Optimization of Single Voxel MR Spectroscopy Sequence Parameters and Data Analysis Methods for Thermometry in Deep Hyperthermia Treatments

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Abstract

Objective:

The difference in the resonance frequency of water and methylene moieties of lipids quantifies in magnetic resonance spectroscopy the absolute temperature using a predefined calibration curve. The purpose of this study was the investigation of peak evaluation methods and the magnetic resonance spectroscopy sequence (point-resolved spectroscopy) parameter optimization that enables thermometry during deep hyperthermia treatments.

Materials and Methods:

Different Lorentz peak-fitting methods and a peak finding method using singular value decomposition of a Hankel matrix were compared. Phantom measurements on organic substances (mayonnaise and pork) were performed inside the hyperthermia 1.5-T magnetic resonance imaging system for the parameter optimization study. Parameter settings such as voxel size, echo time, and flip angle were varied and investigated.

Results:

Usually all peak analyzing methods were applicable. Lorentz peak-fitting method in MATLAB proved to be the most stable regardless of the number of fitted peaks, yet the slowest method. The examinations yielded an optimal parameter combination of 8 cm3 voxel volume, 55 millisecond echo time, and a 90° excitation pulse flip angle.

Conclusion:

The Lorentz peak-fitting method in MATLAB was the most reliable peak analyzing method. Measurements in homogeneous and heterogeneous phantoms resulted in optimized parameters for the magnetic resonance spectroscopy sequence for thermometry.

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