Quantifying bone healing after mandibular displacement in orthognathic surgery

Prognostic implications of a CD8+ TEMRA to CD4+Treg imbalance in mandibular fracture healing: a prospective analysis of immune profiles

Introduction

Open reduction and fixation are the standard of care for treating mandibular fractures and usually lead to successful healing. However, complications such as delayed healing, non-union, and infection can compromise patient outcomes and increase healthcare costs. The initial inflammatory response, particularly the response involving specific CD8+ T cell subpopulations, is thought to play a critical role in healing long bone fractures. In this study, we investigated the role of these immune cell profiles in patients with impaired healing of mandibular fractures.

Materials and methods

In this prospective study, we included patients with mandibular fractures surgically treated at Charité - Universitätsmedizin Berlin, Germany, between September 2020 and December 2022. We used follow-up imaging and clinical assessment to evaluate bone healing. In addition, we analyzed immune cell profiles using flow cytometry and quantified cytokine levels using electrochemiluminescence-based multiplex immunoassays in preoperative blood samples.

Results

Out of the 55 patients enrolled, 38 met the inclusion criteria (30 men and 8 women; mean age 32.18 years). Radiographic evaluation revealed 31 cases of normal healing and 7 cases of incomplete consolidation, including 1 case of non-union. Patients with impaired healing exhibited increased levels of terminally differentiated effector memory CD8+ T cells (TEMRA) and a higher TEMRA to regulatory T cell (Treg) ratio, compared with those with normal healing.

Conclusions

Our analysis of mandibular fracture cases confirms our initial hypothesis derived from long bone fracture healing: monitoring the TEMRA to Treg ratio in preoperative blood can be an early indicator of patients at risk of impaired bone healing. Radiologic follow-up enabled us to detect healing complications that might not be detected by clinical assessment only. This study highlights the potential of individual immune profiles to predict successful healing and may form the basis for future strategies to manage healing complications.

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

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.