Lee Minwoo, Suh Chong Hyun, Sohn Jong-Hee, Kim Chulho, Han Sang-Won, Sung Joo Hye, Yu Kyung-Ho, Lim Jae-Sung, Lee Sang-Hwa
Department of Neurology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea.
Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Front Aging Neurosci. 2024 Jun 21;16:1399457. doi: 10.3389/fnagi.2024.1399457. eCollection 2024.
Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke.
Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke.
Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only.
This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.
尽管白质高信号（WMH）与小血管闭塞（SVO）性卒中具有相似的血管风险和病理特征，但很少有研究评估WMH体积负担对SVO性卒中早期和延迟性卒中结局的影响。
利用多中心注册数据库，我们纳入了2013年8月至2022年11月期间的SVO性卒中患者。WMH体积通过使用深度学习的自动化方法（VUNO Med-DeepBrain，韩国首尔）进行估计，这是一种商业可用的分割模型。在倾向得分匹配（PSM）后，我们评估了WMH体积对SVO性卒中后早期神经功能恶化（END）和3个月改良Rankin量表（mRS）评分定义为mRS评分>2的不良功能结局的影响。
在1718例SVO性卒中病例中，重度WMH（Fazekas评分≥3）患者的患病率为68.9%。PSM后，重度WMH组的END和3个月mRS评分>2的不良功能结局更高（END：6.9%对13.5%，<0.001；3个月mRS>2：11.4%对24.7%，<0.001）。使用PSM队列进行的逻辑回归分析表明，总WMH体积增加了END的风险[比值比（OR），95%置信区间（CI）；1.01，1.00-1.02，P=0.048]和3个月mRS>2的风险（OR，95%CI；1.02，1.01-1.03，P<0.001）。深部WMH与END和3个月mRS>2均相关，但脑室周围WMH仅与3个月mRS>2相关。
本研究使用深度学习分割模型的自动化方法评估WMH负担对SVO性卒中结局的影响。我们的研究结果强调了WMH负担在SVO性卒中预后中的重要性，鼓励采取针对性干预措施以改善患者护理。
