Intra-operative Vessel and Bone Acquisition, Towards Ultrasound Registration for Surgical Navigation
Phase: NA
Conditions: Abdominal Cancer
Sponsor: The Netherlands Cancer Institute

Vessel- and bone-based Ultrasound Registration 
Version 5: 19-03-2025 
Protocol summary 
 
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Protocol summary 
 
 
Study title 
Intra-operative vessel and bone acquisition, towards ultrasound 
registration for surgical navigation 
 
NL: Intra-operatieve beeldvorming van de vaten en botten, voor 
toekomstige navigatie chirurgie met ultrasound registratie 
 
Study coordinator 
M.A.J. Hiep, MSc 
 
Co-investigator(s) 
Prof. Dr. T.J.M. Ruers, surgical oncologist 
Dr. A.G.J. Aalbers 
Dr. C.A.R. Lok 
Dr. H.C. Groen 
Dr. W.J. Heerink 
 
Rationale 
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 
vessels from ultrasound images. 
 
Objectives 
Primary objective:  
 To develop an automatic segmentation algorithm using artificial 
intelligence for real-time intra-operative vessel segmentation 
 
 
 
Secondary objectives:  
 Post-operative evaluating the accuracy of different registration 

Vessel- and bone-based Ultrasound Registration 
Version 5: 19-03-2025 
Protocol summary 
 
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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 
 
Methodology 
This is a feasibility study, without any impacts on the surgical 
procedure itself. The total study-related delay of the surgical 
procedure will be approximately 10 minutes. Participation in the 
study will not involve additional visits to the hospital or additional 
radiation dose for the included patients. Informed consent will be 
obtained during the pre-operative outpatient clinic appointment or 
upon admission to the hospital at least one day before operation.  
Surgery starts according to the standard procedure, which includes 
incision and preparation of the internal tissue required for the 
surgery. For this study, optimal ultrasound image acquisition of the 
vessels (without compressing the tissue with the ultrasound probe) is 
required. For laparotomy, the abdominal cavity will partly be filled 
with 
standard 
warm 
saline. 
Subsequently, 
intra-abdominal 
ultrasound is acquired using the BK ultrasound system linked to the 
NDI Aurora electromagnetic tracking system. For robotic assisted 
lymph node dissections, intra-operative ultrasound could be 
acquired percutaneously and/or intra-abdominal using a drop-in 
ultrasound transducer. If accessible, the abdominal aorta, left and 
right iliac arteries and both internal and external iliac arteries will be 
imaged as well as the pubic bone, sacrum and iliac crests; or other 
relevant arteries and bones close to the target area. For offline 
validation of the registration accuracy, a sterile electromagnetic 
pointer is used to pinpoint several anatomical landmarks, such as the 
aortic bifurcation or lymph nodes. All ultrasound and tracking data 
will be recorded during the measurements and post-operatively 
analyzed and used to train an automatic vessel segmentation 
algorithm. 
 
Inclusion criteria 
 
Age ≥ 18 
 
Patients scheduled for laparotomy (first 30 patients) or 
robotic assisted lymph node dissection (second 20 patients) 
 
A pre-operative CT scan is available 
 
Patients provide written ‘informed consent’ 
 
Exclusion criteria 
 
Metal 
implants 
which 
could 
influence 
the 
vessel 
segmentation or tracking accuracy 
 
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 
 
Number of patients 
50 (firstly 30 laparotomy patients, secondly 20 robotic assisted 
lymph node dissection patients) 
 
Study duration 
2 years 
 

Vessel- and bone-based Ultrasound Registration 
Version 5: 19-03-2025 
Protocol summary 
 
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Evaluation criteria 
 
Number and quality of ultrasound sweeps for automatic 
segmentation of the vessels 
 
Localization of clinical targets with an electromagnetically 
tracked pointer to compute a target registration error 
 
 
Statistical methods 
The main study parameter is the development of an algorithm that 
can automatically segment the vessels from US imaging. With this 
study, we want to obtain intra-operative US data to train such 
algorithm. Statistically, we want to test if the created algorithm is 
able to successfully segment the vessels from US images. This can 
be done by comparing the automatically segmented vessel with the 
ground truth. The segmentation will be defined successful for a Dice 
coefficient ≥ 0.7. 
Since we are interested in the proportion of vessels found on US 
images, the sample size was calculated with a power calculation 
based on the number of US sweeps. It is assumed that the US image 
quality and the number of found vessels are equally correlated 
across different patients, since we use a scanning protocol to 
visualize the same vessel segments in each patient. The 
segmentation of an US sweep will be defined successful for a Dice 
coefficient ≥ 0.7 of that sweep. We estimate a success rate of the 
network to successfully segment the main pelvic arteries in all 
sweeps combined of 93% (P). According to the binomial calculation 
using a 95% confidence interval for proportion with a width of 0.1, 
a sample size of 118 US sweeps is required. In this study, at least 4 
US sweeps will be made per patient, which means that 30 patients 
should be included for a total of 120 US sweeps. 
After successful evaluation of these 30 laparotomy patients, the 
same methods will be applied to 20 patients scheduled for robotic 
assisted lymph node dissection. 
In addition, the registration accuracy will be determined by 
computing the target registration error. The usability of the tracked 
ultrasound setup will be evaluated using standard questionnaires, 
resulting in a score between 1 and 100. 
 
Quality of Life 
 
N.A.  
Pharmakinetics (PK) 
 
N.A. 
 
Translational research (TR) 
 
N.A.  
Risk evaluation 
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 US 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.