Objectives: To detect Rat sarcoma (RAS) mutation in colorectal liver metastasis by Diffusion-Weighted Magnetic Resonance Imaging (DWI-MRI) - and Diffusion Kurtosis imaging (DKI)-derived parameters. Methods: 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. Results: 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). Conclusions: 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.

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Congenital atlas abnormalities are rare and often asymptomatic findings, accidentally detected in trauma and, more rarely, in nontrauma patients. Rachischisis in both anterior and posterior atlas arches, condition defined as ‘‘split atlas,” is extremely uncommon and it may well be confused with fracture. Being able to discriminate between these 2 conditions is an essential step in patient care management. In this article, we report 2 cases of split atlas ascertained in both trauma and nontrauma patients. The first concerning a 54-year-old man fell from a 2 m scaffold, and the second related to a 25-year-old woman suffering from treatment-resistant headaches. Subsequently we proceed to analyse the embryology of these abnormalities, and later to discuss pitfalls, tips and tricks useful to a correct diagnosis, in order to achieve an accurate management of split atlas. Specifically, we outline the crucial radiological features to identify, that are beneficial to an efficient differential diagnosis between congenital atlas abnormalities and fracture. These include smooth corticated margins of the cleft, and <3 mm lateral displacement of C1 lateral masses.

cells exhibited abnormal orientation and poor or totally absent arborization. Conclusions: Overall, we have introduced the novel animal model of neurobiological substrate of chemobrain induced by the application of selected chemotherapeutic regimens. This model can be useful to study neuroprotective and precognitive drugs. Acknowledgements: The work was supported from projects number ERDF PharmaBrain CZ.02.1.01/0.0/0.0/16_025/0007444, AZV 16-29857A and NPUI LO1611.