Vessel- and Bone-based Ultrasound Registration

Intra-operative Vessel and Bone Acquisition, Towards Ultrasound Registration for Surgical Navigation

In this study we aim to develop an automatic artery and bone 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.

Study Overview

• Status: Completed
• Conditions: Abdominal Cancer
• Intervention / Treatment: Procedure: Intra-operative ultrasound measurement

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.

• Study Type: Interventional
• Enrollment (Actual): 50
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Netherlands
  • North Holland
    • Amsterdam, North Holland, Netherlands, 1066 CX
      • Netherlands Cancer Institute

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• ≥ 18 years old
• Scheduled for laparotomy (first 30 patients) or robotic assisted lymph node dissection (second 20 patients)
• A clinical pre-operative CT scan is available
• Patient provides written informed consent

Exclusion Criteria:

• Metal implants which could influence the 3D modelling or tracking accuracy
• Patients with a pacemaker or defibrillator
• Patient received treatment, e.g. surgery or radiotherapy, between the pre-operative CT scan and surgery, which might altered the patient's anatomy

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: Patients scheduled for laparotomy; This is a single-center observational feasibility study to develop an automatic segmentation and registration algorithm based on ultrasound imaging of the arteries and bones. The duration of this study will be approximately 2 years. Patients scheduled for a laparotomy or robotic assisted lymph node dissection at the NKI are eligible for inclusion. Patients are informed about the study before the planned surgery and, after being provided with the necessary information regarding participation in the study, will be asked for informed consent. The ultrasound acquisitions for this study will be performed intra-operatively with CE marked equipment for intra-operative ultrasound. There is no impact on the standard surgical procedure or decision making of the surgery. After surgery, no further participation or cooperation of the patient is required.

Procedure: Intra-operative ultrasound measurement; A patient-specific 3D model will be created using an available pre-operative CT scan. Anatomical target points are selected on this virtual model before the start of the surgery. Prior to surgery, a patient-reference electromagnetic (EM) sensor will be placed between the patient and the matrass on the operating table to account for patient movement during acquisition. Intra-operatively, an initial point registration of the 3D model with the electromagnetic tracking system (EMTS) will be performed based on ultrasound (US) imaging of the arterial bifurcations by the surgeon. Then, the surgeon will acquire multiple US sweeps of the pelvic bone (pubic bone, sacrum and iliac crests) and arteries (abdominal aorta and left and right iliac arteries). For validation purposes, the pre-operatively defined anatomical target points will be visualized on US imaging and by pinpointing the EM tracked pointer. All tracking and US data will be recorded and stored for post-operative analysis.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy of developed automatic segmentation algorithm	An automatic segmentation algorithm for real-time intra-operative vessel and bone segmentation from tracked US images will be developed. The accuracy of this network will be evaluated using the Dice similarity coefficient, ranging from 0 to 1 where a higher score means a better outcome.	One day

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy of intra-operative ultrasound registration	To evaluate the accuracy of different patient registration methods of intra-operative US imaging with pre-operative CT imaging, such as 3D model or centerline registration.	One day
Usability of intra-operative ultrasound registration	Evaluation of the intraoperative usability of the tracked US device and visualization of vessels and bone by the surgeons will be evaluated using the system usability scale (SUS). This scale ranges from 0-100 where a higher score means a better outcome.	One day

Collaborators and Investigators

• Sponsor: The Netherlands Cancer Institute
• Investigators: Principal Investigator: Theo Ruers, prof. dr., NKI

Publications and helpful links

General Publications

• Hiep MAJ, Heerink WJ, Groen HC, Saiz LA, Grotenhuis BA, Beets GL, Aalbers AGJ, Kuhlmann KFD, Ruers TJM. Real-time intraoperative ultrasound registration for accurate surgical navigation in patients with pelvic malignancies. Int J Comput Assist Radiol Surg. 2025 Feb;20(2):249-258. doi: 10.1007/s11548-024-03299-5. Epub 2024 Dec 4.

Study record dates

Study Major Dates

• Study Start (Actual): December 5, 2021
• Primary Completion (Actual): December 11, 2025
• Study Completion (Actual): December 11, 2025

Study Registration Dates

• First Submitted: September 8, 2022
• First Submitted That Met QC Criteria: November 24, 2022
• First Posted (Actual): December 5, 2022

Study Record Updates

• Last Update Posted (Estimated): December 23, 2025
• Last Update Submitted That Met QC Criteria: December 16, 2025
• Last Verified: December 1, 2025

More Information

Terms related to this study

• Keywords: Ultrasound; Deep Learning; Surgical Navigation; Registration; Electromagnetic Tracking; Pelvic Malignancies; Segmentation
• Other Study ID Numbers: N21VUR

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No