Michael J J Douglass1, Alexandre M Caraça Santos2. 1. School of Physical Sciences, University of Adelaide, South Australia, Australia; Department of Medical Physics, Royal Adelaide Hospital, South Australia, Australia. Electronic address: Michael.douglass@adelaide.edu.au. 2. School of Physical Sciences, University of Adelaide, South Australia, Australia; Department of Medical Physics, Royal Adelaide Hospital, South Australia, Australia.
Abstract
PURPOSE: We propose a novel method of designing surface mold brachytherapy applicators using optical photogrammetry. The accuracy of this technique for the purpose of 3D-printing surface mold brachytherapy applicators is investigated. METHODS AND MATERIALS: Photogrammetry was used to generate a 3D model of a patient's right arm. The geometric accuracy of the model was evaluated against CT in terms of volume, surface area, and the Hausdorff distance. A surface mold applicator was then 3D printed using this reconstructed model. The accuracy was evaluated by analyzing the displacement and air-gap volumes between the applicator and plaster cast on a CT image. This technique was subsequently applied to generate a 3D-printed applicator of the author's hand directly, as a proof of principle, using only photographic images. RESULTS: The volume and surface area of the model were within 0.1% and 2.6% of the CT-obtained values, respectively. Using the Hausdorff distance metric, it was determined that 93% of the visible vertices present in the CT-derived model had a matching vertex on the photogrammetry-derived model within 1 mm, indicating a high level of similarity. The maximum displacement between the plaster cast of the patient's arm and the photo-derived 3D-printed applicator was 1.2 mm with a total air-gap volume of approximately 0.05 cm3. CONCLUSIONS: Photogrammetry has been applied to the task of generating 3D-printed brachytherapy surface mold applicators. The current work demonstrates the feasibility and accuracy of this technique and how it may be incorporated into a 3D-printing brachytherapy workflow. Crown
PURPOSE: We propose a novel method of designing surface mold brachytherapy applicators using optical photogrammetry. The accuracy of this technique for the purpose of 3D-printing surface mold brachytherapy applicators is investigated. METHODS AND MATERIALS: Photogrammetry was used to generate a 3D model of a patient's right arm. The geometric accuracy of the model was evaluated against CT in terms of volume, surface area, and the Hausdorff distance. A surface mold applicator was then 3D printed using this reconstructed model. The accuracy was evaluated by analyzing the displacement and air-gap volumes between the applicator and plaster cast on a CT image. This technique was subsequently applied to generate a 3D-printed applicator of the author's hand directly, as a proof of principle, using only photographic images. RESULTS: The volume and surface area of the model were within 0.1% and 2.6% of the CT-obtained values, respectively. Using the Hausdorff distance metric, it was determined that 93% of the visible vertices present in the CT-derived model had a matching vertex on the photogrammetry-derived model within 1 mm, indicating a high level of similarity. The maximum displacement between the plaster cast of the patient's arm and the photo-derived 3D-printed applicator was 1.2 mm with a total air-gap volume of approximately 0.05 cm3. CONCLUSIONS: Photogrammetry has been applied to the task of generating 3D-printed brachytherapy surface mold applicators. The current work demonstrates the feasibility and accuracy of this technique and how it may be incorporated into a 3D-printing brachytherapy workflow. Crown