Long-term apparent diffusion coefficient value changes in patients undergoing radiosurgical treatment of meningiomas

Can Apparent Diffusion Coefficient (ADC) maps replace Diffusion Tensor Imaging (DTI) maps to predict the volumetric response of meningiomas to Gamma Knife Radiosurgery?

PURPOSE

Noninvasive methods are desired to predict the treatment response to Stereotactic Radiosurgery (SRS) to improve individual tumor management. In a previous study, we demonstrated that Diffusion Tensor Imaging (DTI)-derived parameter maps significantly correlate to SRS response. This study aimed to analyze and compare the predictive value of intratumoral ADC and DTI parameters in patients with meningiomas undergoing radiosurgery.

METHODS

MR images of 70 patients treated with Gamma Knife SRS for WHO grade I meningiomas were retrospectively reviewed. MR acquisition included pre- and post-treatment DWI and DTI sequences, and subtractions were calculated to assess for radiation-induced changes in the parameter values.

RESULTS

After a mean follow-up period (FUP) of 52.7 months, 69 of 70 meningiomas were controlled, with a mean volume reduction of 34.9%. Whereas fractional anisotropy (FA) values of the initial exam showed the highest correlation to tumor volume change at the last FU (CC = - 0.607), followed by the differences between first and second FU values of FA (CC = - 0.404) and the first longitudinal diffusivity (LD) value (CC = - 0.375), the correlation coefficients of all ADC values were comparably low. Nevertheless, all these correlations, except for ADC measured at the first follow-up, reached significance.

CONCLUSION

For the first time, the prognostic value of ADC maps measured in meningiomas before and at first follow-up after Gamma Knife SRS, was compared to simultaneously acquired DTI parameter maps. Quantities assessed from ADC maps present significant correlations to the volumetric meningioma response but are less effective than correlations with DTI parameters.

MRI radiomics in the prediction of the volumetric response in meningiomas after gamma knife radiosurgery

PURPOSE

This report presents the first investigation of the radiomics value in predicting the meningioma volumetric response to gamma knife radiosurgery (GKRS).

METHODS

The retrospective study included 93 meningioma patients imaged by three Tesla MRI. Tumor morphology was quantified by calculating 337 shape, first- and second-order radiomic features from MRI obtained before GKRS. Analysis was performed on original 3D MR images and after their laplacian of gaussian (LoG), logarithm and exponential filtering. The prediction performance was evaluated by Pearson correlation, linear regression and ROC analysis, with meningioma volume change per month as the outcome.

RESULTS

Sixty calculated features significantly correlated with the outcome. The feature selection based on LASSO and multivariate regression started from all available 337 radiomic and 12 non-radiomic features. It selected LoG-sigma-1-0-mm-3D_firstorder_InterquartileRange and logarithm_ngtdm_Busyness as the predictively most robust and non-redundant features. The radiomic score based on these two features produced an AUC = 0.81. Adding the non-radiomic karnofsky performance status (KPS) to the score has increased the AUC to 0.88. Low values of the radiomic score defined a homogeneous subgroup of 50 patients with consistent absence (0%) of tumor progression.

CONCLUSION

This is the first report of a strong association between MRI radiomic features and volumetric meningioma response to radiosurgery. The clinical importance of the early and reliable prediction of meningioma responsiveness to radiosurgery is based on its potential to aid individualized therapy decision making.