Fully Automatic Baseline Correction in Magnetic Resonance Spectroscopy

Omid Bazgir, S. Mitra, B. Nutter, E. Walden
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引用次数: 1

Abstract

Proton Magnetic Resonance Spectroscopy (1H MRS) in conjunction with Magnetic Resonance Imaging (MRI) has been a significant topic of research for quantitative assessment and early detection of neurodegenerative disorders for more than two decades. However, robust techniques for MRS data analysis are still being developed for wide clinical use. Many neurodegenerative diseases exhibit changes in concentrations of specific metabolites. One of the challenging problems in developing consistent quantitative estimation of metabolite concentration is proper correction of the MRS baseline due to the contributions from macromolecules and lipids. We have proposed a novel approach based on interpolation of minima in MR spectra and applied this technique to both in vitro and in vivo MRS data analysis. Our results demonstrate that the proposed method is fast, independent of tuning, and provides an accurate estimation of MRS baseline, leading to improved computational estimates for metabolic concentrations.
磁共振波谱的全自动基线校正
二十多年来,质子磁共振波谱(1H MRS)与磁共振成像(MRI)一直是神经退行性疾病定量评估和早期检测的重要研究课题。然而,为了广泛的临床应用,核磁共振数据分析的可靠技术仍在开发中。许多神经退行性疾病表现出特定代谢物浓度的变化。在建立一致的代谢物浓度定量估计中,具有挑战性的问题之一是由于大分子和脂质的贡献而正确校正MRS基线。我们提出了一种基于最小值插值的核磁共振光谱方法,并将其应用于体外和体内核磁共振数据分析。我们的研究结果表明,所提出的方法是快速的,独立于调谐,并提供了一个准确的估计MRS基线,导致改进代谢浓度的计算估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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