Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan.
Department of Psychiatry, National Taiwan University Hospital, Hsin-Chu Branch, Hsin-Chu, Taiwan.
BMC Psychiatry. 2021 Jan 11;21(1):26. doi: 10.1186/s12888-021-03040-5.
Despite the effectiveness of methylphenidate for treating ADHD, up to 30% of individuals with ADHD show poor responses to methylphenidate. Neuroimaging biomarkers to predict medication responses remain elusive. This study characterized neuroanatomical features that differentiated between clinically good and poor methylphenidate responders with ADHD.
Using a naturalistic observation design selected from a larger cohort, we included 79 drug-naive individuals (aged 6-42 years) with ADHD without major psychiatric comorbidity, who had acceptable baseline structural MRI data quality. Based on a retrospective chart review, we defined responders by individuals' responses to at least one-month treatment with methylphenidate. A nonparametric mass-univariate voxel-based morphometric analysis was used to compare regional gray matter volume differences between good and poor responders. A multivariate pattern recognition based on the support vector machine was further implemented to identify neuroanatomical indicators to predict an individual's response.
63 and 16 individuals were classified in the good and poor responder group, respectively. Using the small-volume correction procedure based on the hypothesis-driven striatal and default-mode network masks, poor responders had smaller regional volumes of the left putamen as well as larger precuneus volumes compared to good responders at baseline. The machine learning approach identified that volumetric information among these two regions alongside the left frontoparietal regions, occipital lobes, and posterior/inferior cerebellum could predict clinical responses to methylphenidate in individuals with ADHD.
Our results suggest regional striatal and precuneus gray matter volumes play a critical role in mediating treatment responses in individuals with ADHD.
尽管哌甲酯治疗 ADHD 有效，但多达 30%的 ADHD 患者对哌甲酯反应不佳。用于预测药物反应的神经影像学生物标志物仍然难以捉摸。本研究旨在描述区分 ADHD 患者中临床反应良好和不佳的哌甲酯反应者的神经解剖学特征。
本研究采用自然观察设计，从较大的队列中选择，纳入了 79 名无重大精神共病的药物初治 ADHD 患者（年龄 6-42 岁），这些患者具有可接受的基线结构 MRI 数据质量。根据回顾性图表审查，我们将对至少一个月的哌甲酯治疗有反应的个体定义为反应者。采用非参数单变量基于体素的形态计量学分析比较了良好和不良反应者之间的区域灰质体积差异。进一步实施了基于支持向量机的多变量模式识别，以确定预测个体反应的神经解剖学指标。
分别有 63 名和 16 名患者被归类为良好和不良反应者。使用基于纹状体和默认模式网络假设驱动的小体积校正程序，在基线时，不良反应者的左侧壳核区域以及楔前叶区域的体积较小，而楔前叶区域的体积较大。机器学习方法确定了这些两个区域与左侧额顶叶区域、枕叶区域以及小脑后/下区域的体积信息可以预测 ADHD 个体对哌甲酯的临床反应。
我们的研究结果表明，纹状体和楔前叶的区域灰质体积在介导 ADHD 患者的治疗反应中起着关键作用。
