Image-guided navigation during robot-assisted partial nephrectomy

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.

Single center prospective feasibility study

In the standard clinical workflow, diagnostic CT or MRI scans are acquired to
visualize the renal lesion for removal. These images 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. The surgeon and researcher confirm the alignment visually
through the integration of the model with tracked ultrasound imaging. Once
verified, the surgeon conducts the resection according to own decision-making
according to standard protocol while having navigation support. Data from
tracking and ultrasound are recorded for further analysis after surgery.
Post-operatively, the surgeon completes a questionnaire to evaluate the impact
on decision-making compared to traditional surgical methods. A CT scan is used
to calculate the resected volume and standard pathological assessment to
confirm complete lesion removal.

The decision regarding tissue removal will be at the surgeon's discretion while
having support of the conventional ultrasound and the navigation used for
lesion identification. The study's measurements will not alter the planned
surgical procedures, ensuring that patient treatment remains unaffected. A
thorough risk analysis has indicated minimal to negligible risks, involving
only an additional trocar of 5mm for EM sensor placement (which is negligible
as normally there are five to six 10-15mm trocar placements to assist in RAPN
in which one incision is enlarged for lesion removal) and a possible minor
increase in surgery duration of at most 10 minutes .
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