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Magnetic Resonance Imaging01:24

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Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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NMR Spectrometers: Resolution and Error Correction01:14

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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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A pulse is a short burst of radio waves distributed over a range of frequencies that simultaneously excites all the nuclei in the sample. Upon passing a radio frequency pulse along the x-axis, the nuclei absorb energy corresponding to their Larmor frequencies and achieve resonance. This shifts the net magnetization vector from the z-axis toward the transverse plane. This angle of rotation of the magnetization vector, or the flip angle, is proportional to the duration and intensity of the pulse.
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Double Resonance Techniques: Overview01:12

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Double resonance techniques in Nuclear Magnetic Resonance (NMR) spectroscopy involve the simultaneous application of two different frequencies or radiofrequency pulses to manipulate and observe two distinct nuclear spins. One important application of double resonance is spin decoupling, which selectively suppresses coupling with one type of nucleus while observing the NMR signal from another nucleus, simplifying the spectrum and enhancing resolution.
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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
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Development of advanced signal processing and source imaging methods for superparamagnetic relaxometry.

Ming-Xiong Huang1,2, Bill Anderson3, Charles W Huang4

  • 1Radiology and Research Services, VA San Diego Healthcare System, San Diego, CA, USA.

Physics in Medicine and Biology
|January 11, 2017
PubMed
Summary
This summary is machine-generated.

New signal processing and source modeling tools enhance superparamagnetic relaxometry (SPMR) for sensitive cancer detection. These advancements improve accuracy in identifying and localizing tumor cells using superparamagnetic iron oxide nanoparticles (SPION).

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Nanotechnology

Background:

  • Superparamagnetic relaxometry (SPMR) is a sensitive technique for in vivo tumor cell detection using superparamagnetic iron oxide nanoparticles (SPION).
  • Existing research has focused on hardware and SPION development, with limited advancements in SPMR signal pre-processing and source modeling.
  • Accurate signal analysis is crucial for improving SPMR's sensitivity and reliability in early cancer detection.

Purpose of the Study:

  • To develop and evaluate novel pre-processing tools for SPMR sensor signals.
  • To introduce an automated multi-start dipole imaging approach for source localization in SPMR.
  • To enhance the accuracy and sensitivity of detecting and localizing magnetic sources in SPMR data.

Main Methods:

  • Developed pre-processing tools for artifact removal, single decay process evaluation, flux jump correction, and signal fitting.
  • Implemented an automated multi-start dipole imaging technique for source localization without user-defined initial guesses.
  • Applied regularization and a reduced chi-square cost-function for source variable ambiguity resolution and optimal dipole number determination.

Main Results:

  • Successfully evaluated new pre-processing tools and the multi-start source imaging approach using phantom data.
  • Demonstrated enhanced accuracy and sensitivity in detecting and localizing SPMR signal sources.
  • Achieved robust and accurate solutions under low signal-to-noise ratio (SNR) conditions, comparable to detecting ~1000 cells.

Conclusions:

  • The developed pre-processing tools and automated multi-start source modeling significantly improve SPMR performance.
  • These algorithms provide robust detection and localization capabilities, even in challenging low SNR environments.
  • The advancements are expected to aid in establishing industrial standards for SPMR in pre-clinical and clinical applications.