Lim Changmok, Lee Hunwoo, Moon Yeonsil, Han Seol-Heui, Kim Hee Jin, Chung Hyun Woo, Moon Won-Jin
Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea.
Department of Neurology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea.
J Magn Reson Imaging. 2025 May;61(5):2260-2270. doi: 10.1002/jmri.29631. Epub 2024 Oct 19.
The impact of blood-brain barrier (BBB) leakage on white matter hyperintensity (WMH) subtypes (location) and its association with clinical factors and cognition remains unclear.
To investigate the relationship between WMH volume, permeability, clinical factors, and cognition in older individuals across the cognitive spectrum.
Prospective, cross-sectional.
A total of 193 older adults with/without cognitive impairment; 128 females; mean age 70.1 years (standard deviation 6.8).
FIELD STRENGTH/SEQUENCE: 3 T, GE Dynamic contrast-enhanced, three-dimensional (3D) Magnetization-prepared rapid gradient-echo (MPRAGE T1WI), 3D fluid-attenuated inversion recovery (FLAIR).
Periventricular WMH (PWMH), deep WMH (DWMH), and normal-appearing white matter (NAWM) were segmented using FMRIB automatic segmentation tool algorithms on 3D FLAIR. Hippocampal volume and cortex volume were segmented on 3D T1WI. BBB permeability (Ktrans) and blood plasma volume (Vp) were determined using the Patlak model. Vascular risk factors and cognition were assessed.
Univariate and multivariate analyses were performed to identify factors associated with WMH permeability. Logistic regression analysis assessed the association between WMH imaging features and cognition, adjusting for age, sex, apolipoprotein E4 status, education, and brain volumes. A P-value <0.05 was considered significant.
PWMH exhibited higher Ktrans (0.598 ± 0.509 × 10 minute) compared to DWMH (0.496 ± 0.478 × 10 minute) and NAWM (0.476 ± 0.398 × 10 minute). Smaller PWMH volume and cardiovascular disease (CVD) history were significantly associated with higher Ktrans in PWMH. In DWMH, higher Ktrans were associated with CVD history and cortical volume. In NAWM, it was linked to CVD history and dyslipidemia. Larger PWMH volume (odds ratio [OR] 1.106, confidence interval [CI]: 1.021-1.197) and smaller hippocampal volume (OR 0.069; CI: 0.019-0.253) were independently linked to worse global cognition after covariate adjustment.
Elevated BBB leakage in PWMH was associated with lower PWMH volume and prior CVD history. Notably, PWMH volume, rather than permeability, was correlated with cognitive decline, suggesting that BBB leakage in WMH may be a consequence of CVD rather than indicate disease progression.
2 TECHNICAL EFFICACY: Stage 3.
血脑屏障(BBB)渗漏对脑白质高信号(WMH)亚型(位置)的影响及其与临床因素和认知的关联尚不清楚。
研究认知谱范围内老年人的WMH体积、通透性、临床因素和认知之间的关系。
前瞻性横断面研究。
共193名有/无认知障碍的老年人;128名女性;平均年龄70.1岁(标准差6.8)。
场强/序列:3T,GE动态对比增强,三维(3D)磁化准备快速梯度回波(MPRAGE T1WI),3D液体衰减反转恢复(FLAIR)。
使用FMRIB自动分割工具算法在3D FLAIR上对脑室周围WMH(PWMH)、深部WMH(DWMH)和正常表现白质(NAWM)进行分割。在3D T1WI上对海马体积和皮质体积进行分割。使用Patlak模型确定BBB通透性(Ktrans)和血浆容积(Vp)。评估血管危险因素和认知情况。
进行单变量和多变量分析以确定与WMH通透性相关的因素。逻辑回归分析评估WMH成像特征与认知之间的关联,并对年龄、性别、载脂蛋白E4状态、教育程度和脑体积进行校正。P值<0.05被认为具有统计学意义。
与DWMH(0.496±0.478×10分钟)和NAWM(0.476±0.398×10分钟)相比,PWMH的Ktrans更高(0.598±0.509×10分钟)。较小的PWMH体积和心血管疾病(CVD)病史与PWMH中较高的Ktrans显著相关。在DWMH中,较高的Ktrans与CVD病史和皮质体积相关。在NAWM中,它与CVD病史和血脂异常有关。校正协变量后,较大的PWMH体积(优势比[OR]1.106,置信区间[CI]:1.021-1.197)和较小的海马体积(OR 0.069;CI:0.019-0.253)与较差的整体认知独立相关。
PWMH中BBB渗漏增加与较小的PWMH体积和既往CVD病史相关。值得注意的是,PWMH体积而非通透性与认知衰退相关,这表明WMH中的BBB渗漏可能是CVD的结果而非疾病进展的指标。
2 技术效能:3级