Diffusion-Weighted MRI and Diffusion Kurtosis Imaging to Detect RAS Mutation in Colorectal Liver Metastasis.

Vincenza Granata,Antonio Avallone,Roberta Fusco,Luca Brunese,Alfonso De Stefano,Antonella Petrillo,Chiara Risi,Francesco Izzo,Robert Grimm,Alessandro Ottaiano,Roberta Grassi

doi:10.3390/cancers12092420

Abstract

To detect RAS mutation in colorectal liver metastasis by Diffusion-Weighted Magnetic Resonance Imaging (DWI-MRI) - and Diffusion Kurtosis imaging (DKI)-derived parameters. In total, 106 liver metastasis (60 metastases with RAS mutation) in 52 patients were included in this retrospective study. Diffusion and perfusion parameters were derived by DWI (apparent diffusion coefficient (ADC), basal signal (S0), pseudo-diffusion coefficient (DP), perfusion fraction (FP) and tissue diffusivity (DT)) and DKI data (mean of diffusion coefficient (MD) and mean of diffusional Kurtosis (MK)). Wilcoxon-Mann-Whitney U tests for non-parametric variables and receiver operating characteristic (ROC) analyses were calculated with area under ROC curve (AUC). Moreover, pattern recognition approaches (linear classifier, support vector machine, k-nearest neighbours, decision tree), with features selection methods and a leave-one-out cross validation approach, were considered. A significant discrimination between the group with RAS mutation and the group without RAS mutation was obtained by the standard deviation value of MK (MK STD), by the mean value of MD, and by that of FP. The best results were reached by MK STD with an AUC of 0.80 (sensitivity of 72%, specificity of 85%, accuracy of 79%) using a cut-off of 203.90 × 10-3, and by the mean value of MD with AUC of 0.80 (sensitivity of 84%, specificity of 73%, accuracy of 77%) using a cut-off of 1694.30 mm2/s × 10-6. Considering all extracted features or the predictors obtained by the features selection method (the mean value of S0, the standard deviation value of MK, FP and of DT), the tested pattern recognition approaches did not determine an increase in diagnostic accuracy to detect RAS mutation (AUC of 0.73 and 0.69, respectively). Diffusion-Weighted imaging and Diffusion Kurtosis imaging could be used to detect the RAS mutation in liver metastasis. The standard deviation value of MK and the mean value of MD were the more accurate parameters in the RAS mutation detection, with an AUC of 0.80.

Highlights

Imaging derived parameters, when linked to other clinical data and correlated with outcome, can produce robust and accurate clinical decision support systems [1,2,3]
The best results were reached by mean of Diffusional Kurtosis (MK) standard deviation value (STD) with an area under ROC curve (AUC) of 0.80
The diagnostic diagnostic performance for apparent diffusion coefficient (ADC) and for the extracted Diffusion-Weighted imaging (DWI) (IVIM) and Diffusion Kurtosis imaging (DKI) features in detecting RAS mutation using monovariate and multivariate analysis was evaluated

Summary

Introduction

Imaging derived parameters, when linked to other clinical data and correlated with outcome, can produce robust and accurate clinical decision support systems [1,2,3]. The various microRNA signatures expressions have been shown to correlate with treatment response, metastatic spread and prognosis [4,5,6]. Combined imaging-derived parameters and genomic signatures (“radio-genomic”) may be able to greatly enhance patient selection for different cancer therapy, predicting treatment response, addressing potential resistance to therapy, distinguishing favourable subsets of patients from those with poor prognosis and evaluating which patients may benefit from adjuvant therapy [3,7]. RAS and BRAF mutation and microsatellite instability status are considered significant biomarkers influencing medical oncologists’ decisions for systemic treatments

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