Development and Characterization of a Cranial Bone Cutting Snake Robot for Craniosynostosis Surgery

2025· article· en· W4410011905 on OpenAlexaff
Jones Law, Emma Stickley, Radian Gondokaryono, Thomas Looi, Eric Diller, Dale J. Podolsky

Bibliographic record

VenuePlastic & Reconstructive Surgery Global Open · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsCraniosynostosisCranial boneMedicineOrthodonticsSurgerySkull

Abstract

fetched live from OpenAlex

PURPOSE: There is an evolution towards more minimally invasive approaches for the treatment of patients with craniosynostosis. Minimally invasive approaches utilize rigid, straight instruments, which limits the extent of the osteotomies possible along the curvature of the skull using minimal access incisions. The ability to perform more extensive osteotomies using minimal access incisions may provide more patients with craniosynostosis the option and benefits of minimally invasive surgery. The following study involves the development and characterization of a novel, minimally invasive robotic bone cutting tool for craniosynostosis surgery that allows for extensive osteotomies through a minimal access incision. METHODS: A novel snake robot was developed for navigation along the cranium that was coupled to a 7-degree-of-freedom industrial manipulator for controlling its position and orientation. The snake robot comprises an end-effector, a bending section with two segments, and an actuation unit. The end-effector incorporates a bone punch, a dural and scalp retractor, as well as channels for an endoscope and surgical instruments. The bending mechanism utilizes a geared linkage design which allows for the segments to articulate in a smooth constant curvature shape. The bending actuation is controlled via pre-tensioned antagonistic cables that allow the robot to modulate its stiffness under external loads. A follow-the-leader algorithm was implemented to guide the robot along skull-cutting paths. Three experiments were performed: (1) a kinematics accuracy test validating the mapping between cable length and bending configuration, (2) a stiffness characteristics by applying an external load to measure tip deflection under varying bending configurations and (3) an ex-vitro trial to demonstrate the manipulator’s reachability along three-dimensionally (3D) printed craniosynostosis skull models. RESULTS: Accuracy testing demonstrated bending errors of 15.9° and 11.5° for the two segments at maximum bending angles of 60° and 90°, respectively, with position errors ranging from 2.5 to 21.5 mm during path tracing. The stiffness of the tool increased with tendon pre-tensioning from 20-100 N during bent configurations for both segments at specific bending angles. Tip deflection was reduced from 0.42 to 0.03 cm and 0.37 to 0.10 cm during axial loading, and from 11.40 to 3.88 cm and 3.62 to 0.48 cm during radial loading for different configurations. Ex-vitro trials demonstrated the robot’s ability to perform simulated osteotomies on craniosynostosis skull models, achieving 68-73% of desired path lengths with a maximum deviation of 8 mm. CONCLUSION: This study presents a novel steerable snake robot with adjustable stiffness, capable of following predefined paths and performing osteotomies on simulated skull models. The results demonstrate that the proposed system holds significant potential as a promising new approach to cranial surgery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.260
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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