Motion-compensated targeting in pulmonary interventions using cone-beam CT and locally rigid / globally deformable 3D-2D registration

Rohan C. Vijayan; Niral Sheth; Lina Mekki; Alex Lu; Ali Uneri; Alejandro Sisniega; Jessica Maggaragia; Gerhard Kleinszig; Sebastian Vogt; Jeffrey Thiboutot; Hans Lee; Lonny Yarmus; Jeffrey Siewerdsen

doi:10.1117/12.2612986

4 April 2022 Motion-compensated targeting in pulmonary interventions using cone-beam CT and locally rigid / globally deformable 3D-2D registration

Rohan C. Vijayan, Niral Sheth, Lina Mekki, Alex Lu, Ali Uneri, Alejandro Sisniega, Jessica Maggaragia, Gerhard Kleinszig, Sebastian Vogt, Jeffrey Thiboutot, Hans Lee, Lonny Yarmus, Jeffrey Siewerdsen

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Proceedings Volume 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling; 120342M (2022) https://doi.org/10.1117/12.2612986
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

Purpose. Mobile C-arms capable of 2D fluoroscopy and 3D cone-beam CT (CBCT) are finding application in guidance of transbronchial lung biopsy, but unresolved deformable motion presents challenges to accurate target localization and guidance. We report the initial implementation of a method to resolve deformations via locally rigid / globally deformable 3D-2D registration for motion-compensated overlay of planning data in fluoroscopically-guided pulmonary interventions. Methods. The algorithm proceeds in 3 steps: (1) initialization by 3D-2D rigid registration of CBCT to fluoroscopy (driven by bone gradients); (2) local rigid 3D-2D registration of lung-thresholded CBCT to fluoroscopy within a region of interest (ROI) about each target location; and (3) aggregation of local rigid registrations to estimate global deformation. Several objective functions and optimizers were evaluated for soft-tissue target registration. Phantom studies were performed to determine operating parameters and assess performance with simulated lung deformation. Results. Soft-tissue thresholding and contrast enhancement improved target registration error (TRE) from 10.3 mm for conventional 3D-2D registration (driven primarily by rib gradients) to 3.8 mm using locally rigid 3D-2D registration in regions of interest about each target. The soft-tissue gradient orientation (GO) objective function was found to be superior to alternative similarity measures by de-emphasizing gradient magnitude (in favor of gradient orientation), permitting the algorithm to be better driven by soft-tissue edges. Conclusions. Registration driven by soft-tissue targets is achievable via a novel processing framework to de-emphasize non-target gradients. The proposed method could improve the accuracy of guidance in pulmonary interventions by updating target overlay in fluoroscopy.

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Rohan C. Vijayan, Niral Sheth, Lina Mekki, Alex Lu, Ali Uneri, Alejandro Sisniega, Jessica Maggaragia, Gerhard Kleinszig, Sebastian Vogt, Jeffrey Thiboutot, Hans Lee, Lonny Yarmus, and Jeffrey Siewerdsen "Motion-compensated targeting in pulmonary interventions using cone-beam CT and locally rigid / globally deformable 3D-2D registration", Proc. SPIE 12034, Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling, 120342M (4 April 2022); https://doi.org/10.1117/12.2612986

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KEYWORDS

Lung

Image registration

Bone

Fluoroscopy

Detection and tracking algorithms

Image enhancement

Image processing

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