Vascular lesions of the spinal cord are rare but potentially devastating conditions whose accurate recognition critically determines the clinical outcome. Several conditions lead to myelopathy due to either arterial ischemia, venous congestion or bleeding within the cord. The clinical presentation varies, according with the different aetiology and mechanism of damage. The aim is to provide a comprehensive review on the radiological features of the most common vascular myelopathies, passing through the knowledge of the vascular spinal anatomy and the clinical aspects of the different aetiologies, which is crucial to promptly address the diagnosis and the radiological assessment.

Background and purpose: Computed tomography perfusion (CTP) and multiphase CT angiography (mCTA) help selection for endovascular treatment (EVT) in anterior ischemic stroke (AIS). Our aim was to investigate the ability of perfusion maps and collateral score to predict functional outcome after EVT. Patients and methods: Patients with M1-middle cerebral artery occlusion, evaluated by mCTA and CTP and treated with EVT within six hours of onset, were enrolled. Perfusion parametric maps of cerebral blood flow (CBF), cerebral blood volume (CBV) and time to maximum of tissue residue function ( T_max) were generated; areas of altered perfusion were manually outlined to obtain volumes CBF_v, CBV_v, [ ] and [ ]. Diffusion-weighted imaging (DWI) at 24–36 hours was used to manually outline the ischemic core (volume: DWI_v). Collateral vessels were assessed on mCTA considering extent and delay of maximal enhancement (six-point scale). Functional outcome was evaluated by modified Rankin Scale score at three months. Volumes in good and poor outcome groups were compared by Wilcoxon rank-sum test t, and their discriminative ability for outcome was determined by receiver operating characteristic analysis. A logistic regression model, including T_max, CBF and collaterals, was used to differentiate good and poor outcome. Results: Seventy-one patients (mean age 75 ± 11 years, range 45–99 years) were included. [ ], [ ], CBV_v, CBF_v and DWI_v were statistically different between the two groups. CBF had the best discriminative value for good and poor outcome (area under the curve (AUC) 0.73; 64.5% sensitivity; 74.4% specificity); the logistic regression model might be promising (AUC 0.79, 64.5% sensitivity, 82.1% specificity). Conclusions: In patients with AIS, the combined use of CTP and mCTA predicts functional outcome of EVT and might allow better selection.

Peliosis hepatis (PH) is a rare benign pathological entity characterised by dilatation of the hepatic sinusoids. It has been reported to be associated with infection or malignancy, but the aetiology of PH remains unknown. Distinguishing PH from other malignancies can be difficult on imaging studies. This case report describes the incidental finding of PH in a patient undergoing a cardiac computed tomography (CT) scan at our institution.

The aim of our study is to verify the reliability of Diffusion Kurtosis Imaging (DKI) parameters through correlation with perfusion metrics obtained by Dynamic Contrast Enhanced (DCE)- and Dynamic Susceptibility Contrast (DSC)-MRI techniques in histologic-proven primary central nervous system lymphoma (PCNSL). A total of 15 lesions were analyzed in patient with neo-diagnosis of Epstein-Barr Virus negative PCNSL. DKI was acquired using 5b values from 0 to 2500 s/mm². DCE-MRI was acquired with a long scan time (up to 10 min) and with a temporal resolution of 5 s. DSC was acquired with a T2*-weighted sequence made up by 40 dynamic volumes, with a total scan time of 75 s. The correlation between the DCE- and DSC-MRI metrics and the DWI/DKI parameters was assessed with the Spearman's Rho correlation test. A p-value < 0.05 was considered statistically significant. A strong inverse relationship between D_app and K_ep (Rho = -0.56; p-value = 0.034) and between ADC and the K_ep (Rho = -0.52; p = 0.049) was found. A strong relationship emerged between K_app and relCBV (Rho = 0.62; p = 0.016). Even though a correlation has been detected between DKI and DWI parameters. DKI seem to provide additional information compared to the standard diffusion model, this can be inferred from the results obtained through this study as DKI parameters correlates with both DCE and DSC parameters while ADC only correlates with K_ep and in a statistically less significant manner.