A method for cranial target delineation in radiotherapy treatment planning aided by single-voxel magnetic resonance...

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.

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.

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.

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.

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.