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PTH-103 Evaluation of a novel system for image guided laparoscopic liver surgery in an animal model and first clinical experience
  1. C Schneider1 on behalf of SMART Liver Surgery,
  2. S Thompson2 on behalf of SMART,
  3. J Totz2,
  4. Y Song2,
  5. S Johnsen2,
  6. D Stoyanov2,
  7. S Ourselin2,
  8. K Gurusamy1,
  9. D Hawkes2,
  10. M Clarkson2,
  11. B Davidson1 and SMART Liver Surgery
  1. 1Division of Surgery and Interventional Science, University College London
  2. 2Centre for Medical Image Computing, UCL, London, UK

Abstract

Introduction Compared to open surgery, laparoscopic liver resection (LLR) of cancer benefits patients by reducing pain, length of stay and morbidity. However, LLR is often more challenging than open surgery due to the difficulty of identifying and dividing major vascular and bile duct branches. Some of these challenges may be resolved by using image guidance systems (IGS) to overlay a 3D model of the liver structure onto the liver seen at laparoscopy. Current IGS technologies rely on manual landmark definition or ultrasound for co-registration (alignment of 3D model and in-vivo liver) and do not take organ movement and deformation into account. Image guidance for LLR using a cone beam CT has also been attempted. Our group has developed an IGS that automatically registers a liver model derived from pre-operative CT to the in-vivo liver surface using computer vision techniques. Laparoscope position in relation to the liver is determined by optical tracking. Results from a porcine study and its first application in a patient are presented here.

Method Laparoscopic microwave ablation was used to create identifiable liver “lesions” and a CT was obtained in land race pigs under general anaesthesia (GA). One week later, laparoscopic left hepatectomy was performed under GA, using our system. A 46 year old female who presented with an indeterminate liver lesion in the junction of segment 5/6 underwent a hepatic wedge resection under image guidance. Data on system and surgical performance was collected in both studies.

Results Experiments were conducted in 5 animals with a successful image overlay achieved in 3 cases. Failure of overlay was attributed to distorted liver anatomy secondary to adhesions formed around regions of ablated liver. Initial registration of the overlayed 3d model was accomplished in less than 10 min (min). The setup and calibration of equipment for the clinical case took 20 min. Initial registration required 3 min and similar to the animal study did not require repetition. Image overlay was successfully achieved and the operation carried out using an ultrasonic scalpel with a total procedure time of 190 min. Estimated blood loss was <150 ml and no intraoperative complications occurred. The patient had an uneventful recovery and was discharged on the 6th postoperative day.

Conclusion The IGS presented here has been evaluated in both a large animal model and subsequently in a clinical scenario. The system appears to be feasible for clinical use and has benefits in regards to uninterrupted surgical workflow, lack of radiation exposure and automatic compensation for organ motion.

Disclosure of interest C. Schneider Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., S. Thompson Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., J. Totz Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., Y. Song Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., S. Johnsen Grant/ Research Support from: Intelligent Imaging Programme Grant, ref: EP/H046410/1, D. Stoyanov Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., S. Ourselin Grant/ Research Support from: Intelligent Imaging Programme Grant, ref: EP/H046410/1, K. Gurusamy Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., D. Hawkes Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., M. Clarkson Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health., B. Davidson Grant/ Research Support from: This publication presents independent research commissioned by the Health Innovation Challenge Fund (HICF-T4–317), a parallel funding partnership between the Wellcome Trust and the Department of Health. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health.

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