Performance of Standardized Relative CBV for Quantifying Regional Histologic Tumor Burden in Recurrent High-Grade Glioma: Comparison against Normalized Relative CBV Using Image-Localized Stereotactic Biopsies

Autor: Richard S. Zimmerman, Chandan Krishna, Leland S. Hu, Maciej M. Mrugala, Bernard R. Bendok, Ashley M. Stokes, Christopher Quarles, Jenny Eschbacher, Kristin R. Swanson, Gustavo De Leon, Gina L. Mazza, A.C. Gonzales, Leslie C. Baxter, Devi P. Patra, Kris A. Smith, Yuxiang Zhou, Kyle W. Singleton, Alyx B. Porter, Joseph M. Hoxworth, Jerrold L. Boxerman, Kathleen M. Schmainda
Rok vydání: 2020
Předmět:
Zdroj: AJNR Am J Neuroradiol
ISSN: 1936-959X
0195-6108
DOI: 10.3174/ajnr.a6486
Popis: BACKGROUND AND PURPOSE: Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects. MATERIALS AND METHODS: We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation (r), against histologic tumor content (0%–100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor). RESULTS: Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%–100%) for normalized (r = 0.63, P
Databáze: OpenAIRE