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$1M grant funds research on quantitative imaging for tumors

“For children who are at risk of losing their vision, this project will bring a window of opportunity for physicians to start treatment earlier and save their vision,” says Marius George Linguraru, DPhil, MA, MSc.

A team from Children’s National Hospital is part of a project receiving a two-year grant of nearly $1,000,000 from the National Institutes of Health (NIH) for the first pediatric project in the Quantitative Imaging Network (QIN) of the National Cancer Institute (NCI). Marius George Linguraru, DPhil, MA, MSc, principal investigator from the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National Hospital in Washington, D.C., is one of two principal investigators on the project, which focuses on developing quantitative imaging (QI) tools to improve pediatric tumor measurement, risk predictions and treatment response. Roger Packer, M.D., Senior Vice President of the Center for Neuroscience & Behavioral Health, Director of the Gilbert Neurofibromatosis Institute and Director of the Brain Tumor Institute, is co-investigator.

The project, in collaboration with Children’s Hospital of Philadelphia and Children’s Hospital Colorado, centers on the most common type of brain tumor in children, called a low-grade glioma. This project focuses on a clinically challenging group of children with neurofibromatosis type 1 (NF1), the most common inherited tumor predisposition syndrome. Nearly 20% of children with NF1 will develop a low-grade glioma called optic pathway glioma (OPG). In children with this type of brain tumor, the growth occurs around the optic nerve, chiasm and tracts, also called the optic pathway, which connects the eye to the brain. OPGs can cause vision loss and even blindness. Permanent vision loss usually occurs between one and eight years of age with doctors closely monitoring the tumor with magnetic resonance imaging (MRI) to assess the disease progression.

“Our traditional two-dimensional measures of tumor size are not appropriate to assess the changes in these amorphous tumors over time or how the tumor responds to treatment,” says Linguraru. “This means physicians have difficulty determining the size of the tumor as well as when treatment is working. Research such as this can lead to innovative medical technologies that can improve and possibly change the fate of children’s lives.”

Dr. Linguraru is leading the technical trials on this project, which take place in the first two years, or phase one, starting in June 2020. Phase one focuses on improving the often inaccurate human measurements of tumor size by developing QI tools to make precise and automated measures of tumor volume and shape using machine learning. In this phase, the project will use and homogenize MRI data from multiple centers to develop predictive models of the treatment response based on the tumor volume that are agnostic to the differences in imaging protocols. By doing this, it will allow physicians to make more informed decisions about the treatment’s success and whether the child will recover their vision.

When phase one is complete, Linguraru and the project’s other principal investigator Robert A. Avery, DO, MSCE, neuro-ophthalmologist in the Division of Ophthalmology at Children’s Hospital of Philadelphia, will initiate the second phase, which includes validating the QI application on data from the first ever phase III clinical trial comparing two treatments for NF1-OPGs. Phase two is scheduled to start in the Summer 2022 and continue through Summer 2025.

“For children who are at risk of losing their vision, this project will bring a window of opportunity for physicians to start treatment earlier and save their vision,” says Linguraru. “For those children who won’t benefit from chemotherapy because the tumor poses no threat to their sight, this project will save them from having to go through that difficult treatment unnecessarily. It will be life-changing for the children and their families, which is what excites me about this QI application.”

This project is a collaboration between Children’s Hospital of Philadelphia and Children’s National Hospital in Washington, D.C., in partnership with Children’s Hospital of Colorado and University of Pennsylvania. Upon project completion, the QI application will provide a precision-medicine approach for NF1-OPGs and improve clinical outcomes for pediatric tumors.

Marius George Linguraru

Marius George Linguraru, D.Phil., M.A., M.Sc., awarded Department of Defense grant for Neurofibromatosis application development

Marius George Linguraru

Marius George Linguraru, D.Phil., M.A., M.Sc., is a principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National, where he founded and directs the Precision Medical Imaging Laboratory. He’s an expert in quantitative imaging and artificial intelligence.

Marius George Linguraru, D.Phil., M.A., M.Sc., a principal investigator in the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children’s National has been awarded a Congressionally Directed Medical Research Program (CDMRP) grant through the Department of Defense. This grant allows Dr. Linguraru to develop a novel 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.

This grant is part of the Neurofibromatosis Research Program of the CDMRP, which fills research gaps by funding high impact, high risk and high gain projects. Dr. Linguraru, who directs the Precision Medical Imaging Laboratory in the Sheikh Zayed Institute, is collaborating with the Gilbert Family Neurofibromatosis Institute and the Children’s Hospital of Philadelphia on this project.

An expert in quantitative imaging and artificial intelligence, Dr. Linguraru has published several peer-reviewed studies on NF1 and OPG, a tumor that develops in 20 percent of children with NF1. The OPG tumor can cause irreversible vision loss, leading to permanent disability in about 50 percent of children with the tumor. This project, titled “MRI Volumetrics for Risk Stratification of Vision Loss in Optic Pathway Gliomas Secondary to NF1” will provide doctors certainty when identifying which children with NF1-OPG will lose vision and when the vision loss will occur.

Dr. Linguraru and his team will validate the quantitative MRI application that they’re developing by studying children at 25 NF1 clinics from around the world. Doctors using the application, which will perform comprehensive measurements of the OPG tumor’s volume, shape and texture, will upload their patient’s MRI into Dr. Lingurau’s application. Using recent advances in quantitative image analysis and machine learning, the application will then definitively determine whether the child’s NF1-OPG is going to cause vision loss and therefore requires treatment.

This diagnosis can occur before visual acuity starts to decline, which provides an opportunity for early treatment in children at risk for vision loss. Dr. Linguraru believes that early diagnosis and treatment can help to avoid lifelong visual impairment for these patients while preventing unnecessary MRIs and aggressive chemotherapy in pediatric patients who are not at risk of vision loss.

Occurring in one in 3,000 to 4,000 live births, NF1 is a genetic condition that manifests in early childhood and is characterized by changes in skin coloring and the growth of tumors along nerves in the skin, brain and other parts of the body. It is unknown why the OPG tumor caused by NF1 only results in vision loss for 50 percent of children. Some children will sustain lifelong disability from their vision loss, despite receiving treatment for their tumor, likely because treatment was started late. In other instances, doctors are unknowingly treating NF1-OPGs that would never cause vision loss.

Dr. Linguraru and his team have already proven that their computer-based, quantitative imaging measures are more objective and reliable than the current clinical measures, enabling doctors to make earlier and more accurate diagnoses and develop optimal treatment plans.