Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
Processing Request
Comparison of Five Conductivity Tensor Models and Image Reconstruction Methods Using MRI.
Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
Processing Request
- معلومة اضافية
- المصدر:
Publisher: MDPI Country of Publication: Switzerland NLM ID: 100964009 Publication Model: Electronic Cited Medium: Internet ISSN: 1420-3049 (Electronic) Linking ISSN: 14203049 NLM ISO Abbreviation: Molecules
- بيانات النشر:
Original Publication: Basel, Switzerland : MDPI, c1995-
- الموضوع:
- نبذة مختصرة :
Imaging of the electrical conductivity distribution inside the human body has been investigated for numerous clinical applications. The conductivity tensors of biological tissue have been obtained from water diffusion tensors by applying several models, which may not cover the entire phenomenon. Recently, a new conductivity tensor imaging (CTI) method was developed through a combination of B1 mapping, and multi-b diffusion weighted imaging. In this study, we compared the most recent CTI method with the four existing models of conductivity tensors reconstruction. Two conductivity phantoms were designed to evaluate the accuracy of the models. Applied to five human brains, the conductivity tensors using the four existing models and CTI were imaged and compared with the values from the literature. The conductivity image of the phantoms by the CTI method showed relative errors between 1.10% and 5.26%. The images by the four models using DTI could not measure the effects of different ion concentrations subsequently due to prior information of the mean conductivity values. The conductivity tensor images obtained from five human brains through the CTI method were comparable to previously reported literature values. The images by the four methods using DTI were highly correlated with the diffusion tensor images, showing a coefficient of determination (R2) value of 0.65 to 1.00. However, the images by the CTI method were less correlated with the diffusion tensor images and exhibited an averaged R2 value of 0.51. The CTI method could handle the effects of different ion concentrations as well as mobilities and extracellular volume fractions by collecting and processing additional B1 map data. It is necessary to select an application-specific model taking into account the pros and cons of each model. Future studies are essential to confirm the usefulness of these conductivity tensor imaging methods in clinical applications, such as tumor characterization, EEG source imaging, and treatment planning for electrical stimulation.
- References:
IEEE Trans Biomed Eng. 2014 May;61(5):1390-9. (PMID: 24759274)
Magn Reson Imaging. 2014 Sep;32(7):913-23. (PMID: 24928302)
Magn Reson Med. 1996 Dec;36(6):847-57. (PMID: 8946350)
IEEE Trans Biomed Eng. 2017 Nov.;64(11):2505-2514. (PMID: 28767360)
IEEE Trans Biomed Eng. 1997 Mar;44(3):220-3. (PMID: 9216137)
Neuroimage. 2016 Nov 15;142:394-406. (PMID: 27523449)
Biophys J. 1994 Jan;66(1):259-67. (PMID: 8130344)
Magn Reson Med. 2021 Jul;86(1):382-392. (PMID: 33533114)
Biomed Eng Lett. 2018 Apr 25;8(3):273-282. (PMID: 30603211)
Neuroimage. 2009 Jan 15;44(2):399-410. (PMID: 18848896)
Neuroimage. 2019 Nov 15;202:116137. (PMID: 31473352)
Magn Reson Med. 2017 Jan;77(1):137-150. (PMID: 26762771)
Med Biol Eng. 1967 May;5(3):271-93. (PMID: 6068939)
Magn Reson Med. 2016 Nov;76(5):1574-1581. (PMID: 26745823)
Diagnostics (Basel). 2021 Jan 26;11(2):. (PMID: 33530587)
Adv Biol Med Phys. 1957;5:147-209. (PMID: 13520431)
IEEE Trans Med Imaging. 2018 Apr;37(4):966-976. (PMID: 29610075)
Magn Reson Med. 2000 May;43(5):682-90. (PMID: 10800033)
IEEE Trans Med Imaging. 2009 Sep;28(9):1365-74. (PMID: 19369153)
IEEE Trans Biomed Eng. 2008 Oct;55(10):2481-6. (PMID: 18838374)
Magn Reson Med. 2002 Oct;48(4):577-82. (PMID: 12353272)
Neurol Clin Neurophysiol. 2004 Nov 30;2004:55. (PMID: 16012645)
IEEE Trans Med Imaging. 2012 Feb;31(2):430-7. (PMID: 21990329)
Neuroimage. 2006 Apr 15;30(3):813-26. (PMID: 16364662)
Proc Natl Acad Sci U S A. 1996 Oct 15;93(21):11443-7. (PMID: 8876154)
Exp Neurol. 1965 Dec;13(4):386-401. (PMID: 5847284)
Neuroimage. 2004;23 Suppl 1:S208-19. (PMID: 15501092)
Phys Med Biol. 1996 Nov;41(11):2231-49. (PMID: 8938024)
Phys Med Biol. 2009 Aug 21;54(16):4863-78. (PMID: 19636081)
Biomed Eng Online. 2020 May 24;19(1):35. (PMID: 32448134)
Clin Neurophysiol. 2009 Dec;120(12):2071-2081. (PMID: 19833554)
Proc Natl Acad Sci U S A. 2001 Sep 25;98(20):11697-701. (PMID: 11573005)
IEEE Trans Med Imaging. 2019 Jul;38(7):1569-1577. (PMID: 30507528)
Neuroimage. 2018 Nov 15;182:39-61. (PMID: 29920376)
Biomed Eng Online. 2014 Mar 08;13(1):24. (PMID: 24607262)
Front Neurosci. 2019 Jun 04;13:531. (PMID: 31231178)
Med Biol Eng Comput. 2018 Aug;56(8):1325-1332. (PMID: 29855784)
Eur Radiol. 2018 Jan;28(1):348-355. (PMID: 28698943)
Magn Reson Med. 2011 Jan;65(1):138-45. (PMID: 20878760)
Phys Med Biol. 2014 Jun 21;59(12):2955-74. (PMID: 24841854)
IEEE Trans Biomed Eng. 2017 Nov;64(11):2515-2530. (PMID: 28829299)
Magn Reson Med. 1996 Dec;36(6):893-906. (PMID: 8946355)
Comput Methods Programs Biomed. 2013 Jan;109(1):48-64. (PMID: 23040278)
Phys Rev B Condens Matter. 1989 Mar 1;39(7):4504-4515. (PMID: 9948799)
Magn Reson Med. 2002 Apr;47(4):623-8. (PMID: 11948721)
- Grant Information:
2019R1A2C2088573 National Research Foundation of Korea; 2020R1A2C200790611 National Research Foundation of Korea; 2021R1A2C2004299 National Research Foundation of Korea; HI18C2435 Ministry of Health and Welfare of Korea; 50461-2021 Korea Institute of Radiological and Medical Sciences
- Contributed Indexing:
Keywords: anisotropy; conductivity tensor imaging (CTI); diffusion tensor imaging (DTI); electrical conductivity; magnetic resonance imaging (MRI)
- الموضوع:
Date Created: 20210928 Date Completed: 20240724 Latest Revision: 20240724
- الموضوع:
20240726
- الرقم المعرف:
PMC8467711
- الرقم المعرف:
10.3390/molecules26185499
- الرقم المعرف:
34576970
No Comments.