Ahmed El Kaffas

Sophie Externbrink, Ahmed El Kaffas, Dimitre Hristov et al.

Tumor perfusion and vascular properties are important determinants of a cancer's response to therapy. In this paper, we discuss the estimation of spatially varying blood flow velocities and perfusion parameters from time-resolved contrast agent concentration data. We compare a standard parabolic advection-diffusion model against a two-compartment model governed by a coupled system of hyperbolic advection-reaction equations, which is physiologically more sound. To address the inherent ill-posedness of this parameter identification problem, we employ Tikhonov regularization and derive continuous adjoint equations necessary for efficient, gradient-based minimization. We discuss the numerical discretization of the state and adjoint systems using state-of-the-art schemes, and demonstrate the efficacy of the proposed reconstruction algorithms through numerical experiments on synthetic data and in vivo dynamic contrast-enhanced ultrasound measurements.

Andrew A. Berlin, Mon Young, Ahmed El Kaffas et al.

Molecularly targeted contrast enhanced ultrasound (mCEUS) is a clinically promising approach for early cancer detection through targeted imaging of VEGFR2 (KDR) receptors. We have developed computational enhancement techniques for mCEUS tailored to address the unique challenges of imaging contrast accumulation in humans. These techniques utilize dynamic analysis to distinguish molecularly bound contrast agent from other contrast-mode signal sources, enabling analysis of contrast agent accumulation to be performed during contrast bolus arrival when the signal due to molecular binding is strongest. Applied to the 18 human patient examinations of the first-in-human molecular ultrasound breast lesion study, computational enhancement improved the ability to differentiate between pathology-proven lesion and pathology-proven normal tissue in real-world human examination conditions that involved both patient and probe motion, with improvements in contrast ratio between lesion and normal tissue that in most cases exceed an order of magnitude (10x). Notably, computational enhancement eliminated a false positive result in which tissue leakage signal was misinterpreted by radiologists to be contrast agent accumulation.