BackgroundThe differentiation between benign and malignant parotid lesions is crucial to defining the treatment plan, which highly depends on the tumor histology. We aimed to evaluate the role of MRI-based radiomics using both T2-weighted (T2-w) images and Apparent Diffusion Coefficient (ADC) maps in the differentiation of parotid lesions, in order to develop predictive models with an external validation cohort.Materials and MethodsA sample of 69 untreated parotid lesions was evaluated retrospectively, including 37 benign (of which 13 were Warthin’s tumors) and 32 malignant tumors. The patient population was divided into three groups: benign lesions (24 cases), Warthin’s lesions (13 cases), and malignant lesions (32 cases), which were compared in pairs. First- and second-order features were derived for each lesion. Margins and contrast enhancement patterns (CE) were qualitatively assessed. The model with the final feature set was achieved using the support vector machine binary classification algorithm.ResultsModels for discriminating between Warthin’s and malignant tumors, benign and Warthin’s tumors and benign and malignant tumors had an accuracy of 86.7%, 91.9% and 80.4%, respectively. After the feature selection process, four parameters for each model were used, including histogram-based features from ADC and T2-w images, shape-based features and types of margins and/or CE. Comparable accuracies were obtained after validation with the external cohort.ConclusionsRadiomic analysis of ADC, T2-w images, and qualitative scores evaluating margins and CE allowed us to obtain good to excellent diagnostic accuracies in differentiating parotid lesions, which were confirmed with an external validation cohort.

To determine the utility of 18 F-DOPA PET/MRI versus cross-sectional MRI alone in glioma response assessment and identify whether the two techniques demonstrate different tumour features. Methods 18 F-DOPA PET/MRI studies from 40 patients were analysed. Quantitative PET parameters and conventional MRI features were recorded. Tumour volume was assessed on both PET and MRI. Using DSC-PWI, maps of CBF and CBV were Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporationobtained. Within VOIs of tumour features and normal-appearing white matter (NAWM) drawn on MRI, SUV max , CBF and CBV were recorded. Presence of residual active tumour was assessed by qualitative visual assessment. ROC analysis was performed univariately and on parameter combination to analyse ability to determine presence/absence of disease. Reference standard for presence of viable tissue was biopsy or clinical follow-up. ResultsMedian SUV max was 3.4 for low-grade glioma (LGG) and 3.3 for high-grade glioma (HGG). There was a significant correlation between PWI parameters and WHO grade (p<0.001), but no correlation with SUV max . Median 18 F-DOPA volume was 8216.88 mm 3 for HGG and 6284.94 mm 3 for LGG; MRI volume was 6316.57 mm 3 and 5931.55 mm 3 respectively. SUV max analysis distinguished enhancing and non-enhancing components from necrosis and NAWM and demonstrated active disease in non-enhancing regions. Visually, the modalities were concordant in 37 patients. Combining the multiparametric PET/MRI approach with all available data enhanced detection of the presence of tumour (AUC 0.99, p<0.01). ConclusionMRI and 18 F-DOPA are complementary modalities for assessment of tumour burden. Matching 18 F-DOPA and MRI in assessing residual tumour volume may better delineate the radiotherapy target volume.

No abstract

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 , T 16À25s max,v and T 9:5À25s max,v. 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 AE 11 years, range 45-99 years) were included. T 16À25s max,v , T 9:5À25s max,v , 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.

Bifid sternum is a rare fusion anomaly of the chest wall that accounts for 0.15% of all chest deformities and may be associated with cardiac or vascular anomalies. It is usually diagnosed and surgically corrected at birth or within the first month of life. Being a diagnosis made during the neonatal period, computed tomography scan and magnetic resonance imaging are not often performed; not so many cases in literature have been studied with II level diagnostic imaging, such as computed tomography or magnetic resonance.We describe a case of bifid sternum, rarely diagnosed in adults, discovered in a 21-year-old woman who came to our Diagnostic Imaging Department to perform a chest magnetic resonance after a chest X-ray.