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Related Concept Videos

Endoscopic Procedures III: Video Capsule Endoscopy01:28

Endoscopic Procedures III: Video Capsule Endoscopy

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Capsule endoscopy, or wireless or video capsule endoscopy, is a diagnostic procedure for examining the entire gastrointestinal tract. Patients swallow a capsule about the size of a vitamin tablet. The capsule is equipped with a transmitter, a battery, an LED light source, and a color video camera to capture images throughout the gastrointestinal tract. This procedure is particularly useful for diagnosing conditions such as Crohn's disease, ulcerative colitis, tumors, polyps, ulcers,...
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Related Experiment Video

Updated: Oct 10, 2025

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery
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Real-time virtual intraoperative CT in endoscopic sinus surgery.

Yangming Li1, Neeraja Konuthula2, Ian M Humphreys2

  • 1RoCALab, Rochester Institute of Technology, Rochester, 14623, USA. yangming.li@rit.edu.

International Journal of Computer Assisted Radiology and Surgery
|December 10, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a real-time CT updating method for endoscopic sinus surgery (ESS). This technique improves surgical accuracy and completeness by virtually modifying preoperative scans during procedures.

Keywords:
Endoscopic surgeryReal-time surgical modification detectionSinus surgeryVirtual intraoperative CT

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Area of Science:

  • Medical Imaging
  • Surgical Technology
  • Computational Anatomy

Background:

  • Preoperative computed tomography (CT) for endoscopic sinus surgery (ESS) often diverges from patient anatomy during procedures.
  • High revision surgery rates (28-47%) highlight the need for improved intraoperative guidance.

Purpose of the Study:

  • To present a novel method for real-time updating of preoperative CT scans during ESS.
  • To enhance surgical completeness by improving the accuracy of the reference anatomical model.

Main Methods:

  • Developed and compared three methods using instrument motion data (position, trajectory, shape) and anatomical structures.
  • Employed machine learning techniques like nonparametric filtering and Gaussian process regression.
  • Generated virtual intraoperative CT scans by updating preoperative data with predicted surgical modifications.

Main Results:

  • Evaluated in eight cadaver ESS cases across five surgeons, covering standard ESS procedures.
  • Achieved clinically acceptable accuracy metrics: Dice similarity coefficients > 86%, F-score > 92%, precision > 89.91%.
  • The tip trajectory-based estimator demonstrated the highest precision at 96.87%.

Conclusions:

  • Virtually modified intraoperative CT scans enhance consistency between the surgical field and the reference model.
  • The proposed method improves surgical completeness in ESS without altering surgical protocols.
  • Offers advantages over actual intraoperative CT, including no extra hardware, radiation, or increased anesthesia time.