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In an uncontrolled, open-label pilot study, essential tremor improved in 15 patients treated with MRI-guided focused ultrasound thalamotomy. Adverse effects included persistent paresthesias in four patients. The study was too small to assess the safety of this procedure. Essential tremor, the most common movement disorder, with a prevalence as high as 4%, is characterized by a rhythmic oscillation of agonist and antagonist muscle groups, typically between 8 and 12 Hz. 1 The cause of this disorder remains unknown, although there is often a familial component with a link to a particular polymorphism in the gene encoding leucine-rich repeat and immunoglobulin domain–containing protein 1 ( LINGO1 ). Although essential tremor is not medically dangerous, it is progressive and disabling in the home and workplace. 2 The degree of tremor does not always correlate with the severity of disability, 3 and patients with . . .

Artificial intelligence (AI) and generative language models (GLMs) present significant opportunities for enhancing medical education, including the provision of realistic simulations, digital patients, personalized feedback, evaluation methods, and the elimination of language barriers. These advanced technologies can facilitate immersive learning environments and enhance medical students' educational outcomes. However, ensuring content quality, addressing biases, and managing ethical and legal concerns present obstacles. To mitigate these challenges, it is necessary to evaluate the accuracy and relevance of AI-generated content, address potential biases, and develop guidelines and policies governing the use of AI-generated content in medical education. Collaboration among educators, researchers, and practitioners is essential for developing best practices, guidelines, and transparent AI models that encourage the ethical and responsible use of GLMs and AI in medical education. By sharing information about the data used for training, obstacles encountered, and evaluation methods, developers can increase their credibility and trustworthiness within the medical community. In order to realize the full potential of AI and GLMs in medical education while mitigating potential risks and obstacles, ongoing research and interdisciplinary collaboration are necessary. By collaborating, medical professionals can ensure that these technologies are effectively and responsibly integrated, contributing to enhanced learning experiences and patient care.

This trial assessed the value of brain imaging to guide treatment for stroke. Clinical outcomes with embolectomy were not superior to those with standard care in all patients or in the subgroup identified by brain imaging as most likely to benefit from embolectomy. Multiple randomized, controlled trials have shown the efficacy of the use of intravenous tissue plasminogen activator (t-PA), administered up to 4.5 hours after the onset of symptoms of acute ischemic stroke. 1 , 2 However, the global effect of this therapy has been limited, largely because of the narrow time window available for treatment and the risk of symptomatic intracerebral hemorrhage. Although endovascular approaches, including thrombectomy devices, have been shown to achieve greater rates of recanalization than the use of intravenous t-PA, no randomized, controlled trial has been completed comparing clinical outcomes versus standard medical care. Moreover, the potential to benefit from . . .

As the global COVID-19 pandemic evolves, our knowledge of the respiratory and non-respiratory symptoms continues to grow. One such symptom, anosmia, may be a neurologic marker of coronavirus infection and the initial presentation of infected patients. Because this symptom is not routinely investigated by imaging, there is conflicting literature on neuroimaging abnormalities related to COVID-19-related anosmia. We present a novel case of COVID-19 anosmia with definitive olfactory bulb atrophy compared with pre-COVID imaging. The patient had prior MR imaging related to a history of prolactinoma that provided baseline volumes of her olfactory bulbs. After a positive diagnosis of COVID-19 and approximately 2 months duration of anosmia, an MRI was performed that showed clear interval olfactory bulb atrophy. This diagnostic finding is of prognostic importance and indicates that the olfactory entry point to the brain should be further investigated to improve our understanding of COVID infectious pathophysiology.

Muscle fat infiltration (MFI) of the deep cervical spine extensors has been observed in cervical spine conditions using time-consuming and rater-dependent manual techniques. Deep learning convolutional neural network (CNN) models have demonstrated state-of-the-art performance in segmentation tasks. Here, we train and test a CNN for muscle segmentation and automatic MFI calculation using high-resolution fat-water images from 39 participants (26 female, average = 31.7 ± 9.3 years) 3 months post whiplash injury. First, we demonstrate high test reliability and accuracy of the CNN compared to manual segmentation. Then we explore the relationships between CNN muscle volume, CNN MFI, and clinical measures of pain and neck-related disability. Across all participants, we demonstrate that CNN muscle volume was negatively correlated to pain (R = −0.415, p = 0.006) and disability (R = −0.286, p = 0.045), while CNN MFI tended to be positively correlated to disability (R = 0.214, p = 0.105). Additionally, CNN MFI was higher in participants with persisting pain and disability (p = 0.049). Overall, CNN’s may improve the efficiency and objectivity of muscle measures allowing for the quantitative monitoring of muscle properties in disorders of and beyond the cervical spine.

ObjectivesTo explore the possible concurrent brain functional and structural alterations in patients with migraine without aura (MwoA) patients compared to healthy subjects (HS).MethodsSeventy-two MwoA patients and forty-six HS were recruited. 3D-T1 and resting state fMRI data were collected during the interictal period for MwoA and HS. Voxel-based morphometry (VBM) for structure analysis and regional homogeneity (Reho) for fMRI analysis were applied. The VBM and Reho maps were overlapped to determine a possible brain region with concurrent functional and structural alteration in MwoA patients. Further analysis of resting state functional connectivity (FC) alteration was applied with this brain region as the seed.ResultsCompared with HS, MwoA patients showed decreased volume in the bilateral superior and inferior colliculus, periaqueductal gray matter (PAG), locus ceruleus, median raphe nuclei (MRN) and dorsal pons medulla junction. MwoA patients showed decreased Reho values in the middle occipital gyrus and inferior occipital gyrus, and increased Reho values in the MRN. Only a region in the MRN showed both structural and functional alteration in MwoA patients. Pearson correlation analysis showed that there was no association between volume or Reho values of the MRN and headache frequency, headache intensity, disease duration, self-rating anxiety scale or self-rating depression scale in MwoA patients. Resting state functional connectivity (FC) with the MRN as the seed showed that MwoA patients had increased FC between the MRN and PAG.ConclusionsMRN are involved in the pathophysiology of migraine during the interictal period. This study may help to better understand the migraine symptoms.Trial registrationNCT01152632. Registered 27 June 2010.

ObjectivesTo analyze the mechanical properties in different regions of the brain in healthy adults in a wide age range: 26 to 76 years old.MethodsWe used a multifrequency magnetic resonance elastography (MRE) protocol to analyze the effect of age on frequency-dependent (storage and loss moduli, G′ and G″, respectively) and frequency-independent parameters (μ1, μ2, and η, as determined by a standard linear solid model) of the cerebral parenchyma, cortical gray matter (GM), white matter (WM), and subcortical GM structures of 46 healthy male and female subjects. The multifrequency behavior of the brain and frequency-independent parameters were analyzed across different age groups.ResultsThe annual change rate ranged from − 0.32 to − 0.36% for G′ and − 0.43 to − 0.55% for G″ for the cerebral parenchyma, cortical GM, and WM. For the subcortical GM, changes in G′ ranged from − 0.18 to − 0.23%, and G″ changed − 0.43%. Interestingly, males exhibited decreased elasticity, while females exhibited decreased viscosity with respect to age in some regions of subcortical GM. Significantly decreased values were also found in subjects over 60 years old.ConclusionValues of G′ and G″ at 60 Hz and the frequency-independent μ2 of the caudate, putamen, and thalamus may serve as parameters that characterize the aging effect on the brain. The decrease in brain stiffness accelerates in elderly subjects.Key Points• We used a multifrequency MRE protocol to assess changes in the mechanical properties of the brain with age.• Frequency-dependent (storage moduli G′ and loss moduli G″) and frequency-independent (μ1, μ2, and η) parameters can bequantitatively measured by our protocol.• The decreased value of viscoelastic properties due to aging varies in different regions of subcortical GM in males and females, and the decrease in brain stiffness is accelerated in elderly subjects over 60 years old.

Intracranial haemorrhage can be a devastating disorder that requires rapid diagnosis and management. Neuroimaging studies are not only required for diagnosis but also provide important insights into the type of haemorrhage, the underlying aetiology, and the accompanying pathophysiology. Historically, CT has been the diagnostic imaging study of choice; however, there is a growing body of data that suggest that MRI is at least as sensitive as CT to detect haemorrhage in the hyperacute setting, and superior to CT in the subacute and chronic settings. Blood has characteristic appearances on both imaging modalities at each stage (acute, subacute, and chronic) and it is important that physicians are familiar with the appearance of various types of intracranial haemorrhage on CT and MRI and their clinical implications. In addition, new imaging applications, such as magnetic resonance spectroscopy and diffusion tensor imaging, are promising research techniques that have the potential to enhance our understanding of the tissue injury and recovery that result from intracranial haemorrhage.

Dual-energy CT (DECT) material decomposition techniques may better detect edema within cerebral infarcts than conventional non-contrast CT (NCCT). This study compared if Virtual Ischemia Maps (VIM) derived from non-contrast DECT of patients with acute ischemic stroke due to large-vessel occlusion (AIS-LVO) are superior to NCCT for ischemic core estimation, compared against reference-standard DWI-MRI. Only patients whose baseline ischemic core was most likely to remain stable on follow-up MRI were included, defined as those with excellent post-thrombectomy revascularization or no perfusion mismatch. Twenty-four consecutive AIS-LVO patients with baseline non-contrast DECT, CT perfusion (CTP), and DWI-MRI were analyzed. The primary outcome measure was agreement between volumetric manually segmented VIM, NCCT, and automatically segmented CTP estimates of the ischemic core relative to manually segmented DWI volumes. Volume agreement was assessed using Bland–Altman plots and comparison of CT to DWI volume ratios. DWI volumes were better approximated by VIM than NCCT (VIM/DWI ratio 0.68 ± 0.35 vs. NCCT/DWI ratio 0.34 ± 0.35; P < 0.001) or CTP (CTP/DWI ratio 0.45 ± 0.67; P < 0.001), and VIM best correlated with DWI (r VIM  = 0.90; r NCCT  = 0.75; r CTP  = 0.77; P < 0.001). Bland–Altman analyses indicated significantly greater agreement between DWI and VIM than NCCT core volumes (mean bias 0.60 [95%AI 0.39–0.82] vs. 0.20 [95%AI 0.11–0.30]). We conclude that DECT VIM estimates the ischemic core in AIS-LVO patients more accurately than NCCT.