# RadxTools for assessing tumor treatment response on imaging

> **NIH NIH U01** · CASE WESTERN RESERVE UNIVERSITY · 2022 · $233,950

## Abstract

ABSTRACT: Medulloblastoma (MB) is a malignant, fast-growing pediatric brain tumor with heterogenous
outcomes and a 5-year survival rate of 70-80%. Current treatment strategies for MB patients include surgical
resection, chemotherapy, and craniospinal irradiation (CSI), with dose-intensification in high-risk patients
(defined as residual tumor >1.5 cm2, evidence of leptomeningeal metastases, or large-cell/anaplastic histology)
to improve clinical outcomes, while de-escalation of therapy to reduce long-term sequelae in standard-risk MB
patients. Unfortunately, this treatment protocol has only proven useful as a rough guide for predicting
prognosis with the existing clinical stratification; particularly, the 5-year survival rate for the high-risk patients
are currently at about 60%. Additionally, the existing clinical risk stratification fails to identify about 20–30% of
standard-risk patients who might be overtreated and eventually suffer from long-term morbidities that
significantly affect their quality of life. Consequently, there is a critical need for reliable tools to risk-stratify MB
patients based on their survival, with the goal of identifying high-risk MB cases who are most likely to receive
added benefit from adjuvant and concomitant therapy, while de-escalating therapy in low/standard-risk cases.
Through an ongoing NCI U01 award (1U01CA248226-01) from the Informatics Technology for Cancer
Research (ITCR), our group has been leading the development of peri-tumoral (Eur. Rad 20172, AJNR 20183)
and intra-tumoral spatial heterogeneity radiomics, that go beyond texture, shape-based approaches, for
characterization of adult tumors. As an extension to our U01 efforts, in this supplemental project, we propose
to develop two informatics modules for (1) radiomic analysis for tumor characterization on clinical MRI scans
(Gd-T1w, T2w, FLAIR), and (2) a risk-stratification module, for survival risk-stratification of pediatric MB patients.
In our preliminary work, we demonstrated that our biophysical deformation descriptor that characterizes subtle
changes in vasodilation from brain parenchyma on Gd-T1w MRI scans, had higher concordance-index (C-
index) in predicting overall survival in MB patients compared to employing the molecular subgroup-based
stratification [n=89, p<0.05 vs. p=0.6, C-index=0.831 vs. 0.80]. The 2 modules developed in our supplement
project will be leveraged to improve on our initial model (using deformations alone), to (a) include features
relating to (1) 3D topology, (2) localized entropy, and (3) peri-tumoral features from the vicinity of the tumor and
(b) perform MRI-based risk-stratification of MB patients based on their survival characteristics, independent of
molecular stratification. Our collaborative efforts with Children's Hospital Cinncinati, Nationawide Childrens
Columbus, and Children's Brain Tumor Network, will led to creation of a rich, one-of-the-largest MB cohorts for
the pediatric cancer community and will serve ...

## Key facts

- **NIH application ID:** 10593646
- **Project number:** 3U01CA248226-03S1
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Pallavi Tiwari
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $233,950
- **Award type:** 3
- **Project period:** 2020-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10593646

## Citation

> US National Institutes of Health, RePORTER application 10593646, RadxTools for assessing tumor treatment response on imaging (3U01CA248226-03S1). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10593646. Licensed CC0.

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