PurposeThe interest in applying and modeling dynamic MRS has recently grown. Two‐dimensional modeling yields advantages for the precision of metabolite estimation in interrelated MRS data. However, it is unknown whether including all transients simultaneously in a 2D model without averaging (presuming a stable signal) performs similarly to one‐dimensional (1D) modeling of the averaged spectrum. Therefore, we systematically investigated the accuracy, precision, and uncertainty estimation of both described model approaches.MethodsMonte Carlo simulations of synthetic MRS data were used to compare the accuracy and uncertainty estimation of simultaneous 2D multitransient linear‐combination modeling (LCM) with 1D‐LCM of the average. A total of 2,500 data sets per condition with different noise representations of a 64‐transient MRS experiment at six signal‐to‐noise levels for two separate spin systems (scyllo‐inositol and gamma‐aminobutyric acid) were analyzed. Additional data sets with different levels of noise correlation were also analyzed. Modeling accuracy was assessed by determining the relative bias of the estimated amplitudes against the ground truth, and modeling precision was determined by SDs and Cramér‐Rao lower bounds (CRLBs).ResultsAmplitude estimates for 1D‐ and 2D‐LCM agreed well and showed a similar level of bias compared with the ground truth. Estimated CRLBs agreed well between both models and with ground‐truth CRLBs. For correlated noise, the estimated CRLBs increased with the correlation strength for the 1D‐LCM but remained stable for the 2D‐LCM.ConclusionOur results indicate that the model performance of 2D multitransient LCM is similar to averaged 1D‐LCM. This validation on a simplified scenario serves as a necessary basis for further applications of 2D modeling.

中文翻译：

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MRS 数据的同时多瞬态线性组合建模改进了不确定性估计

目的最近对动态 MRS 的应用和建模的兴趣与日俱增。二维建模对于相关 MRS 数据中代谢物估计的精度具有优势。然而，尚不清楚在 2D 模型中同时包含所有瞬态而不进行平均（假设信号稳定）是否与平均频谱的一维 (1D) 建模类似。因此，我们系统地研究了两种描述的模型方法的准确性、精度和不确定性估计。方法使用合成 MRS 数据的蒙特卡罗模拟来比较同步 2D 多瞬态线性组合建模 (LCM) 与 1D-LCM 的准确性和不确定性估计的平均值。对两种独立自旋系统（鲨肌醇和γ-氨基丁酸）在六个信噪水平下的 64 瞬态 MRS 实验的每种条件总共 2,500 个数据集进行了不同的噪声表示。还分析了具有不同噪声相关性水平的其他数据集。通过确定估计幅度相对于地面实况的相对偏差来评估建模精度，并通过 SD 和 Cramér-Rao 下界 (CRLB) 来确定建模精度。结果 1D-和 2D-​​LCM 的幅度估计非常一致，并显示出类似的结果与真实情况相比的偏差程度。两个模型之间以及真实 CRLB 之间的估计 CRLB 非常吻合。对于相关噪声，估计的 CRLB 随着 1D-LCM 的相关强度增加而增加，但对于 2D-LCM 保持稳定。结论我们的结果表明，2D 多瞬态 LCM 的模型性能与平均 1D-LCM 相似。这种对简化场景的验证是二维建模进一步应用的必要基础。