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Related Experiment Video

Updated: Jun 10, 2026

Three-Dimensional Preoperative Virtual Planning in Derotational Proximal Femoral Osteotomy
08:15

Three-Dimensional Preoperative Virtual Planning in Derotational Proximal Femoral Osteotomy

Published on: February 17, 2023

Towards automatic computer-aided knee surgery by innovative methods for processing the femur surface model.

Pietro Cerveri1, Mario Marchente, Ward Bartels

  • 1Dipartimento di Bioingegneria, Politecnico di Milano, via Golgi 39, I-20133 Milano, Italy. pietro.cerveri@polimi.it

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS
|July 20, 2010
PubMed
Summary

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A new automated method accurately computes key femoral axes for knee arthroplasty planning. This approach offers a reliable alternative to traditional methods, improving surgical precision.

Area of Science:

  • Orthopedic surgery
  • Medical imaging analysis
  • Computational geometry

Background:

  • Accurate measurement of femoral axes is crucial for knee arthroplasty.
  • Existing methods for determining these axes can be time-consuming and require manual input.
  • The anatomical flexion axis (AFA) is proposed as a novel alternative to the transepicondylar axis (TA).

Purpose of the Study:

  • To develop and validate a novel, automated method for computing distal femur axes from surface mesh data.
  • To introduce and assess the reliability of the anatomical flexion axis (AFA) as an alternative to the transepicondylar axis (TA).

Main Methods:

  • A novel method processing femur mesh surfaces to automatically compute femoral shaft (FDA), anatomical flexion (AFA), posterior condylar (PCL), Whiteside's (WL), and transepicondylar (TA) axes.

Related Experiment Videos

Last Updated: Jun 10, 2026

Three-Dimensional Preoperative Virtual Planning in Derotational Proximal Femoral Osteotomy
08:15

Three-Dimensional Preoperative Virtual Planning in Derotational Proximal Femoral Osteotomy

Published on: February 17, 2023

  • Robust ellipse fitting of 2D condylar profiles was used to determine the AFA.
  • Method repeatability was tested on 20 cadaveric femur surfaces from CT scans.

    • Main Results:

    • High surface resolutions yielded median errors < 0.50° (FDA), 1.20° (AFA), 1.0° (PCL), 1.30° (WL), and 1.50° (TA).
    • Lower resolutions decreased repeatability, with errors up to 4.70° for TA.
    • Computed axes (FDA, PCL, WL, TA) showed agreement with expert manual identification and literature values.

    Conclusions:

    • The automated method robustly computes femoral axes, with AFA as a viable alternative to TA.
    • Higher surface resolution significantly improves the repeatability of all computed axes.
    • The transepicondylar axis (TA) demonstrated lower repeatability compared to other measured axes.