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Gordon Donaldson Memorial Session on SQUID Magnetometry at International Superconductor Electronics Conference 2013 (ISEC 2013)
- Gordon Donaldson: A Memory - Part I - Presented by Prof. John Clarke
- Gordon Donaldson: A Memory - Part II - Presented by Colin Pegrum
- Hybrid Magnetoencephalography (MEG) and Magnetic Resonance Imaging (MRI): Techniques and Benefits - Presented by Risto Ilmoniemi
- Magnetic Resonance Imaging of the Human Head at 130 Microtesla - Presented by Kai Buckenmaier
- SQUID Instrumentation for Early Cancer Diagnostics - Presented by Andrei Matlashov
- A High Sensitive Magnetometer System for Natural Magnetic Field Measurements - Presented by Ronny Stolz
- SQUID-based Noise Thermometers for Sub-Kelvin Thermometry - Presented by Joern Beyer
Presenter: Prof. John Clarke
Presenter: Colin Pegrum
Presenter: Risto Ilmoniemi
Functional and structural information about the human brain can be obtained noninvasively with magnetoencephalography (MEG) and magnetic resonance imaging (MRI), respectively. MEG, which is based on the recording of the extracerebral magnetic fields, gives a direct measure (projection) of neuronal currents. On the other hand, MRI, in which polarized spin populations are manipulated and observed magnetically, provides 3-dimensional images of proton density and relaxation times. It was demonstrated recently (McDermott et al., PNAS 21, 7857–7861, 2004) that high-quality MRI is possible at magnetic fields as low as 100 microtesla if the sample is first polarized in a higher field and if SQUID sensors are used to detect the spin precession. Subsequently, it was demonstrated (Zotev et al., J. Magn. Reson. 194, 115–120, 2008; Vesanen et al., Magn. Reson. Med. 2012, DOI 10.1002/mrm.24413) that MEG and ultra-low-field MRI (ULF MRI) can be performed with same SQUID sensor array; this guarantees that the coordinate systems of MEG and MRI are the same. In addition, the combination of the two techniques improves work flow. Advantages of ULF-MRI include high T1 contrast, absence of susceptibility artifacts, quiet and safe operation, open structure, and relatively low cost when added to an MEG system. ULF-MRI may also be suitable for performing electrical impedance tomography (EIT) of the head; better knowledge of the conductivity structure, together with the error-free registration, could dramatically improve the accuracy of locating neuronal sources. The challenge in making combined MEG and MRI practical is to improve the data rate sufficiently. We need to improve SQUID sensitivity by a factor of 5–10 (to about 0.5 fT/sqrt[Hz]) and increase the prepolarization field strength by a factor of 5 (to 100 mT or more). If we succeed in doing this in an array of several hundred sensors, clinically and scientifically useful MEG-MRI systems may be available within a few years.
Presenter: Kai Buckenmaier
We present in vivo images of the human brain acquired with an ultralow field magnetic resonance imaging (ULFMRI) system operating at a field B0 ≈ 130 microtesla. The system features prepolarization of the proton spins at a field Bp ≈ 0.1 T and detection of the nuclear magnetic resonance signals with a SQUID-based, superconducting, second-derivative gradiometer. We report measurements of the longitudinal relaxation time T1 of brain tissue, cerebrospinal fluid (CSF), blood and scalp fat at both B0 and Bp. These measurements enable us to construct inversion recovery sequences that we combine with a Carr-Purcell-Meiboom-Gill (CPMG) echo train to obtain images in which any given tissue can be nulled out and another tissue highlighted. Such techniques greatly enhance the already high intrinsic T1-contrast obtainable at ULF. We illustrate the power of this technique with an image showing only the superior sagittal sinus, with other components eliminated. We further show that, as expected at ULF, the transverse relaxation time T2 approaches T1 in all four brain components. We present T2-weighted images that with our technique can be acquired in about 20% of the time required for T1-weighted images and comparable tissue contrast. With the use of multiple sensors, for example those in a SQUID-based system for magnetic source imaging, we believe these techniques would enable one to obtain high-contrast imaging of the components of the brain, including the visualization of brain tumors without the need of a contrast agent.
Presenter: Andrei Matlashov
SQUIDs can be used for a new technology for ultra-sensitive magnetic detection and imaging of tissue cells marked using superparamagnetic nanoparticles. The detection limit of this technique can be as low as 10,000 cells. By comparison, state of the art spiral X-ray CT requires over 1 million cancerous cells for detection. This method consists of targeting cells using antibody labeled nanoparticles, followed by detection and imaging of the targeted area using a high-resolution SQUID-based gradiometer array. Super-paramagnetic relaxometry (SPMR) is used for detection of targeted cells with high specificity: only bound nanoparticles will be detected via Néel relaxation. The binding occurs only with cancer cells because of specific antibodies conjugated to the nanoparticle surface. By combining SPMR with ultra-low field magnetic resonance imaging (ULF MRI), using the same instrument, the targeted area can be imaged to provide anatomical information. The same magnetic particles work as MRI contrast agents. The combination of ULF MRI and SPMR provide both accurate localization and cell count of the targeted tissue. This approach provides a robust diagnostic tool for detection and localization of cancerous tissue targeted with magnetic markers at a very early disease stage. ULF MRI and SPMR measurements have never been combined before in a single device. We will describe our design of such a combined SQUID-based instrument, and present our first experimental results of combined SPMR and ULF MRI on phantoms.
Presenter: Ronny Stolz
We present our LTS SQUID magnetometer system which contains two SQUID triples with different effective areas. The system was developed to measure the signals of transient electromagnetic method as well as weak natural fluctuations of the Earth magnetic field. The sensors are produced in our recently introduced technology using sub-µm Josephson junctions. They provide very high sensitivity which is difficult to be measured directly. Especially, in the low frequency range one has to deal with strong external disturbances. In this work, two methods to estimate the noise from measurements in the Earth’s magnetic field at a magnetically quiet site are described. The achieved results are compared to measurements in superconducting and magnetic shielding.
Presenter: Joern Beyer
We have developed compact, fast and easy-to-use dc SQUID-based noise thermometers for the temperature range accessible with dilution refrigerators, i.e., from ca. 1K to 1mK. Two implementations have been realized: Magnetic Field Fluctuation Thermometers and Current Sensing Noise Thermometers. In both thermometers, the thermally induced motion of charge carriers in metallic temperature sensors cause thermal magnetic flux noise. SQUID sensors optimized for the detection of this noise are employed, and the sought temperature is extracted from the thermal noise power spectrum using the Nyquist theorem. For the calibration of the thermometers, one reference measurement at a known temperature suffices. We have developed a procedure for reference measurements with direct traceability to the Provisional Low Temperature Scale (PLTS)-2000 as well as methods to determine the uncertainty of the temperature estimates. SQUID sensor design, thermal anchoring and electro-magnetic shielding of our SQUID noise thermometer configurations will be discussed and validation measurements in comparison with the PLTS-2000 will be presented. The results of the validation measurements attest the high linearity, accuracy and speed of our noise thermometers. The devices exhibit noise temperatures below 0.1 mK, and estimates of the sought temperature with relative uncertainties of <1% are obtained within measurement times of a few seconds.