Parotid Warthin's tumor: novel MR imaging score as diagnostic indicator.

OBJECTIVES: Despite known characteristic radiologic and clinical features, differentiation between Warthin's tumor (WT) and other parotid tumors remains challenging. The purpose of this study was to more precisely assess the MR imaging features of WT and to develop a scoring system combining the most specific characteristics. METHODS: A total of 208 patients with parotid gland tumors and presurgical MRI were included. Tumors were divided into 5 histological subtypes, and different MRI features were compared between groups. An MRI scoring test was developed including MR parameters that contributed significantly in distinguishing WT from other tumors. RESULTS: The best MRI features for differentiating between WTs from other tumors included bilaterality (P = 0.002), multifocality (P < 0.001), ADC values <905.1 (P < 0.001), and high signal intensity on T1-W images (P < 0.001). Six or more points on the 14-point scoring MRI scale was associated with an area under the curve of 0.99 (Accuracy of 98%), while a cut-off value of 7 indicated 100% specificity and 100% positive predictive value. CONCLUSIONS: Ill-defined margins, low T1-W signal, and location in the upper 2/3 of the parotid gland excluded WTs in 100% of cases. The proposed scoring method allows WTs to be distinguished from other tumors with high accuracy.

Correlation of PET/CT and Brain MRI Findings in Human African Trypanosomiasis Encephalitis.

ABSTRACT: A 49-year-old woman from Cameroon presented with history of several months of worsening headache, lethargy, left arm weakness, and generalized lymphadenopathy. Brain MRI demonstrated multifocal signal abnormality and enhancement involving the bilateral basal ganglia and cerebral white matter. FDG PET/CT performed as part of lymphadenopathy evaluation demonstrated patchy areas of increased metabolic activity of the brain parenchyma. Human African trypanosomiasis or African sleeping sickness is a protozoan infection caused by Trypanosoma brucei gambiense transmitted by the tsetse fly in sub-Saharan Africa. It is important to recognize the signs and symptoms in nonendemic countries to facilitate early diagnosis and treatment.

Identification of the Somatomotor Network from Language Task-based fMRI Compared with Resting-State fMRI in Patients with Brain Lesions.

Background Resting-state functional MRI (rs-fMRI) is a potential alternative to task-based functional MRI (tb-fMRI) for somatomotor network (SMN) identification. Brain networks can also be generated from tb-fMRI by using independent component analysis (ICA). Purpose To investigate whether the SMN can be identified by using ICA from a language task without a motor component, the sentence completion functional MRI (sc-fMRI) task, compared with rs-fMRI. Materials and Methods The sc-fMRI and rs-fMRI scans in patients who underwent presurgical brain mapping between 2012 and 2016 were analyzed, using the same imaging parameters (other than scanning time) on a 3.0-T MRI scanner. ICA was performed on rs-fMRI and sc-fMRI scans with use of a tool to separate data sets into their spatial and temporal components. Two neuroradiologists independently determined the presence of the dorsal SMN (dSMN) and ventral SMN (vSMN) on each study. Groups were compared by using t tests, and logistic regression was performed to identify predictors of the presence of SMNs. Results One hundred patients (mean age, 40.9 years ± 14.8 [standard deviation]; 61 men) were evaluated. The dSMN and vSMN were identified in 86% (86 of 100) and 76% (76 of 100) of rs-fMRI scans and 85% (85 of 100) and 69% (69 of 100) of sc-fMRI scans, respectively. The concordance between rs-fMRI and sc-fMRI for presence of dSMN and vSMN was 75% (75 of 100 patients) and 53% (53 of 100 patients), respectively. In 10 of 14 patients (71%) where rs-fMRI did not show the dSMN, sc-fMRI demonstrated it. This rate was 67% for the vSMN (16 of 24 patients). Conclusion In the majority of patients, independent component analysis of sentence completion task functional MRI scans reliably demonstrated the somatomotor network compared with resting-state functional MRI scans. Identifying target networks with a single sentence completion scan could reduce overall functional MRI scanning times by eliminating the need for separate motor tasks. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Field and Birn in this issue.

MRI differences between MOG antibody disease and AQP4 NMOSD.

BACKGROUND: MOG antibody and AQP4 antibody seropositive diseases are immunologically distinct subtypes of neuromyelitis optica spectrum disorders (NMOSD) with similar clinical presentations. MRI findings can be instrumental in distinguishing MOG antibody disease from AQP4 antibody NMOSD. OBJECTIVES: The aim of this study is to characterize the neuroradiological differences between MOG antibody disease and AQP4 antibody NMOSD with the aim to distinguish between the two entities. METHODS: This is a retrospective study of 26 MOG and 25 AQP4 seropositive patients in which MRI features of the brain, spinal cord, and orbit were compared. RESULTS: The majority of the abnormal findings in the MOG cohort were located on orbital MRIs, while spinal cord magnetic resonance (MR) abnormalities were more common in the AQP4 cohort. Brain abnormalities showed some overlap, but cortical gray/juxtacortical white matter involvement was distinct to MOG patients, while area postrema involvement was a rare feature. CONCLUSION: Cortical gray/juxtacortical white matter lesions on brain MRI might help distinguish MOG antibody disease from AQP4-positive NMOSD. These findings could be of value in distinguishing the two entities as early as the first presentation.

Spine Anatomy Imaging: An Update.

Spinal MR imaging is excellent for identifying details of spinal anatomy, including intraspinal contents, neural foramina, joints, ligaments, intervertebral discs, and bone marrow. Cortical bony structures of the spine are better imaged using CT. Conventional and CT myelography is an alternative to MR imaging in those with contraindications to MR imaging or in evaluation of spinal cerebrospinal fluid leaks. Motion- and flow-related artifacts may occur during imaging and should not be mistaken for lesions. With advancements in MR imaging hardware and software, spinal MR imaging can expand its role in the delineation of normal and abnormal spinal anatomy.

Contextual effects of noise on vocalization encoding in primary auditory cortex.

Robust auditory perception plays a pivotal function for processing behaviorally relevant sounds, particularly with distractions from the environment. The neuronal coding enabling this ability, however, is still not well understood. In this study, we recorded single-unit activity from the primary auditory cortex (A1) of awake marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise and vocalization babble. Noise effects on neural representation of target vocalizations were quantified by measuring the responses' similarity to those elicited by natural vocalizations as a function of signal-to-noise ratio. A clustering approach was used to describe the range of response profiles by reducing the population responses to a summary of four response classes (robust, balanced, insensitive, and brittle) under both noise conditions. This clustering approach revealed that, on average, approximately two-thirds of the neurons change their response class when encountering different noises. Therefore, the distortion induced by one particular masking background in single-unit responses is not necessarily predictable from that induced by another, suggesting the low likelihood of a unique group of noise-invariant neurons across different background conditions in A1. Regarding noise influence on neural activities, the brittle response group showed addition of spiking activity both within and between phrases of vocalizations relative to clean vocalizations, whereas the other groups generally showed spiking activity suppression within phrases, and the alteration between phrases was noise dependent. Overall, the variable single-unit responses, yet consistent response types, imply that primate A1 performs scene analysis through the collective activity of multiple neurons. NEW & NOTEWORTHY: The understanding of where and how auditory scene analysis is accomplished is of broad interest to neuroscientists. In this paper, we systematically investigated neuronal coding of multiple vocalizations degraded by two distinct noises at various signal-to-noise ratios in nonhuman primates. In the process, we uncovered heterogeneity of single-unit representations for different auditory scenes yet homogeneity of responses across the population.

Defining the ischemic penumbra using magnetic resonance oxygen metabolic index.

BACKGROUND AND PURPOSE: Penumbral biomarkers promise to individualize treatment windows in acute ischemic stroke. We used a novel magnetic resonance imaging approach that measures oxygen metabolic index (OMI), a parameter closely related to positron emission tomography-derived cerebral metabolic rate of oxygen utilization (CMRO2), to derive a pair of ischemic thresholds: (1) an irreversible-injury threshold that differentiates ischemic core from penumbra and (2) a reversible-injury threshold that differentiates penumbra from tissue not-at-risk for infarction. METHODS: Forty patients with acute ischemic stroke underwent magnetic resonance imaging at 3 time points after stroke onset: <4.5 hours (for OMI threshold derivation), 6 hours (to determine reperfusion status), and 1 month (for infarct probability determination). A dynamic susceptibility contrast method measured cerebral blood flow, and an asymmetrical spin echo sequence measured oxygen extraction fraction, to derive OMI (OMI=cerebral blood flow×oxygen extraction fraction). Putative ischemic threshold pairs were iteratively tested using a computation-intensive method to derive infarct probabilities in 3 tissue groups defined by the thresholds (core, penumbra, and not-at-risk tissue). An optimal threshold pair was chosen based on its ability to predict infarction in the core, reperfusion-dependent survival in the penumbra, and survival in not-at-risk tissue. The predictive abilities of the thresholds were then tested within the same cohort using a 10-fold cross-validation method. RESULTS: The optimal OMI ischemic thresholds were found to be 0.28 and 0.42 of normal values in the contralateral hemisphere. Using the 10-fold cross-validation method, median infarct probabilities were 90.6% for core, 89.7% for nonreperfused penumbra, 9.95% for reperfused penumbra, and 6.28% for not-at-risk tissue. CONCLUSIONS: OMI thresholds, derived using voxel-based, reperfusion-dependent infarct probabilities, delineated the ischemic penumbra with high predictive ability. These thresholds will require confirmation in an independent patient sample.

Parietofrontal integrity determines neural modulation associated with grasping imagery after stroke.

Chronic stroke patients with heterogeneous lesions, but no direct damage to the primary sensorimotor cortex, are capable of longitudinally acquiring the ability to modulate sensorimotor rhythms using grasping imagery of the affected hand. Volitional modulation of neural activity can be used to drive grasping functions of the paralyzed hand through a brain-computer interface. The neural substrates underlying this skill are not known. Here, we investigated the impact of individual patient's lesion pathology on functional and structural network integrity related to this volitional skill. Magnetoencephalography data acquired throughout training was used to derive functional networks. Structural network models and local estimates of extralesional white matter microstructure were constructed using T(1)-weighted and diffusion-weighted magnetic resonance imaging data. We employed a graph theoretical approach to characterize emergent properties of distributed interactions between nodal brain regions of these networks. We report that interindividual variability in patients' lesions led to differential impairment of functional and structural network characteristics related to successful post-training sensorimotor rhythm modulation skill. Patients displaying greater magnetoencephalography global cost-efficiency, a measure of information integration within the distributed functional network, achieved greater levels of skill. Analysis of lesion damage to structural network connectivity revealed that the impact on nodal betweenness centrality of the ipsilesional primary motor cortex, a measure that characterizes the importance of a brain region for integrating visuomotor information between frontal and parietal cortical regions and related thalamic nuclei, correlated with skill. Edge betweenness centrality, an analogous measure, which assesses the role of specific white matter fibre pathways in network integration, showed a similar relationship between skill and a portion of the ipsilesional superior longitudinal fascicle connecting premotor and posterior parietal visuomotor regions known to be crucially involved in normal grasping behaviour. Finally, estimated white matter microstructure integrity in regions of the contralesional superior longitudinal fascicle adjacent to primary sensorimotor and posterior parietal cortex, as well as grey matter volume co-localized to these specific regions, positively correlated with sensorimotor rhythm modulation leading to successful brain-computer interface control. Thus, volitional modulation of ipsilesional neural activity leading to control of paralyzed hand grasping function through a brain-computer interface after longitudinal training relies on structural and functional connectivity in both ipsilesional and contralesional parietofrontal pathways involved in visuomotor information processing. Extant integrity of this structural network may serve as a future predictor of response to longitudinal therapeutic interventions geared towards training sensorimotor rhythms in the lesioned brain, secondarily improving grasping function through brain-computer interface applications.