Chaim-Avancini T M, Doshi J, Zanetti M V, Erus G, Silva M A, Duran F L S, Cavallet M, Serpa M H, Caetano S C, Louza M R, Davatzikos C, Busatto G F
Laboratory of Psychiatric Neuroimaging (LIM-21), Department and Institute of Psychiatry, Faculty of Medicine, University of São Paulo, Sao Paulo, Brazil.
Center for Interdisciplinary Research on Applied Neurosciences (NAPNA), University of São Paulo, Sao Paulo, Brazil.
Acta Psychiatr Scand. 2017 Dec;136(6):623-636. doi: 10.1111/acps.12824. Epub 2017 Oct 28.
In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first time, machine learning-based pattern classification methods to structural MRI and diffusion tensor imaging (DTI) data obtained from stimulant-naïve adults with childhood-onset ADHD and healthy controls (HC).
Sixty-seven ADHD patients and 66 HC underwent high-resolution T1-weighted and DTI acquisitions. A support vector machine (SVM) classifier with a non-linear kernel was applied on multimodal image features extracted on regions of interest placed across the whole brain.
The discrimination between a mixed-gender ADHD subgroup and individually matched HC (n = 58 each) yielded area-under-the-curve (AUC) and diagnostic accuracy (DA) values of up to 0.71% and 66% (P = 0.003) respectively. AUC and DA values increased to 0.74% and 74% (P = 0.0001) when analyses were restricted to males (52 ADHD vs. 44 HC).
Although not at the level of clinically definitive DA, the neuroanatomical signature identified herein may provide additional, objective information that could influence treatment decisions in adults with ADHD spectrum symptoms.
在成年期，注意力缺陷多动障碍（ADHD）的诊断一直是近期争议的主题。我们首次将基于机器学习的模式分类方法应用于从童年起病的未使用过兴奋剂的ADHD成人患者和健康对照（HC）获取的结构MRI和扩散张量成像（DTI）数据，以寻找与成人ADHD谱症状相关的神经解剖学特征。
67例ADHD患者和66例HC接受了高分辨率T1加权和DTI采集。将具有非线性核的支持向量机（SVM）分类器应用于在全脑放置的感兴趣区域提取的多模态图像特征上。
混合性别的ADHD亚组与个体匹配的HC（每组n = 58）之间的判别产生的曲线下面积（AUC）和诊断准确性（DA）值分别高达0.71%和66%（P = 0.003）。当分析仅限于男性（52例ADHD vs. 44例HC）时，AUC和DA值分别提高到0.74%和74%（P = 0.0001）。
尽管未达到临床确定性DA的水平，但本文确定的神经解剖学特征可能提供额外的客观信息，这可能会影响有ADHD谱症状的成人的治疗决策。
