Wavelet-Based Radiomics Analysis of Dynamic Contrast-Enhanced (DCE)-MR Information for Characterization of Acute Brain Tumor Response in Animal Model
Recommended Citation
Bagher-Ebadian H, Nagaraja T, Cabral G, Farmer KG, Valadie OG, Acharya P, Movsas B, Brown SL, Ewing J, Chetty I. Wavelet-Based Radiomics Analysis of Dynamic Contrast-Enhanced (DCE)-MR Information for Characterization of Acute Brain Tumor Response in Animal Model. Med Phys 2022; 49(6):e289-e290.
Document Type
Conference Proceeding
Publication Date
7-11-2022
Publication Title
Med Phys
Abstract
Purpose: Recent studies have shown that tumor heterogeneity plays a key role in response to treatment and can hinder the treatment efficacy. Decoding heterogeneity information of tumors and regional characterization of their radiation therapy (RT) response remains a major challenge. This study combines a physiological nested model selection (MS) technique with a novel wavelet-based spatiotemporal modeling of DCE-MRI information, enabling evaluation of the RT-affected regions in an animal model of cerebral U-251n tumors. Methods: Twenty-three immunecompromised- RNU rats were implanted with human U251n cancer cells to form an orthotopic glioma (IACUC #1509). For each rat, 28 days after tumor implantation, two DCE-MRI studies (7T-Dual-Gradient-Echo, FOV:32x32mm2, TR/(TE1-TE2)=24ms/(2ms-4ms), flip-angle=18, 400-acquisitions/1.55sec-interval, Magnevist/tail-vein) were performed 24h apart. A single 20Gy stereotactic-radiation exposure was performed before the second MRI (acquired 1-6.5 hours post-RT). DCE-MRI analysis was done using a model-selection technique to distinguish three brain regions: Normal vasculature (Model-1: No-leakage), leaky tumor tissues with no back-flux to vasculature (Model-2), and leaky tumor tissues with back-flux (Model-3). Normalized time-traces of DCE-MRI information (1st and 2nd echoes for pre, and post-RT cohorts) for three model regions were analyzed using a wavelet-based radiomics technique to characterize their time-frequency information before and after RT. For each model, the pre- and post-RT signal coherence level was estimated and compared to rank the effect of RT on different model regions and time-varying DCE-MRI raw data. Results: Compared to the peritumoral tissues (Model-2 region with r=0.622, p<0.0001), the DCE-MRI information of rat brain in normal and highly permeable tissues (Models-1 and 3: r=0.650 with p<0.0001 and r=0.809 with p<0.0001, respectively) are less impacted by RT. Conclusion: This study demonstrates an important step toward spatiotemporal characterization of RT-affected brain regions and the time-varying DCE-MR information, which can play a key role in treatment planning of cancer patients, optimization of imaging, and DCE-MRI pharmacokinetic analysis.
Volume
49
Issue
6
First Page
e289
Last Page
e290
