Local Soft Tissue and Bone Displacements Following Midfacial Bipartition Distraction in Apert Syndrome – Quantification Using a Semi-Automated Method

ABSTRACT: Patients with Apert syndrome experience midfacial hypoplasia, hypertelorism, and downslanting palpebral fissures which can be corrected by midfacial bipartition distraction with rigid external distraction device. Quantitative studies typically focus on quantifying rigid advancement and rotation postdistraction, but intrinsic shape changes of bone and soft tissue remain unknown. This study presents a method to quantify these changes. Pre- and post-operative computed tomography scans from patients with Apert syndrome undergoing midfacial bipartition distraction with rigid external distraction device were collected. Digital Imaging and Communications in Medicine files were converted to three-dimensional bone and soft tissue reconstructions. Postoperative reconstructions were aligned on the preoperative maxilla, followed by nonrigid iterative closest point transformation to determine local shape changes. Anatomical point-to-point displacements were calculated and visualized using a heatmap and arrow map. Nine patients were included.Zygomatic arches and frontal bone demonstrated the largest changes. Mid-lateral to supra-orbital rim showed an upward, inward motion. Mean bone displacements ranged from 3.3 to 12.8 mm. Soft tissue displacements were relatively smaller, with greatest changes at the lateral canthi. Midfacial bipartition distraction with rigid external distraction device results in upward, inward rotation of the orbits, upward rotation of the zygomatic arch, and relative posterior motion of the frontal bone. Local movements were successfully quantified using a novel method, which can be applied to other surgical techniques/syndromes

Correlation between head shape and volumetric changes following spring-assisted posterior vault expansion

OBJECTIVE: To investigate whether different head shapes show different volumetric changes following spring-assisted posterior vault expansion (SA-PVE) and to investigate the influence of surgical and morphological parameters on SA-PVE. MATERIALS AND METHODS: Preoperative three-dimensional skull models from patients who underwent SA-PVE were extracted from computed tomography scans. Patient head shape was described using statistical shape modelling (SSM) and principal component analysis (PCA). Preoperative and postoperative intracranial volume (ICV) and cranial index (CI) were calculated. Surgical and morphological parameters included skull bone thickness, number of springs, duration of spring insertion and type of osteotomy. RESULTS: In the analysis, 31 patients were included. SA-PVE resulted in a significant ICV increase (284.1 ± 171.6 cm3, p<0.001) and a significant CI decrease (−2.9 ± 4.3%, p<0.001). The first principal component was significantly correlated with change in ICV (Spearman ρ = 0.68, p<0.001). Change in ICV was significantly correlated with skull bone thickness (ρ = −0.60, p<0.001) and age at time of surgery (ρ = −0.60, p<0.001). No correlations were found between the change in ICV and number of springs, duration of spring insertion and type of osteotomy. CONCLUSION: SA-PVE is effective for increasing the ICV and resolving raised intracranial pressure. Younger, brachycephalic patients benefit more from surgery in terms of ICV increase. Skull bone thickness seems to be a crucial factor and should be assessed to achieve optimal ICV increase. In contrast, insertion of more than two springs, duration of spring insertion or performing a fully cut through osteotomy do not seem to impact the ICV increase. When interpreting ICV increases, normal calvarial growth should be taken into account

Comparison of 3D Scanner Systems for Craniomaxillofacial Imaging

Two-dimensional photographs are the standard for assessing craniofacial surgery clinical outcomes despite lacking three-dimensional (3D) depth and shape. Therefore, 3D-scanners have been gaining popularity in various fields of plastic and reconstructive surgery, including craniomaxillofacial surgery. Head shapes of eight adult volunteers were acquired with four 3D scanners: 1.5T Avanto MRI, Siemens; 3dMDface System, 3dMD Inc.; M4D Scan, Rodin4D; and Structure Sensor, Occipital Inc. Accuracy was evaluated as percentage of data within a range of 2 mm from the 3DMDface System reconstruction, by surface-to-surface root mean square distances (RMS), and with facial distance maps. Precision was determined with RMS. Relative to the 3dMDface System, accuracy was highest for M4D Scan (90% within 2 mm; RMS of 0.71 mm ± 0.28 mm), then Avanto MRI (86%; 1.11 mm ± 0.33 mm), and Structure Sensor (80%; 1.33 mm ± 0.46). M4D Scan and Structure Sensor precision were 0.50 mm ± 0.04 mm and 0.51 mm ± 0.03 mm. Clinical and technical requirements govern scanner choice, however, 3dMDface System and M4D Scan provide high-quality results. It is foreseeable that compact, hand-held systems become more popular in the near future

A population-specific material model for sagittal craniosynostosis to predict surgical shape outcomes

Sagittal craniosynostosis consists of premature fusion (ossification) of the sagittal suture during infancy, resulting in head deformity and brain growth restriction. Spring-assisted cranioplasty (SAC) entails skull incisions to free the fused suture and insertion of two springs (metallic distractors) to promote cranial reshaping. Although safe and effective, SAC outcomes remain uncertain. We aimed hereby to obtain and validate a skull material model for SAC outcome prediction. Computed tomography data relative to 18 patients were processed to simulate surgical cuts and spring location. A rescaling model for age matching was created using retrospective data and validated. Design of experiments was used to assess the effect of different material property parameters on the model output. Subsequent material optimization—using retrospective clinical spring measurements—was performed for nine patients. A population-derived material model was obtained and applied to the whole population. Results showed that bone Young’s modulus and relaxation modulus had the largest effect on the model predictions: the use of the population-derived material model had a negligible effect on improving the prediction of on-table opening while significantly improved the prediction of spring kinematics at follow-up. The model was validated using on-table 3D scans for nine patients: the predicted head shape approximated within 2 mm the 3D scan model in 80% of the surface points, in 8 out of 9 patients. The accuracy and reliability of the developed computational model of SAC were increased using population data: this tool is now ready for prospective clinical application

Using principal component analysis to describe the midfacial deformities in patients with craniofacial microsomia

Purpose: Craniofacial microsomia (CFM) is the result of a disturbance in embryologic development and is characterised by an asymmetric, mostly unilateral facial underdevelopment. The aim of this study is to understand the midfacial involvement in CFM using principal component analysis (PCA). Materials and methods: Pre-operative data from 19 CFM and 23 control patients were collected. A set of 71 landmarks was placed on three-dimensional (3D) reconstructions of all skulls to compare both populations. PCA visualised variation within both groups and calculated the vector of change. Linear measurements were taken to compare ratios between the populations and between the affected and unaffected sides in CFM patients. Results: PCA defined a vector that described shape changes between both populations. Videos showed the variation within the control and CFM group and the transformation from a mean CFM skull into a normal phenotype. Linear measurements showed a significant difference between the affected and unaffected sides in CFM patients. Conclusion: PCA has not been applied on asymmetrical data before, but it has proved to be a useful method to describe CFM. The virtual normalisation of a mean CFM skull enables visualisation of the bony shape changes, which is promising to delineate and to plan surgical correction and could be used as an outcome measure

Three-dimensional soft tissue prediction in orthognathic surgery: a clinical comparison of Dolphin, ProPlan CMF, and probabilistic finite element modelling

Three-dimensional surgical planning is used widely in orthognathic surgery. Although numerous computer programs exist, the accuracy of soft tissue prediction remains uncertain. The purpose of this study was to compare the prediction accuracy of Dolphin, ProPlan CMF, and a probabilistic finite element method (PFEM). Seven patients (mean age 18 years; five female) who had undergone Le Fort I osteotomy with preoperative and 1-year postoperative cone beam computed tomography (CBCT) were included. The three programs were used for soft tissue prediction using planned and postoperative maxillary position, and these were compared to postoperative CBCT. Accurate predictions were obtained with each program, indicated by root mean square distances: RMSDolphin = 1.8 0.8 mm, RMSProPlan = 1.2 0.4 mm, and RMSPFEM = 1.3 0.4 mm. Dolphin utilizes a landmark-based algorithm allowing for patient-specific bone-to-soft tissue ratios, which works well for cephalometric radiographs but has limited three-dimensional accuracy, whilst ProPlan and PFEM provide better three-dimensional predictions with continuous displacements. Patient or population-specific material properties can be defined in PFEM, while no soft tissue parameters are adjustable in ProPlan. Important clinical considerations are the topological differences between predictions due to the three algorithms, the non-negligible influence of the mismatch between planned and postoperative maxillary position, and the learning curve associated with sophisticated programs like PFEM