Primary objective: - To develop an automatic segmentation algorithm using artificial intelligence for real-time intra-operative pelvic vessel segmentationSecondary objectives: - Post-operative evaluating the accuracy of different registration…
ID
Source
Brief title
Condition
- Other condition
- Miscellaneous and site unspecified neoplasms benign
Synonym
Health condition
Chirurgische ingrepen: laparotomie en robot geassisteerd lymfeklierdissectie
Research involving
Sponsors and support
Intervention
Outcome measures
Primary outcome
The number and quality of ultrasound sweeps for automatic segmentation of the
vessels.
Secondary outcome
Localization of clinical targets with an electromagnetically tracked pointer to
compute a target registration error.
Background summary
Image-guided navigation surgery allows for full utilization of pre-operative
imaging during surgery and has the potential of reducing both irradical
resections and morbidity. To use navigation, a registration procedure is
required to correlate pre-operative imaging with the patient*s position on the
operating room (OR). Currently, registration is done by Cone-Beam CT (CBCT)
scanning on the OR prior to navigation surgery. However, the main limitation of
the CBCT method is that it cannot compensate for per-operative changes such as
bed rotation, retractor placement and tissue displacement due to the surgery.
Alternatively, by using intra-operative tracked ultrasound and vessel-based
patient registration, changing conditions during surgery can better be dealt
with. This improved patient registration method could lead to an increased
navigation accuracy and improved clinical usability and outcomes.
The main difference between CBCT and proposed ultrasound registration is that
CBCT is based on bones, while the ultrasound is based on vessels. Bones can be
very easily imaged on the CBCT and therefore used for bone-bone registration
with pre-operative CT-scans. However, vessels are more difficult to acquire,
especially with ultrasound, and an automatic registration process with
pre-operative imaging is needed for efficient clinical usability. For this, the
vessels need to be extracted from the tracked ultrasound images to create a 3D
representation that can be registered. Therefore, an algorithm needs to be
developed that can automatically segment the pelvic vessels from ultrasound
images.
Study objective
Primary objective:
- To develop an automatic segmentation algorithm using artificial intelligence
for real-time intra-operative pelvic vessel segmentation
Secondary objectives:
- Post-operative evaluating the accuracy of different registration methods,
such as 3D model or centerline registration
- The usability of the tracked ultrasound setup (SUS-score)
Study design
A single center observational feasibility study.
Study burden and risks
No additional burden or risks are expected apart from to the extended surgery
time, approximately 10 minutes, for the included patients. Ultrasound imaging
takes place in the same way that conventional intra-operative ultrasound is
acquired (for example during liver surgeries), using the same standardized
sterile cover or sterilized ultrasound transducer. The electromagnetic tracking
system (NDI Aurora) including the tracked pointer is the same system as applied
during conventional abdominal navigated surgeries at the NKI-AvL and multiple
navigation studies.
Plesmanlaan 121
Amsterdam 1066CX
NL
Plesmanlaan 121
Amsterdam 1066CX
NL
Listed location countries
Age
Inclusion criteria
- >= 18 years old
- Scheduled for laparotomy (first 30 patients) or robotic assisted pelvic lymph
node dissection (second 20 patients)
- A pre-operative abdominal CT scan is available
- Patient provides written informed consent
Exclusion criteria
- Metal implants in the pelvic area which could influence the 3D modelling or
tracking accuracy
- Patients with a pacemaker or defibrillator
- Patient received pelvic-abdominal treatment, e.g. surgery or radiotherapy,
between the pre-operative CT scan and surgery, which might altered the
patient*s anatomy
Design
Recruitment
Medical products/devices used
Followed up by the following (possibly more current) registration
No registrations found.
Other (possibly less up-to-date) registrations in this register
No registrations found.
In other registers
Register | ID |
---|---|
ClinicalTrials.gov | NCT05637346 |
CCMO | NL78660.031.21 |