NEJM：功能性磁共振成像或可用于评估疼痛强度

持续性疼痛可通过患者自我报告来测定，仅靠这种方式的测定阻碍诊断和治疗。功能性磁共振成像（fMRI）有望辨别出疼痛的客观指标，但尚未鉴别出针对躯体疼痛的既具有敏感性又具有特异性的脑指标。美国科罗拉多州立大学心理学和神经科学研究所的Wager博士等人对此进行了深入研究，他们发现，使用fMRI来评估健康人中有害高热导致的疼痛强度是可行的。未来的研究需要评估该特征能否预测临床疼痛。研究结果发表于NEJM 2013年4月份的在线版上。

在包括共有114名参与者的4项研究中，研究人员开发出一种基于fMRI、可在个体水平预测疼痛强度的指标。在研究1中，研究者用机器学习分析来辨别一种与热致痛相关的一种神经学特征——跨脑区fMRI活动模式。该模式包括丘脑、后脑岛和前脑岛、第二躯体感觉皮质、前扣带皮质、导水管周围灰质以及其他区域。 在研究2中，研究者们在新样本中检测了疼痛与温热对比时该特征的敏感性和特异性。在研究3中，研究者评估了相对于社会痛苦的特异性，社会痛苦和躯体疼痛可激活许多相同的脑区。在研究4中，我们评估了该指标对镇痛药瑞芬太尼的反应性。

结果发现，在研究1中，神经学特征显示从非致痛性温热、疼痛预期和疼痛回忆中鉴别出致痛性高热的敏感性和特异性达94%以上[95%可信区间（CI）89%～98%]。在研究2中，该特征鉴别致痛性高热和非致痛性温热的敏感性和特异性达93%（95%CI 84%～100%）。在研究3中，其鉴别躯体疼痛和社会痛苦的敏感性为85%（95%CI 76%～94%）、特异性为73%（95%CI 61%～84%），在两种条件下权衡哪一个更疼的迫选试验中，敏感性和特异性均为95%。在研究4中，在使用了瑞芬太尼时，该特征的反应强度大幅下降。

研究人员由此得出结论，使用fMRI来评估健康人中有害高热导致的疼痛强度是可行的。未来的研究需要评估该特征能否预测临床疼痛。

与磁共振成像相关的拓展阅读：

• Arch Neurol：新型多光谱磁共振成像计算PD患者黒质体积
• Ann Surg：HR状况与HER2靶向药物影响核磁共振成像准确性
• Cancer Res：动态增强磁共振成像(DCE-MRI)可评估肿瘤的组织间渗透压(IFP)和淋巴结转移
• BJR：核磁共振成像可用来检测癌细胞的骨转移
• 磁共振成像的原理及临床应用
• 磁共振成像的原理及临床应用(ppt)
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An fMRI-Based Neurologic Signature of Physical Pain
Background
Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified.
Methods
In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions — a neurologic signature — that was associated with heat-induced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil.
Results
In study 1, the neurologic signature showed sensitivity and specificity of 94% or more (95% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93% sensitivity and specificity (95% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85% sensitivity (95% CI, 76 to 94) and 73% specificity (95% CI, 61 to 84) and with 95% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered.
Conclusions
It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.)