Ultrasonic radio-frequency spectrum analysis differentiates normal and edematous brain tissue from meningioma intraoperatively.

ABSTRACT

Intraoperative ultrasound imaging of the brain is used for tumor localization and resection control. The aim of the present study was to prove whether spectral analysis of radio-frequency (rf) signals is able to improve its diagnostic capabilities by adding quantitative acoustical parameters to pure visual analysis. Meningioma was chosen as a first model because of its distinct borders during surgery as well as in ultrasound imaging. Rf signals were captured intraoperatively. Spectral analysis of rf signals was performed off-line in areas of normal brain, edematous tissue, and meningioma within the bandwidth of the transducer. At 5.0 MHz, attenuation allowed significant differentiation for normal brain versus edema (P= .00002), normal brain versus meningioma (P= .000004), and edema versus meningioma (P= .002). The slope of attenuation reached significant levels among the three groups, too. Backscatter analysis consisted of determination of the power spectral density with a significant difference for edema versus meningioma at 5 MHz (P= .02). The same was true for a relative integrated backscatter coefficient (P= .01). Frequency-dependent backscatter coefficients were estimated using a standard phantom with edema showing the highest values followed by parenchyma and meningioma. Spectral analysis of rf signals has the potential of differentiating intracranial tissues as could be shown exemplarily with meningioma in this study. If this is also true for infiltrating tumors, the method might serve as a tool to better define tumor borders, thus improving the extent of resection.