Abstract

BackgroundThe laparoscopic approach to liver resection may reduce morbidity and hospital stay. However, uptake has been slow due to concerns about patient safety and oncological radicality. Image guidance systems may improve patient safety by enabling 3D visualisation of critical intra- and extrahepatic structures. Current systems suffer from non-intuitive visualisation and a complicated setup process. A novel image guidance system (SmartLiver), offering augmented reality visualisation and semi-automatic registration has been developed to address these issues. A clinical feasibility study evaluated the performance and usability of SmartLiver with either manual or semi-automatic registration.MethodsIntraoperative image guidance data were recorded and analysed in patients undergoing laparoscopic liver resection or cancer staging. Stereoscopic surface reconstruction and iterative closest point matching facilitated semi-automatic registration. The primary endpoint was defined as successful registration as determined by the operating surgeon. Secondary endpoints were system usability as assessed by a surgeon questionnaire and comparison of manual vs. semi-automatic registration accuracy. Since SmartLiver is still in development no attempt was made to evaluate its impact on perioperative outcomes.ResultsThe primary endpoint was achieved in 16 out of 18 patients. Initially semi-automatic registration failed because the IGS could not distinguish the liver surface from surrounding structures. Implementation of a deep learning algorithm enabled the IGS to overcome this issue and facilitate semi-automatic registration. Mean registration accuracy was 10.9 ± 4.2 mm (manual) vs. 13.9 ± 4.4 mm (semi-automatic) (Mean difference − 3 mm; p = 0.158). Surgeon feedback was positive about IGS handling and improved intraoperative orientation but also highlighted the need for a simpler setup process and better integration with laparoscopic ultrasound.ConclusionThe technical feasibility of using SmartLiver intraoperatively has been demonstrated. With further improvements semi-automatic registration may enhance user friendliness and workflow of SmartLiver. Manual and semi-automatic registration accuracy were comparable but evaluation on a larger patient cohort is required to confirm these findings.

Highlights

  • The laparoscopic approach to liver resection may reduce morbidity and hospital stay

  • Semi-automatic registration is facilitated by a computer vision technique called stereoscopic surface reconstruction which enables the acquisition of the biometrical liver surface features that are subsequently represented as 3D points cloud

  • This study has described the development and current performance of the SmartLiver image guidance systems (IGS)

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Summary

Introduction

The laparoscopic approach to liver resection may reduce morbidity and hospital stay. uptake has been slow due to concerns about patient safety and oncological radicality. Image guidance systems may improve patient safety by enabling 3D visualisation of critical intra- and extrahepatic structures. A novel image guidance system (SmartLiver), offering augmented reality visualisation and semi-automatic registration has been developed to address these issues. A clinical feasibility study evaluated the performance and usability of SmartLiver with either manual or semi-automatic registration. Methods Intraoperative image guidance data were recorded and analysed in patients undergoing laparoscopic liver resection or cancer staging. Secondary endpoints were system usability as assessed by a surgeon questionnaire and comparison of manual vs semi-automatic registration accuracy. Surgeon feedback was positive about IGS handling and improved intraoperative orientation and highlighted the need for a simpler setup process and better integration with laparoscopic ultrasound. Manual and semi-automatic registration accuracy were comparable but evaluation on a larger patient cohort is required to confirm these findings

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