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双指数扩散加权成像用于鉴别高级别胶质瘤与孤立性脑转移瘤:基于感兴趣区的直方图分析

Bi-exponential diffusion-weighted imaging for differentiating high-grade gliomas from solitary brain metastases: a VOI-based histogram analysis.

作者信息

Su Yifei, Wang Junhao, Guo Jinxia, Liu Xuanchen, Yang Xiaoxiong, Cheng Rui, Wang Chunhong, Xu Cheng, He Yexin, Ji Hongming

机构信息

The Neurosurgery Department of Shanxi Provincial People's Hospital, Shanxi Medical University, Taiyuan, 030012, Shanxi, People's Republic of China.

GE Healthcare, Beijing, People's Republic of China.

出版信息

Sci Rep. 2024 Dec 30;14(1):31909. doi: 10.1038/s41598-024-83452-x.

Abstract

This study investigated the use of bi-exponential diffusion-weighted imaging (DWI) combined with structural features to differentiate high-grade glioma (HGG) from solitary brain metastasis (SBM). A total of 57 patients (31 HGG, 26 SBM) who underwent pre-surgical multi-b DWI and structural MRI (T1W, T2W, T1W + C) were included. Volumes of interest (VOI) in the peritumoral edema area (PTEA) and enhanced tumor area (ETA) were selected for analysis. Histogram features of slow diffusion coefficient (D), fast diffusion coefficient (D), and perfusion fraction (frac) were extracted. Results showed that HGG patients had higher skewness of D (P = 0.022) and frac (P = 0.077), higher kurtosis of D (P = 0.019) and frac (P = 0.025), and lower entropy of D (P = 0.005) and frac (P = 0.001) within the ETA. Additionally, HGG exhibited lower mean frac in both ETA (P = 0.007) and PTEA (P = 0.017). Combining skewness of frac in ETA with clear tumor margin enhanced diagnostic performance, achieving an optimal AUC of 0.79. These findings suggest that histogram analysis of diffusion and perfusion characteristics in ETA and structural features can effectively differentiate HGG from SBM.

摘要

本研究探讨了双指数扩散加权成像(DWI)结合结构特征在鉴别高级别胶质瘤(HGG)与孤立性脑转移瘤(SBM)中的应用。纳入了57例接受术前多b值DWI和结构MRI(T1加权像、T2加权像、T1加权像+增强)检查的患者(31例HGG,26例SBM)。选择瘤周水肿区(PTEA)和肿瘤强化区(ETA)的感兴趣区(VOI)进行分析。提取慢扩散系数(D)、快扩散系数(D*)和灌注分数(frac)的直方图特征。结果显示,HGG患者在ETA内D的偏度(P = 0.022)和frac的偏度(P = 0.077)较高,D的峰度(P = 0.019)和frac的峰度(P = 0.025)较高,D*的熵(P = 0.005)和frac的熵(P = 0.001)较低。此外,HGG在ETA(P = 0.007)和PTEA(P = 0.017)中的平均frac均较低。将ETA中frac的偏度与清晰的肿瘤边缘相结合可提高诊断性能,最佳曲线下面积(AUC)为0.79。这些发现表明,对ETA中扩散和灌注特征进行直方图分析以及结合结构特征可有效鉴别HGG与SBM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e83e/11685987/82f718a57f56/41598_2024_83452_Fig1_HTML.jpg

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