Craniosynostosis is the early fusion of one or more cranial sutures and it affects 1 in 2,100-2,500 live births. It may lead to craniofacial malformations and brain growth constraints during childhood, resulting in elevated intra-cranial pressure and subsequent impaired brain growth. The decision to perform surgery, the right time of surgical treatment, and the interventional approach are determined by the subjective evaluation of cranial malformations, the estimation of their temporal evolution, and the subjective prediction of cranial bone development after surgery. This subjectivity results in late diagnosis and suboptimal treatments, with a high variability of incidence reports, treatment approaches, and outcomes among institutions. Since there are no clinical tools available to predict healthy or pathological cranial growth, there are no objective techniques to optimize the long-term outcome of the treatment of patients with craniosynostosis.
The aims of this proposal are: (1) to create a personalized computational predictive model of normal cranial bone development, and (2) to create a cranial bone development model in presence of craniosynostosis. The PI will also quantify the coupled growth patterns of the bones and the brain, using a brain growth model available from his collaborators. In addition, he will contrast and illustrate the developed techniques in patients with craniosynostosis caused by Muenke syndrome, which is the most common cause of syndromic craniosynostosis. The PI, Dr. Antonio R. Porras, with a PhD in Medical Image Analysis and a strong background in both Computer Science and Biomedical Engineering, is uniquely suited to advance the aims of this proposal. During the training phase, Dr. Porras will foster his expertise in quantitative imaging and statistical modeling, and he will obtain specific training in: (1) cranial development during childhood, (2) medical genetics, and (3) clinical management of patients with cranial malformations. Dr. Porras has assembled a strong multi-disciplinary mentoring team of leaders in in Quantitative Imaging and Statistical Modeling (Dr. Marius George Linguraru ? primary mentor), Medical Genetics and craniosynostosis (Dr. Maximilian Muenke, co-mentor), and cranial/brain development and clinical management of patients with craniosynostosis (Dr. Robert Keating, co-mentor). After the period of this award, Dr. Porras will have the expertise and the tools to promote his ultimate goal of transitioning to an independent career focused on computational phenotyping, modeling of childhood development, and quantitative assessment of developmental abnormalities during childhood.
Craniosynostosis is the early fusion of one or more cranial sutures and it affects 1 in 2100-2500 live birth. The lack of objective, quantitative, and personalized tools to predict cranial bone development and quantify cranial development abnormalities in patients with craniosynostosis is responsible for late diagnoses and suboptimal treatments. The proposed work will create quantitative imaging tools to predict cranial development, characterize its relationship to brain growth, quantify cranial development abnormalities, and identify common abnormal development patterns in patients with craniosynostosis, and has the potential to change their management and prognosis.
