Purpose: Accurate baseline modeling is essential for reliable MRS analysis and interpretation - particularly at short echo-times, where enhanced metabolite information coincides with elevated baseline interference. The degree of baseline smoothness is a key analysis parameter for metabolite estimation, and in this study a new method is presented to estimate its optimal value. Methods: An adaptive baseline fitting algorithm (ABfit) is described, incorporating a spline basis into a frequency-domain analysis model, with a penalty parameter to enforce baseline smoothness. A series of candidate analyses are performed over a range of smoothness penalties, as part of a four stage algorithm, and the Akaike information criterion is used to estimate the appropriate penalty. ABfit is applied to a set of simulated spectra with differing baseline features and experimentally acquired 2D MRSI - both at a field strength of 3 Tesla. Results: Simulated analyses demonstrate metabolite errors result from two main sources: bias from an inflexible baseline (underfitting) and increased variance from an overly flexible baseline (overfitting). In the case of an ideal flat baseline ABfit is shown to correctly estimate a highly rigid baseline, and for more realistic spectra a reasonable compromise between bias and variance is found. Analysis of experimentally acquired data demonstrates good agreement with known correlations between metabolite ratios and the contributing volumes of gray and white matter tissue. Conclusion: ABfit has been shown to perform accurate baseline estimation and is suitable for fully-automated routine MRS analysis.

中文翻译：

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1H MR光谱分析的自适应基线拟合

目的：准确的基线建模对于可靠的MRS分析和解释至关重要-尤其是在短回波时间内，代谢物信息的增强与基线干扰的增加相吻合。基线平滑度是代谢物估计的关键分析参数，在这项研究中，提出了一种新方法来估计其最佳值。方法：描述了一种自适应基线拟合算法（ABfit），该算法将样条曲线基础合并到频域分析模型中，并带有惩罚参数以增强基线平滑度。作为四阶段算法的一部分，在一系列平滑度惩罚上执行了一系列候选分析，并且使用Akaike信息标准来估计适当的惩罚。ABfit适用于一组具有不同基线特征的模拟光谱和实验获得的2D MRSI-两者的场强均为3 Tesla。结果：模拟分析表明，代谢物错误是由两个主要来源造成的：基线不灵活（偏拟合）造成的偏倚和基线过灵活（偏拟合）导致的方差增加。在理想的平坦基线情况下，ABfit可以正确估计高刚性基线，而对于更真实的光谱，可以找到偏差和方差之间的合理折衷。对实验获得的数据的分析表明，代谢物比例与灰色和白色物质组织的贡献量之间的已知相关性很好。结论：