[{"innerBlocks":[],"name":"core\/freeform","postId":704,"blockType":{"name":"core\/freeform","keywords":[],"attributes":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"providesContext":[],"usesContext":[],"selectors":[],"supports":{"className":false,"customClassName":false,"reusable":false},"styles":[],"variations":[],"apiVersion":3,"title":"Classic","description":"Use the classic WordPress editor.","category":"text"},"originalContent":"Researchers from Children\u2019s National Health System are looking to see if predictive modeling can be used to anticipate rare diseases.

The study, recently funded by federal grants, seeks to incorporate the use of quantitative imaging, computer modeling and artificial intelligence to diagnose some rare diseases.

Antonio Porras, a staff scientist at the Sheikh Zayed Institute for Pediatric Surgical Innovation, has received the Pathway to Independence Award from the National Institutes of Health to fund research on developing two bone growth models that will better inform clinicians treating patients with craniosynostosis and help to optimize outcomes.

Craniosynostosis is the early fusion of one or more cranial sutures that may lead to craniofacial malformations and brain growth constraints during childhood. Affecting one in 2,100 to 2,500 live births, the condition is treatable but there are currently no personalized clinical tools available to predict healthy or pathological cranial growth and no objective techniques to optimize the long-term outcome of treatment for patients with the disease.

Another Children\u2019s National researcher, Marius George Linguraru, has been awarded a Congressionally Directed Medical Research Program grant through the Department of Defense. This grant enables Linguraru to develop a quantitative MRI application that can inform treatment decisions by accurately identifying which children with neurofibromatosis type 1 (NF1) and optic pathway glioma (OPG) are at risk of losing their vision.

NF1 is a genetic condition occurring in one in 3,000 to 4,000 live births that is characterized by changes in skin coloring and the growth of tumors along nerves in the skin, brain and other parts of the body.

This project will provide doctors with certainty when identifying which children with NF1-OPG will lose vision\u2014and when the vision loss will occur\u2014through computational modeling validated in clinics worldwide. Using Linguraru's technology, diagnosis can occur before visual acuity starts to decline, providing an opportunity for early intervention in children at risk for vision loss.

Early diagnosis and treatment can help to avoid lifelong visual impairment for patients who need intervention while preventing unnecessary MRIs and aggressive chemotherapy in pediatric patients who are not at risk of vision loss.","saveContent":"Researchers from Children\u2019s National Health System are looking to see if predictive modeling can be used to anticipate rare diseases.

The study, recently funded by federal grants, seeks to incorporate the use of quantitative imaging, computer modeling and artificial intelligence to diagnose some rare diseases.

Antonio Porras, a staff scientist at the Sheikh Zayed Institute for Pediatric Surgical Innovation, has received the Pathway to Independence Award from the National Institutes of Health to fund research on developing two bone growth models that will better inform clinicians treating patients with craniosynostosis and help to optimize outcomes.

Craniosynostosis is the early fusion of one or more cranial sutures that may lead to craniofacial malformations and brain growth constraints during childhood. Affecting one in 2,100 to 2,500 live births, the condition is treatable but there are currently no personalized clinical tools available to predict healthy or pathological cranial growth and no objective techniques to optimize the long-term outcome of treatment for patients with the disease.

Another Children\u2019s National researcher, Marius George Linguraru, has been awarded a Congressionally Directed Medical Research Program grant through the Department of Defense. This grant enables Linguraru to develop a quantitative MRI application that can inform treatment decisions by accurately identifying which children with neurofibromatosis type 1 (NF1) and optic pathway glioma (OPG) are at risk of losing their vision.

NF1 is a genetic condition occurring in one in 3,000 to 4,000 live births that is characterized by changes in skin coloring and the growth of tumors along nerves in the skin, brain and other parts of the body.

This project will provide doctors with certainty when identifying which children with NF1-OPG will lose vision\u2014and when the vision loss will occur\u2014through computational modeling validated in clinics worldwide. Using Linguraru's technology, diagnosis can occur before visual acuity starts to decline, providing an opportunity for early intervention in children at risk for vision loss.

Early diagnosis and treatment can help to avoid lifelong visual impairment for patients who need intervention while preventing unnecessary MRIs and aggressive chemotherapy in pediatric patients who are not at risk of vision loss.","order":0,"get_parent":{},"attributes":[],"attributesType":{"content":{"type":"string","source":"raw"},"lock":{"type":"object"}},"dynamicContent":""}]

Research eyes AI, imaging and modeling to find rare diseases

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