High-Resolution Laser Surface Scanning for Patient Registration in Cranial Computer-Assisted Surgery

Zusammenfassung

Diese Zusammenfassung ist satztechnisch bedingt - bitte nicht ausfüllen. In jedem MIN-Artikel so übernehmen.

Abstract

Objective: Markerless patient registration is a new procedure that may reduce logistical efforts and possibly also the radiation load on the patients prior to a computer-assisted intervention. Congruent surfaces, such as bone surfaces or skin surfaces, represented in a data set and in the surgical site, can be overlapped using surface-matching. Previous studies describing this kind of markerless registration, however, show inaccuracies of up to 10 mm during computer-assisted navigation. Furthermore, these systems use less than 1000 surface points of the soft tissue surface in order to establish a correlation between the patient and the data set. Previous papers did not answer the question whether it is this scanning resolution that induces these inaccuracies in registration or rather intraoperative skin deformations.

Study Design: In the present study therefore a new navigation system (SSN++) was used which is able to register up to 180,000 surface points of the surgical site. SSN++ is an infrared navigation system enlarged by a Minolta VI 900 3D volume digitizer. Three different kinds of laser scan-resolution were used for data correlation. An additional congruence analysis was performed in order to assess the geometry of the matched skin surfaces. 22 patients suffering from different cranial diseases (tumors, bony malformations, foreign bodies) were prepared for a computer-assisted intervention. Intraoral titanium-markers, rigidly fixed on the patients by a maxillary splint, were placed as targets while the CT data sets were made. These targets were - after markerless laser scan registration of the patients - supposed to serve for validating the new high-resolution navigation system SSN++.

Results: The accuracy of markerless laser scan registration depends on the intraoperative laser scan's resolution. A high accuracy of the data correlation can be achieved if the number of the laser scan cloud points is about the same as the number of voxels of the corresponding surface on the CT data set. A reduction of the laser scan cloud points to less than 10 % compared to the number of voxels of the CT surface, however, leads to a significant loss of accuracy after markerless patient registration.

Conclusion: The markerless laser scan registration of the surgical site may achieve the same accuracy as a patient registration made by rigidly fixed titanium screws (mean accuracy: 1.2 mm) as long as a high-resolution laser scan is being used.

Key words

Surface registration - markerless patient registration - image-guided surgery - neuronavigation

References

• 1 Barnett G H, Kormos D W, Steiner C P, Weisenberger J. Use of a frameless, armless stereotactic wand for brain tumor localization with two-dimensional and three-dimensional neuroimaging.  Neurosurgery. 1993;  33 674-678
• 2 Cutting C, Taylor R, Khorramabadi D, Haddad B, McCarthy J G. A virtual reality approach to intraoperative bone fragment positioning during craniofacial surgical procedures.  Craniofacial Surgery. 1995;  6 33-37
• 3 Gumprecht H K, Widenka D C, Lurnenta C B. BrainLab VectorVision Neuronavigation System: Technology and clinical experiences in 131 cases.  Neurosurgery. 1999;  44 97-104
• 4 Hassfeld S, Mühling J, Wirtz C R, Knauth M, Lutze T, Schulz H J. Intraoperative guidance in maxillofacial and craniofacial surgery.  Proc Inst Mech Eng H. 1997;  211 277-283
• 5 Marmulla R, Niederdellmann H. Computer-assisted bone segment navigation.  J Craniomaxillofac Surg. 1 998;  6 347-359
• 6 Marmulla R (to Carl Zeiss). System and method for bone segment navigation. US Patent 6,241,735 2001
• 7 Santler G. The Graz hemisphere splint: a new precise, non-invasive method of replacing the dental arch of 3D models by plaster models.  J Craniomaxillofac Surg. 1998;  26 169-173
• 8 Bucholz R, Macneil W, Fewings P, Ravindra A, McDurmont L, Baumann C. Automated rejection of contaminated surface measurements for improved surface registration in image guided neurosurgery.  Studies in Health Technology and Informatics. 2000;  70 39-45
• 9 Raabe A, Krishnan R, Wolff R, Hermann E, Zimmermann M, Seifert V. Laser surface scanning for patient registration in intracranial image-guided surgery.  Neurosurgery. 2002;  50 797-803
• 10 Saborowski G. z-touch - markerless patient registration. http://www.brainlab.com/scripts/website_py_neurosurgery-products.asp 2001
• 11 Technical note from Medtronics: The Fazer contour laser. http://www.xomed.com/NewProducts/IGSInnovations/frazer.asp
• 12 Golfinos J G, Fitzpatrick B C, Smith L R, Spetzler R J. Clinical use of a frameless stereotactic arm: Results of 325 cases.  J Neurosurg. 1995;  83 197-205
• 13 Marmulla R, Niederdellmann H. Surgical planning of computer-assisted repositioning osteotomies.  Plast Reconstr Surg. 1999;  104 938-944
• 14 Marmulla R. Device for optoelectronical correlation between data set, surgical site and 3D markers for instrument and bone segment navigation. German Patent DE 19 960 020.1 1999
• 15 Bronstein I N, Semendjejew K A. Taschenbuch der Mathematik. Stuttgart: Teubner-Verlag 1991
• 16 Marmulla R, Hassfeld S, Lüth T, Mühling J. Laser-scan-based navigation in cranio-maxillofacial surgery. J Craniomaxillofac Surg 2003 31: 267-277