Background

MRI assessment in multiple sclerosis (MS) focuses on the presence of typical white matter (WM) lesions. Neurodegeneration characterised by brain atrophy is recognised in the research field as an important prognostic factor. It is not routinely reported clinically, in part due to difficulty in achieving reproducible measurements. Automated MRI quantification of WM lesions and brain volume could provide important clinical monitoring data. In general, lesion quantification relies on both T1 and FLAIR input images, while tissue volumetry relies on T1. However, T1-weighted scans are not routinely included in the clinical MS protocol, limiting the utility of automated quantification.

Objectives

We address an aspect of this important translational challenge by assessing the performance of FLAIR-only lesion and brain segmentation, against a conventional approach requiring multi-contrast acquisition. We explore whether FLAIR-only grey matter (GM) segmentation yields more variability in performance compared with two-channel segmentation; whether this is related to field strength; and whether the results meet a level of clinical acceptability demonstrated by the ability to reproduce established biological associations.

Methods

We used a multicentre dataset of subjects with a CIS suggestive of MS scanned at 1.5T and 3T in the same week. WM lesions were manually segmented by two raters, ‘manual 1′ guided by consensus reading of CIS-specific lesions and ‘manual 2′ by any WM hyperintensity. An existing brain segmentation method was adapted for FLAIR-only input. Automated segmentation of WM hyperintensity and brain volumes were performed with conventional (T1/T1 + FLAIR) and FLAIR-only methods.

Results

WM lesion volumes were comparable at 1.5T between ‘manual 2′ and FLAIR-only methods and at 3T between ‘manual 2′, T1 + FLAIR and FLAIR-only methods. For cortical GM volume, linear regression measures between conventional and FLAIR-only segmentation were high (1.5T: α = 1.029, R² = 0.997, standard error (SE) = 0.007; 3T: α = 1.019, R² = 0.998, SE = 0.006). Age-associated change in cortical GM volume was a significant covariate in both T1 (p = 0.001) and FLAIR-only (p = 0.005) methods, confirming the expected relationship between age and GM volume for FLAIR-only segmentations.

Conclusions

FLAIR-only automated segmentation of WM lesions and brain volumes were consistent with results obtained through conventional methods and had the ability to demonstrate biological effects in our study population. Imaging protocol harmonisation and validation with other MS phenotypes could facilitate the integration of automated WM lesion volume and brain atrophy analysis as clinical tools in radiological MS reporting.

中文翻译：

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仅 FLAIR 对提示多发性硬化的临床孤立综合征 (CIS) 中脑损伤和萎缩的联合体积分析

背景

多发性硬化症 (MS) 的 MRI 评估侧重于典型白质 (WM) 病变的存在。以脑萎缩为特征的神经变性在研究领域被认为是重要的预后因素。临床上没有常规报告，部分原因是难以实现可重复的测量。WM 病变和脑容量的自动 MRI 量化可以提供重要的临床监测数据。一般来说，病变量化依赖于 T1 和 FLAIR 输入图像，而组织体积测量依赖于 T1。然而，T1 加权扫描通常不包括在临床 MS 协议中，这限制了自动量化的实用性。

目标

我们通过评估 FLAIR-only 病变和大脑分割的性能，与需要多对比度采集的传统方法相比，解决了这一重要转化挑战的一个方面。我们探讨了与双通道分割相比，仅 FLAIR 灰质 (GM) 分割是否会产生更大的性能可变性；这是否与场强有关；以及结果是否符合重现已建立的生物学关联的能力所证明的临床可接受性水平。

方法

我们使用了一个多中心的受试者数据集，其 CIS 提示 MS 在同一周以 1.5T 和 3T 扫描。WM 病变由两名评估者手动分割，“手动 1”由 CIS 特异性病变的共识读数引导，“手动 2”由任何 WM 高信号引导。现有的大脑分割方法适用于仅 FLAIR 输入。使用常规（T1/T1 + FLAIR）和仅 FLAIR 方法对 WM 高信号和脑容量进行自动分割。

结果

WM 病变体积在 1.5T 时在“手动 2”和仅 FLAIR 方法之间相当，在 3T 时在“手动 2”、T1 + FLAIR 和仅 FLAIR 方法之间相当。对于皮质 GM 体积，常规分割和仅 FLAIR 分割之间的线性回归测量值很高（1.5T：α = 1.029，R ²  = 0.997，标准误差 (SE) = 0.007；3T：α = 1.019，R ²  = 0.998，SE = 0.006)。在 T1（p = 0.001）和仅 FLAIR（p = 0.005）方法中，与年龄相关的皮质 GM 体积变化是一个显着的协变量，证实了仅 FLAIR 分割的年龄和 GM 体积之间的预期关系。

结论

WM 病变和脑容量的仅 FLAIR 自动分割与通过传统方法获得的结果一致，并且能够在我们的研究人群中证明生物学效应。成像协议与其他 MS 表型的协调和验证可以促进自动化 WM 病变体积和脑萎缩分析作为放射 MS 报告中的临床工具的整合。