Clinical trial NCT05637346: Vessel-based Ultrasound Registration
Official title: Intra-operative Pelvic Vessel Acquisition, Towards Ultrasound Registration for Surgical Navigation
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Abdominal Cancer
Keywords: Surgical Navigation
Ultrasound
Registration
Electromagnetic Tracking
Pelvic Malignancies
Deep Learning
Segmentation
Lead sponsor: The Netherlands Cancer Institute
Sponsor class: OTHER
First posted: 2022-12-05
Enrollment: 30
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: One group to evaluate the feasibility and accuracy of the proposed methods.
Primary purpose: OTHER

Brief summary: In this study we aim to develop an automatic pelvic artery segmentation algorithm, which is required for future clinical implementation of US registration for surgical navigation. Various registration methods will be evaluated with the data of this study to obtain most optimal results. If automatic segmentation and registration is successful, the final accuracy of the developed US registration method for tumor tracking should be evaluated in future studies in patients eligible for surgical navigation. Eventually, we aim to replace the CBCT-scan with an automatic tracked US registration pipeline for a more efficient and accurate registration procedure, which could improve the applicability and accuracy of surgical navigation and patient outcomes.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* ≥ 18 years old
* Scheduled for laparotomy
* A clinical 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 laparotomy, which might altered the patient's anatomy

Primary outcomes:
measure: Accuracy of developed automatic segmentation algorithm
timeFrame: One day
Secondary outcomes:
measure: Accuracy of intra-operative ultrasound registration
timeFrame: One day
measure: Usability of intra-operative ultrasound registration
timeFrame: One day
Other outcomes:
Locations:
city: Amsterdam
country: Netherlands
facility: Netherlands Cancer Institute
state: North Holland
Study officials:
affiliation: NKI
name: Theo Ruers, prof. dr.
role: PRINCIPAL_INVESTIGATOR
References: