Literature DB >> 31556332

A method for cranial target delineation in radiotherapy treatment planning aided by single-voxel magnetic resonance spectroscopy: evaluation using a custom-designed gel-based phantom and simulations.

Banafsheh Zeinali-Rafsanjani1,2, Mohammad Amin Mosleh-Shirazi3,4, Reza Faghihi2,5, Mahdi Saeedi-Moghadam1, Mehrzad Lotfi1, Reza Jalli1.   

Abstract

OBJECTIVE: Magnetic resonance spectroscopy (MRS) has been useful in radiotherapy treatment planning (RTP) especially in tumor delineation. Routinely, 2D/3D MRSI data are used for this application. However, not all centers have access to 2D/3D MRSI. The objective of this study was to introduce a method of using single-voxel spectroscopy (SVS) data in target delineation and assess its reliability.
METHODS: A gel-based phantom containing Creatine (Cr), N-acetyl-l-aspartic-acid (NAA), and Choline (Cho) was designed and built. The metabolite ratios simulate the normal and tumoral part of the brain. The jMRUI software (v. 6.0) was used to simulate a 1.5 T GE MRI scanner. The metabolite spectra provided by different time of echos (TE)s of the Point-RESolved Spectroscopy pulse-sequence (PRESS), different data-points, and post-processings were quantized by jMRUI. PseudoMRSI maps of Cho/Cr, NAA/Cr, and Cho + Cr/NAA were created. A conformity index (CI) was used to determine which metabolite-ratio isolines are more appropriate for tumor delineation.
RESULTS: The simulation accuracy was verified. There were no differences > 4% between the measured and simulated spectra in peak regions. The pseudoMRSI map of Cho + Cr/NAA smoothly followed the complicated geometry of the tumor inside the gel-based phantom. The results showed that the single-voxel spectra produced by the PRESS pulse sequence with the TE of 144 ms, 512 data-points, and minimum post-processings of water suppression, eddy current correction, and baseline correction can be used for target delineation.
CONCLUSION: This study suggests that SVS data can be used to aid target delineation by using a mathematical approach. This can enable a wider use of MR-derived information in radiotherapy. ADVANCES IN KNOWLEDGE: To the best of our knowledge, until now, 2D or 3D MRSI data provided from 3T MRI scanners have been used for MRS-based radiotherapy treatment planning. However, there are a lot of centers that are equipped to 1.5 T MRI scanners and some of them just equipped to SVS. This study introduces a mathematical approach to help these centers to take the benefits of MRS-based treatment planning.

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Year:  2019        PMID: 31556332      PMCID: PMC6913370          DOI: 10.1259/bjr.20190216

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  35 in total

1.  Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals.

Authors:  A Naressi; C Couturier; I Castang; R de Beer; D Graveron-Demilly
Journal:  Comput Biol Med       Date:  2001-07       Impact factor: 4.589

2.  Simultaneous integrated boost (SIB) for treatment of gynecologic carcinoma: Intensity-modulated radiation therapy (IMRT) vs volumetric-modulated arc therapy (VMAT) radiotherapy.

Authors:  Irina Vergalasova; Kim Light; Junzo Chino; Oana Craciunescu
Journal:  Med Dosim       Date:  2017-07-12       Impact factor: 1.482

3.  Fast Padé transform for increasing the signal to noise ratio of spectra provided by STEAM pulse sequence.

Authors:  Mahdi Saeedi-Moghadam; Majid Pouladian; Reza Faghihi; Mehrzad Lotfi
Journal:  Technol Health Care       Date:  2019       Impact factor: 1.285

4.  Proton and phosphorus magnetic resonance spectroscopy of human astrocytomas in vivo. Preliminary observations on tumor grading.

Authors:  D L Arnold; E A Shoubridge; J G Villemure; W Feindel
Journal:  NMR Biomed       Date:  1990-08       Impact factor: 4.044

5.  Treatment planning for prostate implants using magnetic-resonance spectroscopy imaging.

Authors:  M Zaider; M J Zelefsky; E K Lee; K L Zakian; H I Amols; J Dyke; G Cohen; Y Hu; A K Endi; C Chui; J A Koutcher
Journal:  Int J Radiat Oncol Biol Phys       Date:  2000-07-01       Impact factor: 7.038

Review 6.  Molecular and functional imaging of breast cancer.

Authors:  Narges K Tafreshi; Virendra Kumar; David L Morse; Robert A Gatenby
Journal:  Cancer Control       Date:  2010-07       Impact factor: 3.302

7.  Comparison of T(1) and T(2) metabolite relaxation times in glioma and normal brain at 3T.

Authors:  Yan Li; Radhika Srinivasan; Helene Ratiney; Ying Lu; Susan M Chang; Sarah J Nelson
Journal:  J Magn Reson Imaging       Date:  2008-08       Impact factor: 4.813

8.  Accuracy of single-voxel proton MR spectroscopy in distinguishing neoplastic from nonneoplastic brain lesions.

Authors:  S D Rand; R Prost; V Haughton; L Mark; J Strainer; J Johansen; T A Kim; V K Chetty; W Mueller; G Meyer; H Krouwer
Journal:  AJNR Am J Neuroradiol       Date:  1997-10       Impact factor: 3.825

Review 9.  3 Tesla magnetic resonance spectroscopy: cerebral gliomas vs. metastatic brain tumors. Our experience and review of the literature.

Authors:  R Caivano; A Lotumolo; P Rabasco; A Zandolino; F D'Antuono; A Villonio; M I Lancellotti; L Macarini; A Cammarota
Journal:  Int J Neurosci       Date:  2013-03-11       Impact factor: 2.292

10.  Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T.

Authors:  Ioannis Tsougos; Patricia Svolos; Evanthia Kousi; Konstantinos Fountas; Kyriaki Theodorou; Ioannis Fezoulidis; Eftychia Kapsalaki
Journal:  Cancer Imaging       Date:  2012-10-26       Impact factor: 3.909

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