Intra-operative Vessel and Bone Acquisition, Towards Ultrasound Registration for Surgical Navigation
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 50
- 试验地点
- 1
- 主要终点
- Accuracy of developed automatic segmentation algorithm
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Other
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •≥ 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
排除标准
- •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
研究组 & 干预措施
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.
干预措施: Intra-operative ultrasound measurement (Procedure)
结局指标
主要结局
Accuracy of developed automatic segmentation algorithm
时间窗: 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.
Accuracy of developed automatic segmentation algorithm
时间窗: 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.
次要结局
- Accuracy of intra-operative ultrasound registration(One day)
- Usability of intra-operative ultrasound registration(One day)
- Accuracy of intra-operative ultrasound registration(One day)
- Usability of intra-operative ultrasound registration(One day)