Known-component 3D–2D registration for quality assurance of spine surgery pedicle screw placement. (30th September 2015)

• Record Type: Journal Article
• Authors: Uneri, A; De Silva, T; Stayman, J W; Kleinszig, G; Vogt, S; Khanna, A J; Gokaslan, Z L; Wolinsky, J-P; Siewerdsen, J H
• Is Part Of: Physics in medicine & biology. Volume 60:Number 20(2015:Oct.)
• Page Start: 8007
• Page End: 8024
• Publication Date: 2015-09-30
• Subjects: 3D–2D image registration -- image-guided surgery -- x-ray fluoroscopy -- quality assurance -- spine surgery; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/0031-9155/60/20/8007
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: A 3D–2D image registration method is presented that exploits knowledge of interventional devices (e.g. K-wires or spine screws—referred to as 'known components') to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product. The known-component registration (KC-Reg) algorithm uses robust 3D–2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g. approximation of a screw as a simple cylinder, referred to as 'parametrically-known' component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as 'exactly-known' component [eKC] registration). 3D–2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the 'acceptance window' of the spinal pedicle. Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1–4 mm and <5° using simple parametric (pKC) models, further improved to <1 mm and <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach. 3D–2D registration combined with 3D models of known surgical devices offers a novel method for intraoperative QA. The method provides a near-real-time independent check against pedicle breach, facilitating revision within the same procedure if necessary and providing more rigorous verification of the surgical product.