Semi-Automatic Generation of Preoperative Surgical Plans for Forearm Deformity Correction
L.F. Vergeer (TU Delft - Mechanical Engineering)
Bart Kaptein – Graduation committee member (TU Delft - Biomechanical Engineering)
Joost Colaris – Graduation committee member (Erasmus MC)
Jasper Gerbers – Graduation committee member (Leiden University Medical Center)
Eline van Es – Graduation committee member (Erasmus MC)
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Abstract
Introduction
Corrective forearm osteotomies are complex procedures aimed at restoring anatomical alignment and function in patients with deformities caused by trauma or congenital conditions. While computer-assisted planning improves precision, existing workflows are labour-intensive and limit exploration of optimal solutions. This thesis presents the 3D-SurgiGen Add-on, a semi-automated, open-source planning tool designed to enhance efficiency, consistency, and clinical applicability.
Methods
The 3D-SurgiGen Add-on was developed as a modular plugin for Blender using open-source technologies and a multi-objective optimization framework. Development involved defining requirements, analyzing and restructuring an existing codebase, designing a new architecture, incremental integration, and iterative refinement based on testing and clinical feedback. The tool enables import of 3D forearm models, annotation of anatomical landmarks, and planning based on the mirrored contralateral bone. It supports both opening and closing osteotomies via an innovative optimisation strategy that enables multiple osteotomies while providing explicit control over distal alignment, critical for joint congruency. A key innovation is the user-in-the-loop workflow, which enables clinicians to interactively explore osteotomy alignment options and select a preferred solution from multiple optimised alternatives. The performance and usability of the tool were subsequently evaluated to assess its potential as a clinically relevant semi-automated planning solution.
Results
The tool was prospectively evaluated in five clinical cases involving deformities of both the radius and ulna. Semi-automated planning yielded a comparable number of clinically acceptable plans to manual planning, with similar failure rates and no reduction in planning time (median difference: 7 minutes, range: 4–17). Limitations include the small sample size and the exclusive evaluation of single-shaft osteotomies. Usability feedback further highlighted current limitations in visualisation, parameter interaction, and overall robustness of the Add-on.
Conclusion
The 3D-SurgiGen Add-on demonstrates the feasibility of semi-automated, optimisation-based forearm osteotomy planning. Future work should expand validation, refine clinical objectives, and improve usability. With continued refinement, the 3D-SurgiGen Add-on could serve as an efficient complementary tool for clinical decision-making, providing insight into surgical options and enabling the customisation of preoperative corrective osteotomy plans efficiently.