Selecting Appropriate 3D Scanning Technologies for Prosthetic Socket Design and Transtibial Residual Limb Shape Characterization

Introduction: Plaster casting and manual rectification represent the benchmark prosthetic socket design method. 3D technologies have increasing potential for prosthetic limb design and fabrication, especially for enhancing access to these services in low-resource settings. However, the community has a responsibility to verify the efficacy of these new digital technologies. The motivation for this study was to establish benchmarking data to assess digital shape capture technologies, specifically for clinically relevant residual limb shape and landmark capture for limb survey and socket design. The objective was therefore to assess the repeatability of plaster casting in vivo and to compare this with three clinically used 3D scanners. Materials and Methods: A comparative reliability assessment of casting and 3D scanning was conducted in 11 participants with established transtibial amputation. For each participant, two positive molds were cast by a prosthetist and digitized using a white-light 3D surface scanner. Between casts, each participant's residual limb was scanned. The deviation among scan volumes, cross-sections, and shapes was calculated. Results: A total of 95% of the clinically relevant socket shape surface area had a deviation between manual casts of less than 2.87 mm (SD, 0.44 mm), and the average deviation was 0.18 mm (SD, 1.72 mm). The repeatability coefficient of casting was 46.1 ml (3.47%) for volume and 9.6 mm (3.53%) for perimeters. For all clinically meaningful measures, greater reliability was observed for the Omega scanner and worse for the Sense and iSense scanners, although it was observed that the Sense scanner performance was comparable to casting (95th percentile shape consistency). Conclusions: This study provides a platform to appraise new clinical shape capture technologies in the context of best practice in manual plaster casting and starts the conversation of which 3D scanning devices are most appropriate for different types of clinical use. The methods and benchmark results may support prosthetists in acquiring and applying their clinical experience, as part of their continuing professional development.