This study aims to evaluate electromagnetic (EM) tracked navigation in robot-assisted partial nephrectomy (RAPN), addressing kidney movement issues by attaching a tracked EM sensor close to the lesion. This assessment will be based on the navigation's ability to achieve preoperatively planned resection volumes aiming to assist in radical resection margins of the lesion. The current challenge for surgeons performing RAPN is to minimize the removal of healthy kidney tissue, as the rates of positive resections are very low. Additionally, the study aims to explore the practical application of image guidance in RAPN, evaluating aspects such as duration, surgical and technical success, and the surgeons' perceptions. Ultimately, this research seeks to determine if the addition of navigation can enhance RAPN outcomes, particularly in terms of kidney tissue preservation and radical lesion removal. The success of this technique could result in broader adoption of kidney-sparing surgeries, even in complex scenarios where radical resection is at risk.
Robot-assisted partial nephrectomy (RAPN) is now the preferred option for treatable renal lesions due to its ability to preserve kidney function while effectively treating cancer. Despite RAPN's effectiveness, its surgical complexity and varied approach requirements pose challenges. Image-guided surgery applies pre-operative imaging for patient-specific intra-operative visualization of the kidney and lesion margins to support the surgeon during resection. However, adapting to surgery-induced deformations remains a challenge. An approach that is able to correct for organ movements during surgery might result in an optimal preservation rate of healthy kidney parenchyma and improved decisiveness for the surgeon during resection. On the long term, this might result in a larger shift from radical to partial nephrectomies, leading to patients with improved renal functions after lesion resection. The primary objective is to assess the ability to achieve preoperatively planned resection volumes by adding EM tracked navigation in RAPN, as minimizing the removal of healthy kidney tissue is challenging nowadays. A deviation within 35% between the planned and actual resection volumes is considered comparable and therefore deemed successful. Secondary objectives are the time for localizing and removing the renal lesion, the impact on surgical decisiveness, and the clinical and technical success of implementing the navigation setup.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
OTHER
Masking
NONE
Enrollment
20
Diagnostic CT and MRI scans are used to create a 3D digital model to illustrate the lesion's relation to the kidney and surrounding anatomy. The surgeon reviews this model, validates the segmentation, and plans the resection volume. The surgical procedure proceeds according to standard protocols in a standard operational setting, with the addition of navigation tools. A sterile EM sensor is inserted through a separate 5mm trocar and affixed to the kidney in proximity to the lesion in a region intended to be resected. Registration of the 3D model is conducted using an EM pointer or a tracked instrument, pointing to identifiable anatomical landmarks or structures on the kidney to validate accuracy. Both the digital model and the location of tracked instruments are displayed in real-time to the surgeon in the video console of the robot, allowing real-time navigation.
Netherlands Cancer Institute
Amsterdam, North Holland, Netherlands
Accuracy of the EM navigation setup in preserving the volume of renal tissue designated for resection prior to surgery
The planned resection volume will be compared to the actual resected volume using CT scan data. A navigation is deemed successful if comparable resection volumes are measured. The criteria for comparable resection volume measurement is defined as a discrepancy of no more than 35% between the preoperative and post-operative volumes, ensuring that the navigation aids in achieving precision in surgical outcomes. The study is successful when 70% of the navigations (i.e. 14 out of 20 patients) are successful.
Time frame: One day
Time required for navigation implementation
Time frame: One day
Clinical success of number of negative resection margins
Time frame: One day
Technical usability of the navigation setup using post-operative questionnaires for surgeons
Time frame: One day
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