A review of digital orthopedic techniques in pre- and intra-operative management of scaphoid fracture
Digital orthopedics integrates artificial intelligence, finite element analysis, virtual surgical planning, intraoperative navigation, robotics, and three-dimensional printing into a precise, individualized workflow for scaphoid fracture management. Artificial intelligence-based algorithms achieve high diagnostic accuracy for scaphoid fractures on plain radiographs, aid in detecting occult fractures, and support treatment decisions. Three-dimensional fracture mapping and finite element analysis enable quantitati…
AI-based algorithms improve detection of scaphoid fractures including occult fractures on plain radiographs to support treatment decisions, while navigation and robotics improve screw accuracy and reduce radiation and guidewire attempts.
Computer-assisted navigation remains limited by registration inaccuracy and manual dependence, and robot-assisted surgery is constrained by longer setup times, high costs, and predominantly low-level evidence from small series and cadaveric studies.
Current evidence base is limited to small case series and cadaveric studies, with robotics supported predominantly by level IV evidence, requiring standardized protocols and high-quality comparative trials.
Evidence
- Peer-reviewedEFORT Open Reviews2026-10-01
How should this claim be treated?
Truvace Impact Record TRV-2026-1259, v1: “A review of digital orthopedic techniques in pre- and intra-operative management of scaphoid fracture.” Truvace, 2026-10-03. /record/TRV-2026-1259 (accessed at citation time). sha256 3e93d4a304e06895…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1259 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.
ace