Magnetic Relaxometry: A Comparison to Magnetoencephalography
Magnetic relaxometry is a technology utilizing SQUID sensors and superparamagnetic nanoparticles to target various diseases using antibodies or other biomolecules specific to disease cells. The nanoparticles are magnetized in a small field, and the SQUID sensors are used to detect the nanoparticle decaying field. The method has high sensitivity, more than 1000 times a mammogram for breast cancer, high contrast as only nanoparticles bound to cells are measured, and high specificity using specific biomarkers conjugated to the nanoparticles. Future directions of magnetic relaxometry include diagnosis of neural diseases using biomarkers specific to these diseases coupled to nanoparticles; this will complement ongoing diagnostic programs using magnetoencephalography.
KeywordsSQUID Magnetic relaxometry Nanoparticles Cancer
The development of superconducting quantum interference detector (SQUID) sensor technology (Zimmerman 1966) opened up a number of new research areas where the measurement of ultralow magnetic fields provided new illumination into underlying phenomenon. Some of the earliest of these programs were in the area of measurement of magnetic fields from the heart (MCG) and brain (MEG) by (Cohen 1968) followed by the measurement of evoked responses in the brain by Brenner et al. (1975). These early efforts have been summarized in the review of Hämäläinen et al. (1993) where the details of the SQUID sensors and applications are described. These applications are based on the measurements of biomagnetic magnetic fields emanating from currents involved in living tissue.
Magnetic relaxometry, or as defined here as superparamagnetic relaxometry (SPMR), is a more recent emerging technology (Flynn and Bryant 2005; Kötitz 1995; Romanus et al. 2001) that is similar in many respects to MEG and MCG in its application and in the procedures used to analyze the data. At Senior Scientific, SPMR has been used to investigate various disease states, in particular cancer through the use of biomarkers conjugated to the nanoparticles [NP]. The method has been shown to be very sensitive for detecting cancer; for example, it is more than 1000 times more sensitive than a mammogram for detecting breast cancer. Because of the unique nature of superparamagnetic NP, very high contrast can be obtained between bound and unbound NP and high specificity to disease using biomarkers. As in MEG, SPMR typically uses SQUID sensors to measure the low magnitude fields emitted by the NP during their magnetic relaxation. Similarly, SPMR uses arrays of SQUID sensors to localize sources of magnetic activity with the analysis normally performed with inverse theory algorithms of the same type as in MEG and MCG (see, e.g., the inverse theory described by Huang et al. (1998) for MEG). The resulting data are also subject to filtering and noise-suppression methods developed for biomagnetism measurements. As in MEG, the use of phantoms to calibrate and test the sensor systems and develop the software analysis methods is directly applicable to SPMR; both MEG and SPMR take advantage of the basic principles of electromagnetism.
The principal difference is that SPMR measures the relaxing magnetic fields from magnetic nanoparticles (NP) that have been briefly magnetized in a magnetic field and are not biomagnetic in nature. In MEG and MCG, the sources are described in terms of current dipoles with units corresponding to picoamps, whereas in SPMR, the sources are described in terms of magnetic moments with units corresponding to pJ/T (picoJoule/Tesla). However many of the applications of SPMR are directly related to biological phenomena. In the following discussions, SPMR is applied to the measurement of specificity and sensitivity of various antibodies to various cell types – in particular cancer cells – to the study of incubation rates for attachment of NP to cells, to localization of tumors in living animals, and to measurement of percentage of injected material delivered to tumors and other targeted organs in living animals.
There are two important principals that SPMR methods utilize in their measurements: (1) the high sensitivity of SQUID sensors for detecting extremely small amounts of magnetite – the principal ingredients of NP used – and (2) the special properties of superparamagnetic NP that yield high magnetic moments and high contrast for bound NP. In this regard, the SQUID sensors are exactly the same as used in MEG and the prototype system described here was originally used for MEG measurements. The sensitivity required is somewhat less than MEG, and this fact combined with the method of measurement allows most SPMR measurements to be made without the need for shielded rooms. As in MEG, it is typical to use gradiometers for the sensor configuration. An important difference between MEG and SPMR in the SQUID sensor configuration considerations is that the magnetic NP must be magnetized and this requires the presence of a pulsed magnetic field. This magnetizing field needs be only some tens of gauss due to the intrinsic saturation properties of the NP, and the magnetizing field is only applied for a fraction of a second. However, this requires that the SQUID sensor system be turned on and off during the pulsing and that the components of the system do not respond to this magnetic pulse for any extended duration. The coil configuration producing this magnetizing field also limits the configuration of the sensors such that this field is relatively uniform in strength and direction over the sensor array; thus, a whole-head MEG system is not amenable to SPMR measurements, whereas a relatively flat array such as used in MCG works quite well.
2 The SPMR Method
3 Applications of SPMR to Nanomedicine
The methodology of SPMR has been applied to a number of diseases in the area of nanomedicine. T-cells have been labeled with NP conjugated to an antibody for the specific T-cells responsible for rejecting transplanted organs and used to measure transplant rejection in a mouse model (Flynn et al. 2007; Butler et al. 2013). A study of leukemia minimal residual disease (MRD) has been carried out using NP with antibodies (CD-34) specific to a number of leukemia types (Jaetao et al. 2009). SPMR has also been applied to the study of solid tumors in breast cancer (Hathaway et al. 2011; Adolphi et al. 2012), ovarian cancer (Flynn et al. 2014), and prostate cancer. The results have also been compared to MRI imaging in some detail using an animal model (Adolphi et al. 2012). A further advantage of the SPMR technique over many other biomedical methods is the transparency of tissue and bone to low-frequency magnetic fields. This implies, just as in the case of MEG, that source localization is not affected by intervening tissue. For animal studies this is quite important and is unlike the scattering that occurs in the use of fluorescent markers resulting in loss of localization of source accuracy with depth.
3.1 Linearity of Response
3.3 In Vivo Detection and Localization
Through the use of phantoms containing vials of live cells, it has been shown that spatial resolutions of approximately 0.5 mm for multiple sources can be obtained (Hathaway et al. 2011). This is better than the resolution normally obtained in MEG experiments. The principal reason for this is that in the inverse problem only the coordinates and the magnitude of the source have to be determined since the sources are all aligned with the magnetizing field. In MEG, two more factors are needed that determine the orientation of the source.
4 Future SPMR Systems
Although the primary thrust of this manuscript has been on cancer and similar diseases, there are many other diseases with biomarkers known that SPMR can be applied to. These include several diseases of the brain, and in the future the combination of MEG and SPMR in the diagnosis and treatment of neural diseases will be quite promising. There are a number of biomarkers known for the tau and amyloid plaque that build up in the brain of Alzheimer’s patients. There is also increasing evidence for the role of tau in PTSD and CTE, and it will be possible to identify this with SPMR using the known biomarkers for tau. Recent MEG research in these areas have identified methods for MEG biomarkers in brain disorders (Georgopoulos et al. 2007), PTSD (Georgopoulos et al. 2010) and traumatic brain injury (Huang et al. 2009). The combination of these approaches could be a significant advance in understanding these increasingly common neural diseases.
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