Quantifying dysmorphologies of the neurocranium using artificial neural networks.

BACKGROUND: Craniosynostosis, a congenital condition characterized by the premature fusion of cranial sutures, necessitates objective methods for evaluating cranial morphology to enhance patient treatment. Current subjective assessments often lead to inconsistent outcomes. This study introduces a novel, quantitative approach to classify craniosynostosis and measure its severity. METHODS: An artificial neural network was trained to classify normocephalic, trigonocephalic, and scaphocephalic head shapes based on a publicly available dataset of synthetic 3D head models. Each 3D model was converted into a low-dimensional shape representation based on the distribution of normal vectors, which served as the input for the neural network, ensuring complete patient anonymity and invariance to geometric size and orientation. Explainable AI methods were utilized to highlight significant features when making predictions. Additionally, the Feature Prominence (FP) score was introduced, a novel metric that captures the prominence of distinct shape characteristics associated with a given class. Its relationship with clinical severity scores was examined using the Spearman Rank Correlation Coefficient. RESULTS: The final model achieved excellent test accuracy in classifying the different cranial shapes from their low-dimensional representation. Attention maps indicated that the network's attention was predominantly directed toward the parietal and temporal regions, as well as toward the region signifying vertex depression in scaphocephaly. In trigonocephaly, features around the temples were most pronounced. The FP score showed a strong positive monotonic relationship with clinical severity scores in both scaphocephalic (ρ = 0.83, p < 0.001) and trigonocephalic (ρ = 0.64, p < 0.001) models. Visual assessments further confirmed that as FP values rose, phenotypic severity became increasingly evident. CONCLUSION: This study presents an innovative and accessible AI-based method for quantifying cranial shape that mitigates the need for adjustments due to age-specific size variations or differences in the spatial orientation of the 3D images, while ensuring complete patient privacy. The proposed FP score strongly correlates with clinical severity scores and has the potential to aid in clinical decision-making and facilitate multi-center collaborations. Future work will focus on validating the model with larger patient datasets and exploring the potential of the FP score for broader applications. The publicly available source code facilitates easy implementation, aiming to advance craniofacial care and research.

3D Analysis of the Cranial and Facial Shape in Craniosynostosis Patients: A Systematic Review.

With increasing interest in 3D photogrammetry, diverse methods have been developed for craniofacial shape analysis in craniosynostosis patients. This review provides an overview of these methods and offers recommendations for future studies. A systematic literature search was used to identify publications on 3D photogrammetry analyses in craniosynostosis patients until August 2023. Inclusion criteria were original research reporting on 3D photogrammetry analyses in patients with craniosynostosis and written in English. Sixty-three publications that had reproducible methods for measuring cranial, forehead, or facial shape were included in the systematic review. Cranial shape changes were commonly assessed using heat maps and curvature analyses. Publications assessing the forehead utilized volumetric measurements, angles, ratios, and mirroring techniques. Mirroring techniques were frequently used to determine facial asymmetry. Although 3D photogrammetry shows promise, methods vary widely between standardized and less conventional measurements. A standardized protocol for the selection and documentation of landmarks, planes, and measurements across the cranium, forehead, and face is essential for consistent clinical and research applications.

Automated three-dimensional analysis of facial asymmetry in patients with syndromic coronal synostosis: A retrospective study.

Craniosynostosis, characterized by premature fusion of one or more cranial sutures, results in a distorted skull shape. Only three studies have assessed facial asymmetry manually in unicoronal synostosis patients. It is therefore important to understand how uni- and bicoronal synostosis affect facial asymmetry with a minimum risk of human bias. An automated algorithm was developed to quantify facial asymmetry from three-dimensional images, generating a mean facial asymmetry (MFA) value in millimeters to reflect the degree of asymmetry. The framework was applied to analyze postoperative 3D images of syndromic patients (N = 35) diagnosed with Muenke syndrome, Saethre-Chotzen syndrome, and TCF12-related craniosynostosis with respect to MFA values from a healthy control group (N = 89). Patients demonstrated substantially higher MFA values than controls: Muenke syndrome (unicoronal 1.74 ± 0.40 mm, bicoronal 0.77 ± 0.21 mm), Saethre-Chotzen syndrome (unicoronal 1.15 ± 0.20 mm, bicoronal 0.69 ± 0.16 mm), and TCF12-related craniosynostosis (unicoronal 1.40 ± 0.51 mm, bicoronal 0.66 ± 0.05 mm), compared with controls (0.49 ± 0.12 mm). Longitudinal analysis identified an increasing MFA trend in unicoronal synostosis patients. Our study revealed higher MFA in syndromic patients with uni- and bicoronal synostosis compared with controls, with the most pronounced MFA in Muenke syndrome patients with unilateral synostosis. Bicoronal synostosis patients demonstrated higher facial asymmetry than expected given the condition's symmetrical presentation.

Reliability and Agreement of Automated Head Measurements From 3-Dimensional Photogrammetry in Young Children.

This study aimed to assess the reliability and agreement of automated head measurements using 3-dimensional (3D) photogrammetry in young children. Specifically, the study evaluated the agreement between manual and automated occipitofrontal circumference (OFC) measurements (n = 264) obtained from 3D images of 188 patients diagnosed with sagittal synostosis using a novel automated method proposed in this study. In addition, the study aimed to determine the interrater and intrarater reliability of the automatically extracted OFC, cephalic index, and volume. The results of the study showed that the automated OFC measurements had an excellent agreement with manual measurements, with a very strong regression score ( R2 = 0.969) and a small mean difference of -0.1 cm (-0.2%). The limits of agreement ranged from -0.93 to 0.74 cm, falling within the reported limits of agreement for manual OFC measurements. High interrater and intrarater reliability of OFC, cephalic index, and volume measurements were also demonstrated. The proposed method for automated OFC measurements was found to be a reliable alternative to manual measurements, which may be particularly beneficial in young children who undergo 3D imaging in craniofacial centers as part of their treatment protocol and in research settings that require a reproducible and transparent pipeline for anthropometric measurements. The method has been incorporated into CraniumPy, an open-source tool for 3D image visualization, registration, and optimization, which is publicly available on GitHub ( https://github.com/T-AbdelAlim/CraniumPy ).

Sagittal Craniosynostosis: Comparing Surgical Techniques Using 3D Photogrammetry.

BACKGROUND: The aim of this study was to compare three surgical interventions for correction of sagittal synostosis-frontobiparietal remodeling (FBR), extended strip craniotomy (ESC), and spring-assisted correction (SAC)-based on three-dimensional (3D) photogrammetry and operation characteristics. METHODS: Patients who were born between 1991 and 2019 and diagnosed with nonsyndromic sagittal synostosis who underwent FBR, ESC, or SAC and had at least one postoperative 3D photogrammetry image taken during one of six follow-up appointments until age 6 were considered for this study. Operative characteristics, postoperative complications, reinterventions, and presence of intracranial hypertension were collected. To assess cranial growth, orthogonal cranial slices and 3D photocephalometric measurements were extracted automatically and evaluated from 3D photogrammetry images. RESULTS: A total of 322 postoperative 3D images from 218 patients were included. After correcting for age and sex, no significant differences were observed in 3D photocephalometric measurements. Mean cranial shapes suggested that postoperative growth and shape gradually normalized with higher occipitofrontal head circumference and intracranial volume values compared with normal values, regardless of type of surgery. Flattening of the vertex seems to persist after surgical correction. The authors' cranial 3D mesh processing tool has been made publicly available as a part of this study. CONCLUSIONS: The findings suggest that until age 6, there are no significant differences among the FBR, ESC, and SAC in their ability to correct sagittal synostosis with regard to 3D photocephalometric measurements. Therefore, efforts should be made to ensure early diagnosis so that minimally invasive surgery is a viable treatment option. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

A bibliometric overview of craniosynostosis research development.

This article reviews the development of research in the field of craniosynostosis from a bibliometric standpoint. Craniosynostosis is a malformation occurring during the early development of the skull, when one or more of the sutures close too early, causing problems with normal brain and skull growth. Research in this field has developed from early clinical case descriptions, to genetic discoveries responsible for the occurring malformations and onwards to developing sophisticated surgical treatment. In this article we describe these developments, zoom in on publication trends and characteristics and visualize developing networks and topic shifts in this research field.

Three-Dimensional Stereophotogrammetry in the Evaluation of Craniosynostosis: Current and Potential Use Cases.

ABSTRACT: Three-dimensional (3D) stereophotogrammetry is a novel imaging technique that has gained popularity in the medical field as a reliable, non-invasive, and radiation-free imaging modality. It uses optical sensors to acquire multiple 2D images from different angles which are reconstructed into a 3D digital model of the subject's surface. The technique proved to be especially useful in craniofacial applications, where it serves as a tool to overcome the limitations imposed by conventional imaging modalities and subjective evaluation methods. The capability to acquire high-dimensional data in a quick and safe manner and archive them for retrospective longitudinal analyses, provides the field with a methodology to increase the understanding of the morphological development of the cranium, its growth patterns and the effect of different treatments over time.This review describes the role of 3D stereophotogrammetry in the evaluation of craniosynostosis, including reliability studies, current and potential clinical use cases, and practical challenges. Finally, developments within the research field are analyzed by means of bibliometric networks, depicting prominent research topics, authors, and institutions, to stimulate new ideas and collaborations in the field of craniofacial 3D stereophotogrammetry.We anticipate that utilization of this modality's full potential requires a global effort in terms of collaborations, data sharing, standardization, and harmonization. Such developments can facilitate larger studies and novel deep learning methods that can aid in reaching an objective consensus regarding the most effective treatments for patients with craniosynostosis and other craniofacial anomalies, and to increase our understanding of these complex dysmorphologies and associated phenotypes.