Volume 4, 2018
|Number of page(s)||6|
|Published online||13 July 2018|
Accuracy of bone resection in total knee arthroplasty using CT assisted-3D printed patient specific cutting guides
1356 High Street,
VIC 3144, Australia
* Corresponding author: firstname.lastname@example.org
Accepted: 29 May 2018
Introduction: We conducted this study to determine if the pre-surgical patient specific instrumented planning based on Computed Tomography (CT) scans can accurately predict each of the femoral and tibial resections performed through 3D printed cutting guides. The technique helps in optimization of component positioning determined by accurate bone resection and hence overall alignment thereby reducing errors.
Methods: Prophecy evolution medial pivot patient specific instrumented knee replacement systems were used for end stage arthrosis in all consecutive cases over a period of 20 months by a single surgeon. All resections (4 femoral and 2 tibial) were measured using a vernier callipers intraoperatively. These respective measurements were then compared with the preoperative CT predicted bone resection surgical plan to determine margins of errors that were categorized into 7 groups (0 mm to ≥2.6 mm).
Results: A total of 3618 measurements (averaged to 1206) were performed in 201 knees (105 right and 96 left) in 188 patients (112 females and 76 males) with an average age of 67.72 years (44 to 90 years) and average BMI of 32.3 (25.1 to 42.3). 94% of all collected resection readings were below the error margin of ≤1.5 mm of which 90% showed resection error of ≤1 mm. Mean error of different resections were ≤0.60 mm (P ≤ 0.0001). In 24% of measurements there were no errors or deviations from the templated resection (0.0 mm).
Conclusion: The 3D printed cutting blocks with slots for jigs accurately predict bone resections in patient specific instrumentation total knee arthroplasty which would directly affect component positioning.
Key words: Patient specific instrumentation / 3D cutting guides / Total knee arthroplasty / Bone resection
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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