背景:通过临床脑MRI研究的全自动分割测量的脑实质(BP)和颅内脑脊液(iCSF)体积可能有助于小儿脑积水的诊断和随访。然而,以前发表的分割技术要么依赖于专用序列,在临床实践中不常规使用,或空间归一化,当严重的大脑扭曲时,准确性有限,比如脑积水患者,是存在的。
目的:我们开发了一种完全自动化的方法来测量小儿脑积水患者的临床脑MRI研究中的BP和iCSF体积,利用临床实践中常用的T2和T1加权图像中包含的互补信息。
方法:建议的程序,在合并体积的头骨剥离之后,使用多参数方法进行,以获得可靠的内颅骨轮廓定义,通过在全尺寸动态重新缩放后将T2w-除以T1w-体积来最大化CSF与实质的对比度,从而允许通过简单的阈值化例程分离iCSF和BP。
结果:对23项研究(4例对照和19例脑积水患者)的人工追踪进行验证显示出极好的一致性(ICC>0.98)和空间重叠(Dice系数从iCSF的77.2%到颅内体积的96.8%)。准确性与手动分割的操作者内部再现性相当,在14项研究中,由同样经验丰富的神经放射学家处理了两次。将该算法应用于63名对照和57名脑积水患者(19名有实质损害)的数据集的结果,测量正常发育和脑积水患者的体积变化,也是为了示范目的而报告的。
结论:所提出的方法允许在临床研究中全自动分割BP和iCSF,在严重扭曲的大脑中,能够评估颅内组织体积的年龄和疾病相关变化,其准确性与专家手动分割相当。
BACKGROUND: Brain parenchyma (BP) and intracranial cerebrospinal fluid (iCSF) volumes measured by fully automated segmentation of clinical brain MRI studies may be useful for the diagnosis and follow-up of pediatric hydrocephalus. However, previously published segmentation techniques either rely on dedicated sequences, not routinely used in clinical practice, or on spatial normalization, which has limited accuracy when severe brain distortions, such as in hydrocephalic patients, are present.
OBJECTIVE: We developed a fully automated method to measure BP and iCSF volumes from clinical brain MRI studies of pediatric hydrocephalus patients, exploiting the complementary information contained in T2- and T1-weighted images commonly used in clinical practice.
METHODS: The proposed procedure, following skull-stripping of the combined volumes, performed using a multiparametric method to obtain a reliable definition of the inner skull profile, maximizes the CSF-to-parenchyma contrast by dividing the T2w- by the T1w- volume after full-scale dynamic rescaling, thus allowing separation of iCSF and BP through a simple thresholding routine.
RESULTS: Validation against manual tracing on 23 studies (four controls and 19 hydrocephalic patients) showed excellent concordance (ICC > 0.98) and spatial overlap (Dice coefficients ranging from 77.2% for iCSF to 96.8% for intracranial volume). Accuracy was comparable to the intra-operator reproducibility of manual segmentation, as measured in 14 studies processed twice by the same experienced neuroradiologist. Results of the application of the algorithm to a dataset of 63 controls and 57 hydrocephalic patients (19 with parenchymal damage), measuring volumes\' changes with normal development and in hydrocephalic patients, are also reported for demonstration purposes.
CONCLUSIONS: The proposed approach allows fully automated segmentation of BP and iCSF in clinical studies, also in severely distorted brains, enabling to assess age- and disease-related changes in intracranial tissue volume with an accuracy comparable to expert manual segmentation.