PDF(Pubmed)
Abstract：
The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer\'s disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans\' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans\' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans\' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < -0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.
摘要：
这项研究的目的是采用基于人工智能（AI）的磁共振成像（MRI）脑容积来区分特发性正常压力脑积水（iNPH）。阿尔茨海默病（AD），和年龄和性别匹配的健康对照（CG）通过评估皮质，皮质下,和心室容积。此外,检查了测得的脑和心室体积与iNPH的两个已建立的半定量放射学标志物之间的相关性。对123名年龄和性别匹配的受试者进行了IRB批准的回顾性分析（41iNPH，公元41年，和41个控件)，所有iNPH患者在脑室-腹腔分流术植入前接受常规临床脑MRI检查。基于AI的自动确定不同的皮质和皮质下脑和心室容积，以mL为单位，以及根据嵌入式数据库计算基于人口的归一化百分位数，执行；CE认证的软件mdbrainv4.4.1或更高版本与标准化的T1加权3D磁化准备的快速梯度回波（MPRAGE）序列一起使用。分析测得的脑容量和百分位数的组间差异，并与Evans指数和call体角的半定量测量相关：与AD患者和对照组相比，iNPH患者表现出心室扩大以及灰质和白质的变化，在总心室容积（+67%）和外侧心室容积（+68%）中观察到最显著的差异，第三（+38%），与对照组相比，第四（+31%）心室。与AD和CG相比，整体脑室肥大和白质明显减少，同时保留灰质是iNPH的特征，而全球和正面突出的灰质减少是AD的特征。三组之间的Evans指数和call体角度存在显着差异，并且与iNPH患者的侧脑室容积呈中度相关[Evans指数（r>0.83，p≤0.001），胼胝体角（r<-0.74，p≤0.001）]。iNPH患者的基于AI的MRI容积分析显示整体心室扩大和局灶性脑萎缩，which,与健康对照组和AD患者相比，主要涉及幕上白质，并在时间和中脑中被标记，同时在很大程度上保留了灰质。将AI容量与传统的放射学措施相结合可以增强iNPH的识别和分化，有可能改善患者管理和治疗反应评估。
