Quantitative Conductivity Estimation Error due to Statistical Noise in Complex B1 + Map
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초록
In-vivo conductivity reconstruction using transmit field (B1+) information of MRI was proposed. We assessed theaccuracy of conductivity reconstruction in the presence of statistical noise in complex B1+ map and provided a parametricmodel of the conductivity-to-noise ratio value. Materials and Methods: The B1+ distribution was simulated for a cylindrical phantom model. By adding complex Gaussiannoise to the simulated B1+ map, quantitative conductivity estimation error was evaluated. The quantitative evaluationprocess was repeated over several different parameters such as Larmor frequency, object radius and SNR of B1+ map. Aparametric model for the conductivity-to-noise ratio was developed according to these various parameters. Results: According to the simulation results, conductivity estimation is more sensitive to statistical noise in B1+ phase thanto noise in B1+ magnitude. The conductivity estimate of the object of interest does not depend on the external object surroundingit. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the B1+ map, Larmor frequency,the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targetedtissue, SNR of B1+ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. Conclusion: Through all these relationships, quantitative conductivity estimation error due to statistical noise in B1+ map ismodeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.
Abstract
In-vivo conductivity reconstruction using transmit field (B1+) information of MRI was proposed. We assessed theaccuracy of conductivity reconstruction in the presence of statistical noise in complex B1+ map and provided a parametricmodel of the conductivity-to-noise ratio value. Materials and Methods: The B1+ distribution was simulated for a cylindrical phantom model. By adding complex Gaussiannoise to the simulated B1+ map, quantitative conductivity estimation error was evaluated. The quantitative evaluationprocess was repeated over several different parameters such as Larmor frequency, object radius and SNR of B1+ map. Aparametric model for the conductivity-to-noise ratio was developed according to these various parameters. Results: According to the simulation results, conductivity estimation is more sensitive to statistical noise in B1+ phase thanto noise in B1+ magnitude. The conductivity estimate of the object of interest does not depend on the external object surroundingit. The conductivity-to-noise ratio is proportional to the signal-to-noise ratio of the B1+ map, Larmor frequency,the conductivity value itself and the number of averaged pixels. To estimate accurate conductivity value of the targetedtissue, SNR of B1+ map and adequate filtering size have to be taken into account for conductivity reconstruction process. In addition, the simulation result was verified at 3T conventional MRI scanner. Conclusion: Through all these relationships, quantitative conductivity estimation error due to statistical noise in B1+ map ismodeled. By using this model, further issues regarding filtering and reconstruction algorithms can be investigated for MREPT.
참고문헌 (24)
- Haacke EM, "Extraction of conductivity and permittivity using magnetic resonance imaging", Phys Med Biol, 36, pp.723~734 (1991)
- Katscher U, "Determination of electric conductivity and local SAR via B1 mapping", IEEE Trans Med Imaging, 28, pp.1365~1374 (2009)
- Joines WT, "The measured electrical properties of normal and malignant human tissues from 50 to 900 MHz", Med Phys, 21, pp.547~550 (1994)
- Schaefer M, "The complex dielectric spectrum of heart tissue during ischemia", Bioelectro-chemistry, 58, pp.171~180 (2002)
- Haemmerich D, "In vivo electrical conductivity of hepatic tumours", Physiol Meas, 24, pp.251~260 (2003)
- Fallert MA, "Myocardial electrical-impedance mapping of iscemic sheep hearts and healing aneurysm", Circulation, 87, pp.199~207 (1993)
- Voigt T, "Patient-individual local SAR determination: in vivo measurements and numerical validation", Magn Reson Med, 68, pp.1117~1126 (2012)
- Yarnykh VL, "Actual flip-angle imaging in the pulsed steady state: a method for rapid three-dimensional mapping of the transmitted radiofrequency field", Magn Reson Med, 57, pp.192~200 (2007)
- Voigt T, "T1 corrected B1mapping using multi-TR gradient echo sequences", Magn Reson Med, 64, pp.725~733 (2010)
- Stollberger R, "Imaging of the active B1 field in vivo", Magn Reson Med, 35, pp.246~251 (1996)
- Sacolick LI, "B1 mapping by Bloch-Siegert shift", Magn Reson Med, 63, pp.1315~1322 (2010)
- Kim DH, "Simultaneous Electromagnetic Property Imaging using multiecho gradient echo", Proceedings of the 20th Annual Meeting of ISMRM, pp.3464~ (2012)
- Voigt T, "Quantitative conductivity and permittivity imaging of the human brain using electric properties tomography", Magn Reson Med, 66, pp.456~466 (2011)
- Bulumulla SB, "Conductivity and permittivity imaging at 3.0 T", Concept Magn Reson B, 41B(1), pp.13~21 (2012)
- van Lier AL, "B1(+) phase mapping at 7 T and its application for in vivo electrical conductivity mapping", Magn Reson Med, 67, pp.552~561 (2012)
- Seo JK, "Error analysis of nonconstant admittivity for MR-based electric property imaging", IEEE Trans Med Imaging, 31, pp.430~437 (2012)
- van Lier AL, "Comparing Electric Properties Tomography at 1.5, 3 and 7 T", Proceedings of the 19th Annual Meeting of ISMRM, pp.125~ (2011)
- van den Bergen B, "Ultra fast electromagnetic field computations for RF multi-transmit techniques in high field MRI", Phys Med Biol, 54, pp.1253~1264 (2009)
- Gudbjartsson H, "The Rician distribution of noisy MRI data", Magn Reson Med, 34, pp.910~914 (1995)
- Morrell GR, "An analysis of the accuracy of magnetic resonance flip angle measurement methods", Phys Med Biol, 55, pp.6157~6174 (2010)
- Stogryn A, "Equations for calculating the dielectric constant of saline water", IEEE Trans Microwave Theory Tech, 19, pp.733~736 (1971)
- Gabriel S, "The dielectric properties of biological tissues: II. Measurements in the frequency range 10Hz to 20 GHz", Phys Med Biol, 41, pp.2251~2269 (1996)
- Zypman FR, "MRI electromagnetic field penetration in cylindrical objects", Comput Biol Med, 26, pp.161~175 (1996)