Computational Magnetic Resonance Spectroscopy using Microsoft Excel Macros

Abstract

Magnetic resonance spectroscopy (MRS) is a technique that can be used in preclinical and clinical applications to study cancer metabolism improvement of spatial and temporal resolution of spectral data due to advancements in pulse sequence and hardware design has made MRS interesting modality to be used side by side with clinical magnetic resonance imaging. In recent times, clinical MR scanners now carried routine imaging sequences for IH-MRS measurements with direct applications in metabolic and functional information combined wit contemporary MRI localization. MRS has the ability to detect N-acetylaspartate (NAA) in the normal brain tissue and citrate in the m prostate, and their levels decrease once the tumor cells start replacing normal cells. MRS detection of total choline signal has been impressive in the diagnosis and monitoring of brain, breast and prostate cancers. It has also been useful in monitoring of patient's response to anticancer However, MRS has lower sensitivities and requires much longer acquisition times and more complex data processing. In addition clinicians are not very much familiar with this technique and thus, limiting the application of MRS in the clinical setting. In order to overcame problem, we attempt developing a computational program (macros) with Microsoft excel for MRS of tissues with fast data processing In this study, we have demonstrated that clinical scientists do not necessarily require the knowledge of advanced mathematics and rig analysis in order to perform MRS of tissues towards the diagnosis of diseases of the brain. With the computational model presented in t and the computer program developed, MRS is simply achieved by entering the measured values of T1 and T2 relaxation times.