Lee Grace Yoojin, Choi Yun Ho, Kim Dongwon, Jang Miso, Kim Hong-Kyu, Nam Hyo-Jung, Park Sungwon, Kim Mi Jung, Hwang Yoon Ho, Lee Seung Ku, Shin Chol, Kim Namkug
Department of Medical Science, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-Ro 43-Gil, Seoul, 05505, Republic of Korea.
Department of Neurology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 56 Dongsu-Ro, Bupyeong-Gu, Incheon, 21431, Republic of Korea.
J Imaging Inform Med. 2025 Jan 6. doi: 10.1007/s10278-024-01372-8.
Although the relationships between basic clinical parameters and white matter hyperintensity (WMH) have been studied, the associations between vascular factors and WMH volume in general populations remain unclear. We investigated the associations between clinical parameters including comprehensive vascular factors and WMH in two large general populations. This retrospective, cross-sectional study involved two populations: individuals who underwent general health examinations at the Asan Medical Center (AMC) and participants from a regional cohort, the Korean Genome and Epidemiology Study (KoGES). WMH volume was quantified using the deep learning model nnU-Net. The associations between vascular factors and WMH volume were analyzed using multivariate linear regression. Individuals in the AMC cohort (n = 7471) had a mean [SD] age of 58.0 [9.2] years, and the KoGES participants (n = 2511), 59.2 [6.8] years. The normalized and logit-transformed WMH volumes for the AMC and KoGES were - 8.5 [1.3] and - 7.9 [1.2], respectively. The presence of carotid plaque, brachial-ankle pulse wave velocity, Agaston score, and coronary artery stenosis were associated with WMH volume after adjustments (AMC: carotid plaque β 0.13; 95% CI, 0.06-0.20; p < 0.001, baPWV β 0.001; CI 0-0.001; p < 0.001, Agaston score β 0.0003; CI 0.0001-0.0005; p < 0.001, minimal-to-mild coronary artery stenosis β 0.20; CI 0.12-0.29; p < 0.001, moderate-to-severe coronary artery stenosis β 0.30; CI 0.15-0.44; p < 0.001, KoGES: carotid plaque β 0.15; CI 0.02-0.27; p = 0.02, baPWV β 0.0004; CI 0-0.001; p = 0.001). Vascular parameters, reflecting atherosclerotic changes in carotid and coronary arteries and arterial stiffness, were independently associated with WMH volume in the general population.
尽管已经对基本临床参数与脑白质高信号（WMH）之间的关系进行了研究，但一般人群中血管因素与WMH体积之间的关联仍不清楚。我们在两个大型一般人群中调查了包括综合血管因素在内的临床参数与WMH之间的关联。这项回顾性横断面研究涉及两个人群：在峨山医疗中心（AMC）进行一般健康检查的个体以及来自区域队列韩国基因组与流行病学研究（KoGES）的参与者。使用深度学习模型nnU-Net对WMH体积进行量化。使用多元线性回归分析血管因素与WMH体积之间的关联。AMC队列中的个体（n = 7471）的平均[标准差]年龄为58.0[9.2]岁，KoGES参与者（n = 2511）的平均年龄为59.2[6.8]岁。AMC和KoGES的标准化和对数转换后的WMH体积分别为-8.5[1.3]和-7.9[1.2]。调整后，颈动脉斑块的存在、臂踝脉搏波速度、阿加斯顿评分和冠状动脉狭窄与WMH体积相关（AMC：颈动脉斑块β0.13；95%置信区间，0.06 - 0.20；p < 0.001，臂踝脉搏波速度β0.001；置信区间0 - 0.001；p < 0.001，阿加斯顿评分β0.0003；置信区间0.0001 - 0.0005；p < 0.001，轻度至中度冠状动脉狭窄β0.20；置信区间0.12 - 0.29；p < 0.001，中度至重度冠状动脉狭窄β0.30；置信区间0.15 - 0.44；p < 0.001，KoGES：颈动脉斑块β0.15；置信区间0.02 - 0.27；p = 0.02，臂踝脉搏波速度β0.0004；置信区间0 - 0.001；p = 0.001）。反映颈动脉和冠状动脉动脉粥样硬化变化以及动脉僵硬度的血管参数与一般人群中的WMH体积独立相关。
