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

Email Principal Investigator
Ongoing
Data
LGG
Default project image
benjamin_kann.jpg

Benjamin H. Kann

Harvard Medical School
Boston, MA

CBTN Data

About this

Project

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.

Ask The

Scientists

Ask the scientists

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.

Explore the data in these informatics portals

cbioportal_logo.png

Meet The

Team

benjamin_kann.jpg

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

101032_1331178.jpg.2000x1333_q95_crop-smart_upscale.jpg

Harvard Medical School

Boston, MA
nabavizadeh_seyed.jpg

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

CHOP.jpg

Children’s Hospital of Philadelphia

Philadelphia, PA, USA
Default person avatar

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-campus-upenn_1200xx3800-2138-0-198.jpg

University of Pennsylvania

Philadelphia, PA
ewc_CHOPFoundation(1)01201604184.jpg

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

CHOP.jpg

Children’s Hospital of Philadelphia

Philadelphia, PA, USA