In vivo metabolite quantification by short echo time MR spectroscopy is a challenge for which various methods have been proposed. In this study, the reproducibility of quantification outcomes is questioned at three distinct levels: (i) between-software (LCModel and cQUEST), (ii) withinsoftware (with different parameter sets), and (iii) across software executions (when the fitting algorithm uses random seeds, like cQUEST). After running multiple quantification tasks on a dedicated platform (VIP), metrics from Bland-Altman analysis were used to assess the variability of outcomes in signals acquired on a lysolecithin rat model, from a study on demyelination. Results show substantial variations at the three levels, allowing for more potent analyses than from a single parameter set / single software point of view.

翻译：活体短回波时间磁共振波谱中的代谢物量化是一项挑战，针对此问题已提出多种方法。本研究从三个不同层面质疑量化结果的可重复性：（i）软件间（LCModel与cQUEST）、（ii）软件内（使用不同参数集）以及（iii）跨软件运行（当拟合算法使用随机种子时，如cQUEST）。在专用平台（VIP）上执行多次量化任务后，采用Bland-Altman分析指标评估了基于溶血卵磷脂大鼠模型（来自一项脱髓鞘研究）采集的信号结果的变异性。结果显示，在三个层面均存在显著变异，这比从单一参数集/单一软件角度进行的分析更能揭示深层洞见。