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姜双士,刘力硕,冯洪燕,王科,卜丽红,涂宁.基于神经黑色素MRI、¹¹C-CFT PET及¹⁸F-FDG PET联合诊断PD及评估其严重程度[J].中国医学影像技术,2023,39(10):1450~1454

基于神经黑色素MRI、¹¹C-CFT PET及¹⁸F-FDG PET联合诊断PD及评估其严重程度

Neuromelanin-MRI, ¹¹C-CFT PET and ¹⁸F-FDG PET for diagnosing and evaluating severity of Parkinson's disease

投稿时间：2023-05-29 修订日期：2023-08-16

DOI：10.13929/j.issn.1003-3289.2023.10.003

英文关键词:Parkinson disease dopamine plasma membrane transport proteins magnetic resonance imaging positron-emission tomography

基金项目:国家自然科学基金(82101548)。

作者	单位	E-mail
姜双士	武汉大学人民医院PET中心, 湖北武汉 430061
刘力硕	武汉大学人民医院PET中心, 湖北武汉 430061
冯洪燕	武汉大学人民医院PET中心, 湖北武汉 430061
王科	武汉大学人民医院PET中心, 湖北武汉 430061
卜丽红	武汉大学人民医院PET中心, 湖北武汉 430061
涂宁	武汉大学人民医院PET中心, 湖北武汉 430061	tuning@whu.edu.cn

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中文摘要:

目的观察联合应用神经黑色素(NM)-MRI、¹¹C-CFT PET及¹⁸F-FDG PET诊断帕金森病(PD)及评估其严重程度的价值。方法回顾性分析52例原发性PD患者(PD组)和16名健康受检者(对照组)NM-MRI、¹¹C-CFT PET及¹⁸F-FDG PET资料,根据Hoehn-Yahr分级将PD患者分为早期亚组(n=29)和中晚期亚组(n=23)。比较组间及亚组间纹状体各亚区标准化CFT(sCFT)、不对称指数(ASI)、标准化FDG(sFDG)及黑质致密部(SNc)面积;行logistic回归分析,建立MRI、PET及PET/MRI模型,分析其诊断PD及评估病情的效能。结果 PD组与对照组间壳核后部sCFT、ASI及SNc面积差异有统计学意义(P均＜0.05);基于壳核后部sCFT及ASI建立的PET模型诊断PD的曲线下面积(AUC)为0.946,基于SNc面积建立的MRI模型的AUC为0.864;基于上述3个参数建立的PET/MRI模型的AUC为0.948,明显高于MRI模型(Z=2.079,P=0.038)。PD组内早期亚组与中晚期亚组间壳核前部sCFT、壳核后部ASI及SNc面积差异有统计学意义(P均＜0.05);基于壳核前部sCFT及壳核后部ASI建立的PET模型评估PD严重程度的AUC为0.754,基于SNc面积建立的MRI模型的AUC为0.822,基于上述3个参数建立的PET/MRI模型的AUC为0.882,明显高于PET模型(Z=2.127,P=0.033)。结论联合应用 NM-MRI、¹¹C-CFT PET及¹⁸F-FDG PET有助于诊断PD及评估病情。

英文摘要:

Objective To observe the value of the combination of neuromelanin (NM)-MRI, ¹¹C-CFT PET and ¹⁸F-FDG PET for diagnosing and evaluating the severity of Parkinson's disease (PD). Methods Data of NM-MRI, ¹¹C-CFT PET and ¹⁸F-FDG PET of 52 primary PD patients (PD group) and 16 healthy subjects (control group) were retrospectively analyzed. PD patients were divided into early subgroup (n=29) or mid-late subgroup (n=23) according to Hoehn-Yahr classification. The standardized CFT (sCFT), asymmetry index (ASI), standardized FDG (sFDG) and substantia nigra compacta (SNc) area of subregion of the striatum were compared between groups and subgroups. Logistic regression analysis was performed to establish MRI, PET and PET/MRI models, and their efficacy for diagnosing and evaluating severity of PD were explored. Results Significant differences of posterior putamen sCFT, ASI and SNc were found between PD group and control group (all P＜0.05). The area under the curve (AUC) of PET model established based on posterior putamen sCFT and ASI for diagnosing PD was 0.946, of MRI model based on SNc area was 0.864, while of PET/MRI model based on the above 3 factors was 0.948. AUC of PET/MRI model was significantly higher than that of MRI model (Z=2.079, P=0.038). Meanwhile, significant differences of anterior putamen sCFT, posterior putamen ASI and SNc area were observed between early subgroup and mid-late subgroup within PD group (all P＜0.05). AUC of PET model established based on anterior putamen sCFT and posterior putamen ASI for evaluating severity of PD was 0.754, of MRI model based on SNc area was 0.822, of while PET/MRI model based on all above 3 factors was 0.882, significantly higher than that of PET model (Z=2.127, P=0.033). Conclusion The combination of NM-MRI, ¹¹C-CFT PET and ¹⁸F-FDG PET was helpful for diagnosing and evaluating the severity of PD.

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