|Awarded On||August 19, 2020|
|Title||Development of Artificial Intelligence Framework for Assessment of Responses to Treatment and Automated Tumor Volume Measurement in Glioblastoma|
|Award Mechanism||High Impact/High Risk|
|Institution/Organization||The University of Texas Health Science Center at Houston|
|Principal Investigator/Program Director||Jay-Jiguang Zhu|
|Cancer Sites||Brain and Other Nervous System|
Poor prognosis with short median overall survival of 11 months of glioblastoma patients (GBM, WHO grade IV) has been a prominent problem in brain cancer field. One of the major challenges is the lack of accurate tool for identification of GBM status post chemo-radiation (SOC), which is often ambiguous. The limited reliability of MRIs in determination of GBM progression has been a big issue for physicians to decide when to change treatment. Although advanced brain tumor imaging MRI technologies (ABTI MRI) helps, their cost and availability make them not accessible to most patients, especially in non-academic centers. There are also data, such as information electronic health records and molec...