Synopsis

Keywords: Tumors, Diffusion/other diffusion imaging techniques

The natural history of meningioma remains unclear and a simple, practical method is needed to identify fast growth tumors. This study evaluated correlations between clinical parameters, tumor growth rate (TGR), tumor volume doubling time (VDT), Ki-67 and relative apparent diffusion coefficient (rADC) derived from diffusion weighted imaging (DWI). The results showed that rADC was an independent predictive parameter of meningioma growth and baseline rADC had a good predictive ability for differentiating slow growth from fast growth meningioma. This suggests that in asymptomatic meningiomas, DWI might be a valuable predictive imaging method.

Purpose

Individualized treatment strategies are needed for patients with meningiomas because the nature of meningiomas and the potential consequences of treatment vary widely among patients ⁽¹⁾. The general trend in meningioma treatment is shifting from surgery to active surveillance, but its natural history remains unclear and a simple, practical method is needed to identify fast growth tumors and for more appropriate timing of surgical intervention ⁽²⁾. It has been reported that the ADC value of meningioma is related to the cell density and proliferation index of the tumor ⁽³⁾. But to the best of our knowledge, the predictive value of DWI for meningioma growth has not been investigated. We hypothesized that DWI could be a valuable diagnostic technique for predicting the growth of meningiomas. The purpose of this study is two-fold: 1) to determine whether ADC value can predict the growth of meningiomas (non-growth or growth), and 2) whether it has predictive value for tumor growth patterns (slow growth or fast growth).

Methods

Between July 2011 and July 2019, asymptomatic adult patients diagnosed with meningioma by MRI and followed up in our hospital were consecutively included in this study. The inclusion criteria were as follows: (a) MR examination at least two-time points before surgery; (b) the first (baseline) MR examination including DWI. The exclusion criteria were the following: (a) patients who received any form of treatment targeting the meningioma; (b) insufficient image quality to meet the research requirements; (c) patients with neurofibromatosis type 2 (NF2); (d) time interval of two MRI examinations＜12 months. The MR images were obtained on a 3.0T MR scanner according to our standard institutional protocols. Conventional MRI sequences included axial T1-weighted, axial T2-weighted, axial T2 fluid-attenuated inversion recovery, axial T2-weighted gradient-recalled echo, and axial T1-weighted images after contrast administration. DWI used a spin echo (SE)-echo planar imaging (EPI) diffusion sequence in the axial plane. The DWI was performed by applying sequentially in the x, y, and z directions with the following parameters: TR/TE, 3100/91 ms; FOV, 20 cm; flip angle, 90 degrees; slice thickness/spacing, 5 mm/1.5 mm; matrix 192 × 192; voxel size, 1.2 × 1.2 × 5 mm³; b = 0 and 1000 sec/mm². ADC maps were obtained from these imaging data. Univariable and multivariable logistic regression analyses were performed to evaluate the tumor growth associated with clinical parameters (including sex, age, and follow-up time) and relative apparent diffusion coefficient (rADC). Correlations between tumor growth rate (TGR), tumor volume doubling time (VDT), Ki-67, and rADC were conducted with the Pearson correlation coefficient. The prediction ability was evaluated by receiver operating characteristic (ROC) curves. P values <0.05 were considered statistically significant.

Results

Univariable and multivariable analyses demonstrated that only rADC is an independent predictor of meningioma growth (All, p=0.001, Figure 1A). ROC curve analysis presented in Figure 1B showed that baseline rADC had good predictive power for non-growing meningioma (AUC=0.88, p=0.001), as well as slow or fast growth meningioma (AUC=0.83, p=0.03). The log-rank test for trend (p=0.003) was statistically significant, indicating that the cumulative risk of disease progression greatly increases from the high rADC to the low rADC group (Figure 2A). The overall growth status of 64 patients is shown in Figure 2B. In 20 patients with tumor growth, rADC was moderately negatively correlated (r=-0.50, p=0.02) with tumor growth rate (Figure 3A) and strongly positively correlated (r=0.63, p=0.003) with doubling time (Figure 3B), indicating that lower rADC was associated with faster tumor growth and shorter doubling time. Typical cases in different groups (non-growth, slow growth, and fast growth) are shown in Figure 4. Moreover, Ki-67 was significantly associated with rADC in 8 patients who underwent surgery (r=-0.75, p=0.03). The corresponding scatter plot is shown in Figure 5.

Discussion

Our findings suggest that meningiomas with different growth patterns differ in rADC. Meningiomas with low rADC values at baseline tend to be more likely to grow than tumors with high rADC values, while lower rADC in growing meningiomas is associated with a faster growth rate and shorter tumor doubling time. To our knowledge, this is the first time that a noninvasive DWI technique has been used to directly predict the growth of meningiomas.

Conclusion

In asymptomatic meningiomas, the lower rADC at baseline, the faster TGR, and the shorter VDT. DWI could be a valuable predictive imaging tool in asymptomatic meningiomas. Patients with rapidly progressive asymptomatic meningiomas close to fragile structures such as cranial nerves or blood vessels would benefit from early surgery.

Acknowledgements

No acknowledgement found.