Optimal Enhancement Configuration of Silica Nanoparticles for Ultrasound Imaging and Automatic Detection at Conventional Diagnostic Frequencies

Objectives: To experimentally investigate the acoustical behavior of silica nanoparticles within conventional diagnostic ultrasound fields and to determine a suitable configuration, in terms of particle size and concentration, for their employment as targetable contrast agents. We also assessed the effectiveness of a novel method for automatic detection of targeted silica nanoparticles for future tissue typing applications. Materials and Methods: Silica nanospheres of variable size (160, 330, and 660 nm in diameter) and concentration (10(10)-10(13) part/mL) were dispersed in different custom-designed agarose-based gel samples and imaged at 7.5 MHz with a conventional echograph linked to a research platform for radiofrequency signal acquisition. Off-line analysis included evaluation of backscattered ultrasound amplitude, image brightness, and nanoparticle automatic detection through radiofrequency signal processing. Results: Amplitude of nanoparticle-backscattered signals linearly increased with particle number concentration, but image brightness did not show the same trend, because the logarithmic compression caused the reaching of a plateau where brightness remained almost constant for further increments in particle concentration. On the other hand, both backscatter amplitude and image brightness showed significant increments when particle diameter was increased. Taking into account particle size constraints for tumor targeting (pore size of tumor endothelium and trapping effects because of reticuloendothelial system limit the dimension of effectively employable particles to less than 380 nm), a suitable compromise is represented by the employment of 330-nm silica nanospheres at a concentration of about 1 to 2 X 10(11) part/mL. These particles, in fact, showed the best combination of number concentration and diameter value to obtain an effective enhancement on conventional echographic images. Furthermore, also the sensitivity of the developed method for automatic nanoparticle detection had a maximum (72.8%) with 330-nm particles, whereas it was lower with both bigger and smaller particles (being equal to 64.1% and 17.5%, respectively). Conclusions: Silica nanoparticles at a diameter of about 330 nm are very promising contrast agents for ultrasound imaging and specific tumor targeting at conventional diagnostic frequencies, being in particular automatically detectable with high sensitivity already at low doses. Future studies will be carried out to assess the acoustic behavior of nanoparticles with different geometries/sizes and to improve sensitivity of the automatic detection algorithm.