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

Results Following Adoption of a Modified Melbourne Technique of Total Scaphocephaly Correction

The Melbourne technique was described in 2008 as a novel method for complete correction of scaphocephaly. Since 2015, it has become our operation of choice for children with sagittal synostosis who are too old at presentation for minimally invasive techniques. Our modifications were 2-position (initially supine then prone) technique and undertaking a formal fronto-orbital remodeling to correct forehead contour. Retrospective chart review was used to record demographics, blood transfusion frequency and volumes, operating time, length of stay, clinical outcome, and complications. Eleven underwent modified Melbourne procedure between July 2015 and March 2017; 9 of 11 were male. All had a diagnosis of nonsyndromic sagittal synostosis. Mean age at surgery was 29 months. Mean surgical time was 6 hours. All patients required blood transfusion with a mean volume transfused of 29 mL/kg (range 13–83 mL/kg). For those 5 patients where preoperative and postoperative measurements were available, there was an increase in mean cephalic index (CI) from 0.64 to 0.75. All postoperative patients had a CI of over 0.70. Three-dimensional shape analysis indicated head shape change addressing all phenotypic aspects of scaphocephaly. In the 5 patients in which analysis could be undertaken, the mean intracranial volume increased from 1481 cm^{3} preoperatively to 1671 cm^{3} postoperatively, a mean increase in intracranial volume of 14%. The postoperative intracranial volume was higher than preoperative in all 5 patients. There were 4 minor and no major complications. Modified Melbourne procedure is safe and effective for the treatment of severe scaphocephaly in sagittal synostosis

ERF‐related craniosynostosis: The phenotypic and developmental profile of a new craniosynostosis syndrome

Mutations in the ERF gene, coding for ETS2 repressor factor, a member of the ETS family of transcription factors cause a recently recognized syndromic form of craniosynostosis (CRS4) with facial dysmorphism, Chiari‐1 malformation, speech and language delay, and learning difficulties and/or behavioral problems. The overall prevalence of ERF mutations in patients with syndromic craniosynostosis is around 2%, and 0.7% in clinically nonsyndromic craniosynostosis. Here, we present findings from 16 unrelated probands with ERF‐related craniosynostosis, with additional data from 20 family members sharing the mutations. Most of the probands exhibited multisutural (including pan‐) synostosis but a pattern involving the sagittal and lambdoid sutures (Mercedes‐Benz pattern) predominated. Importantly the craniosynostosis was often postnatal in onset, insidious and progressive with subtle effects on head morphology resulting in a median age at presentation of 42 months among the probands and, in some instances, permanent visual impairment due to unsuspected raised intracranial pressure (ICP). Facial dysmorphism (exhibited by all of the probands and many of the affected relatives) took the form of orbital hypertelorism, mild exorbitism and malar hypoplasia resembling Crouzon syndrome but, importantly, a Class I occlusal relationship. Speech delay, poor gross and/or fine motor control, hyperactivity and poor concentration were common. Cranial vault surgery for raised ICP and/or Chiari‐1 malformation was expected when multisutural synostosis was observed. Variable expressivity and nonpenetrance among genetically affected relatives was encountered. These observations form the most complete phenotypic and developmental profile of this recently identified craniosynostosis syndrome yet described and have important implications for surgical intervention and follow‐up

ERF‐related craniosynostosis: The phenotypic and developmental profile of a new craniosynostosis syndrome

Mutations in the ERF gene, coding for ETS2 repressor factor, a member of the ETS family of transcription factors cause a recently recognized syndromic form of craniosynostosis (CRS4) with facial dysmorphism, Chiari‐1 malformation, speech and language delay, and learning difficulties and/or behavioral problems. The overall prevalence of ERF mutations in patients with syndromic craniosynostosis is around 2%, and 0.7% in clinically nonsyndromic craniosynostosis. Here, we present findings from 16 unrelated probands with ERF‐related craniosynostosis, with additional data from 20 family members sharing the mutations. Most of the probands exhibited multisutural (including pan‐) synostosis but a pattern involving the sagittal and lambdoid sutures (Mercedes‐Benz pattern) predominated. Importantly the craniosynostosis was often postnatal in onset, insidious and progressive with subtle effects on head morphology resulting in a median age at presentation of 42 months among the probands and, in some instances, permanent visual impairment due to unsuspected raised intracranial pressure (ICP). Facial dysmorphism (exhibited by all of the probands and many of the affected relatives) took the form of orbital hypertelorism, mild exorbitism and malar hypoplasia resembling Crouzon syndrome but, importantly, a Class I occlusal relationship. Speech delay, poor gross and/or fine motor control, hyperactivity and poor concentration were common. Cranial vault surgery for raised ICP and/or Chiari‐1 malformation was expected when multisutural synostosis was observed. Variable expressivity and nonpenetrance among genetically affected relatives was encountered. These observations form the most complete phenotypic and developmental profile of this recently identified craniosynostosis syndrome yet described and have important implications for surgical intervention and follow‐up