Intraoperative application of hand-held structured light scanning: a feasibility study

PurposeStructured light scanning is an emerging technology that shows potential in the field of medical imaging and image-guided surgery. The purpose of this study was to investigate the feasibility of applying a hand-held structured light scanner in the operating theatre as an intraoperative image modality and registration tool.MethodsWe performed an in vitro study with three fresh frozen knee specimens and a clinical pilot study with three patients (one total knee arthroplasty and two hip replacements). Before the procedure, a CT scan of the affected joint was obtained and isosurface models of the anatomies were created. A conventional surgical exposure was performed, and a hand-held structured light scanner (Artec Group, Palo Alto, USA) was used to scan the exposed anatomy. Using the texture information of the scanned model, bony anatomy was selected and registered to the CT models. Registration RMS errors were documented, and distance maps between the scanned model and the CT model were created.ResultsFor the in vitro trial, the average RMS error was 1.00 mm for the femur and 1.17 mm for the tibia registration. We found comparable results during clinical trials, with an average RMS error of 1.3 mm.ConclusionsThe results of this preliminary study indicate that structured light scanning could be applied accurately and safely in a surgical environment. This could result in a variety of applications for these scanners in image-guided interventions as intraoperative imaging and registration tools.

[1]  Randy E. Ellis,et al.  The influence of osteophyte depiction in CT for patient-specific guided hip resurfacing procedures , 2015, International Journal of Computer Assisted Radiology and Surgery.

[2]  Brian Lennon,et al.  Design and evaluation of an optically-tracked single-CCD laser range scanner. , 2012, Medical physics.

[3]  Franz Kainberger,et al.  Comparison of laser surface scanning and fiducial marker-based registration in frameless stereotaxy. Technical note. , 2007, Journal of neurosurgery.

[4]  Patrick J Byrne,et al.  Custom-made, 3D, intraoperative surgical guides for nasal reconstruction. , 2011, Facial plastic surgery clinics of North America.

[5]  Julien Favre,et al.  New insight in the relationship between regional patterns of knee cartilage thickness, osteoarthritis disease severity, and gait mechanics. , 2015, Journal of biomechanics.

[6]  Purang Abolmaesumi,et al.  A multi-vertebrae CT to US registration of the lumbar spine in clinical data , 2015, International Journal of Computer Assisted Radiology and Surgery.

[7]  J. Debus,et al.  Projector-based augmented reality for intuitive intraoperative guidance in image-guided 3D interstitial brachytherapy. , 2008, International journal of radiation oncology, biology, physics.

[8]  Randy E. Ellis,et al.  Robust registration for computer-integrated orthopedic surgery: Laboratory validation and clinical experience , 2003, Medical Image Anal..

[9]  J Schlaier,et al.  Registration accuracy and practicability of laser-directed surface matching. , 2002, Computer aided surgery : official journal of the International Society for Computer Aided Surgery.

[10]  D. Caleb Rucker,et al.  A Mechanics-Based Nonrigid Registration Method for Liver Surgery Using Sparse Intraoperative Data , 2014, IEEE Transactions on Medical Imaging.

[11]  B M Dawant,et al.  Laser range scanning for image-guided neurosurgery: investigation of image-to-physical space registrations. , 2008, Medical physics.

[12]  Graeme P. Penney,et al.  Fully automated 2D-3D registration and verification , 2015, Medical Image Anal..