# Magneto-Acoustic Imaging in Biology
## 3 Mat-Mi
### Development of MAT-MI in [PERSON]'s Laboratory  
Although the 2005 article by [PERSON] and [PERSON] established MAT-MI as a feasible way to measure conductivity, the nagging question was if it could image biological tissue instead of a loop of wire. Working with graduate student [PERSON], they soon improved the method so it could image saline and gel phantoms having a conductivity comparable to that of tissue [11,12]. Moreover, they performed a detailed theoretical analysis in which they started with a known conductivity distribution, calculated the ultrasound signal that should be produced by it during MAT-MI, added noise, and then ran the results through their conductivity imaging algorithm [12]. This analysis allowed them to determine how sensitive MAT-MI was to noise. He, collaborating with [PERSON] and visiting scientist [PERSON], altered MAT-MI by adding an acoustic lens in front of the ultrasound transducer [13]. In this way, the transducer detected an acoustic signal from a single plane, producing a two-dimensional image that is analogous to a traditional ultrasound B-scan. The sample could then be scanned in the direction perpendicular to that plane, providing a three-dimensional imaging procedure that they called the \"focused cylindrical scanning mode.\" They used this technique to analyze a block of pork muscle embedded in a layer of fat, which produced the first image of a biological sample using MAT-MI. Graduate student [PERSON] and coworkers in [PERSON]'s lab [14] extended this idea, showing that focusing allowed the transducer to be placed closer to the sample than a nonfocused \"point-receiver\" transducer, increasing its sensitivity. [PERSON] and [PERSON] further explored the theoretical underpinnings of MAT-MI [15,16]. [PERSON], [PERSON], and [PERSON] then formulated a new theory for MAT-MI imaging [17]. They started by noting that the source of the acoustic signal is the _divergence_ of the Lorentz force distribution, which for a uniform magnetic field is equal to the dot product of the magnetic field and the curl of the current density. However, a general vector field is specified by its divergence and curl, and [PERSON] et al. lacked information about the _curl_ of the Lorentz force distribution. They noted that the curl of the force typically produces shear waves rather than pressure waves, and shear waves attenuate rapidly. Therefore, they ignored the curl of the force and analyzed a curl-free vector field whose divergence was the acoustic source. Their theoretical analysis and computer simulations showed that this innovative vectorial approach improved the reconstruction of the conductivity distribution. One of the most frustrating limitations of most MAT-MI algorithms for imaging conductivity was that they detected a signal arising from where the conductivity changed, but could not image regions having a uniform conductivity. [PERSON] and [PERSON] discovered they could get around this limitation if they utilized multiple coils to induce the eddy currents [18] (Figure 5). Their novel design, which they named \"multi-excitation MAT-MI,\" provided a better estimation of the conductivity in regions where it is homogeneous. A subsequent paper combined the multi-excitation scheme with acoustic focusing to create a truly three-dimensional imaging technique [19]. By 2010--a mere five years after the introduction of magnetoacoustic tomography with magnetic induction--[PERSON]'s group was perfecting MAT-MI as a powerful tool for imaging biological tissue [20]. With [PERSON], [PERSON] was able to image tissue with a spatial resolution of better than 2 mm [21]. The resolution is ultimately set by the frequency response of the ultrasonic transducer. Their transducers responded to signals with a frequency of about 500 kHz. To further improve the resolution would require detecting higher frequencies, but such high-frequency waves suffer from severe attenuation.