A. Tsalach, I. Steinberg, and I. Gannot, Tel Aviv University, Israel, & Johns Hopkins University
Volume 61, Issue 8, Page: 2313-2323
Cancer is a major public health problem worldwide, especially in developed countries in which life expectancy is longer. Early detection of cancer can greatly increase both survival rates and quality of life for patients. In order to detect cancer at its very early stages, sections of the general population must undergo routine screening tests. Such tests should be rapid, highly sensitive and at very low cost. Yet, for most cancer types there is no accepted diagnostic method that meets the above requirements. To overcome the drawbacks of existing methods, and to enable treatment capacities, we are proposing a super paramagnetic nano-particle (SNP) based magneto-acoustic detection. We present a design and prototype of an optimal multi-sensor array, for measuring the acoustic signals generated by the SNPs. Those are specifically attached to tumor. Through this system we estimate the 3D location of the tumor in real time, deep under tissue surface. A Time Difference of Arrival (TDOA) based localization algorithm was developed, and implemented on the breast tissue geometry in both computerized simulations and in-vitro experiments. Tumor localization feasibility and the hyperbolic positioning algorithm performance were evaluated. Preliminary results are very encouraging. Results demonstrate the ability to localize small tumors, a few mm in diameter, at a depth of a few cm below the skin surface. The positioning accuracy was less than 4mm. Such performance indicates that tumor localization was estimated with high accuracy, and suggests that the combination of magneto-acoustic detection along with a TDOA based localization algorithm can produce an efficient tumor diagnostic system. It enables the detection of tumor presence, as well as triangulation of its location. The presence of these SNP, specifically at tumor surroundings, can be further developed into a powerful “image and treat” system.
Key words: Cancer detection, Magnetic nanoparticles, Magneto-Acoustics.