From the Imaging Research Unit, Department of Radiology (Girona Biomedical Research Institute) Girona Biomedical Research Institute, Diagnostic Imaging Institute (IDI) (J.P., G.B., C.B., M.N.-M., C.L.O.-R., S.P.), Dr Josep Trueta University Hospital, Girona, Spain.
Quantitative Imaging Biomarkers In Medicine, La Fe Health Research Institute, La Fe Polytechnics and University Hospital, Valencia, Spain (A.A.-B.).
Stroke. 2018 Oct;49(10):2353-2360. doi: 10.1161/STROKEAHA.118.021319.
Background and Purpose- Physiological effects of stroke are best assessed over entire brain networks rather than just focally at the site of structural damage. Resting-state functional magnetic resonance imaging can map functional-anatomic networks by analyzing spontaneously correlated low-frequency activity fluctuations across the brain, but its potential usefulness in predicting functional outcome after acute stroke remains unknown. We assessed the ability of resting-state functional magnetic resonance imaging to predict functional outcome after acute stroke. Methods- We scanned 37 consecutive reperfused stroke patients (age, 69±14 years; 14 females; 3-day National Institutes of Health Stroke Scale score, 6±5) on day 3 after symptom onset. After imaging preprocessing, we used a whole-brain mask to calculate the correlation coefficient matrices for every paired region using the Harvard-Oxford probabilistic atlas. To evaluate functional outcome, we applied the modified Rankin Scale at 90 days. We used region of interest analyses to explore the functional connectivity between regions and graph-computation analysis to detect differences in functional connectivity between patients with good functional outcome (modified Rankin Scale score ≤2) and those with poor outcome (modified Rankin Scale score >2). Results- Patients with good outcome had greater functional connectivity than patients with poor outcome. Although 3-day National Institutes of Health Stroke Scale score was the most accurate independent predictor of 90-day modified Rankin Scale (84.2%), adding functional connectivity increased accuracy to 94.7%. Preserved bilateral interhemispheric connectivity between the anterior inferior temporal gyrus and superior frontal gyrus and decreased connectivity between the caudate and anterior inferior temporal gyrus in the left hemisphere had the greatest impact in favoring good prognosis. Conclusions- These data suggest that information about functional connectivity from resting-state functional magnetic resonance imaging may help predict 90-day stroke outcome.
背景与目的- 中风的生理影响最好通过整个大脑网络进行评估，而不仅仅是在结构损伤部位进行局部评估。静息态功能磁共振成像可以通过分析大脑中自发相关的低频活动波动来绘制功能解剖网络，但它在预测急性中风后功能结果方面的潜在用途尚不清楚。我们评估了静息态功能磁共振成像预测急性中风后功能结果的能力。
方法- 我们在症状发作后 3 天扫描了 37 例连续再灌注中风患者（年龄 69±14 岁；14 名女性；3 天 NIHSS 评分为 6±5）。在图像预处理后，我们使用全脑掩模，使用哈佛-牛津概率图谱计算每个配对区域的相关系数矩阵。为了评估功能结果，我们在 90 天时应用改良 Rankin 量表。我们使用感兴趣区域分析来探索区域之间的功能连接，使用图计算分析来检测功能结果良好（改良 Rankin 量表评分≤2）和功能结果差（改良 Rankin 量表评分>2）患者之间的功能连接差异。
结果- 功能结果良好的患者比功能结果差的患者具有更大的功能连接。尽管 3 天 NIHSS 评分是 90 天改良 Rankin 量表的最准确独立预测因素（84.2%），但添加功能连接可将准确性提高至 94.7%。保留左侧前颞下回和额上回之间双侧半球间连接以及降低左侧尾状核和前颞下回之间的连接对预后良好有最大影响。
结论- 这些数据表明，静息态功能磁共振成像的功能连接信息可能有助于预测 90 天的中风结果。
