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Proof-of-concept of a robotic-driven photogrammetric scanner for intra-operative knee cartilage repair
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  • Álvaro Bertelsen,
  • Amaia Iribar-Zabala,
  • Ekiñe Otegi-Alvaro,
  • Rafael Benito,
  • Karen López-Linares,
  • Iván Macía
Álvaro Bertelsen
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)

Corresponding Author:[email protected]

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Amaia Iribar-Zabala
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)
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Ekiñe Otegi-Alvaro
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)
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Rafael Benito
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)
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Karen López-Linares
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)
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Iván Macía
Vicomtech Foundation, Basque Research and Technology Alliance (BRTA)
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Abstract

This work present a proof-of-concept of a robotic-driven intra-operative scanner designed for knee cartilage lesion repair, part of a system for direct in vivo bioprinting. The proposed system is based on a photogrammetric pipeline, which reconstructs the cartilage and lesion surfaces from sets of photographs acquired by a robotic-handled endoscope, and produces 3D grafts for further printing path planning. A validation on a synthetic phantom is presented, showing that —despite the cartilage smooth and featureless surface— the current prototype can accurately reconstruct osteochondral lesions and their surroundings with mean error values of 0.199 ± 0.096 mm but with noticeable concentration on areas with poor lighting or low photographic coverage. The system can also accurately generate grafts for bioprinting, although with a slight tendency to underestimate the actual lesion sizes, producing grafts with coverage errors of -12.2 ± 3.7, -7.9 ± 4.9 and -15.2 ± 3.4 % for the medio-lateral, antero-posterior and craneo-caudal directions respectively. Improvements in lighting and acquisition for enhancing reconstruction accuracy are planned as future work, as well as integration into a complete bioprinting pipeline and validation with ex vivo phantoms.
30 Oct 2023Submitted to Healthcare Technology Letters
01 Nov 2023Submission Checks Completed
01 Nov 2023Assigned to Editor
15 Nov 2023Reviewer(s) Assigned
15 Nov 2023Review(s) Completed, Editorial Evaluation Pending
17 Nov 2023Editorial Decision: Accept