Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA.
Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
J Neuroimaging. 2022 Jan;32(1):63-67. doi: 10.1111/jon.12928. Epub 2021 Sep 10.
Ischemic diffusion-weighted imaging-fluid-attenuated inversion recovery (DWI-FLAIR) mismatch may be useful in guiding acute stroke treatment decisions given its relationship to onset time and parenchymal viability; however, it relies on subjective grading. Radiomics is an emerging image quantification methodology that may objectively represent continuous image characteristics. We propose a novel radiomics approach to characterize DWI-FLAIR mismatch.
Ischemic lesions were visually graded for FLAIR positivity (absent, subtle, obvious) among consecutive large vessel occlusion stroke patients who underwent hyperacute MRI. Radiomic features were extracted from within the lesions on DWI and FLAIR. The DWI-FLAIR mismatch radiomics signature was built with features systematically selected by a cross-validated ElasticNet linear regression model of mismatch.
We identified 103 patients with mean age 68 ± 16 years; 63% were female. FLAIR hyperintensity was absent in 25%, subtle in 55%, and obvious in 20%. Inter-rater agreement for visual grading was moderate (Κ = .58). The radiomics signature of DWI-FLAIR mismatch included native FLAIR histogram kurtosis and local binary pattern-filtered FLAIR gray-level cluster shade; both correlated with visual grading (ρ = -.42, p < .001 and ρ = .40, p < .001, respectively).
Radiomics can describe DWI-FLAIR mismatch and may provide objective, continuous biomarkers for infarct evolution using clinical-grade images. These novel biomarkers may prove useful for treatment decisions and future research.
缺血性弥散加权成像-液体衰减反转恢复(DWI-FLAIR)不匹配可能因其与发病时间和实质存活能力的关系而有助于指导急性脑卒中的治疗决策;然而,它依赖于主观分级。放射组学是一种新兴的图像量化方法,可能能够客观地表示连续的图像特征。我们提出了一种新的放射组学方法来描述 DWI-FLAIR 不匹配。
在连续的大血管闭塞性脑卒中患者中进行超急性 MRI 检查时,对 FLAIR 阳性(缺失、轻微、明显)进行视觉分级。从 DWI 和 FLAIR 上的病变内提取放射组学特征。通过交叉验证的弹性网络线性回归模型对不匹配进行系统选择,构建 DWI-FLAIR 不匹配放射组学特征。
我们共纳入 103 例患者,平均年龄 68 ± 16 岁;63%为女性。FLAIR 高信号缺失占 25%,轻微占 55%,明显占 20%。视觉分级的组内一致性为中度(Κ =.58)。DWI-FLAIR 不匹配的放射组学特征包括原始 FLAIR 直方图峰度和局部二值模式滤波的 FLAIR 灰度聚类阴影;与视觉分级均相关(ρ = -.42,p <.001 和 ρ =.40,p <.001)。
放射组学可以描述 DWI-FLAIR 不匹配,并且可以使用临床级图像为梗死演变提供客观的、连续的生物标志物。这些新的生物标志物可能对治疗决策和未来的研究有用。