An augmented reality C-arm for intraoperative assessment of the mechanical axis: a preclinical study

Fallavollita, Pascal; Brand, Alexander; Wang, Lejing; Euler, Ekkehard; Thaller, Peter; Navab, Nassir und Weidert, Simon (2016): An augmented reality C-arm for intraoperative assessment of the mechanical axis: a preclinical study. In: International Journal of Computer Assisted Radiology and Surgery, Bd. 11, Nr. 11: S. 2111-2117

Abstract

Determination of lower limb alignment is a prerequisite for successful orthopedic surgical treatment. Traditional methods include the electrocautery cord, alignment rod, or axis board which rely solely on C-arm fluoroscopy navigation and are radiation intensive. To assess a new augmented reality technology in determining lower limb alignment. A camera-augmented mobile C-arm (CamC) technology was used to create a panorama image consisting of hip, knee, and ankle X-rays. Twenty-five human cadaver legs were used for validation with random varus or valgus deformations. Five clinicians performed experiments that consisted in achieving acceptable mechanical axis deviation. The applicability of the CamC technology was assessed with direct comparison to ground-truth CT. A t test, Pearson's correlation, and ANOVA were used to determine statistical significance. The value of Pearson's correlation coefficient R was 0.979 which demonstrates a strong positive correlation between the CamC and ground-truth CT data. The analysis of variance produced a p value equal to 0.911 signifying that clinician expertise differences were not significant with regard to the type of system used to assess mechanical axis deviation. All described measurements demonstrated valid measurement of lower limb alignment. With minimal effort, clinicians required only 3 X-ray image acquisitions using the augmented reality technology to achieve reliable mechanical axis deviation.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1861-6410
• Sprache: Englisch