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

Clin Oral Investig

Department of Oral and Maxillofacial Surgery, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Augustenburger Platz 1, 13353, Berlin, Germany.

Published: June 2024

AI Article Synopsis

  • The study aimed to create a systematic method to evaluate the bone healing process after bilateral sagittal split osteotomy (BSSO) using volumetric analysis.
  • Cone-beam computed tomography (CBCT) was utilized to capture data before, immediately after, and 6-12 months post-surgery, with both manual and semi-automatic image segmentation methods compared for effectiveness.
  • Results showed that the semi-automatic method had better consistency and repeatability than manual segmentation, suggesting it could improve the monitoring of bone healing in patients after BSSO.

Article Abstract

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

Patients And Methods: 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.

Results: 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.

Conclusion: 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11156743PMC
http://dx.doi.org/10.1007/s00784-024-05753-9DOI Listing

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