Automated measurement of intracranial volume using three-dimensional photography.

OBJECTIVE Current methods to analyze three-dimensional (3D) photography do not quantify intracranial volume (ICV), an important metric of development. This study presents the first non-invasive, radiation-free, accurate and reproducible method to quantify ICV from 3D photography. METHODS In this retrospective study, cranial bones and head skin were automatically segmented from CT images of 575 subjects without cranial pathology (average age 5 ± 5 years; range 0-16 years). The ICV and the head volume were measured at the cranial vault region, and their relation was modeled by polynomial regression, also accounting for age and sex. Then, the regression model was used to estimate the ICV of 30 independent pediatric patients from their head volume measured in 3D photography. Evaluation was performed by comparing the estimated ICV with the true ICV of these patients computed from paired CT images; two growth models were used to compensate for the time gap between CT and 3D photography. RESULTS The regression model estimated the ICV of the normative population from the head volume calculated from CT images with an average error of 3.81 ± 3.15 % (p = 0.93) and a correlation (R²) of 0.96. We obtained an average error of 4.07 ± 3.01% (p = 0.57) in estimating the ICV of the patients from 3D photography using the regression model. CONCLUSION 3D photography with image analysis provides measurement of ICV with clinically acceptable accuracy, thus offering a non-invasive, precise and reproducible method to evaluate normal and abnormal brain development in young children.