Volumetric evaluation of osteotomy gap following mandibular bilateral sagittal split osteotomy using a novel semi-automated approach: a pilot study

TL;DR

This pilot study introduces a semi-automated method to evaluate bone healing after jaw surgery, showing better consistency than manual methods.

Contribution

A novel semi-automated approach for volumetric evaluation of osteotomy gaps after BSSO with improved repeatability.

Findings

Manual segmentation showed high inter-rater variability with a mean ICC of 0.782 and standard deviation of 0.080.

The semi-automated method achieved a mean ICC of 0.491 with less deviation, indicating better consistency.

The semi-automated approach showed similar trends to manual methods but with higher repeatability.

Abstract

To establish an analysis pipeline for the volumetric evaluation of the osteotomy site after bilateral sagittal split osteotomy (BSSO).

Cone-beam computed tomography (CBCT) was performed before, directly after BSSO, and 6–12 months after surgery. Image segmentations of each osteotomy gap data set were performed manually by four physicians and were compared to a semi-automatic segmentation approach.

Five patients with a total of ten osteotomy gaps were included. The mean interclass correlation coefficient (ICC) of individual patients was 0.782 and the standard deviation 0.080 when using the manual segmentation approach. However, the mean ICC of the evaluation of anatomical sites and time points separately was 0.214, suggesting a large range of deviation within the manual segmentation of each rater. The standard deviation was 0.355, further highlighting the extent of the variation. In contrast, the semi-automatic approach had a mean ICC of 0.491 and a standard deviation of 0.365, which suggests a relatively higher agreement among the operators compared to the manual segmentation approach. Furthermore, the volume of the osteotomy gap in the semi-automatic approach showed the same tendency in every site as the manual segmentation approach, but with less deviation.

The semi-automatic approach developed in the present study proved to be valid as a standardised method with high repeatability. Such image analysis methods could help to quantify the progression of bone healing after BSSO and beyond, eventually facilitating the earlier identification of patients with retarded healing.

The online version contains supplementary material available at 10.1007/s00784-024-05753-9.

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