Validation of Normalized Singular Spectrum Area as a Classifier for Molecularly Targeted Microbubble Adherence

Abstract

Ultrasound molecular imaging is a diagnostic technique wherein molecularly targeted microbubble contrast agents are imaged to reveal disease markers on the blood vessel endothelium. Currently, microbubble adhesion to affected tissue can be quantified using differential targeted enhancement (dTE), which measures the late enhancement of adherent microbubbles through administration of destructive ultrasound pressures. In this study, we investigated a statistical parameter called the normalized singular spectrum area (NSSA) as a means to detect microbubble adhesion without microbubble destruction. We compared the signal differentiation capability of NSSA with matched dTE measurements in a mouse hindlimb tumor model. Results indicated that NSSA-based signal classification performance matches dTE when differentiating adherent microbubble from non-adherent microbubble signals (receiver operating characteristic area under the curve = 0.95), and improves classification performance when differentiating microbubble from tissue signals (p < 0.005). NSSA-based signal classification eliminates the need for destruction of contrast, and may offer better sensitivity, specificity and the opportunity for real-time microbubble detection and classification.

Keywords: Differential targeted enhancement; Microbubbles; Normalized singular spectrum area; Ultrasound molecular imaging.