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34th Annual Scientific Meeting proceedings
Stream:
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Session:
Date/Time: 04-07-2025 (17:45 - 18:00)
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Location:
Evaluation of the accuracy of preoperative templating for canine total knee replacement
Prabakaran A1, Guiot LP*2, Marcellin-Little DJ*3
1Small Animal Specialist Hospital, Tuggerah, Australia, 2ACCESS Specialty Animal Hospitals, Culver City, USA, 3School of Veterinary Medicine, University of California, Davis, USA.
Objectives:
The aim is to compare the accuracy of 2D and 3D templating for predicting femoral prosthesis size in canine total knee replacement (TKR). The secondary aim is to compare the accuracy of the femoral prosthesis alignment and fit in the sagittal and frontal planes using 2D or 3D templating.
Methods:
Preoperative radiographs, CT and postoperative radiographs were collected from patients that underwent TKR. The femoral prosthesis was templated using orthogonal radiographs and CT images following segmentation. Anatomic and mechanical angles were measured for preoperative templated radiographs and CTs, and postoperative radiographs.
Results:
Eighteen dogs met enrolment criteria. Prediction of femoral prosthesis size was 66% accurate in both 2D templating and 3D templating. There was no significant difference between the anatomic lateral distal femoral prosthesis angle (aLDFPA) (p = 0.522), mechanical lateral distal femoral prosthesis angle (mLDFPA) (p = 0.634), anatomic femoral prosthesis flexion angle (aFPFA) (p = 0.544) and mechanical caudal distal femoral prosthesis angle (mCdDFPA) (p = 0.640) between groups.
Conclusions:
The templating method had no effect on accuracy for prediction of prosthesis size in canine TKR. There was no difference in anatomic and mechanical alignment of the femoral prosthesis between groups. The authors conclude that 2D and 3D templating techniques are acceptable planning methods for TKR, but only accurately predict femoral prosthesis size in 66% of cases. It is therefore recommended that surgeons have a prosthesis available one size above and one size below the predicted size when performing TKR.
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