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

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

TLDR

  • The study used DWI and structural MRI features to differentiate HGG from SBM, with the combined use of skewness of frac and clear tumor margin achieving optimal diagnostic performance.
  • The study suggests that these features can be used to effectively differentiate HGG from SBM and potentially guide surgical planning and treatment decisions.

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.

Overview

  • The 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).
  • The study included 57 patients (31 HGG, 26 SBM) who underwent pre-surgical multi-b DWI and structural MRI (T1W, T2W, T1W+C).
  • The primary objective was to identify a robust method for differentiation between HGG and SBM using DWI and structural features.

Comparative Analysis & Findings

  • Results showed that HGG patients had higher skewness of D and frac, higher kurtosis of D and frac, and lower entropy of D and frac within the enhanced tumor area (ETA).
  • HGG also exhibited lower mean frac in both ETA and peritumoral edema area (PTEA) compared to SBM patients.
  • Combining skewness of frac in ETA with clear tumor margin enhanced diagnostic performance, achieving an optimal AUC of 0.79.

Implications and Future Directions

  • The study suggests that histogram analysis of diffusion and perfusion characteristics in ETA and structural features can effectively differentiate HGG from SBM.
  • Future studies can investigate the use of machine learning algorithms to combine these features and improve diagnostic accuracy.
  • The study highlights the potential for using DWI and structural MRI to guide surgical planning and treatment decisions for brain tumors.
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