Geometric morphometrics aided by machine learning in craniofacial surgery

Geometric morphometrics aided by machine learning provide detailed and accurate statistical models of facial form. They promise to be extremely effective tools in surgical planning and assessment; however, a clinical tool to use this information is still to be created

Skin measurement devices to assess skin quality: A systematic review on reliability and validity

Background: Many treatments aim to slow down or reverse the visible signs of skin aging and thereby improve skin quality. Measurement devices are frequently employed to measure the effects of these treatments to improve skin quality, for example, skin elasticity, color, and texture. However, it remains unknown which of these devices is most reliable and valid. Materials and methods: MEDLINE, Embase, Cochrane Central, Web of Science, and Google Scholar databases were searched. Instruments were scored on reporting construct validity by means of convergent validity, interobserver, intraobserver, and interinstrument reliability. Results: For the evaluation of skin color, 11 studies were included describing 16 measurement devices, analyzing 3172 subjects. The most reliable device for skin color assessment is the Minolta Chromameter CR-300 due to good interobserver, intraobserver, and interinstrument reliability. For skin elasticity, seven studies assessed nine types of devices analyzing 290 subjects in total. No intra and interobserver reliability was reported. Skin texture was assessed in two studies evaluating 72 subjects using three different types of measurement devices. The PRIMOS device reported excellent intra and interobserver reliability. None of the included reviewed devices could be determined to be valid based on construct validity. Conclusion: The most reliable devices to evaluate skin color and texture in ordinary skin were, respectively, the Minolta Chromameter and PRIMOS. No reliable device is available to measure skin elasticity in ordinary skin and none of the included devices could be determined to be designated as valid

Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction

Lambdoid craniosynostosis (LC) is a rare non-syndromic craniosynostosis characterised by fusion of the lambdoid sutures at the back of the head. Surgical correction including the spring assisted cranioplasty is the only option to correct the asymmetry at the skull in LC. However, the aesthetic outcome from spring assisted cranioplasty may remain suboptimal. The aim of this study is to develop a parametric finite element (FE) model of the LC skulls that could be used in the future to optimise spring surgery. The skull geometries from three different LC patients who underwent spring correction were reconstructed from the pre-operative computed tomography (CT) in Simpleware ScanIP. Initially, the skull growth between the pre-operative CT imaging and surgical intervention was simulated using MSC Marc. The osteotomies and spring implantation were performed to simulate the skull expansion due to the spring forces and skull growth between surgery and post-operative CT imaging in MSC Marc. Surface deviation between the FE models and post-operative skull models reconstructed from CT images changed between ± 5 mm over the skull geometries. Replicating spring assisted cranioplasty in LC patients allow to tune the parameters for surgical planning, which may help to improve outcomes in LC surgeries in the future

Maxillary Changes Following Facial Bipartition – A Three-Dimensional Quantification

INTRODUCTION: Children with Apert syndrome have hypertelorism and midfacial hypoplasia, which can be treated with facial bipartition (FB), often aided by rigid external distraction. The technique involves a midline osteotomy that lateralizes the maxillary segments, resulting in posterior cross-bites and midline diastema. Varying degrees of spontaneous realignment of the dental arches occurs postoperatively. This study aims to quantify these movements and assess whether they occur as part of a wider skeletal relapse or as dental compensation. METHODS: Patients who underwent FB and had high quality computed tomography scans at the preoperative stage, immediately postsurgery, and later postoperatively were reviewed. DICOM files were converted to three-dimensional bone meshes and anatomical point-to-point displacements were quantified using nonrigid iterative closest point registration. Displacements were visualized using arrow maps, thereby providing an overview of the movements of the facial skeleton and dentition. RESULTS: Five patients with Apert syndrome were included. In all cases, the arrow maps demonstrated initial significant anterior movement of the frontofacial segment coupled with medial rotation of the orbits and transverse divergence of the maxillary arches. The bony position following initial surgery was shown to be largely stable, with primary dentoalveolar relapse correcting the dental alignment. CONCLUSIONS: This study showed that spontaneous dental compensation occurs following FB without compromising the surgical result. It may be appropriate to delay active orthodontic for 6-months postoperatively until completion of this early compensatory phase

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

The 3D skull 0–4 years: A validated, generative, statistical shape model

BACKGROUND: This study aims to capture the 3D shape of the human skull in a healthy paediatric population (0–4 years old) and construct a generative statistical shape model. METHODS: The skull bones of 178 healthy children (55% male, 20.8 ± 12.9 months) were reconstructed from computed tomography (CT) images. 29 anatomical landmarks were placed on the 3D skull reconstructions. Rotation, translation and size were removed, and all skull meshes were placed in dense correspondence using a dimensionless skull mesh template and a non-rigid iterative closest point algorithm. A 3D morphable model (3DMM) was created using principal component analysis, and intrinsically and geometrically validated with anthropometric measurements. Synthetic skull instances were generated exploiting the 3DMM and validated by comparison of the anthropometric measurements with the selected input population. RESULTS: The 3DMM of the paediatric skull 0–4 years was successfully constructed. The model was reasonably compact - 90% of the model shape variance was captured within the first 10 principal components. The generalisation error, quantifying the ability of the 3DMM to represent shape instances not encountered during training, was 0.47 mm when all model components were used. The specificity value was <0.7 mm demonstrating that novel skull instances generated by the model are realistic. The 3DMM mean shape was representative of the selected population (differences <2%). Overall, good agreement was observed in the anthropometric measures extracted from the selected population, and compared to normative literature data (max difference in the intertemporal distance) and to the synthetic generated cases. CONCLUSION: This study presents a reliable statistical shape model of the paediatric skull 0–4 years that adheres to known skull morphometric measures, can accurately represent unseen skull samples not used during model construction and can generate novel realistic skull instances, thus presenting a solution to limited availability of normative data in this field

Craniofacial Syndrome Identification Using Convolutional Mesh Autoencoders

Background: Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In general, these systems use 2D images and analyse texture and colour. While these are powerful tools for photographic analysis, they are not suitable for use with medical imaging modalities such as ultrasound, MRI or CT, and are unable to take shape information into consideration when making a diagnostic prediction. 3D morphable models (3DMMs), and their recently proposed successors, mesh autoencoders, analyse surface topography rather than texture enabling analysis from photography and all common medical imaging modalities, and present an alternative to image-based analysis. // Methods: We present a craniofacial analysis framework for syndrome identification using Convolutional Mesh Autoencoders (CMAs). The models were trained using 3D photographs of the general population (LSFM and LYHM), computed tomography data (CT) scans from healthy infants and patients with 3 genetically distinct craniofacial syndromes (Muenke, Crouzon, Apert). // Findings: Machine diagnosis outperformed expert clinical diagnosis with an accuracy of 99.98%, sensitivity of 99.95% and specificity of 100%. The diagnostic precision of this technique supports its potential inclusion in clinical decision support systems. Its reliance on 3D topography characterisation makes it suitable for AI assisted diagnosis in medical imaging as well as photographic analysis in the clinical setting. // Interpretation: Our study demonstrates the use of 3D convolutional mesh autoencoders for the diagnosis of syndromic craniosynostosis. The topological nature of the tool presents opportunities for this method to be applied as a diagnostic tool across a number of 3D imaging modalities

Convolutional mesh autoencoders for the 3-dimensional identification of FGFR-related craniosynostosis

Clinical diagnosis of craniofacial anomalies requires expert knowledge. Recent studies have shown that artificial intelligence (AI) based facial analysis can match the diagnostic capabilities of expert clinicians in syndrome identification. In general, these systems use 2D images and analyse texture and colour. They are powerful tools for photographic analysis but are not suitable for use with medical imaging modalities such as ultrasound, MRI or CT, and are unable to take shape information into consideration when making a diagnostic prediction. 3D morphable models (3DMMs), and their recently proposed successors, mesh autoencoders, analyse surface topography rather than texture enabling analysis from photography and all common medical imaging modalities and present an alternative to image-based analysis. We present a craniofacial analysis framework for syndrome identification using Convolutional Mesh Autoencoders (CMAs). The models were trained using 3D photographs of the general population (LSFM and LYHM), computed tomography data (CT) scans from healthy infants and patients with 3 genetically distinct craniofacial syndromes (Muenke, Crouzon, Apert). Machine diagnosis outperformed expert clinical diagnosis with an accuracy of 99.98%, sensitivity of 99.95% and specificity of 100%. The diagnostic precision of this technique supports its potential inclusion in clinical decision support systems. Its reliance on 3D topography characterisation make it suitable for AI assisted diagnosis in medical imaging as well as photographic analysis in the clinical setting

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

Evaluation of Swallow Function in Patients with Craniofacial Microsomia: A Retrospective Study

Craniofacial microsomia (CFM) is characterized by underdevelopment of the structures derived from the first and second pharyngeal arches resulting in aesthetic, psychological, and functional problems including feeding and swallowing difficulties. The aim of this study is to gain more insight into swallowing difficulties in patients with CFM. A retrospective study was conducted in the population of patients diagnosed with CFM at three major craniofacial units. Patients with feeding difficulties and those who underwent video fluoroscopic swallow (VFS) studies were included for further analyses. The outcome of the VFS-studies was reviewed with regard to the four phases of swallowing. In our cohort, 13.5% of the 755 patients were diagnosed with swallowing difficulties. The outcome of the VFS-studies of 42 patients showed difficulties in the oral and pharyngeal phases with both thin and thick liquids. Patients with more severe mandibular hypoplasia showed more difficulties to form an appropriate bolus compared to patients who were less severely affected. This is the first study to document swallowing problems in patients with CFM. Difficulties were seen in both the oral and pharyngeal phases. We recommend routine screening for swallowing issues by a speech and language therapist in all patients with CFM and to obtain a VFS-study in patients with a type III mandible