HARLI: Real-time High-Fidelity Augmented Reality For Liver Resection

  • Research type

    Research Study

  • Full title

    Real-time High-Fidelity Augmented Reality in Laparoscopic or Robotic Liver Resection

  • IRAS ID

    343345

  • Contact name

    Sharib Ali

  • Contact email

    s.s.ali@leeds.ac.uk

  • Sponsor organisation

    University of Leeds

  • Duration of Study in the UK

    2 years, 11 months, 31 days

  • Research summary

    Laparoscopic and robotic liver resections are crucial in modern surgery, providing minimally invasive surgery (MIS) options for tumour removal while preserving liver function. Despite advancements, these procedures remain technically challenging due to the need for precise spatial localisation of tumours and vasculature within the liver parenchyma. Current navigation methods, relying on preoperative CT or MRI and intraoperative ultrasound, are limited in providing real-time surgical guidance.

    Our goal is to enhance parenchymal preserving liver surgery (PPLS), which focuses on excising multiple tumours while retaining maximum healthy liver tissue, and to improve safety in traditional anatomical liver resections, thereby accelerating recovery and reducing hospital stays. Protecting the liver's intricate vascular network is essential to avoid excessive blood loss and the need for transfusions while maintaining the viability of the remaining liver. This approach also offers a paradigm shift in training future surgeons.

    We are aiming to develop advanced computer vision methods to generate a comprehensive spatial map of the liver, integrating intra-parenchymatous structures. Preoperative 3D models from CT/MRI will be segmented and fused with the intraoperative (robotic/laparoscopic) surgical view.

    We are hoping to collect fully anonymised 5-10 per-centre MIS procedures that should include: 1) Preoperative 3D CT or 3D MRI scans – formats (Dicom, .nii.gz or any 3D format).
    2) Intraoperative procedure data: MIS videos from laparoscopic camera (any format in .mp4/avi/.mpeg), MIS ultrasound data (any readable imaging format such as .png/.jpeg)

  • REC name

    Wales REC 3

  • REC reference

    25/WA/0289

  • Date of REC Opinion

    29 Sep 2025

  • REC opinion

    Favourable Opinion