A phantom to assess the accuracy of tumor delineation using MRSI

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A phantom to assess the accuracy of tumor delineation using MRSI

Background. Studies have demonstrated that magnetic resonance spectroscopic imaging (MRSI) can detect regions of abnormal activity (tumor) that would not have been covered using conventional imaging and contouring methods. With increased interest in MRSI it is important that its accuracy in tumor delineation be investigated. While some effort has been made to design phantoms to examine the performance of MRSI sequences, most phantoms rely on using traditional glass or acrylic as the phantom building material.

Material and methods. In this work, a gel-based detail phantom has been developed to assess the ability of the spectroscopic imaging sequences to accurately represent the geometry of tumors. The gel-based phantom is used as an alternative to conventional acrylic or glass based phantoms for use with MRSI.

Results. Gel-based phantoms have the advantage of having a magnetic susceptibility close to that of water. In addition, we demonstrate the benefits of having no finite wall thickness separating phantom compartments. The utility of the phantom was illustrated in comparisons between different MRSI sequences of the same nominal resolution as well as different filtering parameters.

Conclusions. Due to their ease of construction and the reduced artifacts, gel phantoms are a reliable tool for assessing the performance of MRSI sequences.

Pallud J, Devaux B, Nataf F, Roux FX, Daumas-Duport C. Spatial delimitation of low grade oligodendrogliomas. Neurochirurgie 2005; 51: 253-9.

Pirzkall A, Li X, Oh J, Chang S, Berger MS, Larson DA, et al. 3D MRSI for resected high-grade gliomas before RT: tumor extent according to metabolic activity in relation to MRI. Int J Radiat Oncol Biol Phys 2004; 59: 126-37.

Walecki J, Tarasow E, Kubas B, Czemicki Z, Lewko J, Podgorski J., et al. Hydrogen-1 MR spectroscopy of the peritumoral zone in patients with cerebral glioma: assessment of the value of the method. Acad Radiol 2003; 10: 145-53.

Chang J, Thakur S, Perera G, Kowalski A, Huang W, Karimi S., et al. Image-fusion of MR spectroscopic images for treatment planning of gliomas. Med Phys 2006; 33: 32-40.

McKnight TR, Noworolski SM, Vigneron DB, Nelson SJ. An automated technique for the quantitative assessment of 3D-MRSI data from patients with glioma. J Magn Reson Imaging 2001; 13: 167-77.

Hunjan S, Adalsteinsson E, Kim DH, Harsh GR, Boyer AL, Spielman D., et al. Quality assurance of magnetic resonance spectroscopic imaging-derived metabolic data. Int J Radiat Oncol Biol Phys 2003; 57: 1159-73.

Woo DC, Kim BS, Jung SL, Park HJ, Rhim HS, Jahng GH., et al. Develpment of a cone-shaped phantom for multi-voxel MR scpectroscopy. J Neurosci Methods 2007; 162: 101-7.

Rice JR, Milbrandt RH, Madsen EL, Frank GR, Boote EJ, Blenchinger JC. Anthromorphic 1H MRS head phantom. Med Phys 1998; 25: 1145-56.

Barker PB, Hearshen DO, Boska MD. Single-voxel proton MRS of the human brain at 1.5T and 3.0T. Magn Reson Med 2001; 45: 765-9.

Drost DJ, Riddle WR, Clarke GD. Proton magnetic resonance spectroscopy in the brain: Report of AAPM Task Group #9. Med Phys 2002; 29: 2177-97.

Nishimura DG. Principles of magnetic resonance imaging: Stanford: Stanford University; 1996.

Haacke EM. Magnetic resonance imaging, physics principles and sequence design. New York: John Wiley & Sons; 1999.

Doddrell DM, Galloway G, Brooks W, Filed J, Bulsing J, Irving M, et al. Water signal elimination in vivo, using suppression by mistimed echo and repetitive gradient episodes. J Magn Reson 1986; 70: 176-80.

Hasse A, Frahm J, Hanicke W, Mattaei W. 1H NMR chemical shift selective (CHESS) imaging. Phys Med Biol 1985; 30: 341-4.

Mierisova S, Ala-Korpela M. MR spectroscopy quantitation: a review of frequency domain methods. NMR Biomed 2001; 14: 247-59.

Moré JJ. The Levenberg-Marquardt algorithm: implementation and theory. In: GA Watson, editor. Lecture notes in mathematics. Heidelberg: Springer Verlag; 1977. p. 105-16.

Nelson SJ, Graves E, Pirzkall A, Li X, Chan AA, Vigneron DB., et al. In vivo molecular imaging for planning radiation therapy of gliomas: an application of 1H MRSI. J Magn Reson Imaging 2002; 16: 464-76.

Narayana A, Chang J, Thakur S, Huang W, Karimi S, Hou B, et al. Use of MR spectroscopy and functional imaging in the treatment planning of gliomas. Br J Radiol 2007; 80: 347-54.

Jeun SS, Kim MC, Kim BS, Lee JM, Chung ST, Oh CH, et al. Assessment of malignancy in gliomas by 3T 1H MR spectroscopy. J Clin Imaging 2005; 29: 10-5.

Radiology and Oncology

The Journal of Association of Radiology and Oncology

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