Evaluating the feasibility of differentiating glioblastoma and normal brain tissue using H-scan imaging: an ex vivo study

Abstract

H-scan imaging is a quantitative ultrasound technique in which raw radiofrequency (RF) echoes are matched to Gaussian-weighted Hermite polynomials of order n, which is related to the size of scatterers. This information is used to characterize tissue structures based on color-mapping large scatterers in the red channel and small scatterers in the blue channel of the H-scan image. Glioblastoma is a malignant tumor of the brain and has one of the most dismal prognoses of all tumors. In this study, we assessed the feasibility of differentiating glioblastoma and normal brain tissue ex vivo using H-scan imaging. Raw RF echoes from ex vivo brain tissues embedded in agarose phantoms were acquired using a Verasonics Vantage 128 system equipped with an L11-5v array. A total of 11 samples each of glioblastoma and normal tissues were evaluated. The intensity-weighted percentage of thered channel (IWPRED), a scatterer size-dependent and concentration-independentparameter, was computed for each sample. The IWPRED parameter estimates of glioblastoma and normal tissue samples were significantly different (24.0% ± 0.7% vs 34.2% ± 1.1%, respectively; p < 0.001). This work demonstrates the feasibility of differentiating glioblastoma tumors from normal tissue using H-scan imaging.