A biomagnetic system for in vivo cancer imaging

Abstract

An array of highly sensitive biomagnetic sensors of the superconducting quantum interference detector (SQUID) type can identify disease in vivo by detecting and imaging microscopic amounts of nanoparticles. We describe in detail procedures and parameters necessary for implementation of in vivo detection through the use of antibody-labelled magnetic nanoparticles as well as methods of determining magnetic nanoparticle properties. We discuss the weak field magnetic sensor SQUID system, the method of generating the magnetic polarization pulse to align the magnetic moments of the nanoparticles, and the measurement techniques to measure their magnetic remanence fields following this pulsed field. We compare these results to theoretical calculations and predict optimal properties of nanoparticles for in vivo detection.

Figure 1

Photograph of system with silicone breast phantom in place.

Figure 2

Cartoon of coated nanoparticle.

Figure 3

MRI of phantom containing nanoparticles.

Figure 4

Remanence fields for slide with leukocyte cells.

Figure 5

Remanence fields for four nanoparticle types of table 1.

Figure 6

Remanence fields from three different phantom sources.

Figure 7

Effects of pre-magnetization on 15 nm nanoparticles.

Figure 8

Effective magnetic moment for times after the termination of the magnetizing pulse as a function of the particle radius.

Figure 9

Average remanent dipole.

Figure 10

The fraction of saturation, L(x){1 − exp(t₀/τ_N)}, reached on the average by a given nanoparticle with a magnetite core of radius r is shown for a magnetizing field of 32.8 × 10⁻⁴ T with various durations of application. These results indicate that our technique can be made much more efficient if the pulse duration is reduced.

Figure 11

The fraction of saturation, L(x){1 − exp(t₀/τ_N)}, reached on the average by a given nanoparticle with a magnetite core of radius r is shown using a magnetizing pulse duration of 1 s for various strengths of the magnetizing field.

Figure 12

The peak fractions of saturation for various field strengths shown in figure 13 plotted versus the field strength. We see that our signal can be increased by increasing the field strength, but that we are nearing the point of diminishing returns at around 50 G.

Figure 13

Source image from electromagnetic forward calculation compared to measured data. The results are shown in terms of goodness of fit using contour lines to indicate chi-squared values. The central region indicates an error of ±4 mm in localizing the source. The x and y axes are in millimetres in relative values.