磁共振弥散加权成像对急性小脑梗死患者不良预后的预测作用
Diffusion-Weighted Magnetic Resonance Imaging for Predicting Poor Outcomes in Patients with Acute Cerebellar Infarction
DOI: 10.12677/acm.2026.1652165, PDF,    科研立项经费支持
作者: 张艳芳, 白亮亭, 李全浩, 李永华*：高密市人民医院神经内一科，山东 潍坊；马玲君：高密市人民医院病案室，山东 潍坊
关键词: 卒中；小脑梗死；磁共振成像(MRI)；脑水肿；曲线下面积；Stroke； Cerebellar Infarction； Magnetic Resonance Imaging (MRI)； Brain Edema； Area under the Curve
摘要: 目的：对有神经功能恶化风险的小脑梗死患者的早期识别仍具有挑战性。基于MRI的大脑中动脉(MCA)梗死评估可预测不良预后。本研究的目的是，验证以下假设：基于MRI的小脑梗死体积可以预测急性小脑梗死患者不良预后的发生。方法：我们回顾性纳入了80例连续接受弥散加权成像(DWI)MRI检查的小脑卒中患者(年龄59.2 ± 11.43岁)。受试者分为预后不良组(n = 17)和预后良好组(n = 63)。预后不良定义为符合以下至少一项标准：(1) 死亡；(2) 减压颅骨切除术；(3) 脑室造瘘术；(4) 意识水平下降；(5) 出院后3个月随访，mRS ≥ 3分的患者。DWI参数及小脑体积通过表观扩散系数图进行评估，并计算病灶体积与全小脑体积的比值。结果：逻辑回归分析显示，病灶体积(P = 0.005)和体积比(P = 0.004)与不良预后风险增加相关，即使在调整年龄和NIHSS后仍如此。经年龄和NIHSS校正的逻辑回归模型显示，病灶体积的AUC为0.890 (95% CI: 0.768~0.995)，体积比的AUC为0.939 (95% CI: 0.868~0.999)。结论：定量体积测量可预测小脑梗死患者的不良预后，即使在控制年龄和NIHSS评分后仍具预测价值。弥散加权成像MRI定量分析有助于识别神经系统功能恶化风险高的小脑梗死患者，进一步行前瞻性研究验证。
Abstract: Objective: Early identification of patients with cerebellar infarction who are at risk of neurological deterioration remains challenging. MRI-based assessment of middle cerebral artery (MCA) infarction has been shown to predict poor outcomes. This study aimed to test the hypothesis that MRI-based cerebellar infarct volume can predict the occurrence of poor outcomes in patients with acute cerebellar infarction. Methods: We retrospectively enrolled 80 consecutive patients with acute cerebellar infarction (age 59.2 ± 11.43 years) who underwent diffusion-weighted imaging (DWI) MRI. The patients were divided into a poor outcome group (n = 17) and a favorable outcome group (n = 63). Poor outcome was defined as meeting at least one of the following criteria: (1) death; (2) decompressive craniectomy; (3) ventriculostomy; (4) decreased level of consciousness; or (5) a modified Rankin Scale (mRS) score ≥ 3 at the 3-month follow-up visit. DWI parameters and cerebellar volume were assessed using apparent diffusion coefficient maps, and the ratio of lesion volume to total cerebellar volume was calculated. Results: Logistic regression analysis revealed that lesion volume (P = 0.005) and volume ratio (P = 0.004) were associated with an increased risk of poor outcome, even after adjusting for age and National Institutes of Health Stroke Scale (NIHSS) score. After adjusting for age and NIHSS score, the logistic regression model showed an area under the curve (AUC) of 0.890 (95% CI: 0.768~0.995) for lesion volume and 0.939 (95% CI: 0.868~0.999) for volume ratio. Conclusion: Quantitative volumetric measurement predicts poor outcomes in patients with cerebellar infarction, even after controlling for age and NIHSS score. Quantitative analysis of DWI MRI may help identify patients with cerebellar infarction at high risk of neurological deterioration. Further prospective studies are warranted to validate these findings.
文章引用：张艳芳, 白亮亭, 李全浩, 马玲君, 李永华. 磁共振弥散加权成像对急性小脑梗死患者不良预后的预测作用[J]. 临床医学进展, 2026, 16(5): 3424-3435. https://doi.org/10.12677/acm.2026.1652165

参考文献

[1] Calic, Z., Cappelen-Smith, C., Cuganesan, R., Anderson, C.S., Welgampola, M. and Cordato, D.J. (2017) Frequency, Aetiology, and Outcome of Small Cerebellar Infarction. Cerebrovascular Diseases Extra, 7, 173-180. [Google Scholar] [CrossRef] [PubMed]
[2] Amarenco, P., Lévy, C., Cohen, A., Touboul, P.J., Roullet, E. and Bousser, M.G. (1994) Causes and Mechanisms of Territorial and Nonterritorial Cerebellar Infarcts in 115 Consecutive Patients. Stroke, 25, 105-112. [Google Scholar] [CrossRef] [PubMed]
[3] Bogousslavsky, J., Van Melle, G. and Regli, F. (1988) The Lausanne Stroke Registry: Analysis of 1,000 Consecutive Patients with First Stroke. Stroke, 19, 1083-1092. [Google Scholar] [CrossRef] [PubMed]
[4] Hornig, C.R., Rust, D.S., Busse, O., Jauss, M. and Laun, A. (1994) Space-Occupying Cerebellar Infarction. Clinical Course and Prognosis. Stroke, 25, 372-374. [Google Scholar] [CrossRef] [PubMed]
[5] Lindeskog, D., Lilja-Cyron, A., Kelsen, J. and Juhler, M. (2019) Long-Term Functional Outcome after Decompressive Suboccipital Craniectomy for Space-Occupying Cerebellar Infarction. Clinical Neurology and Neurosurgery, 176, 47-52. [Google Scholar] [CrossRef] [PubMed]
[6] Tohgi, H., Takahashi, S., Chiba, K. and Hirata, Y. (1993) Cerebellar Infarction. Clinical and Neuroimaging Analysis in 293 Patients. the Tohoku Cerebellar Infarction Study Group. Stroke, 24, 1697-1701. [Google Scholar] [CrossRef] [PubMed]
[7] Koh, M.G., Phan, T.G., Atkinson, J.L.D. and Wijdicks, E.F.M. (2000) Neuroimaging in Deteriorating Patients with Cerebellar Infarcts and Mass Effect. Stroke, 31, 2062-2067. [Google Scholar] [CrossRef] [PubMed]
[8] Chen, H.J., Lee, T.C. and Wei, C.P. (1992) Treatment of Cerebellar Infarction by Decompressive Suboccipital Craniectomy. Stroke, 23, 957-961. [Google Scholar] [CrossRef] [PubMed]
[9] Mathew, P., Teasdale, G., Bannan, A. and Oluoch-Olunya, D. (1995) Neurosurgical Management of Cerebellar Haematoma and Infarct. Journal of Neurology, Neurosurgery & Psychiatry, 59, 287-292. [Google Scholar] [CrossRef] [PubMed]
[10] 闫琳琳, 谢佳蕾, 张小龙. 占位性小脑梗死[J]. 国际脑血管病杂志, 2020, 28(3): 212-215.
[11] Mühlbacher, T., Bohner, G., Bührer, C. and Dame, C. (2017) Cerebellar Infarction: Unusual Manifestation with Facial Palsy, Focal Seizures, and Secondary Generalization. Neonatology, 113, 33-36. [Google Scholar] [CrossRef] [PubMed]
[12] Savitz, S.I., Caplan, L.R. and Edlow, J.A. (2007) Pitfalls in the Diagnosis of Cerebellar Infarction. Academic Emergency Medicine, 14, 63-68. [Google Scholar] [CrossRef] [PubMed]
[13] Suyama, Y., Wakabayashi, S., Aihara, H., et al. (2019) Evaluation of Clinical Significance of Decompressive Suboccipital Craniectomy on the Prognosis of Cerebellar Infarction. Fujita Medical Journal, 5, 21-24.
[14] Jensen, M.B. and St. Louis, E.K. (2005) Management of Acute Cerebellar Stroke. Archives of Neurology, 62, 537-544. [Google Scholar] [CrossRef] [PubMed]
[15] Choi, K.D., Lee, H. and Kim, J.S. (2016) Ischemic Syndromes Causing Dizziness and Vertigo. Handbook of Clinical Neurology, 137, 317-340.
[16] Ayling, O.G.S., Alotaibi, N.M., Wang, J.Z., Fatehi, M., Ibrahim, G.M., Benavente, O., et al. (2018) Suboccipital Decompressive Craniectomy for Cerebellar Infarction: A Systematic Review and Meta-Analysis. World Neurosurgery, 110, 450-459.e5. [Google Scholar] [CrossRef] [PubMed]
[17] Wijdicks, E.F.M., Sheth, K.N., Carter, B.S., Greer, D.M., Kasner, S.E., Kimberly, W.T., et al. (2014) Recommendations for the Management of Cerebral and Cerebellar Infarction with Swelling: A Statement for Healthcare Professionals from the American Heart Association/American Stroke Association. Stroke, 45, 1222-1238. [Google Scholar] [CrossRef] [PubMed]
[18] Sporns, P.B., Minnerup, J., Warneke, N., Dziewas, R., Hanning, U., Berkemeyer, S., et al. (2015) Impact of the Implementation of Thrombectomy with Stent Retrievers on the Frequency of Hemicraniectomy in Patients with Acute Ischemic Stroke. Clinical Neuroradiology, 27, 193-197. [Google Scholar] [CrossRef] [PubMed]
[19] Hwang, D.Y., Silva, G.S., Furie, K.L. and Greer, D.M. (2012) Comparative Sensitivity of Computed Tomography vs. Magnetic Resonance Imaging for Detecting Acute Posterior Fossa Infarct. The Journal of Emergency Medicine, 42, 559-565. [Google Scholar] [CrossRef] [PubMed]
[20] Mullins, M.E., Schaefer, P.W., Sorensen, A.G., Halpern, E.F., Ay, H., He, J., et al. (2002) CT and Conventional and Diffusion-Weighted MR Imaging in Acute Stroke: Study in 691 Patients at Presentation to the Emergency Department. Radiology, 224, 353-360. [Google Scholar] [CrossRef] [PubMed]
[21] Chalela, J.A., Kidwell, C.S., Nentwich, L.M., Luby, M., Butman, J.A., Demchuk, A.M., et al. (2007) Magnetic Resonance Imaging and Computed Tomography in Emergency Assessment of Patients with Suspected Acute Stroke: A Prospective Comparison. The Lancet, 369, 293-298. [Google Scholar] [CrossRef] [PubMed]
[22] Oppenheim, C., Samson, Y., Manaï, R., Lalam, T., Vandamme, X., Crozier, S., et al. (2000) Prediction of Malignant Middle Cerebral Artery Infarction by Diffusion-Weighted Imaging. Stroke, 31, 2175-2181. [Google Scholar] [CrossRef] [PubMed]
[23] Thomalla, G., Hartmann, F., Juettler, E., Singer, O.C., Lehnhardt, F., Köhrmann, M., et al. (2010) Prediction of Malignant Middle Cerebral Artery Infarction by Magnetic Resonance Imaging within 6 Hours of Symptom Onset: A Prospective Multicenter Observational Study. Annals of Neurology, 68, 435-445. [Google Scholar] [CrossRef] [PubMed]
[24] Thomalla, G.J., Kucinski, T., Schoder, V., Fiehler, J., Knab, R., Zeumer, H., et al. (2003) Prediction of Malignant Middle Cerebral Artery Infarction by Early Perfusion-and Diffusion-Weighted Magnetic Resonance Imaging. Stroke, 34, 1892-1899. [Google Scholar] [CrossRef] [PubMed]
[25] Arenillas, J.F., Rovira, A., Molina, C.A., Grivé, E., Montaner, J. and Álvarez-Sabín, J. (2002) Prediction of Early Neurological Deterioration Using Diffusion-and Perfusion-Weighted Imaging in Hyperacute Middle Cerebral Artery Ischemic Stroke. Stroke, 33, 2197-2205. [Google Scholar] [CrossRef] [PubMed]
[26] 中华医学会神经病学分会, 中华医学会神经病学分会脑血管病学组. 中国急性缺血性卒中诊治指南2023 [J]. 中华神经科杂志, 2024, 57(6): 523-559.
[27] Zhang, S., Wang, W., Ma, X., Xia, Y. and Liu, A. (2014) Anticoagulation Therapy Is Harmful to Large‐Sized Cerebellar Infarction. CNS Neuroscience & Therapeutics, 20, 867-873. [Google Scholar] [CrossRef] [PubMed]
[28] Tchopev, Z., Hiller, M., Zhuo, J., Betz, J., Gullapalli, R. and Sheth, K.N. (2013) Prediction of Poor Outcome in Cerebellar Infarction by Diffusion MRI. Neurocritical Care, 19, 276-282. [Google Scholar] [CrossRef] [PubMed]
[29] Wang, Y., Binkley, M.M., Qiao, M., Pardon, A., Keyrouz, S., Dhar, R., et al. (2022) Rate of Infarct-Edema Growth on CT Predicts Need for Surgical Intervention and Clinical Outcome in Patients with Cerebellar Infarction. Neurocritical Care, 36, 1011-1021. [Google Scholar] [CrossRef] [PubMed]
[30] Jüttler, E., Schweickert, S., Ringleb, P.A., Huttner, H.B., Köhrmann, M. and Aschoff, A. (2009) Long-Term Outcome after Surgical Treatment for Space-Occupying Cerebellar Infarction: Experience in 56 Patients. Stroke, 40, 3060-3066. [Google Scholar] [CrossRef] [PubMed]
[31] Boone, M., Chillon, J.-M., Garcia, P.-Y., et al. (2012) NIHSS and Acute Complications after Anterior and Posterior Circulation Strokes. Therapeutics and Clinical Risk Management, 8, 87-93. [Google Scholar] [CrossRef] [PubMed]
[32] Vahedi, K., Hofmeijer, J., Juettler, E., Vicaut, E., George, B., Algra, A., et al. (2007) Early Decompressive Surgery in Malignant Infarction of the Middle Cerebral Artery: A Pooled Analysis of Three Randomised Controlled Trials. The Lancet Neurology, 6, 215-222. [Google Scholar] [CrossRef] [PubMed]
[33] Edlow, J.A., Newman-Toker, D.E. and Savitz, S.I. (2008) Diagnosis and Initial Management of Cerebellar Infarction. The Lancet Neurology, 7, 951-964. [Google Scholar] [CrossRef] [PubMed]
[34] Linfante, I., Llinas, R.H., Schlaug, G., Chaves, C., Warach, S. and Caplan, L.R. (2001) Diffusion-Weighted Imaging and National Institutes of Health Stroke Scale in the Acute Phase of Posterior-Circulation Stroke. Archives of Neurology, 58, 621-628. [Google Scholar] [CrossRef] [PubMed]
[35] Yoo, A.J., Barak, E.R., Copen, W.A., Kamalian, S., Gharai, L.R., Pervez, M.A., et al. (2010) Combining Acute Diffusion-Weighted Imaging and Mean Transmit Time Lesion Volumes with National Institutes of Health Stroke Scale Score Improves the Prediction of Acute Stroke Outcome. Stroke, 41, 1728-1735. [Google Scholar] [CrossRef] [PubMed]
[36] Makharia, A., Agarwal, A., Garg, D., Vishnu, V.Y. and Srivastava, M.V.P. (2024) The Pitfalls of NIHSS: Time for a New Clinical Acute Stroke Severity Scoring System in the Emergency? Annals of Indian Academy of Neurology, 27, 15-18. [Google Scholar] [CrossRef] [PubMed]
[37] Olivato, S., Nizzoli, S., Cavazzuti, M., Casoni, F., Nichelli, P.F. and Zini, A. (2016) E-Nihss: An Expanded National Institutes of Health Stroke Scale Weighted for Anterior and Posterior Circulation Strokes. Journal of Stroke and Cerebrovascular Diseases, 25, 2953-2957. [Google Scholar] [CrossRef] [PubMed]
[38] Siniscalchi, A., Sztajzel, R., Malferrari, G. and Gallelli, L. (2017) The National Institutes of Health Stroke Scale: Its Role in Patients with Posterior Circulation Stroke. Hospital Topics, 95, 79-81. [Google Scholar] [CrossRef] [PubMed]
[39] Lu, W., Lin, H., Bai, C. and Lin, S. (2021) Posterior Circulation Acute Stroke Prognosis Early CT Scores in Predicting Functional Outcomes: A Meta-analysis. PLOS ONE, 16, e0246906. [Google Scholar] [CrossRef] [PubMed]
[40] Puetz, V., Sylaja, P.N., Coutts, S.B., Hill, M.D., Dzialowski, I., Mueller, P., et al. (2008) Extent of Hypoattenuation on CT Angiography Source Images Predicts Functional Outcome in Patients with Basilar Artery Occlusion. Stroke, 39, 2485-2490. [Google Scholar] [CrossRef] [PubMed]
[41] Baki, E., Baumgart, L., Kehl, V., Hess, F., Wolff, A.W., Wagner, A., et al. (2024) Functional Outcomes after Decompressive Surgery in Patients with Malignant Space-Occupying Cerebellar Infarction. Neurology International, 16, 1239-1246. [Google Scholar] [CrossRef] [PubMed]
[42] Lucia, K., Reitz, S., Hattingen, E., Steinmetz, H., Seifert, V. and Czabanka, M. (2023) Predictors of Clinical Outcomes in Space-Occupying Cerebellar Infarction Undergoing Suboccipital Decompressive Craniectomy. Frontiers in Neurology, 14, Article ID: 1165258. [Google Scholar] [CrossRef] [PubMed]
[43] 王薇, 赵静, 彭明洋, 等. 探讨不同时间窗的急性缺血性脑卒中机械取栓术后预后的差异[J]. 磁共振成像, 2021, 12(3): 39-43.
[44] 孙海珍, 张慧, 倪红艳, 等. 缺血性脑卒中早期DKI, DWI预测病灶最终转变的对比研究[J]. 磁共振成像, 2016, 7(10): 732-737.
[45] Grosse-Dresselhaus, F., Galinovic, I., Villringer, K., Audebert, H.J. and Fiebach, J.B. (2014) Difficulty of MRI Based Identification of Lesion Age by Acute Infra-Tentorial Ischemic Stroke. PLOS ONE, 9, e92868. [Google Scholar] [CrossRef] [PubMed]
[46] Fabritius, M.P., Reidler, P., Froelich, M.F., Rotkopf, L.T., Liebig, T., Kellert, L., et al. (2019) Incremental Value of Computed Tomography Perfusion for Final Infarct Prediction in Acute Ischemic Cerebellar Stroke. Journal of the American Heart Association, 8, e013069. [Google Scholar] [CrossRef] [PubMed]
[47] Sakamoto, Y., Aoki, J., Nishi, Y., Shoda, S., Kimura, R., Saito, T., et al. (2025) Acute DWI Volume Is a Strong Imaging Predictor of Favorable Outcomes in Patients with Acute Stroke and Treated with Mechanical Thrombectomy. Journal of the Neurological Sciences, 468, 123334. [Google Scholar] [CrossRef] [PubMed]
[48] Wong, K.K., Cummock, J.S., Li, G., Ghosh, R., Xu, P., Volpi, J.J., et al. (2022) Automatic Segmentation in Acute Ischemic Stroke: Prognostic Significance of Topological Stroke Volumes on Stroke Outcome. Stroke, 53, 2896-2905. [Google Scholar] [CrossRef] [PubMed]
[49] Wouters, A., Robben, D., Christensen, S., Marquering, H.A., Roos, Y.B.W.E.M., van Oostenbrugge, R.J., et al. (2022) Prediction of Stroke Infarct Growth Rates by Baseline Perfusion Imaging. Stroke, 53, 569-577. [Google Scholar] [CrossRef] [PubMed]
[50] Bra, B.T., Bastan, B., Fisher, M., Bouley, J. and Henninger, N. (2009) Ischemic Lesion Volume Determination on Diffusion Weighted Images vs. Apparent Diffusion Coefficient Maps. Brain Research, 1279, 182-188. [Google Scholar] [CrossRef] [PubMed]

为你推荐