A Photogrammetry-based Approach for Patient-Specific Modeling in Syndactyly Surgery: Prototyping, 3D Reconstruction, and Finite Element Analysis
Location
Ada, Ohio
Start Date
9-12-2025 1:50 PM
End Date
9-12-2025 2:00 PM
Description
Syndactyly, a congenital condition in which fingers or toes are fused, often requires surgical intervention to restore both function and aesthetics. The procedure involves separating the fused digits, reconstructing the web space, and covering the exposed areas with a dorsal flap harvested from the patient. A major challenge in this process is determining the optimal size and shape of the dorsal flap for individuals. Our research aims to provide an objective, quantitative framework for improving surgical outcomes by generating patient-specific 3D models and using finite element analysis (FEA) for dorsal flap optimization.
As a preliminary study, this work has two main objectives: 1) developing a photogrammetry system capable of 3D reconstructing accurate hand models and 2) performing FEA to analyze stress and strain distribution in the web space from the reconstructed model to refine the dorsal flap design. A prototype with four rotating arms, each holding a camera, was built to create 3D models of the hand. A real hand was scanned and reconstructed using it, and key flap parameters were extracted from the model to perform FEA evaluating a hexagonal flap design. The FEA result reveals high stress concentrations at the four corners of the flap, especially along the top edge where the flap is stretched and sutured to the palmar commissure.
This finding demonstrates the potential of integrating computational modeling into preoperative planning through FEA to improve flap design. Future work will focus on expanding the system’s analytical scope, enhancing automation, exploring effective ways to present FEA results, and improving clinical integration to advance personalized surgical planning.
Recommended Citation
Betts, Carter M.; Clawson, Samuel J.; Geibel, Hunter G.; and Herdman, Vladimir T., "A Photogrammetry-based Approach for Patient-Specific Modeling in Syndactyly Surgery: Prototyping, 3D Reconstruction, and Finite Element Analysis" (2025). College of Engineering Student Research Colloquium. 11.
https://digitalcommons.onu.edu/eng_student_research_colloquium/2025/Presentations/11
A Photogrammetry-based Approach for Patient-Specific Modeling in Syndactyly Surgery: Prototyping, 3D Reconstruction, and Finite Element Analysis
Ada, Ohio
Syndactyly, a congenital condition in which fingers or toes are fused, often requires surgical intervention to restore both function and aesthetics. The procedure involves separating the fused digits, reconstructing the web space, and covering the exposed areas with a dorsal flap harvested from the patient. A major challenge in this process is determining the optimal size and shape of the dorsal flap for individuals. Our research aims to provide an objective, quantitative framework for improving surgical outcomes by generating patient-specific 3D models and using finite element analysis (FEA) for dorsal flap optimization.
As a preliminary study, this work has two main objectives: 1) developing a photogrammetry system capable of 3D reconstructing accurate hand models and 2) performing FEA to analyze stress and strain distribution in the web space from the reconstructed model to refine the dorsal flap design. A prototype with four rotating arms, each holding a camera, was built to create 3D models of the hand. A real hand was scanned and reconstructed using it, and key flap parameters were extracted from the model to perform FEA evaluating a hexagonal flap design. The FEA result reveals high stress concentrations at the four corners of the flap, especially along the top edge where the flap is stretched and sutured to the palmar commissure.
This finding demonstrates the potential of integrating computational modeling into preoperative planning through FEA to improve flap design. Future work will focus on expanding the system’s analytical scope, enhancing automation, exploring effective ways to present FEA results, and improving clinical integration to advance personalized surgical planning.