The authors conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data. The authors believe that the method has potential in interventions on moving abdominal organs such as MR or ultrasound guided focused ultrasound therapy and radiotherapy, pending the method is enabled to run in real-time. The data and the annotations used for this study are made publicly available for those who would like to test other methods on 4D liver ultrasound data.
Future therapy using focused ultrasound (FUS) to treat tumors in abdominal organs, such as the liver, must incorporate motion tracking of these organs due to breathing and drift caused by gravity and intestines (peristalsis). Motion tracking of the target (e.g. tumor) is needed to ensure accurately located sonications. We have performed a quantitative validation of a methodology for motion tracking of the liver with 4D (3D+time) ultrasound. The offline analysis was done using a recently published non-rigid registration algorithm that was specifically designed for motion estimation from dynamic imaging data. The method registers the entire 4D sequence in a group-wise optimization fashion, thus avoiding a bias towards a specifically chosen reference time point. Both spatial and temporal smoothness of the transformations are enforced by using a 4D free-form B-spline deformation model. For our evaluation, three healthy volunteers were scanned over several breath cycles from three different positions and angles on the abdomen (totally nine 4D scans). A skilled physician performed the scanning and manually annotated well-defined anatomic landmarks for assessment of the automatic algorithm. Four engineers each annotated these points in all time frames, the mean of which was taken as a gold standard. The error of the automatic motion estimation method was compared with inter-observer variability. The registration method estimated liver motion better than the observers and had an error (75% percentile over all datasets) of 1 mm. We conclude that the methodology was able to accurately track the motion of the liver in the 4D ultrasound data.
The results can contribute to the use of intraoperative imaging to correct for anatomic shift so that preoperative data can be used with greater confidence and accuracy during guidance of laparoscopic liver procedures.
Background: For many abdominal surgical interventions, laparotomy has gradually been replaced by laparoscopy, with numerous benefits for the patient in terms of post-operative recovery. However, during laparoscopy, the endoscope only provides a single viewpoint to the surgeon, leaving numerous blind-spots and opening the way to peri-operative adverse events. Alternative camera systems have been proposed, but many lack the requisite resolution/robustness for use during surgery or cannot provide real-time images. Here, we present the added value of the Enhanced Laparoscopic Vision System (ELViS) which overcomes these limitations and provides a broad view of the surgical field in addition to the usual high-resolution endoscope.Methods: Experienced laparoscopy surgeons performed several typical procedure steps on a live pig model. The time-to-completion for surgical exercises performed by conventional endoscopy and ELViSassisted surgery was measured. A debriefing interview following each operating session was conducted by an ergonomist, and a System Usability Scale (SUS) score was determined.Results: Proof of concept of ELVIS was achieved in an animal model with 7 expert surgeons without peroperative adverse events related to the surgical device. No differences were found in time-tocompletion. Mean SUS score was 74.7, classifying the usability of the ELViS as "good". During the debriefing interview, surgeons highlighted several situations where the ELViS provided a real advantage (such as during instrument insertion, exploration of the abdominal cavity or for orientation during close work), and also suggested avenues for improvement of the system.Conclusions: This first test of the ELViS prototype on a live animal model demonstrated its usability and provided promising and useful feedback for further development.
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