In vivo evaluation of a hyperspectral imaging system for minimally invasive surgery (HSI-MIS)

Madeleine T Thomaßen; Hannes Köhler; Annekatrin Pfahl; Sigmar Stelzner; Matthias Mehdorn; René Thieme; Boris Jansen-Winkeln; Ines Gockel; Claire Chalopin; Yusef Moulla

doi:10.1007/s00464-023-09874-2

In vivo evaluation of a hyperspectral imaging system for minimally invasive surgery (HSI-MIS)

Surg Endosc. 2023 May;37(5):3691-3700. doi: 10.1007/s00464-023-09874-2. Epub 2023 Jan 16.

Affiliations

¹ Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Liebigstr. 20, 04103, Leipzig, Germany.
² Innovation Center Computer Assisted Surgery (ICCAS), Faculty of Medicine, Leipzig University, Semmelweisstr. 14, 04103, Leipzig, Germany.
³ Department of General, Visceral, Thoracic, and Vascular Surgery, Klinikum St. Georg, 04129, Leipzig, Germany.
⁴ Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Liebigstr. 20, 04103, Leipzig, Germany. yusef.moulla@medizin.uni-leipzig.de.

^# Contributed equally.

Abstract

Background: Hyperspectral Imaging (HSI) is a reliable and safe imaging method for taking intraoperative perfusion measurements. This is the first study translating intraoperative HSI to an in vivo laparoscopic setting using a CE-certified HSI-system for minimally invasive surgery (HSI-MIS). We aim to compare it to an established HSI-system for open surgery (HSI-Open).

Methods: Intraoperative HSI was done using the HSI-MIS and HSI-Open at the Region of Interest (ROI). 19 patients undergoing gastrointestinal resections were analyzed in this study. The HSI-MIS-acquired images were aligned with those from the HSI-Open, and spectra and parameter images were compared pixel-wise. We calculated the Mean Absolute Error (MAE) for Tissue Oxygen Saturation (StO₂), Near-Infrared Perfusion Index (NIR-PI), Tissue Water Index (TWI), and Organ Hemoglobin Index (OHI), as well as the Root Mean Squared Error (RMSE) over the whole spectrum. Our analysis of parameters was optimized using partial least squares (PLS) regression. Two experienced surgeons carried out an additional color-change analysis, comparing the ROI images and deciding whether they provided the same (acceptable) or different visual information (rejected).

Results: HSI and subsequent image registration was possible in 19 patients. MAE results for the original calculation were StO_{2 orig.} 17.2% (± 7.7%)_, NIR-PI_orig. 16.0 (± 9.5), TWI_orig. 18.1 (± 7.9), OHI_orig. 14.4 (± 4.5). For the PLS calculation, they were StO_{2 PLS} 12.6% (± 5.2%), NIR-PI_PLS 10.3 (± 6.0), TWI_PLS 10.6 (± 5.1), and OHI_PLS 11.6 (± 3.0). The RMSE between both systems was 0.14 (± 0.06). In the color-change analysis; both surgeons accepted more images generated using the PLS method.

Conclusion: Intraoperative HSI-MIS is a new technology and holds great potential for future applications in surgery. Parameter deviations are attributable to technical differences and can be reduced by applying improved calculation methods. This study is an important step toward the clinical implementation of HSI for minimally invasive surgery.

Keywords: Clinical evaluation study; Gastrointestinal surgery; Hyperspectral imaging; Laparoscopic surgery; Minimally invasive surgery; Perfusion.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Gastrointestinal Tract
Hemoglobins
Humans
Hyperspectral Imaging*
Laparoscopy*

Substances

Hemoglobins