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Towards Navigation in Endoscopic Kidney Surgery based on Preoperative Imaging
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  • Ayberk Acar,
  • Daiwei Lu,
  • Yifan Wu,
  • Ipek Oguz,
  • Nicholas Kavoussi,
  • Jie Ying Wu
Ayberk Acar
Vanderbilt University

Corresponding Author:[email protected]

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Daiwei Lu
Vanderbilt School of Engineering
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Yifan Wu
Vanderbilt School of Engineering
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Ipek Oguz
Vanderbilt School of Engineering
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Nicholas Kavoussi
Vanderbilt University Medical Center
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Jie Ying Wu
Vanderbilt School of Engineering
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Endoscopic renal surgeries have high re-operation rates, particularly for lower volume surgeons. Due to the limited field and depth of view of current endoscopes, mentally mapping preoperative computed tomography (CT) images of patient anatomy to the surgical field is challenging. The inability to completely navigate the intrarenal collecting system leads to missed kidney stones and tumors, subsequently raising recurrence rates. We propose a guidance system to estimate the endoscope positions within the CT to reduce re-operation rates. We use a Structure from Motion algorithm to reconstruct the kidney collecting system from the endoscope videos. In addition, we segment the kidney collecting system from CT scans using 3D U-Net to create a 3D model. We can then register the two collecting system representations to provide information on the relative endoscope position. We demonstrate correct reconstruction and localization of intrarenal anatomy and endoscope position. Furthermore, we create a 3D map supported by the RGB endoscope images to reduce the burden of mental mapping during surgery. The proposed reconstruction pipeline has been validated for guidance. It can reduce the mental burden for surgeons and is a step towards our long-term goal of reducing re-operation rates in kidney stone surgery.
08 Nov 2023Submitted to Healthcare Technology Letters
09 Nov 2023Assigned to Editor
09 Nov 2023Submission Checks Completed
15 Nov 2023Reviewer(s) Assigned
20 Nov 2023Review(s) Completed, Editorial Evaluation Pending
21 Nov 2023Editorial Decision: Accept