The primary study objective is to build a video dataset, consisting of both colour and depth information, of spine surgery that includes both 'open' and 'minimally invasive' (MIS) surgeries. Using accompanying preoperative CT scans of the patient's spine, we aim to develop a markerless tracking system for spine surgery, which the collected dataset will be used to both train, and then benchmark against.
Candidate surgeries include all spine surgeries taking a posterior approach. This includes both 'open' and 'minimally invasive' surgeries, provided some portion of vertebrae bone is exposed.
Candidate surgeries will be excluded if the patient is under the age of 18 or the clinical lead feels the patient lacks capacity to consent.
Adult spine surgery candidates treated within the Imperial College Healthcare NHS Trust , with the capacity to consent (non-vulnerable)
Other
Retrospective
Spine surgery
Procedure/SurgerySpine surgery, such as fusion requiring the need for precise intraoperative registration and navigation
Number of Data Collection completed
Success in recording 25 RGB-D videos of spine surgeries along with corresponding CT scans
Number of Data points collected containing a variety of exposed spine anatomy
Collected samples should contain a wide variety of exposed vertebrae, including cervical, thoracic and lumbar vertebrae
Patient diversity in Ethnicity
Patients undergoing surgery should be diverse in terms of ethnicity, diversity being the % of patients who are not 'white british'
Patient diversity in Age
Patients undergoing surgery should be diverse in terms of age, diversity being captured by range and standard deviation measures
Usefulness for training navigation system
Outcome is to leverage the recordings to train a markerless tracking system that will intraoperatively track the pose and location of the spine within the surgical site. The trained system will be benchmarked against a test subset of the collected videos. The success of the trained system will be determined by its accuracy in automatically tracking the pose of vertebrae features within the test subset videos, against the labelled pose indicated in the video by the operating surgeon.
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Imperial College London
Lead sponsor
Imperial College Healthcare NHS Trust
Collaborator
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