Biomagnetism using SQUIDs: status and perspectives

Biomagnetism involves the measurement and analysis of very weak local magnetic fields of living organisms and various organs in humans. Such fields can be of physiological origin or due to magnetic impurities or markers. This paper reviews existing and prospective applications of biomagnetism in clinical research and medical diagnostics. Currently, such applications require sensitive magnetic SQUID sensors and amplifiers. The practicality of biomagnetic methods depends especially on techniques for suppressing the dominant environmental electromagnetic noise, and on suitable nearly real-time data processing and interpretation methods. Of the many biomagnetic methods and applications, only the functional studies of the human brain (magnetoencephalography) and liver susceptometry are in clinical use, while functional diagnostics of the human heart (magnetocardiography) approaches the threshold of clinical acceptance. Particularly promising for the future is the ongoing research into low-field magnetic resonance anatomical imaging using SQUIDs.

[1]  I F Gorodnitsky,et al.  Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.

[2]  Alex I. Braginski,et al.  The SQUID handbook , 2006 .

[3]  S. Taulu,et al.  Suppression of Interference and Artifacts by the Signal Space Separation Method , 2003, Brain Topography.

[4]  John S George,et al.  Simultaneous magnetoencephalography and SQUID detected nuclear MR in microtesla magnetic fields , 2004, Magnetic resonance in medicine.

[5]  John P. Wikswo.  SQUIDs Remain Best Tools for Measuring Brain’s Magnetic Field , 2004 .

[6]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[7]  Martin Burghoff,et al.  Nuclear magnetic resonance in the nanoTesla range , 2005 .

[8]  J. Vrba,et al.  Multichannel SQUID Biomagnetic Systems , 2000 .

[9]  J.C. Mosher,et al.  Multiple dipole modeling and localization from spatio-temporal MEG data , 1992, IEEE Transactions on Biomedical Engineering.

[10]  R. Ilmoniemi,et al.  Interpreting magnetic fields of the brain: minimum norm estimates , 2006, Medical and Biological Engineering and Computing.

[11]  J. Tripp,et al.  Magnetic-susceptibility measurement of human iron stores. , 1982, The New England journal of medicine.

[12]  L. Trahms,et al.  Magnetocardiography and 32‐Lead Potential Mapping , 1997, Journal of cardiovascular electrophysiology.

[13]  R Wynands,et al.  Dynamical mapping of the human cardiomagnetic field with a room-temperature, laser-optical sensor. , 2003, Optics express.

[14]  A. Kandori,et al.  Open-type magnetocardiograph with cylindrical magnetic shield , 2005 .

[15]  Giovanni Cancellieri,et al.  Independent component analysis: fetal signal reconstruction from magnetocardiographic recordings , 2004, Comput. Methods Programs Biomed..

[16]  Jenny R Holzer,et al.  High resolution magnetic images of planar wave fronts reveal bidomain properties of cardiac tissue. , 2004, Biophysical journal.

[17]  P. Hugenholtz,et al.  Magnetocardiography Predicts Coronary Artery Disease in Patients with Acute Chest Pain , 2005, Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc.

[18]  A. Bohr,et al.  Quantum World Is Only Smoke and Mirrors , 2004 .

[19]  M. Hatridge,et al.  SQUID-detected in vivo MRI at microtesla magnetic fields , 2005, IEEE Transactions on Applied Superconductivity.

[20]  J. Hutchison,et al.  Use of a DC SQUID receiver preamplifier in a low field MRI system , 1995, IEEE Transactions on Applied Superconductivity.

[21]  R. O. Schmidt,et al.  Multiple emitter location and signal Parameter estimation , 1986 .

[22]  H. Bryant,et al.  A biomagnetic system for in vivo cancer imaging , 2005, Physics in medicine and biology.

[23]  K Lehnertz,et al.  Nonlinear noise reduction using reference data. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[24]  T. W. Kornack,et al.  A subfemtotesla multichannel atomic magnetometer , 2003, Nature.

[25]  J. Hutchison,et al.  A tuned SQUID amplifier for MRI based on a DOIT flux locked loop , 1997, IEEE Transactions on Applied Superconductivity.

[26]  Jean-Francois Cardoso,et al.  Blind signal separation: statistical principles , 1998, Proc. IEEE.

[27]  R. L. Fagaly,et al.  Biomagnetic susceptometer with SQUID instrumentation , 1991 .

[28]  John Clarke,et al.  SQUID‐detected MRI at 132 μT with T1‐weighted contrast established at 10 μT–300 mT , 2005 .

[29]  L Toivonen,et al.  Nonfluoroscopic Localization of an Amagnetic Stimulation Catheter by Multichannel Magnetocardiography , 1999, Pacing and clinical electrophysiology : PACE.

[30]  Boleslaw K. Szymanski,et al.  Use of machine learning for classification of magnetocardiograms , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[31]  Hubert Preissl,et al.  Fetal magnetoencephalography: current progress and trends , 2004, Experimental Neurology.

[32]  Stephen E. Robinson,et al.  SQUID sensor array configurations for magnetoencephalography applications , 2002 .

[33]  L. Trahms,et al.  MCG to ECG source differences: measurements and a two-dimensional computer model study. , 2004, Journal of electrocardiology.

[34]  Kevin Pratt,et al.  BabySQUID: A mobile, high-resolution multichannel magnetoencephalography system for neonatal brain assessment , 2006 .

[35]  J. Vrba,et al.  Signal processing in magnetoencephalography. , 2001, Methods.

[36]  Michael V. Romalis,et al.  Unshielded three-axis vector operation of a spin-exchange-relaxation-free atomic magnetometer , 2004 .

[37]  Robert McDermott,et al.  Low-field magnetic resonance imaging with a high-Tc dc superconducting quantum interference device , 1999 .