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

Pascal Fallavollita, Alexander Brand, Lejing Wang, Ekkehard Euler, Peter Thaller, Nassir Navab, Simon Weidert

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

17 Zitate (Scopus)

Abstract

Background: 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. Study objectives: To assess a new augmented reality technology in determining lower limb alignment. Methods: 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. Results: 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. Conclusion: 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.

OriginalspracheEnglisch
Seiten (von - bis)2111-2117
Seitenumfang7
FachzeitschriftInternational Journal of Computer Assisted Radiology and Surgery
Jahrgang11
Ausgabenummer11
DOIs
PublikationsstatusVeröffentlicht - 1 Nov. 2016

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