Using principal component analysis to describe the Apert skull deformity and simulate its correction

Understanding the influence of surgical parameters on craniofacial surgery outcomes: a computational study

Sagittal craniosynostosis (SC) is a congenital condition whereby the newborn skull develops abnormally owing to the premature ossification of the sagittal suture. Spring-assisted cranioplasty (SAC) is a minimally invasive surgical technique to treat SC, where metallic distractors are used to reshape the newborn's head. Although safe and effective, SAC outcomes remain uncertain owing to the limited understanding of skull-distractor interaction and the limited information provided by the analysis of single surgical cases. In this work, an SC population-averaged skull model was created and used to simulate spring insertion by means of the finite-element analysis using a previously developed modelling framework. Surgical parameters were varied to assess the effect of osteotomy and spring positioning, as well as distractor combinations, on the final skull dimensions. Simulation trends were compared with retrospective measurements from clinical imaging (X-ray and three-dimensional photogrammetry scans). It was found that the on-table post-implantation head shape change is more sensitive to spring stiffness than to the other surgical parameters. However, the overall end-of-treatment head shape is more sensitive to spring positioning and osteotomy size parameters. The results of this work suggest that SAC surgical planning should be performed in view of long-term results, rather than immediate on-table reshaping outcomes.

Analysis of Cranial Morphology of Healthy Infants Using Homologous Modeling

OBJECTIVE

Data on cranial morphology of healthy individuals can be used as the guide in the treatment of cranial deformity. There are many reports analyzing the cranial morphology of healthy children in the past. But most of them focus on 2-dimensional values, and there are only a few reports, which analyzed the cranial morphology of Japanese healthy infants. We report a novel method that enables the comprehensive analysis of cranial morphology of Japanese healthy infants in 3D.

METHODS

Craniofacial CT data of 20 healthy infants (9 males, 11 females) ranging in age from 1 to 11 months were collected. Based on the CT data, we created 20 homologous models of cranium using software specifically designed to support homologous modeling. We averaged vertex coordinates of the homologous models to create average model. We further performed principal component analysis, and created virtual models based on each principal component. The contribution rate was calculated, and the features described by each principal component were interpreted.

RESULTS

We created the average cranial model of Japanese healthy infants. Seven principal components (cumulative contribution rate: 89.218%) were interpreted as to which part of the cranial shape each component was related to. The elements were extracted that may characterize the cranial morphology of some of the clinical conditions such as dolico/brachycephaly and deformational plagiocephaly. Some of these elements have not been mentioned in the past literature.

CONCLUSION

Homologous modeling was considered to be valid and strong tool for comprehensive analysis of cranial morphology.

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.

Statistical shape modelling to aid surgical planning: associations between surgical parameters and head shapes following spring-assisted cranioplasty

PURPOSE

Spring-assisted cranioplasty is performed to correct the long and narrow head shape of children with sagittal synostosis. Such corrective surgery involves osteotomies and the placement of spring-like distractors, which gradually expand to widen the skull until removal about 4 months later. Due to its dynamic nature, associations between surgical parameters and post-operative 3D head shape features are difficult to comprehend. The current study aimed at applying population-based statistical shape modelling to gain insight into how the choice of surgical parameters such as craniotomy size and spring positioning affects post-surgical head shape.

METHODS

Twenty consecutive patients with sagittal synostosis who underwent spring-assisted cranioplasty at Great Ormond Street Hospital for Children (London, UK) were prospectively recruited. Using a nonparametric statistical modelling technique based on mathematical currents, a 3D head shape template was computed from surface head scans of sagittal patients after spring removal. Partial least squares (PLS) regression was employed to quantify and visualise trends of localised head shape changes associated with the surgical parameters recorded during spring insertion: anterior-posterior and lateral craniotomy dimensions, anterior spring position and distance between anterior and posterior springs.

RESULTS

Bivariate correlations between surgical parameters and corresponding PLS shape vectors demonstrated that anterior-posterior (Pearson's [Formula: see text]) and lateral craniotomy dimensions (Spearman's [Formula: see text]), as well as the position of the anterior spring ([Formula: see text]) and the distance between both springs ([Formula: see text]) on average had significant effects on head shapes at the time of spring removal. Such effects were visualised on 3D models.

CONCLUSIONS

Population-based analysis of 3D post-operative medical images via computational statistical modelling tools allowed for detection of novel associations between surgical parameters and head shape features achieved following spring-assisted cranioplasty. The techniques described here could be extended to other cranio-maxillofacial procedures in order to assess post-operative outcomes and ultimately facilitate surgical decision making.

Characterizing the skull base in craniofacial microsomia using principal component analysis

The aim of this study was to compare the anatomical differences in the skull base between the affected and non-affected side in patients with craniofacial microsomia (CFM), and to compare the affected and non-affected sides with measurements from a normal population. Three-dimensional computed tomography scans of 13 patients with unilateral CFM and 19 normal patients (age range 7-12 years) were marked manually with reliable homologous landmarks. Principal component analysis (PCA), as part of a point distribution model (PDM), was used to analyse the variability within the normal and preoperative CFM patient groups. Through analysis of the differences in the principal components calculated for the two groups, a model was created to describe the differences between CFM patients and normal age-matched controls. The PDMs were also used to describe the shape changes in the skull base between the cohorts and validated this model. Using thin-plate splines as a means of interpolation, videos were created to visualize the transformation from CFM skull to normal skull, and to display the variability in shape changes within the groups themselves. In CFM cases, the skull base showed significant asymmetry. Anatomical areas around the glenoid fossa and mastoid process showed the most asymmetry and restriction of growth, suggesting a pathology involving the first and second pharyngeal arches.

Quantitative analysis of fetal facial morphology using 3D ultrasound and statistical shape modeling: a feasibility study

BACKGROUND

The antenatal detection of facial dysmorphism using 3-dimensional ultrasound may raise the suspicion of an underlying genetic condition but infrequently leads to a definitive antenatal diagnosis. Despite advances in array and noninvasive prenatal testing, not all genetic conditions can be ascertained from such testing.

OBJECTIVES

The aim of this study was to investigate the feasibility of quantitative assessment of fetal face features using prenatal 3-dimensional ultrasound volumes and statistical shape modeling. STUDY DESIGN: Thirteen normal and 7 abnormal stored 3-dimensional ultrasound fetal face volumes were analyzed, at a median gestation of 29⁺⁴ weeks (25⁺⁰ to 36⁺¹). The 20 3-dimensional surface meshes generated were aligned and served as input for a statistical shape model, which computed the mean 3-dimensional face shape and 3-dimensional shape variations using principal component analysis.

RESULTS

Ten shape modes explained more than 90% of the total shape variability in the population. While the first mode accounted for overall size differences, the second highlighted shape feature changes from an overall proportionate toward a more asymmetric face shape with a wide prominent forehead and an undersized, posteriorly positioned chin. Analysis of the Mahalanobis distance in principal component analysis shape space suggested differences between normal and abnormal fetuses (median and interquartile range distance values, 7.31 ± 5.54 for the normal group vs 13.27 ± 9.82 for the abnormal group) (P = .056).

CONCLUSION

This feasibility study demonstrates that objective characterization and quantification of fetal facial morphology is possible from 3-dimensional ultrasound. This technique has the potential to assist in utero diagnosis, particularly of rare conditions in which facial dysmorphology is a feature.

Describing Crouzon and Pfeiffer syndrome based on principal component analysis

Crouzon and Pfeiffer syndrome are syndromic craniosynostosis caused by specific mutations in the FGFR genes. Patients share the characteristics of a tall, flattened forehead, exorbitism, hypertelorism, maxillary hypoplasia and mandibular prognathism. Geometric morphometrics allows the identification of the global shape changes within and between the normal and syndromic population.

METHODS

Data from 27 Crouzon-Pfeiffer and 33 normal subjects were landmarked in order to compare both populations. With principal component analysis the variation within both groups was visualized and the vector of change was calculated. This model normalized a Crouzon-Pfeiffer skull and was compared to age-matched normative control data.

RESULTS

PCA defined a vector that described the shape changes between both populations. Movies showed how the normal skull transformed into a Crouzon-Pfeiffer phenotype and vice versa. Comparing these results to established age-matched normal control data confirmed that our model could normalize a Crouzon-Pfeiffer skull.

CONCLUSIONS

PCA was able to describe deformities associated with Crouzon-Pfeiffer syndrome and is a promising method to analyse variability in syndromic craniosynostosis. The virtual normalization of a Crouzon-Pfeiffer skull is useful to delineate the phenotypic changes required for correction, can help surgeons plan reconstructive surgery and is a potentially promising surgical outcome measure.

Assessing the corrective effects of facial bipartition distraction in Apert syndrome using geometric morphometrics

Apert syndrome is a congenital disorder characterized by craniosynostosis and midface hypoplasia. This study looks to identify to what extent bipartition distraction corrects the morphological abnormalities of this condition. Preoperative and postoperative three-dimensional computed tomography (3DCT) scans of 10 patients with Apert syndrome (12-21 years) were identified from the Great Ormond Street Hospital database. To analyse preoperative and postoperative scans, 98 landmarks and 13 normal skulls were used. Principal component analysis (PCA) was used to analyse patterns in the datasets. Within each group, eigenvectors were identified that demonstrated the aspects of the skull where most variations were found. The analysis allowed both global shape measurement and local proportions. Postoperative and normal scans both showed the same first three principal components. Warping from preoperative to postoperative illustrates midface advancement and inward rotation of the orbits. Postoperative to normal warps demonstrate some remaining differences. The reliability of the used land marks varied between 77% and 95% for the highly reproducible landmarks between the two observers. 95% versus 100% were at least acceptable reproducible landmarks. This study allows us to understand the way bipartition distraction corrects the abnormalities of the Apert skull. Analysing the surgical outcome of facial bipartition with geometric morphometrics shows that some major Apert characteristics are corrected. Using the data and the output of further studies, surgical procedures can be adapted in order to achieve a postoperative result closer to the normal population.

LEVEL OF EVIDENCE

Therapeutic clinical question Level IV.