Introduction

Non-invasive methods for tumour tissue characterization would facilitate prediction and early assessment of therapy response and thereby personalized treatment planning. Diffusion weighted MRI (dMRI) is a promising technique for this purpose and holds the potential to indirectly estimate microstructural parameters beyond the conventional resolution limits of MRI. Two suggested dMRI based models are the Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours (VERDICT)¹ and kurtosis (DKI) models. VERDICT aims to separate the MR signal coming from different tissue compartments and utilizes multiple diffusion gradient timings and strengths to estimate microstructural parameters such as cell size, intracellular (IC), vascular (VASC) and extracellular extravascular (EES) volume fractions. DKI estimates the presence of microstructural barriers and compartments by modelling the non-gaussian behaviour of the diffusing water molecules. DKI also provides estimates of the kurtosis-corrected apparent diffusion coefficient.

To our knowledge, studies using VERDICT and DKI for assessment of therapy response in small-intestine neuroendocrine tumours (SI-NET) have not been conducted. The aim of this study was to investigate if VERDICT and DKI analysis can be used for early and longitudinal assessment of external radiation therapy response in SI-NETs.

Subjects and methods

Balb/C nude mice (n=20) with subcutaneous SI-NET (GOT1) xenografts were irradiated externally with an absorbed dose of 8 Gy to the tumour on day 0, using a 6 MV photon beam (Varian Medical Systems). In vivo dMRI experiments were conducted on days -1, 2, 3 as well as one week (day 6 or 7) and two weeks (day 15) after the treatment using a 7T preclinical MR system (Bruker, Biospec), table 1. The kurtosis model was fitted using an in-house built MATLAB (MathWorks, Natick, USA) software to the subset of the dMRI experiments with TE=39 ms. The VERDICT model was fitted to the full set of dMRI experiments using the AMICO framework² where the EES and IC compartments were described using the BallSphere model, and the VASC compartment was described using a model which separates the blood flow from the diffusion of the blood³. To make the model fit more robust some parameters of the VERDICT model were fixed. A grid search was used to find the fixed parameter combination which yielded the lowest fitting cost function for the entire data set (dIC=1x10-9 m²/s, dEES=1.5x10-9 m²/s, dVASC=1.75x10-9 m²/s, vdVASC=0.6x10-3 m/s).

Tumour volumes were measured externally on days -4, -1, 0, 2, 3, 7, and 15 using callipers. The tumour treatment response (TTR) was calculated according to

$$TTR=-ln\left(\frac{V_{15}}{V'_{15}}\right)$$

where V₁₅ is the measured tumour volume on day 15 and V'₁₅ is the hypothetical non-treated tumour volume on day 15 assuming an exponential growth based on volume measurements prior to the treatment⁴. Linear correlations between TTR and estimated diffusion parameters were analysed using the Pearson correlation coefficient (r).

The Gothenburg Ethical Committee on Animal Research approved this study.

Results & discussion

Out of the parameters estimated by VERDICT, the IC and EES volume fractions showed the most prominent trends early after treatment where the IC volume fraction tended to decrease and the EES volume fraction tended to increase during the first week (Fig 1), possibly indicating a reduction in cell density. The same trends could also be qualitatively analysed and observed in parameter maps of the estimated parameters (Fig 3), where the heterogeneity of the tumour tissues was revealed as well.

Trends were also observed for the parameters estimated with DKI where the kurtosis-corrected diffusion coefficient (D_k) tended to increase and the kurtosis (K) tended to decrease during the first week (Fig 2), suggesting a reduction in microscopical compartments and diffusion barriers. After day 7 the progression of both VERDICT and DKI parameters showed a more scattered result.

Multiple linear correlations were found between TTR and estimated diffusion parameters early after treatment (Fig 4). A relative increase of D_k (r = 0.60) and EES volume fraction (r = 0.57) from day -1 to day 3 correlated with a higher TTR. On the contrary, a relative decrease of K (r = -0.61) and IC volume fraction (r = -0.67) from day -1 to day 3 correlated with a higher TTR. These results suggest that early signs of reduced cell density and microscopical barriers after treatment may indicate a more substantial response. Additionally, a higher cell radius on day 3 correlated with a higher TTR (r = 0.54).

Conclusion

Our results show that VERDICT and kurtosis modelling of dMRI data holds great potential for early assessment of tumour response to external radiation therapy in the GOT1 tumour model.

Acknowledgements

No acknowledgement found.