Leveraging existing pediatric low-grade tumor specimens, clinical and imaging outcome data and artificial intelligence innovations to develop integrated biomarkers of response for children with low-grade glioma

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Benjamin H. Kann

Harvard Medical School
Boston, MA


About this


The overall hypothesis is that by using state of the art molecular profiling and artificial intelligence (AI) methods, we will develop imaging biomarkers that predict underlying subtype and response to therapies for pediatric low grade glioma (pLGG). The knowledge gap that will be addressed is our current limited understanding of integrated imaging and molecular characteristics; such increased insights will allow us to better match an individual child’s tumor to a specific therapy.

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What are the goals of this project?

To develop and validate (a) imaging-based correlates for multi-omic LGG/BRAF signatures, and (b) prognostic radiomic and radiogenomic biomarkers for progression and survival. We will develop non-invasive, imaging-based signatures to predict underlying BRAF-alterations and molecular subtype. We will determine if radiomic signatures can predict tumor aggressiveness, progression and survival in pLGG.

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Meet The



Benjamin H. Kann, MD

Dr. Benjamin Kann's research is focused on the development and application of machine learning and neural networks for cancer imaging analysis and the development of digital biomarkers to predict clinical outcomes. He is interested in the use of artificial intelligence and cancer imaging to develop


Harvard Medical School

Boston, MA

Seyed Ali Nabavizadeh, MD

Dr. Ali’s research focuses on multimodality imaging using structural and physiologic MRI imaging with additional PET probes and molecular imaging techniques to better understand the complex nature of brain tumor microenvironment. The ultimate goal of his research is to use imaging and liquid biopsy


Children’s Hospital of Philadelphia

Philadelphia, PA, USA
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Christos Davatzikos, PhD

Christos Davatzikos is the Wallace T. Miller Sr. Professor of Radiology at the University of Pennsylvania, and Director of the Center for Biomedical Image Computing and Analytics. Dr. Davatzikos’s interests are in medical image analysis. He oversees a diverse research program ranging from basic pro


University of Pennsylvania

Philadelphia, PA

Scientific Committee

Executive Board

Scientific co-Chair

Principal Investigator

Adam Resnick, PhD

Adam Resnick is the Director of Data Driven Discovery in Biomedicine (D3b) at Children’s Hospital of Philadelphia (CHOP) responsible for leading a multidisciplinary team to build and support a scalable, patient-focused healthcare and educational discovery ecosystem on behalf of all children. He is a


Children’s Hospital of Philadelphia

Philadelphia, PA, USA