Scientific Reports (Nov 2023)

Accuracy of facial skeletal surfaces segmented from CT and CBCT radiographs

  • Mohammed Ghamri,
  • Konstantinos Dritsas,
  • Jannis Probst,
  • Maurus Jäggi,
  • Symeon Psomiadis,
  • Ralf Schulze,
  • Carlalberta Verna,
  • Christos Katsaros,
  • Demetrios Halazonetis,
  • Nikolaos Gkantidis

DOI
https://doi.org/10.1038/s41598-023-48320-0
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 12

Abstract

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Abstract The accuracy of three-dimensional (3D) facial skeletal surface models derived from radiographic volumes has not been extensively investigated yet. For this, ten human dry skulls were scanned with two Cone Beam Computed Tomography (CBCT) units, a CT unit, and a highly accurate optical surface scanner that provided the true reference models. Water-filled head shells were used for soft tissue simulation during radiographic imaging. The 3D surface models that were repeatedly segmented from the radiographic volumes through a single-threshold approach were used for reproducibility testing. Additionally, they were compared to the true reference model for trueness measurement. Comparisons were performed through 3D surface approximation techniques, using an iterative closest point algorithm. Differences between surface models were assessed through the calculation of mean absolute distances (MAD) between corresponding surfaces and through visual inspection of facial surface colour-coded distance maps. There was very high reproducibility (approximately 0.07 mm) and trueness (0.12 mm on average, with deviations extending locally to 0.5 mm), and no difference between radiographic scanners or settings. The present findings establish the validity of lower radiation CBCT imaging protocols at a similar level to the conventional CT images, when 3D surface models are required for the assessment of facial morphology.