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 IJMPCERO  Vol.6 No.3 , August 2017
Feasibility of a Direct-Conversion Method from Magnetic Susceptibility to Relative Electron Density for Radiation Therapy Treatment Planning
Abstract: Recently, several institutions have been developing magnetic resonance imaging (MRI)-guided radiotherapy treatment systems. In this study, we examine whether it is possible to perform radiation therapy planning (RTP) using a magnetic susceptibility map obtained using MRI. The head of a healthy volunteer was scanned using dual-energy computed tomography (CT) and MRI. A T2-star-weighted 3D gradient echo-based sequence (GRE) with images taken at four different echo times was acquired using the MRI scanner. The CT images were converted to relative electron density (rED) using a predefined ΔCT-rED conversion table. ΔCT was derived using the energy-subtraction method. The rED map was obtained from a single-linear relationship with the ΔCT-rED conversion table, whereas the magnetic susceptibility map was obtained from quantitative susceptibility mapping (QSM) via MRI. Subsequently, to obtain the relationship between the magnetic susceptibility and the rED, the rED map was rigidly aligned to the susceptibility map and resampled at the susceptibility map’s resolution. Finally, the magnetic susceptibility rED conversion table was obtained via voxel-by-voxel mapping between the two maps. No strong relationship between magnetic susceptibility and rED was obtained in the healthy volunteer’s head or in this study. The coefficient correlation between these parameters was 0.0145. Magnetic susceptibility values may be not able to convert to rED using our proposed method in healthy volunteer’s head. In contrast to the magnetic-susceptibility values obtained from the QSM algorithm, which were strongly affected by calcification and iron content, the rED or CT number was not considerably affected by such materials.
Cite this paper: Ito, K. , Kadoya, N. , Nakajima, Y. , Saito, M. , Sato, K. , Nagasaka, T. , Yamanaka, K. , Dobashi, S. , Takeda, K. , Matsushita, H. and Jingu, K. (2017) Feasibility of a Direct-Conversion Method from Magnetic Susceptibility to Relative Electron Density for Radiation Therapy Treatment Planning. International Journal of Medical Physics, Clinical Engineering and Radiation Oncology, 6, 252-265. doi: 10.4236/ijmpcero.2017.63023.
References

[1]   Crijns, S.P., Raaymakers, B.W. and Lagendijk, J.J. (2011) Real-Time Correction of Magnetic Field Inhomogeneity-Induced Image Distortions for MRI-Guided Conventional and Proton Radiotherapy. Physics in Medicine & Biology, 56, 289-297.
https://doi.org/10.1088/0031-9155/56/1/017

[2]   Cusack, R. and Papadakis, N. (2002) New Robust 3-D Phase Unwrapping Algorithms: Application to Magnetic Field Mapping and Undistorting Echoplanar Images. Neuroimage, 16, 754-764.

[3]   Irarrazabal, P., Meyer, C.H., Nishimura, D.G. and Macovski, A. (1996) Inhomogeneity Correction Using an Estimated Linear Field Map. Magnetic Resonance in Medicine, 35, 278-282.
https://doi.org/10.1002/mrm.1910350221

[4]   Moerland, M.A., Beersma, R., Bhagwandien, R., Wijrdeman, H.K. and Bakker, C.J. (1995) Analysis and Correction of Geometric Distortions in 1.5 T Magnetic Resonance Images for Use in Radiotherapy Treatment Planning. Physics in Medicine & Biology, 40, 1651-1654.
https://doi.org/10.1088/0031-9155/40/10/007

[5]   Prabhakar, R., Julka, P.K., Ganesh, T., Munshi, A., Joshi, R.C. and Rath, G.K. (2007) Feasibility of Using MRI Alone for 3D Radiation Treatment Planning in Brain Tumors. Japanese Journal of Clinical Oncology, 37, 405-411.
https://doi.org/10.1093/jjco/hym050

[6]   Pasquier, D., Betrouni, N., Vermandel, M., Lacornerie, T., Lartigau, E. and Rousseau, J. (2006) MRI Alone Simulation for Conformal Radiation Therapy of Prostate Cancer: Technical Aspects. Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, 30 Aug.-3 Sept. 2006, 160-163.
https://doi.org/10.1109/IEMBS.2006.260341

[7]   Reber, P.J., Wong, E.C., Buxton, R.B. and Frank, L.R. (1998) Correction of Off Resonance-Related Distortion in Echo-Planar Imaging Using EPI-Based Field Maps. Magnetic Resonance in Medicine, 39, 328-330.
https://doi.org/10.1002/mrm.1910390223

[8]   Stanescu, T., Wachowicz, K. and Jaffray, D.A. (2012) Characterization of Tissue Magnetic Susceptibility-Induced Distortions for MRIgRT. Medical Physics, 39, 7185-7193.
https://doi.org/10.1118/1.4764481

[9]   Kadah, Y.M. and Hu, X. (1997) Simulated Phase Evolution Rewinding (SPHERE): A Technique for Reducing B0 Inhomogeneity Effects in MR Images. Magnetic Resonance in Medicine, 38, 615-627.
https://doi.org/10.1002/mrm.1910380416

[10]   Potter, R., Heil, B., Schneider, L., Lenzen, H., al-Dandashi, C. and Schnepper, E. (1992) Sagittal and Coronal Planes from MRI for Treatment Planning in Tumors of Brain, Head and Neck: MRI Assisted Simulation. Radiotherapy Oncology, 23, 127-130.
https://doi.org/10.1016/0167-8140(92)90344-T

[11]   Rasch, C., Barillot, I., Remeijer, P., Touw, A., Van, H.M. and Lebesque, J.V. (1999) Definition of the Prostate in CT and MRI: A Multi-Observer Study. International Journal of Radiation Oncology, Biology, Physics, 43, 57-66.
https://doi.org/10.1016/S0360-3016(98)00351-4

[12]   Khoo, V.S., Adams, E.J., Saran, F., Bedford, J.L., Perks, J.R., Warrington, A.P. and Brada, M. (2000) A Comparison of Clinical Target Volumes Determined by CT and MRI for the Radiotherapy Planning of Base of Skull Meningiomas. International Journal of Radiation Oncology, Biology, Physics, 46, 1309-1317.
https://doi.org/10.1016/S0360-3016(99)00541-6

[13]   Jonsson, J.H., Karlsson, M.G., Karlsson, M. and Nyholm, T. (2010) Treatment Planning Using MRI Data: An Analysis of the Dose Calculation Accuracy for Different Treatment Regions. Radiation Oncology, 5, 62.
https://doi.org/10.1186/1748-717X-5-62

[14]   Chen, L., Price, R.A.J., Wang, L., Li, J., Qin, L., McNeeley, S., Ma, C.M., Freedman, G.M. and Pollack, A. (2004) MRI-Based Treatment Planning for Radiotherapy: Dosimetric Verification for Prostate IMRT. International Journal of Radiation Oncology, Biology, Physics, 60, 636-647.
https://doi.org/10.1016/j.ijrobp.2004.05.068

[15]   Hofmann, M., Steinke, F., Scheel, V., Charpiat, G., Farquhar, J., Aschoff, P., Brady, M., Scholkopf, B. and Pichler, B.J. (2008) MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration. Journal of Nuclear Medicine, 49, 1875-1883.
https://doi.org/10.2967/jnumed.107.049353

[16]   Keereman, V., Fierens, Y., Broux, T., Deene, Y., Lonneux, M. and Vandenberghe, S. (2010) MRI-Based Attenuation Correction for PET/MRI Using Ultrashort Echo Time Sequences. Journal of Nuclear Medicine, 51, 812-818.
https://doi.org/10.2967/jnumed.109.065425

[17]   Johansson, A., Karlsson, M. and Nyholm, T. (2011) CT Substitute Derived from MRI Sequences with Ultrashort Echo Time. Medical Physics, 38, 2708-2714.
https://doi.org/10.1118/1.3578928

[18]   Acosta-Cabronero, J., Williams, G.B., Cardenas-Blanco, A., Arnold, R.J., Lupson, V. and Nestor, P.J. (2013) In Vivo Quantitative Susceptibility Mapping (QSM) in Alzheimer’s Disease. PLoS One, 8, e81093.
https://doi.org/10.1371/journal.pone.0081093

[19]   Acosta-Cabronero, J., Betts, M.J., Cardenas-Blanco, A., Yang, S. and Nestor, P.J. (2016) In Vivo MRI Mapping of Brain Iron Deposition across the Adult Lifespan. Journal of Neuroscience, 36, 364-374.
https://doi.org/10.1523/JNEUROSCI.1907-15.2016

[20]   Zhang, J., Liu, T., Gupta, A., Spincemaille, P., Nguyen, T.D. and Wang, Y. (2015) Quantitative Mapping of Cerebral Metabolic Rate of Oxygen (CMRO2) Using Quantitative Susceptibility Mapping (QSM). Magnetic Resonance in Medicine, 74, 945-952.
https://doi.org/10.1002/mrm.25463

[21]   Azuma, M., Hirai, T., Yamada, K., Yamashita, S., Ando, Y., Tateishi, M., Iryo, Y., Yoneda, T., Kitajima, M., Wang, Y. and Yamashita, Y. (2016) Lateral Asymmetry and Spatial Difference of Iron Deposition in the Substantia Nigra of Patients with Parkinson Disease Measured with Quantitative Susceptibility Mapping. American Journal of Neuroradiology, 37, 782-788.
https://doi.org/10.3174/ajnr.A4645

[22]   Liu, C., Li, W., Tong, K.A., Yeom, K.W. and Kuzminski, S. (2015) Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in the Brain. Journal of Magnetic Resonance Imaging, 42, 23-41.
https://doi.org/10.1002/jmri.24768

[23]   Wharton, S., Schafer, A. and Bowtell, R. (2010) Susceptibility Mapping in the Human Brain Using Threshold-Based K-Space Division. Magnetic Resonance in Medicine, 63, 1292-1304.
https://doi.org/10.1002/mrm.22334

[24]   Liu, J., Liu, T., Rochefort, L., Ledoux, J., Khalidov, I., Chen, W., Tsiouris, A.J., Wisnieff, C., Spincemaille, P., Prince, M.R. and Wang, Y. (2012) Morphology Enabled Dipole Inversion for Quantitative Susceptibility Mapping Using Structural Consistency between the Magnitude Image and the Susceptibility Map. Neuroimage, 59, 2560-2568.
https://doi.org/10.1016/j.neuroimage.2011.08.082

[25]   Khabipova, D., Wiaux, Y., Gruetter, R. and Marques, J.P. (2015) A Modulated Closed Form Solution for Quantitative Susceptibility Mapping—A Thorough Evaluation and Comparison to Iterative Methods Based on Edge Prior Knowledge. Neuroimage, 107, 163-174.
https://doi.org/10.1016/j.neuroimage.2014.11.038

[26]   Wharton, S. and Bowtell, R. (2010) Whole-Brain Susceptibility Mapping at High Field: A Comparison of Multiple- and Single-Orientation Methods. Neuroimage, 53, 515-525.
https://doi.org/10.1016/j.neuroimage.2010.06.070

[27]   Lim, I.A., Li, X., Jones, C.K., Farrell, J.A., Vikram, D.S. and Van, Z.P.C. (2014) Quantitative Magnetic Susceptibility Mapping without Phase Unwrapping Using WASSR. Neuroimage, 86, 265-279.
https://doi.org/10.1016/j.neuroimage.2013.09.072

[28]   Chen, W., Zhu, W., Kovanlikaya, I., Kovanlikaya, A., Liu, T., Wang, S., Salustri, C. and Wang, Y. (2014) Intracranial Calcifications and Hemorrhages: Characterization with Quantitative Susceptibility Mapping. Radiology, 270, 496-505.
https://doi.org/10.1148/radiol.13122640

[29]   Liu, T., Khalidov, I., Rochefort, L., Spincemaille, P., Liu, J., Tsiouris, A.J. and Wang, Y. (2011) A Novel Background Field Removal Method for MRI Using Projection onto Dipole Fields (PDF). NMR in Biomedicine, 24, 1129-1136.
https://doi.org/10.1002/nbm.1670

[30]   Schneider, U., Pedroni, E. and Lomax, A. (1996) The Calibration of CT Hounsfield Units for Radiotherapy Treatment Planning. Physics in Medicine and Biology, 41, 111-124.
https://doi.org/10.1088/0031-9155/41/1/009

[31]   Saito, M. (2012) Potential of Dual-Energy Subtraction for Converting CT Numbers to Electron Density Based on a Single Linear Relationship. Medical Physics, 39, 2021-2030.
https://doi.org/10.1118/1.3694111

[32]   Tsukihara, M., Noto, Y., Hayakawa, T. and Saito, M. (2013) Conversion of the Energy-Subtracted CT Number to Electron Density Based on a Single Linear Relationship: An Experimental Verification Using a Clinical Dual-Source CT Scanner. Physics in Medicine and Biology, 58, N135-N144.

[33]   Ogata, T., Ueguchi, T., Yagi, M., Yamada, S., Tanaka, C., Ogihara, R., Isohashi, F., Yoshioka, Y., Tomiyama, N., Ogawa, K. and Koizumi, M. (2013) Feasibility and Accuracy of Relative Electron Density Determined by Virtual Monochromatic CT Value Subtraction at Two Different Energies Using the Gemstone Spectral Imaging. Radiation Oncology, 8, 83.
https://doi.org/10.1186/1748-717X-8-83

[34]   Schofield, M.A. and Zhu, Y. (2003) Fast Phase Unwrapping Algorithm for Interferometric Applications. Optics Letters, 28, 1194-1196.
https://doi.org/10.1364/OL.28.001194

[35]   Liu, T., Liu, J., Rochefort, L., Spincemaille, P., Khalidov, I., Ledoux, J.R. and Wang, Y. (2011) Morphology Enabled Dipole Inversion (MEDI) from a Single-Angle Acquisition: Comparison with COSMOS in Human Brain Imaging. Magnetic Resonance in Medicine, 66, 777-783.
https://doi.org/10.1002/mrm.22816

[36]   Liu, C., Wei, H., Gong, N.J., Cronin, M., Dibb, R. and Decker, K. (2015) Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications. Tomography, 1, 3-17.

[37]   Schweser, F., Deistung, A., Lehr, B.W. and Reichenbach, J.R. (2011) Quantitative Imaging of Intrinsic Magnetic Tissue Properties Using MRI Signal Phase: An Approach to in Vivo Brain Iron Metabolism? Neuroimage, 54, 2789-2807.
https://doi.org/10.1016/j.neuroimage.2010.10.070

[38]   Lee, Y.K., Bollet, M., Charles-Edwards, G., Flower, M.A., Leach, M.O., McNair, H., Moore, E., Rowbottom, C. and Webb, S. (2003) Radiotherapy Treatment Planning of Prostate Cancer Using Magnetic Resonance Imaging Alone. Radiotherapy and Oncology, 66, 203-216.
https://doi.org/10.1016/S0167-8140(02)00440-1

[39]   Juttukonda, M.R., Mersereau, B.G., Chen, Y., Su, Y., Rubin, B.G., Benzinger, T.L., Lalush, D.S. and An, H. (2015) MR-Based Attenuation Correction for PET/MRI Neurological Studies with Continuous-Valued Attenuation Coefficients for Bone through a Conversion from R2 to CT-Hounsfield Units. Neuroimage, 112, 160-168.
https://doi.org/10.1016/j.neuroimage.2015.03.009

 
 
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