Reliable in vivo lactate and lipid estimation in glioma patients

Lactate is a sensitive indicator of anaerobic glycolysis and reduced cellular oxygenation in living tissues. Mobile lipid resonances have been correlated with necrosis and cell breakdown. Reliable estimates of levels of lactate and lipid are of interest for evaluating prognosis and hence guiding the clinical management of patients with brain tumors. The goal of this study was to develop a robust and reliable estimation scheme to evaluate the in vivo lactate and lipid levels in glioma patients. The acquisition method combined J-difference modulation and reduced k-space sampling to obtain two set of 3D 1H-magnetic resonance spectroscopic imaging (MRSl) data, from which lactate editing was implemented. An iterative nonlinear least-squares algorithm for fitting Voigt line shape models in the frequency domain was developed for quantification for choline, creatine, NAA, lactate and lipid after non-parametric phase, frequency and baseline correction. Simulated data showed that the presented algorithm was robust and reliable. The quantification scheme was also applied to sixteen glioma patients prior to therapy.