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Virtual Intraoperative CT (viCT): Sequential Anatomic Updates for Modeling Tissue Resection Throughout Endoscopic Sinus Surgery

Nicole M. Gunderson, Graham J. Harris, Jeremy S. Ruthberg, Pengcheng Chen, Di Mao, Randall A. Bly, Waleed M. Abuzeid, Eric J. Seibel

TL;DR

Virtual Intraoperative CT is presented, a method for sequentially updating pCT throughout ESS using intraoperative 3D reconstructions from monocular endoscopic video to enable visualization of evolving anatomy in CT format and enables CT-format anatomic updating in an ESS setting without ancillary hardware.

Abstract

Purpose: Incomplete dissection is a common cause of persistent disease and revision endoscopic sinus surgery (ESS) in chronic rhinosinusitis. Current image-guided surgery systems typically reference static preoperative CT (pCT), and do not model evolving resection boundaries. We present Virtual Intraoperative CT (viCT), a method for sequentially updating pCT throughout ESS using intraoperative 3D reconstructions from monocular endoscopic video to enable visualization of evolving anatomy in CT format. Methods: Monocular endoscopic video is processed using a depth-supervised NeRF framework with virtual stereo synthesis to generate metrically scaled 3D reconstructions at multiple surgical intervals. Reconstructions undergo rigid, landmark-based registration in 3D Slicer guided by anatomical correspondences, and are then voxelized into the pCT grid. viCT volumes were generated using a ray-based occupancy comparison between pCT and reconstruction to delete outdated voxels and remap preserved anatomy and updated boundaries. Performance is evaluated in a cadaveric feasibility study of four specimens across four ESS stages using volumetric overlap (DSC, Jaccard) and surface metrics (HD95, Chamfer, MSD, RMSD), and qualitative comparisons to ground-truth CT. Results: viCT updates show agreement with ground-truth anatomy across surgical stages, with submillimeter mean surface errors. Dice Similarity Coefficient (DSC) = 0.88 +/- 0.05 and Jaccard Index = 0.79 +/- 0.07, and Hausdorff Distance 95% (HD95) = 0.69 +/- 0.28 mm, Chamfer Distance = 0.09 +/- 0.05 mm, Mean Surface Distance (MSD) = 0.11 +/- 0.05 mm, and Root Mean Square Distance (RMSD) = 0.32 +/- 0.10 mm. Conclusion: viCT enables CT-format anatomic updating in an ESS setting without ancillary hardware. Future work will focus on fully automating registration, validation in live cases, and optimizing runtime for real-time deployment.

Virtual Intraoperative CT (viCT): Sequential Anatomic Updates for Modeling Tissue Resection Throughout Endoscopic Sinus Surgery

TL;DR

Virtual Intraoperative CT is presented, a method for sequentially updating pCT throughout ESS using intraoperative 3D reconstructions from monocular endoscopic video to enable visualization of evolving anatomy in CT format and enables CT-format anatomic updating in an ESS setting without ancillary hardware.

Abstract

Purpose: Incomplete dissection is a common cause of persistent disease and revision endoscopic sinus surgery (ESS) in chronic rhinosinusitis. Current image-guided surgery systems typically reference static preoperative CT (pCT), and do not model evolving resection boundaries. We present Virtual Intraoperative CT (viCT), a method for sequentially updating pCT throughout ESS using intraoperative 3D reconstructions from monocular endoscopic video to enable visualization of evolving anatomy in CT format. Methods: Monocular endoscopic video is processed using a depth-supervised NeRF framework with virtual stereo synthesis to generate metrically scaled 3D reconstructions at multiple surgical intervals. Reconstructions undergo rigid, landmark-based registration in 3D Slicer guided by anatomical correspondences, and are then voxelized into the pCT grid. viCT volumes were generated using a ray-based occupancy comparison between pCT and reconstruction to delete outdated voxels and remap preserved anatomy and updated boundaries. Performance is evaluated in a cadaveric feasibility study of four specimens across four ESS stages using volumetric overlap (DSC, Jaccard) and surface metrics (HD95, Chamfer, MSD, RMSD), and qualitative comparisons to ground-truth CT. Results: viCT updates show agreement with ground-truth anatomy across surgical stages, with submillimeter mean surface errors. Dice Similarity Coefficient (DSC) = 0.88 +/- 0.05 and Jaccard Index = 0.79 +/- 0.07, and Hausdorff Distance 95% (HD95) = 0.69 +/- 0.28 mm, Chamfer Distance = 0.09 +/- 0.05 mm, Mean Surface Distance (MSD) = 0.11 +/- 0.05 mm, and Root Mean Square Distance (RMSD) = 0.32 +/- 0.10 mm. Conclusion: viCT enables CT-format anatomic updating in an ESS setting without ancillary hardware. Future work will focus on fully automating registration, validation in live cases, and optimizing runtime for real-time deployment.
Paper Structure (28 sections, 17 equations, 17 figures)

This paper contains 28 sections, 17 equations, 17 figures.

Table of Contents

  1. Introduction
  2. Chronic Rhinosinusitis and Endoscopic Sinus Surgery
  3. Existing IGS Systems
  4. Intraoperative CT
  5. Contributions
  6. Methods
  7. 3D Reconstruction
  8. Camera Pose Estimation
  9. NeRF Initialization (Hash + Spherical Harmonics)
  10. NeRF Rendering
  11. Optimized Novel Stereo View Generation
  12. Stereo Depth and Metric Scale
  13. Depth-Supervised Iterative Refinement
  14. Registration
  15. Virtual Intraoperative CT (viCT) Updating
  16. ...and 13 more sections

Figures (17)

  • Figure 1: Flowchart of simulated stereoscopy NeRF-based reconstruction workflow.
  • Figure 2: Ray-based viCT updating workflow and example of tissue resection modeling.
  • Figure 3: Qualitative comparison of viCT updates with ground-truth postoperative CT across surgical intervals. (A) Post Maxillary, (B) Post Ethmoid, and (C) Complete. Axial, coronal, and sagittal views demonstrate close correspondence between updated viCT volumes and postoperative ground-truth anatomy.
  • Figure 4: Summarized quantitative data across the four cadaveric specimens.
  • Figure 5: Sample monocular endoscopic views from videos used as input to the 3D reconstruction and viCT algorithms.
  • ...and 12 more figures