Differentiation of glioma and solitary brain metastasis: a multi-parameter magnetic resonance imaging study using histogram analysis

Abstract

Background: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn't been fully investigated for the differentiation and may have the potential to improve it.

Methods: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance.

Results: Higher ADC_kurtosis (P = 0.022), frac_kurtosis (P<0.001),and frac_skewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm)₁₀ (P = 0.045), frac₁₀ (P<0.001),frac₉₀ (P = 0.001), frac_mean (P<0.001), and frac_entropy (P<0.001) were observed for SBM. frac_kurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm)₁₀, frac₁₀, and frac_kurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac₁₀ and frac_kurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25).

Conclusions: The frac₁₀ and frac_kurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm)₁₀ helps improving the differentiation specificity.

Keywords: Amide proton transfer-weighted imaging; Glioma; Intravoxel incoherent motion; MRI; Solitary brain metastasis.

Fig. 1

Study Flowchart

Fig. 2

Representative images of patients with glioma or metastases. (Row A & Row B): a: T2W, b: T1W, c: contrast-enhanced T1W, d: MTRasym@3.5ppm, e: Dfast(×10^− 3mm²/s), f: Dslow(×10^− 3mm²/s), g: frac (%), h: ADC(×10^− 3mm²/s). Row C: 3D reconstruction of tumor ROI of glioma patient (a) and SBM patient (b). Row A: A 63-year-old woman pathologically confirmed with glioblastoma. MRI showed an irregular lesion with unclear margin in the right frontal lobe, presenting as a diffuse enhanced lesion with hyper-intensity on T2W and hypo-intensity on T1W accompanied by peritumoral edema. Histogram features of the enhanced tumor parenchyma are as follows: ADC_kurtosis:4.84. (MTRasym@3.5ppm)₁₀: 1.5, frac₁₀:7.38, frac₉₀:18.79, frac_mean:12.85, frac_entropy:3.26, frac_kurtosis:4.92, frac_skewness:0.90. Row B: A 34-year-old woman was pathologically confirmed with adenocarcinoma; a primary lesion was found in her left lung. MRI showed a regular lesion with a clear margin in the left frontal lobe, presenting as a diffuse-enhanced lesion with iso-intensity on T2W and T1W accompanied by peritumoral edema. Histogram features of the enhanced tumor parenchyma are as follows: ADC_kurtosis:2.74. (MTRasym@3.5ppm)₁₀: 1.9, frac₁₀:12.62, frac₉₀:21.94, frac_mean:17.21, frac_entropy:3.95, frac_kurtosis:3.22, frac_skewness:0.13

Fig. 3

Histogram of frac in the enhanced tumor region. The histogram showed that the glioma patient (A) has higher frac_kurtosis, and frac_skewness but lower frac_entropy, than the SBM patient (B) in the enhanced tumor parenchyma region

Fig. 4

The ROC curves for univariate (A) and multivariate regression (B)