Abstract
Purpose
Currently, no gold standard exists for 3D analysis of virtually planned surgery accuracy postoperatively. The aim of this study was to present a new, validated and standardised methodology for 3D postoperative assessment of surgical accuracy in patients undergoing 3D virtually planned and guided corrective osteotomies.
Methods
All patients who underwent 3D planned corrective osteotomy in 2021–2022 at our center with a postoperative CT were included. Postoperative surgical outcome was analysed with a postoperative CT and compared to the preoperative virtual surgical planning to determine achieved accuracy. Validation of the analysis was performed by evaluating the individual assessment of six experienced observers. A postoperative quantification was performed according to the proposed innovative methodology based on rotation axes of a virtual postoperative bone model aligned to the virtual preoperative bone model and virtual surgical planned bone model. To evaluate the intra-observer variability, one observer performed the assessment twice.
Results
Quantification of 13 patients according resulted in measurements with a median range (and its interquartile range) for 3D translation of: 2.43 mm (3.17), for the angle deviations: 3D rotation, 2D coronal, 2D sagittal and 2D axial were: 0.66° (1.66°), 0.74° (0.44°), 0.99° (1.27°), 2.37° (5.00°), respectively. The inter- and intraobserver reliability established with the Intraclass correlation coefficient was for all measurements excellent (> 0.76).
Conclusion
The proposed 3D CT technique provides an significant more accurate and objective method for assessment of surgical outcome of a guided corrective osteotomy. The present proposed novel methodology showed excellent inter- and intra-observer reliability with clinically acceptable absolute surgical outcome measurements.
Currently, no gold standard exists for 3D analysis of virtually planned surgery accuracy postoperatively. The aim of this study was to present a new, validated and standardised methodology for 3D postoperative assessment of surgical accuracy in patients undergoing 3D virtually planned and guided corrective osteotomies.
Methods
All patients who underwent 3D planned corrective osteotomy in 2021–2022 at our center with a postoperative CT were included. Postoperative surgical outcome was analysed with a postoperative CT and compared to the preoperative virtual surgical planning to determine achieved accuracy. Validation of the analysis was performed by evaluating the individual assessment of six experienced observers. A postoperative quantification was performed according to the proposed innovative methodology based on rotation axes of a virtual postoperative bone model aligned to the virtual preoperative bone model and virtual surgical planned bone model. To evaluate the intra-observer variability, one observer performed the assessment twice.
Results
Quantification of 13 patients according resulted in measurements with a median range (and its interquartile range) for 3D translation of: 2.43 mm (3.17), for the angle deviations: 3D rotation, 2D coronal, 2D sagittal and 2D axial were: 0.66° (1.66°), 0.74° (0.44°), 0.99° (1.27°), 2.37° (5.00°), respectively. The inter- and intraobserver reliability established with the Intraclass correlation coefficient was for all measurements excellent (> 0.76).
Conclusion
The proposed 3D CT technique provides an significant more accurate and objective method for assessment of surgical outcome of a guided corrective osteotomy. The present proposed novel methodology showed excellent inter- and intra-observer reliability with clinically acceptable absolute surgical outcome measurements.
| Original language | English |
|---|---|
| Article number | 81 |
| Number of pages | 11 |
| Journal | European Journal of Trauma and Emergency Surgery |
| Volume | 51 |
| Issue number | 1 |
| Early online date | 24 Jan 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Keywords
- 3D technology
- accuracy
- Osteotomy
- Patient-specific
- Validation
- Virtual surgical planning
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