Cranial normality indices in Ugandan infants based on smartphone photogrammetry: key parameters for the study of cranial deformation
[EN] Background Early identification of cranial deformities in infants is essential for timely intervention and preventing long-term complications. In Uganda, particularly in rural areas, access to specialised paediatric healthcare remains limited, making it difficult to diagnose and manage cranial...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:riunet______::b14d2be544a12efee8b5d8abe077c4c3 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/235831 |
| Access Level: | acceso abierto |
| Palabra clave: | Cranial morphology Cranial indices Infant head shape Uganda Paediatric health Photogrammetry Cephalic index CVAI Frontal angle Early diagnosis 03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades 10.- Reducir las desigualdades entre países y dentro de ellos |
| Sumario: | [EN] Background Early identification of cranial deformities in infants is essential for timely intervention and preventing long-term complications. In Uganda, particularly in rural areas, access to specialised paediatric healthcare remains limited, making it difficult to diagnose and manage cranial abnormalities early. This study takes a unique approach by using the PhotoMeDAS system. This non-invasive technology allows accurate cranial measurements through QR-based imaging to define normative cranial index ranges for Ugandan infants. By analysing key cranial parameters associated with head shape, symmetry, and overall growth patterns, this study aims to establish reference values that can serve as a baseline for clinical assessments. Methods A cross-sectional study was conducted in healthcare centres in Lugazi, Uganda, collecting cranial measurements from 195 infants aged 0¿2 years old. The data was collected using the PhotoMeDAS system, a noninvasive technology that allows accurate cranial measurements through QR-based imaging. The primary cranial variables analysed included Head Circumference (HC), Cephalic Index (CI), Cranial Vault Asymmetry Index (CVAI), Pseudovolume (PV), and Frontal Angle (FA). HC was measured to establish general growth patterns, while the CI provided insights into head shape classification (dolichocephalic, mesocephalic, or brachycephalic). The CVAI assessed cranial symmetry, detecting potential cases of plagiocephaly, while the PV evaluated the proportionality of cranial growth relative to the perimeter. Finally, the FA was considered to assess anterior cranial development and forehead morphology. For the management and optimisation of processes, Microsoft Visio was used to create flow diagrams that facilitated the organisation of the paediatric campaign. SPSS and Excel were employed for statistical analysis, evaluating the relationship between cranial indices and variables such as sex, age, and ethnicity. Normality tests (KolmogorovSmirnov), chi-square tests, and ANOVA were applied to identify distribution patterns and significant variations among subgroups. In addition, Python was used to process cranial images obtained during the paediatric research. |
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