接收机工作特性
磁共振成像
磁共振弥散成像
脑膜瘤
有效扩散系数
医学
手术计划
核医学
软组织
放射科
一致性(知识库)
计算机科学
人工智能
内科学
作者
Yan Bai,Rui Zhang,Xianchang Zhang,Xinhui Wang,Mathias Nittka,Gregor Koerzdoerfer,Qiyong Gong,Meiyun Wang
标识
DOI:10.1016/j.acra.2021.09.008
摘要
Preoperative meningioma consistency prediction is highly beneficial for surgical planning and prognostication. We aimed to use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to preoperatively predict meningioma consistency.A total of 51 patients with meningiomas were enrolled in this study. MRF, T1-weighted imaging, T2-weighted imaging, and diffusion-weighted imaging were performed in all patients before surgery using a 3T MRI scanner. MRF-derived T1 and T2 values, T1-weightd and T2-weighted signal intensities, as well as apparent diffusion coefficient value yield from diffusion-weighted imaging were compared between the soft, moderate and hard meningiomas. Receiver operating characteristic curve analyses were used to determine the diagnostic performance of T1, T2 value, and a combination of T1 and T2 values.After Bonferroni corrections, quantitative T1 and T2 values yielded from MRF were significantly different between the soft, moderate and hard meningiomas (all p < 0.05). T2 signal intensity was significantly different between the soft and hard, soft and moderate meningiomas (both p < 0.05), whereas was not significantly different between the moderate and hard meningiomas. However, T1 signal intensity and apparent diffusion coefficient value had no significant differences between the soft, moderate and hard meningiomas (all p > 0.05). The combination of T1 and T2 values had greater areas under receiver operating characteristic curve curves compared to individual T1 or T2 value.MRF may help to preoperatively differentiate between the soft, moderate and hard meningiomas and may be useful in guiding the surgical planning.
科研通智能强力驱动
Strongly Powered by AbleSci AI