Revista de Ciências e Engenharia de Materiais

A Preprocessing Filter to Improve Super Paramagnetic Iron Oxide Nanoparticle (SPION): Based Early Tumor Detection

Abstract

Mehdi Baqri*, Sri Kamal K andala and David Fuentes

The early detection of aggressive forms of ovarian cancer before they metastasize is critical for reducing overall mortality from the disease. Super Paramagnetic Relaxometry (SPMR) is an imaging technique useful for visualizing early stage tumors with high sensitivity and specificity. It uses Superconducting Quantum Interference Devices (SQUIDs) to detect targeted Superparamagnetic Iron Oxide Nanoparticles (SPIONs) that visualize tumors ten times smaller than what conventional imaging techniques can. However, the ultra-sensitivity of SQUIDs increases their risk of distortion due to far-field artifacts. Therefore, a preprocessing filter was developed to mitigate far-field, low-frequency disturbances to SQUID signal acquisition. This is based on the hypothesis that correcting SQUID signal acquisition using a magnetometer for far-field detection will increase the accuracy of SPMR for early tumor detection. The hypothesis was tested in three steps. First, it was shown that the Magnetometer (MAG) could specifically detect far-field noise and effectively avoid Nanoparticle (NP) signatures. Second, low-frequency noise was induced to show that far-field artifacts in the MAG signal correlated with distortions in the SQUID channels. Therefore, a preprocessing filter was developed to parse through and parameterize MAG signal extrema to SQUID signal distortions. A series of further optimization steps included anchoring the MAG signal to respective channels, modelling and subtracting the component of structural (environmental) relaxation and constraining a general subtraction window. Third, success was measured by the image reconstruction accuracy of sources with various NP concentrations, using the HSPMR dipole-fitting technique. Overall, the MAG-filter increased reconstruction accuracy more effectively with decreasing NP signal; accuracy increased the most at very low concentrations (~ 1ug). This preliminary data indicate that the filter increases SPMR sensitivity for low NP concentrations representative of small cell clusters, typical of early disease stages. Future work will optimize this initial filter to work uniformly and effectively across different NP concentrations (and tumor sizes) and translate this technology to highly sensitive early tumor detection.