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Intraoperative Hyperspectral Label-Free Imaging: From System Design to First-In-Patient Translation

Research output: Contribution to journalArticlepeer-review

Michael Ebner, Eli Nabavi, Jonathan Shapey, Yijing Xie, Florentin Liebmann, José Miguel Spirig, Armando Hoch, Mazda Farshad, Shakeel R. Saeed, Robert Bradford, Iain Yardley, Sebastien Ourselin, David Edwards, Philipp Führnstahl , Tom Vercauteren

Original languageEnglish
Article number294003
JournalJournal of Physics D: Applied Physics
Volume54
Issue number29
Early online date27 Apr 2021
DOIs
E-pub ahead of print27 Apr 2021
PublishedJul 2021

Documents

  • 2021-03-28-HSISystemPaper-Ebner

    2021_03_28_HSISystemPaper_Ebner.pdf, 887 KB, application/pdf

    Uploaded date:29 Mar 2021

    Version:Submitted manuscript

    Licence:CC BY

King's Authors

Abstract

Despite advances in intraoperative surgical imaging, reliable discrimination of critical tissue during surgery remains challenging. As a result, decisions with potentially life-changing consequences for patients are still based on the surgeon's subjective visual assessment. Hyperspectral imaging (HSI) provides a promising solution for objective intraoperative tissue characterisation, with the advantages of being non-contact, non-ionising and non-invasive. However, while its potential to aid surgical decision-making has been investigated for a range of applications, to date no real-time intraoperative HSI (iHSI) system has been presented that follows critical design considerations to ensure a satisfactory integration into the surgical workflow. By establishing functional and technical requirements of an intraoperative system for surgery, we present an iHSI system design that allows for real-time wide-field HSI and responsive surgical guidance in a highly constrained operating theatre. Two systems exploiting state-of-the-art industrial HSI cameras, respectively using linescan and snapshot imaging technology, were designed and investigated by performing assessments against established design criteria and ex vivo tissue experiments. Finally, we report the use of our real-time iHSI system in a clinical feasibility case study as part of a spinal fusion surgery. Our results demonstrate seamless integration into existing surgical workflows.

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