利用弥散加权和动态敏感性对比磁共振成像鉴别非增强性胶质母细胞瘤和血管源性水肿。

Sahar Alizada, Yasmin Aly, Hongbo Bao, Dhairya Lakhani, Vivek Yedavalli, Haris Sair, Janet Mei
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引用次数: 0

摘要

背景和目的:鉴别非增强性胶质母细胞瘤和血管源性水肿仍然是神经影像学的一个挑战。本研究评估了扩散加权和动态敏感性对比MR成像,特别是ADC和相对CBV (rCBV)在区分这些实体方面的效用。材料和方法:我们回顾性分析了2022年1月1日至2023年12月31日期间111例经可用预处理mri诊断为胶质母细胞瘤的患者,其中13例为15个实体性、非强化性胶质母细胞瘤病变,98例为强化性胶质母细胞瘤周围非强化性T2-FLAIR高强度病变。将他们的ADC和rCBV值与30个年龄和性别匹配的脑转移病变与实体性非增强胶质母细胞瘤病变进行比较。进行受试者工作特征分析以确定最佳ADC和rCBV阈值进行分类。结果:与血管源性水肿相比,实体性非增强胶质母细胞瘤的平均ADC值显著降低,平均rCBV值显著升高(分别为1.08 [SD, 0.22] × 10-3和1.74 [SD, 0.17] × 10-3 mm2/s和2.4 [SD, 0.86]和0.30 [SD, 0.13], P < 0.001)。区分实体性非强化胶质母细胞瘤和血管源性水肿的最佳ADC和rCBV截止值分别为1.36 × 10-3 mm2/s和1.04,具有优异的灵敏度(0.93-1)和特异性(1)。增强型胶质母细胞瘤周围非增强型T2-FLAIR高信号的ADC值与血管源性水肿相似(1.67 [SD, 0.33] × 10-3 vs 1.74 [SD, 0.17] × 10-3 mm2/s; P = 0.32),但rCBV显著高于前者(0.60 [SD, 0.61] vs 0.30 [SD, 0.13]; P = 0.03)。rCBV截断值为0.42,区分病灶周围肿瘤浸润和纯粹血管源性水肿的特异性为86%。结论:弥散和灌注加权MR成像,特别是ADC和rCBV测量,为区分非增强胶质母细胞瘤和血管源性水肿提供了有价值的生物标志物。确定的阈值可以增强胶质母细胞瘤的特征,改善术前与转移瘤的区分,并支持更精确的、图像引导的临床管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Differentiation between Nonenhancing Tumor in Glioblastoma and Vasogenic Edema using Diffusion-Weighted and Dynamic Susceptibility Contrast MR Imaging.

Background and purpose: Differentiating nonenhancing glioblastoma from vasogenic edema remains a challenge in neuroimaging. This study evaluates the utility of diffusion-weighted and dynamic susceptibility contrast MR imaging, particularly ADC and relative CBV (rCBV), in distinguishing these entities.

Materials and methods: We retrospectively analyzed 111 patients diagnosed with glioblastoma with available pretreatment MRIs from January 1, 2022, to December 31, 2023, including 13 patients with 15 solid, nonenhancing glioblastoma lesions and 98 patients with perilesional nonenhancing T2-FLAIR hyperintensity surrounding enhancing glioblastomas. Their ADC and rCBV values were compared with those of 30 brain metastatic lesions age- and sex-matched to solid, nonenhancing glioblastoma lesions. Receiver operating characteristic analysis was performed to determine optimal ADC and rCBV thresholds for classification.

Results: Solid, nonenhancing glioblastomas had significantly lower mean ADC values and higher mean rCBV values compared with vasogenic edema (1.08 [SD, 0.22] × 10-3 versus 1.74 [SD, 0.17] × 10-3 mm2/s and 2.4 [SD, 0.86] versus 0.30 [SD, 0.13], respectively; P < .001). The optimal ADC and rCBV cutoffs for differentiating solid, nonenhancing glioblastoma from vasogenic edema were 1.36 × 10-3 mm2/s and 1.04, achieving excellent sensitivity (0.93-1) and specificity (1). Perilesional nonenhancing T2-FLAIR hyperintensity around enhancing glioblastomas had ADC values similar to those of vasogenic edema (1.67 [SD, 0.33] × 10-3 versus 1.74 [SD, 0.17] × 10-3 mm2/s; P = .32) but significantly higher rCBV (0.60 [SD, 0.61] versus 0.30 [SD, 0.13]; P = .03). An rCBV cutoff value of 0.42 distinguished perilesional tumor infiltration from pure vasogenic edema with 86% specificity.

Conclusions: Diffusion- and perfusion-weighted MR imaging, particularly ADC and rCBV measurements, provide valuable biomarkers for differentiating nonenhancing glioblastoma from vasogenic edema. The identified threshold values may enhance glioblastoma characterization, improve preoperative differentiation from metastases, and support more precise, image-guided clinical management.

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