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We aimed to assess whether brain volumes may affect the results of deep brain stimulation (DBS) in patients with Parkinson's disease (PD). Eighty-one consecutive patients with PD (male:female 40:41), treated with DBS between June 2012 and December 2017, were enrolled. Total and regional brain volumes were measured using automated brain volumetry (NeuroQuant). The Unified Parkinson Disease Rating Scale motor score quotient was used to assess changes in clinical outcome and compare the preoperative regional brain volume in patients categorized into the higher motor improvement and lower motor improvement groups based on changes in the postoperative scores. The study groups showed significant volume differences in multiple brain areas. In the higher motor improvement group, the anterior cingulate and right thalamus showed high volumes after false discovery rate (FDR) correction. In the lower motor improvement group, the left caudate, paracentral, right primary sensory and left primary motor cortex showed high volume, but no area showed high volumes after FDR correction. Our data suggest that the effectiveness of DBS in patients with PD may be affected by decreased brain volume in different areas, including the cingulate gyrus and thalamus. Preoperative volumetry could help predict outcomes in patients with PD undergoing DBS.

Objectives: To investigate whether clinical condition, imaging session, and locations affect repeatability of amide proton transfer-weighted (APTw) magnetic resonance imaging (MRI) in the brain., Materials and Methods: Three APTw MRI data sets were acquired, involving two intrasession scans and one intersession scan for 19 healthy, 15 glioma, and 12 acute stroke adult participants (mean age 53.8, 54.6, and 68.5, respectively) on a 3T MR scanner. The mean APTw signals from five locations in healthy brain (supratentorial and infratentorial locations) and from entire tumor and stroke lesions (supratentorial location) were calculated. The within-subject coefficient of variation (wCV) and intraclass correlation coefficient (ICC) were calculated for each clinical conditions, image sessions, and anatomic locations. Differences in APTw signals between sessions were analyzed using repeated-measures analysis of variance., Results: The ICC and wCV were 0.96 (95% confidence interval [CI], 0.91-0.99) and 16.1 (12.6-21.3) in glioma, 0.93 (0.82-0.98) and 15.0 (11.4-20.6) in stroke, and 0.84 (0.72-0.91) and 34.0 (28.7-41.0) in healthy brain. There were no significant differences in APTw signal between three sessions, irrespective of disease condition and location. The ICC and wCV were 0.85 (0.68-0.94) and 27.4 (21.8-35.6) in supratentorial, and 0.44 (- 0.18 to 0.76) and 32.7 (25.9 to 42.9) in infratentorial locations. There were significant differences in APTw signal between supra- (mean, 0.49%; 95% CI, 0.38-0.61) and infratentorial locations (1.09%, 0.98-1.20; p < 0.001)., Conclusion: The repeatability of APTw signal was excellent in supratentorial locations, while it was poor in infratentorial locations due to severe B0 inhomogeneity and susceptibility which affects MTR asymmetry., Key Points: • In supratentorial locations, APTw MRI showed excellent intrasession and intersession repeatability in brains of healthy controls and patients with glioma, as well as in stroke-affected regions. • APTw MRI showed excellent repeatability in supratentorial locations, but poor repeatability in infratentorial locations. • Considering poor repeatability in the infratentorial locations, the use of APTw MRI in longitudinal assessment in infratentorial locations is not indicated.

Objectives: To determine whether fast scanned MRI using a 1.5-T scanner is a reliable method for the detection and characterization of acute ischemic stroke in comparison with conventional MRI., Methods: From May 2015 to June 2016, 862 patients (FLAIR, n = 482; GRE, n = 380; MRA, n = 190) were prospectively enrolled in the study, with informed consent and under institutional review board approval. The patients underwent both fast (EPI-FLAIR, ETL-FLAIR, TR-FLAIR, EPI-GRE, parallel-GRE, fast CE-MRA) and conventional MRI (FLAIR, GRE, time-of-flight MRA, fast CE-MRA). Two neuroradiologists independently assessed agreements in acute and chronic ischemic hyperintensity, hyperintense vessels (FLAIR), microbleeds, susceptibility vessel signs, hemorrhagic transformation (GRE), stenosis (MRA), and image quality (all MRI), between fast and conventional MRI. Agreements between fast and conventional MRI were evaluated by generalized estimating equations. Z-scores were used for comparisons of the percentage agreement among fast FLAIR sequences and fast GRE sequences and between conventional and fast MRA., Results: Agreements of more than 80% were achieved between fast and conventional MRI (ETL-FLAIR, 96%; TR-FLAIR, 97%; EPI-GRE, 96%; parallel-GRE, 98%; fast CE-MRA, 86%). ETL- and TR-FLAIR were significantly superior to EPI-FLAIR in the detection of acute ischemic hyperintensity and hyperintense vessels, while parallel-GRE was significantly superior to EPI-GRE in the detection of susceptibility vessel sign (p value < 0.05 for all). There were no significant differences in the other scores and image qualities (p value > 0.05)., Conclusions: Fast MRI at 1.5 T is a reliable method for the detection and characterization of acute ischemic stroke in comparison with conventional MRI., Key Points: • Fast MRI at 1.5 T may achieve a high intermethod reliability in the detection and characterization of acute ischemic stroke with a reduction in scan time in comparison with conventional MRI.

Although advanced magnetic resonance imaging (MRI) techniques provide useful information for the differential diagnosis of intra-axial mass-like lesions, the specific diagnostic role of multimodal MRI over conventional magnetic resonance imaging (CMRI) alone in the differential diagnosis of mass-like lesions from a large heterogeneous cohort has not been studied. In this study, we aimed to determine the added value of a joint approach of diffusion-weighted imaging (DWI) and dynamic-susceptibility-contrast perfusion imaging (DSC-PWI) for diagnosis of intra-axial mass-like lesions, comparing them with CMRI alone. Furthermore, we performed these evaluations in a manner simulating clinical practice. Our institutional review board approved this retrospective study and waived the requirement for informed consent. A total of 1038 patients with intra-axial mass-like lesions were retrospectively recruited according to their histological and clinico-radiological diagnoses made between January 2005 and December 2014. All patients underwent CMRI, DWI and DSC-PWI. The diagnostic accuracy and confidence in diagnosing each type of intra-axial mass-like lesions, and for differentiating the intra-axial brain tumors from non-neoplastic lesions, were compared according to the MRI protocols. The disease-specific sensitivity of joint approach differed according to specific disease entities in diagnosing each disease category. Joint approach provided the best diagnostic accuracy for discriminating intra-axial brain tumors from non-neoplastic lesions, with high diagnostic accuracy (95.3-96.7%), specificity (82-84.0%), positive-predictive-value (97.0-97.3%), and negative-predictive-value (84.8-92.7%), with the reader's confidence values being significantly improved over those on CMRI alone (all p-values < 0.001). In conclusion, joint approach of DWI, DSC-PWI to CMRI helps to differentiate non-neoplastic lesions from intra-axial brain tumors, and improves diagnostic confidence compared with CMRI alone. The benefit from the combined imaging differs for each disease category; thus joint approach needs to be customized according to clinical suspicion., Competing Interests: The authors have declared that no competing interests exist.

Objectives: To investigate the prevalence of cerebrovascular stenosis and white matter lesions on preoperative magnetic resonance angiography (MRA) and magnetic resonance imaging (MRI) in liver transplantation candidates., Methods: This retrospective study included 1,460 consecutive patients with liver cirrhosis (LC) who underwent MRA with/without brain MRI for pretransplantation evaluation. These patients were matched with 5,331 controls using propensity scores, and the prevalences of significant cerebrovascular stenosis and white matter lesions were compared., Results: A matched analysis of 1,264 pairs demonstrated that the prevalence of significant stenosis was comparable between LC patients and controls (2.2% vs. 1.4%, P = 0.143). LC and most of LC-related parameters were not associated with stenosis. Significant white matter lesions were more common in LC patients (2.8% vs. 1.3%, P = 0.036). A high Model for End-Stage Liver Disease (MELD) score (OR 1.11, CI 1.03-1.20, P = 0.008, for infarction; OR 1.1, CI 1.04-1.16, P = 0.001, for haemorrhage) and stroke history (OR 179.06, CI 45.19-709.45, P < 0.001) were predictors of perioperative stroke., Conclusions: LC patients and control subjects demonstrated similar cerebrovascular stenosis prevalences, whereas white matter lesions were more common in LC patients. A high MELD score and stroke history contribute as predictors of perioperative stroke., Key Points: • Routine preoperative MR imaging in liver transplantation candidates may not be necessary. • Liver cirrhosis patients and control subjects had similar prevalences of significant cerebrovascular stenosis. • Liver cirrhosis and cirrhosis-related parameters were not correlated with significant cerebrovascular stenosis. • Significant white matter lesions were more frequent in liver cirrhosis patients.

Although Parkinson's disease is a neurodegenerative disease primarily involving basal ganglia and midbrain, the deficit of white matter is also involved during the disease progression. As the diffusion tensor imaging method is sensitive to the microstructural changes, we investigated the microstructural alterations in white matter and deep gray matter in patients with Parkinson's disease. Brain images of 64 patients and sex- and age-matched 64 healthy controls were obtained from a 3T MRI scanner. Tract-based spatial statistics were used to compare the mean diffusivity of the white matter tract between the groups. Voxel-based analysis was used to compare the mean diffusivity of the subcortical gray matter between the groups. There were white matter deficits in the corticofugal tract, cingulum, uncinate fasciculus, crus of fornix or stria terminalis, corpus callosum, external capsule, superior longitudinal fasciculus, posterior thalamic radiation including optic radiation, and the tracts adjacent to the precuneus and supramarginal gyrus, as indicated by higher mean diffusivity in Parkinson's disease patients than in controls. There were also deficits in the left putamen, pallidum, thalamus, and caudate as indicated by higher mean diffusivity in Parkinson's disease patients than in controls. Using diffusion tensor imaging and multi-methods of image analysis, we successfully characterized and visualized brain white matter and deep gray matter areas with microstructural deficits in Parkinson's disease patients., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

We report a case of intracranial foreign body granuloma that showed features of a high grade tumor on magnetic resonance (MR) imaging. However, the relative cerebral blood volume was not increased in the enhancing mass on perfusion MRI and the choline/creatine ratio only slightly increased on MR spectroscopy. The results suggest that the lesion is benign in nature. Perfusion MRI and MR spectroscopy may be helpful to differentiate a foreign body granuloma from a neoplastic condition.

Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images may cause misalignments, particularly in brain PET and CT images that have low correspondence rates between features due to differences in image characteristics. To cope with this limitation, we propose a robust feature-based registration technique using a Gaussian-weighted distance map (GWDM) that finds the best alignment of feature points even when features of two images are mismatched. A GWDM is generated by propagating the value of the Gaussian-weighted mask from feature points of CT images and leads the feature points of PET images to be aligned on an optimal location even though there is a localization error between feature points extracted from PET and CT images. Feature points are extracted from two images by our automatic brain segmentation method. In our experiments, simulated and clinical data sets were used to compare our method with conventional methods such as normalized mutual information (NMI)-based registration and chamfer matching in accuracy, robustness, and computational time. Experimental results showed that our method aligned the images robustly even in cases where conventional methods failed to find optimal locations. In addition, the accuracy of our method was comparable to that of the NMI-based registration method.

Objective: The purposes of this study were to review the anatomy of the oculosympathetic pathway, to describe the clinical characteristics of the three types of Horner syndrome, and to illustrate underlying pathologic features with an emphasis on neuroimaging strategies based on three symptom complexes., Conclusion: Horner syndrome results from interruption of the oculosympathetic pathway and is usually associated with unique clinical features classified into central, preganglionic, and postganglionic types according to the anatomic location of the underlying pathologic process.