Abdominal CancerNCT05637346
Vessel- and Bone-based Ultrasound Registration
A study testing Intra-operative ultrasound measurement in people with Abdominal Cancer, run by The Netherlands Cancer Institute at 1 site in Netherlands.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Abdominal Cancer
- What is being tested?
- Intra-operative ultrasound measurement
- Type of treatment
- Surgery or procedure
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 50 participants
- Where
- 1 siteNetherlands
- Study dates
- 5 Dec 2021to 11 Dec 2025
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- ≥ 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
Netherlands1 site
Netherlands Cancer Institute
Amsterdam, North Holland, 1066 CX
About this study
Official title: 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.
Read the 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.
- Conditions
- Abdominal Cancer
- Being tested
- Intra-operative ultrasound measurement
- Keywords
- Surgical Navigation, Ultrasound, Registration, Electromagnetic Tracking, Pelvic Malignancies, Deep Learning, Segmentation
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Intra-operative ultrasound measurementProcedure or surgery
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.
| Study group | Role | What they receive |
|---|---|---|
| Patients scheduled for laparotomy | Experimental | 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. Receives: Procedure: Intra-operative ultrasound measurement |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: One day
Secondary outcomes (2)
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.
Measured: 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.
Measured: One day
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted5 Dec 2022
- Study start5 Dec 2021
- Primary completion11 Dec 2025
- Study completion11 Dec 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Abdominal CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- One group to evaluate the feasibility and accuracy of the proposed methods.
- Masking
- None (open label)
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- The Netherlands Cancer Institute
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Theo Ruers, prof. dr., Principal investigator, NKI
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05637346
- Sponsor's protocol ID
- N21VUR
- Status last verified
- Dec 2025
- First submitted
- 8 Sep 2022
- Last updated
- 23 Dec 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
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.
PubMed 39633142
Study at a glance
From the registry record, last updated by the sponsor on 23 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Intra-operative Vessel and Bone Acquisition, Towards Ultrasound Registration for Surgical Navigation
- ClinicalTrials.gov ID
- NCT05637346
- Acronym / sponsor ID
- N21VUR
- Conditions
- Abdominal Cancer
- Keywords
- Surgical Navigation, Ultrasound, Registration, Electromagnetic Tracking, Pelvic Malignancies, Deep Learning, Segmentation
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- The Netherlands Cancer InstituteUniversity, hospital or other
- Study start
- 5 Dec 2021 (actual)
- Primary completion
- 11 Dec 2025 (actual)
- Study completion
- 11 Dec 2025 (actual)
- First posted
- 5 Dec 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Primary purpose
- Other
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- One group to evaluate the feasibility and accuracy of the proposed methods.
| Arm | Type | Receives |
|---|---|---|
| Patients scheduled for laparotomy | Experimental | Procedure: Intra-operative ultrasound measurementThis 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- ≥ 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
Key exclusion criteria (3 listed)
- 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
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Intra-operative ultrasound measurementA 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. | Procedure or surgery | Patients scheduled for laparotomy |
Primary outcome
Accuracy of developed automatic segmentation algorithm
Time frame: One day
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.
2 secondary outcomes
Accuracy of intra-operative ultrasound registration
Time frame: One day
Usability of intra-operative ultrasound registration
Time frame: One day
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 23 Dec 2025.
- Results publication: PubMed 39633142Hiep 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Theo Ruers, prof. dr. principal investigator
NKI
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Intra-operative ultrasound measurement in people with Abdominal Cancer, run by The Netherlands Cancer Institute at 1 site in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 23 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of developed automatic segmentation algorithm (time frame: One day). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05637346, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 23 Dec 2025.