以ReHo异常体素数来预判难治性抑郁症

Increasing evidence suggests that patients with treatment-resistant depression exhibit more abnormal neural activities in a great number of brain regions than those with treatment non-resistant depression. Thus we deduce that treatment-resistant depression may be the result of abnormal neural activities in a large body of brain regions. However, current lack of the indictor to predict treatment resistance in major depressive disorder is widely recognized as a challenge to the clinician. The present study is devoted to explore such an indictor by inspecting the regional homogeneity (ReHo) of brain neural activities in patients with treatment-resistant or treatment non-resistant depression in the resting state by means of functional magnetic resonance imaging (fMRI). Then a Cox's regression model is established by calculating the number of voxels with abnormal ReHo. The goodness of fit of the Cox's regression model is investigated in the tracing the number of voxels with abnormal ReHo and the treatment outcome of another group of patients with first-episode, treatment-naive major depressive disorder. The success of the present study will help the clinicians to discriminate the treatment-resistant patients and to suggest the effective treatment such as an augment treatment strategy in advance. It will also benefit the patients avoiding the risks of adverse events, expand the literature in eluding the pathogenesis of major depressive disorder, and promote the development of new drugs.

不同研究发现难治性抑郁症较非难治性抑郁症在更多脑区存在神经活动异常，据此我们推测并证实难治性抑郁症可能是多个脑区神经活动异常的结果。然而，临床上迄今对难治性抑郁症的预判缺乏敏感有效的客观指标。本项目致力寻找一种对难治性抑郁症进行预判的敏感有效的客观指标，拟对难治性抑郁症和非难治性抑郁症两组患者进行静息态功能磁共振成像（fMRI），统计局部一致性(ReHo)异常体素的大小，建立Cox回归模型并拟合Cox曲线，并在另一组首发未服药的抑郁症患者中对Cox回归模型的拟合优度进行考察。如研究得以顺利进行，不仅可以将难治性抑郁症预先甄别出来，选择恰当的治疗方案如增效治疗等，帮助患者避免药物的不良事件，而且对阐明难治性抑郁症的脑机制、新药研发等方面亦具有指导价值。

临床上迄今对难治性抑郁症（TRD）的预判缺乏敏感有效的客观指标。本项目致力寻找一种对TRD预判的敏感有效的客观指标，对TRD和治疗有反应的抑郁症(TSD)患者进行静息态功能磁共振成像，使用局部一致性（ReHo）和功能连接（FC）等分析方法来分析数据，结果发现：1）TRD较TSD患者在更多脑区存在神经活动异常；2）小脑降低的Cohe-ReHo值可以用来区分TRD患者和TSD患者； 3）calcarine cortex的VMHC值可以区分TRD患者和TSD患者；4）小脑-默认网络的FC值可以区分TRD患者和TSD患者。结果提示静息态功能磁共振的一些指标可用于TRD的预判。