Purpose Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. Methods Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. Results There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. Conclusion PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

OBJECTIVEAneurysm wall enhancement (AWE) on 3D vessel wall MRI (VWMRI) has been suggested as an imaging biomarker for intracranial aneurysms (IAs) at higher risk of rupture. While computational fluid dynamics (CFD) studies have been used to investigate the association between hemodynamic forces and rupture status of IAs, the role of hemodynamic forces in unruptured IAs with AWE is poorly understood. The authors investigated the role and implications of abnormal hemodynamics related to aneurysm pathophysiology in patients with AWE in unruptured IAs.METHODSTwenty-five patients who had undergone digital subtraction angiography (DSA) and VWMRI studies from September 2016 to September 2017 were included, resulting in 22 patients with 25 IAs, 9 with and 16 without AWE. High-resolution CFD models of hemodynamics were created from DSA images. Univariate and multivariate analyses were performed to investigate the association between AWE and conventional morphological and hemodynamic parameters. Normalized MRI signal intensity was quantified and quantitatively associated with wall shear stresses (WSSs) for the entire aneurysm sac, and in regions of low, intermediate, and high WSS.RESULTSThe AWE group had lower WSS (p < 0.01) and sac-averaged velocity (p < 0.01) and larger aneurysm size (p < 0.001) and size ratio (p = 0.0251) than the non-AWE group. From multivariate analysis of both hemodynamic and morphological factors, only low WSS was found to be independently associated with AWE. Sac-averaged normalized MRI signal intensity correlated with WSS and was significantly different in regions of low WSS compared to regions of intermediate (p = 0.018) and high (p < 0.001) WSS.CONCLUSIONSThe presence of AWE was associated with morphological and hemodynamic factors related to rupture risk. Low WSS was found to be an independent predictor of AWE. Our findings support the hypothesis that low WSS in IAs with AWE may indicate a growth and remodeling process that may predispose such aneurysms to rupture; however, a causality between the two cannot be established.

BACKGROUND AND PURPOSE: MR imaging and PET/CT are integrated in the work-up of head and neck cancer patients. The hybrid imaging technology 18 F-FDG-PET/MR imaging combining morphological and functional information might be attractive in this patient

•F18-FDG PET/MRI shows similar performance to F18-FDG PET/CT in lung cancer N staging. •PET/MRI has substantial interobserver agreement in N staging. •A three-segment model attenuation correction is reliable for assessing the mediastinum.

• Features determinable in the course of admission of a patient with aneurysmal subarachnoid haemorrhage (aSAH) can predict the functional outcome 6 months after the occurrence of aSAH. • The top five predictive features were the modified Fisher grade, age, the mean transit time (MTT) range from computed tomography perfusion (CTP), the WFNS grade and the early necessity for an external ventricular drainage (EVD). • The range between the minimum and the maximum MTT may prove to be a valuable biomarker for detrimental functional outcome.

BACKGROUND AND PURPOSE: Impairment of tissue oxygenation caused by inhomogeneous microscopic blood flow distribution, the so-called capillary transit time heterogeneity, is thought to contribute to delayed cerebral ischemia after aneurysmal SAH but has so far not been systematically evaluated in patients. We hypothesized that heterogeneity of the MTT, derived from CTP parameters, would give insight into the clinical course of patients with aneurysmal SAH and may identify patients at risk of poor outcome. MATERIALS AND METHODS:We retrospectively analyzed the heterogeneity of the MTT using the coefficient of variation in CTP scans from 132 patients. A multivariable logistic regression model was used to model the dichotomized mRS outcome. Linear regression was used to eliminate variables with high linear dependence. T tests were used to compare the means of 2 groups. Furthermore, the time of the maximum coefficient of variation for MTT after bleeding was evaluated for correlation with the mRS after 6 months. RESULTS:On average, each patient underwent 5.3 CTP scans during his or her stay. Patients with high coefficient of variation for MTT presented more often with higher modified Fisher (P ¼ .011) and World Federation of Neurosurgical Societies grades (P ¼ .014). A high coefficient of variation for MTT at days 3-21 after aneurysmal SAH correlated significantly with a worse mRS score after 6 months (P ¼ .016). We found no correlation between the time of the maximum coefficient of variation for MTT after bleeding and the patients' outcomes after 6 months (P ¼ .203).CONCLUSIONS: Heterogeneity of MTT in CTP after aneurysmal SAH correlates with the patients' outcomes. Because the findings are in line with the pathophysiologic concept of the capillary transit time heterogeneity, future studies should seek to verify the coefficient of variation for MTT as a potential imaging biomarker for outcome. ABBREVIATIONS: aSAH ¼ aneurysmal SAH; CTH ¼ capillary transit time heterogeneity; cvMTT ¼ coefficient of variation for MTT; cvMTT-peak ¼ maximum cvMTT after bleeding; DCI ¼ delayed cerebral ischemia; EVD ¼ external ventricular drainage; ICP ¼ intracranial pressure; RTH ¼ relative transit time heterogeneity; Tmax ¼ time-to-maximum; WFNS ¼ World Federation of Neurosurgical Societies

• Hyoscine butylbromide (HBB) improved image quality in over 2/3 of patients. • Severe artefacts were reduced after HBB in more than 20%. • The number of non-diagnostic MRI was reduced to <1% after HBB. • HBB effect was independent of bodyweight and prostate volume. • No side effects of HBB were reported in this study population.

Objective: Evaluation of a data-driven, model-based classification approach to discriminate idiopathic Parkinson’s disease (PD) patients from healthy controls (HC) based on between-network connectivity in whole-brain resting-state functional MRI (rs-fMRI). Methods: Whole-brain rs-fMRI (EPI, TR = 2.2 s, TE = 30 ms, flip angle = 90°. resolution = 3.1 × 3.1 × 3.1 mm, acquisition time ≈ 11 min) was assessed in 42 PD patients (medical OFF) and 47 HC matched for age and gender. Between-network connectivity based on full and L2-regularized partial correlation measures were computed for each subject based on canonical functional network architectures of two cohorts at different levels of granularity (Human Connectome Project: 15/25/50/100/200 networks; 1000BRAINS: 15/25/50/70 networks). A Boosted Logistic Regression model was trained on the correlation matrices using a nested cross-validation (CV) with 10 outer and 10 inner folds for an unbiased performance estimate, treating the canonical functional network architecture and the type of correlation as hyperparameters. The number of boosting iterations was fixed at 100. The model with the highest mean accuracy over the inner folds was trained using an non-nested 10-fold 20-repeats CV over the whole dataset to determine feature importance. Results: Over the outer folds the mean accuracy was found to be 76.2% (median 77.8%, SD 18.2, IQR 69.4 – 87.1%). Mean sensitivity was 81% (median 80%, SD 21.1, IQR 75 – 100%) and mean specificity was 72.7% (median 75%, SD 20.4, IQR 66.7 – 80%). The 1000BRAINS 50-network-parcellation, using full correlations, performed best over the inner folds. The top features predominantly included sensorimotor as well as sensory networks. Conclusion: A rs-fMRI whole-brain-connectivity, data-driven, model-based approach to discriminate PD patients from healthy controls shows a very good accuracy and a high sensitivity. Given the high sensitivity of the approach, it may be of use in a screening setting. Advances in knowledge: Resting-state functional MRI could prove to be a valuable, non-invasive neuroimaging biomarker for neurodegenerative diseases. The current model-based, data-driven approach on whole-brain between-network connectivity to discriminate Parkinson’s disease patients from healthy controls shows promising results with a very good accuracy and a very high sensitivity.