RMS and Registration Accuracy Data for Cervical Pedicle Puncture Navigation

Xuanhuang Chen's dataset contains intraoperative root mean square (RMS) values, registration accuracy, and deviation measurements from a study validating a structured light navigation system for minimally invasive cervical pedicle punctures. The data includes results from 124 Kirschner wire insertions across nine bovine cervical spine models, with an average RMS of 0.424 mm and registration accuracy of 0.01 mm. It was last updated on May 11, 2026.

Use Cases

• Validate surgical navigation system accuracy based on reported RMS and registration error metrics.
• Compare preoperative design to postoperative trajectory deviations for pedicle puncture procedures.
• Analyze the relationship between bone surface factors and entry/exit point deviation angles.
• Benchmark the performance of a single dynamic structured light navigation system against other methods.

Strengths

• Reports a high puncture accuracy of 100% across 124 insertions, as evaluated by the Neo classification system.
• Provides specific, quantified error metrics, including average RMS (0.424 mm) and registration accuracy (0.01 mm).
• Includes detailed deviation measurements for entry points (0.904 mm) and exit points (1.253 mm).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data is derived from a small-scale study using nine bovine spine models, which may limit generalizability.

Provenance

Source

Xuanhuang Chen via figshare

Collection Method

Data collected from an experimental study using bovine cervical spine models, CT scanning, structured light scanning, and Kirschner wire insertion.

Freshness

Last updated 2026-05-11 17:24:46; freshness should be verified.