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Magnetic resonance imaging (MRI) is a non-destructive technique that is capable of localizing pathologies and assessing other anatomical features (e.g., tissue volume, microstructure, and white matter connectivity) in postmortem, ex vivo human brains. However, when brains are removed from the skull and cerebrospinal fluid (i.e., their normal in vivo magnetic environment), air bubbles and air–tissue interfaces typically cause magnetic susceptibility artifacts that severely degrade the quality of ex vivo MRI data. In this report, we describe a relatively simple and cost-effective experimental setup for acquiring artifact-free ex vivo brain images using a clinical MRI system with standard hardware. In particular, we outline the necessary steps, from collecting an ex vivo human brain to the MRI scanner setup, and have also described changing the formalin (as might be necessary in longitudinal postmortem studies). Finally, we share some representative ex vivo MRI images that have been acquired using the proposed setup in order to demonstrate the efficacy of this approach. We hope that this protocol will provide both clinicians and researchers with a straight-forward and cost-effective solution for acquiring ex vivo MRI data from whole postmortem human brains.

Fatigue is one of the most disabling side effects in people with multiple sclerosis. While this fact is well known, there has been a remarkable lack of progress in determining the pathophysiological mechanisms behind fatigue and the establishment of effective treatments. The main barrier has been the lack of a unified definition of fatigue that can be objectively tested with validated experimental models. In this “perspective article” we propose the use of the following model and definition of fatigue: the decrease in physical and/or mental performance that results from changes in central, psychological, and/or peripheral factors. These changes depend on the task being performed, the environmental conditions it is performed in, and the physical and mental capacity of the individual. Our definition and model of fatigue outlines specific causes of fatigue and how it affects task performance. We also outline the strengths and weaknesses of commonly used measures of fatigue and suggest, based on our model and definition, new research strategies, which should include multiple measures. These studies should be mechanistic with validated experimental models to determine changes in central, psychological, and/or peripheral factors that explain fatigue. The proposed new research strategies may lead to the identification of the origins of MS related fatigue and the development of new, more effective treatments.

Purpose: Alterations of the central serotonergic system have been implicated in the pathophysiology of dystonia. In this molecular imaging study, we assessed whether altered presynaptic serotonin transporter (SERT) binding contributes to the pathophysiology of cervical dystonia (CD), concerning both motor and non-motor symptoms (NMS).Methods: We assessed the non-displaceable binding potential (BPND) using the selective SERT tracer [11C]DASB and positron emission tomography (PET) in 14 CD patients and 12 age- and gender-matched controls. Severity of motor symptoms was scored using the Toronto Western Spasmodic Torticollis Rating Scale and Clinical Global Impression jerks/tremor scale. NMS for depressive symptoms, anxiety, fatigue, and sleep disturbances were assessed with quantitative rating scales. The relationship between SERT binding and clinical patient characteristics was analyzed with the Spearman's rho test and multiple regression.Results: When comparing the CD patients with controls, no significant differences in BPNDwere found. Higher BPNDin the dorsal raphe nucleus was statistically significantly correlated (p < 0.001) with motor symptom severity (rs = 0.65), pain (rs = 0.73), and sleep disturbances (rs = 0.73), with motor symptom severity being the most important predictor of SERT binding. Furthermore, fatigue was negatively associated with the BPNDin the medial raphe nucleus (rs = -0.61,p = 0.045), and sleep disorders were positively associated with the BPNDin the caudate nucleus (rs = 0.58,p = 0.03) and the hippocampus (rs = 0.56,p = 0.02).Conclusion: Motor symptoms, as well as pain, sleep disturbances, and fatigue in CD showed a significant relationship with SERT binding in the raphe nuclei. Moreover, fatigue showed a significant relationship with the medial raphe nucleus and sleep disorders with the caudate nucleus and hippocampus. These findings suggest that an altered serotonergic signaling in different brain areas in CD is related to different motor as well as NMS, which will further stimulate research on the role of serotonin in the pathogenesis of dystonia.

Radiologists are among the first physicians to be directly affected by advances in computer technology. Computers are already capable of analyzing medical imaging data, and with decades worth of digital information available for training, will an artificial intelligence (AI) one day signal the end of the human radiologist? With the ever increasing work load combined with the looming doctor shortage, radiologists will be pushed far beyond their current estimated 3 s allotted time-of-analysis per image; an AI with super-human capabilities might seem like a logical replacement. We feel, however, that AI will lead to an augmentation rather than a replacement of the radiologist. The AI will be relied upon to handle the tedious, time-consuming tasks of detecting and segmenting outliers while possibly generating new, unanticipated results that can then be used as sources of medical discovery. This will affect not only radiologists but all physicians and also researchers dealing with medical imaging. Therefore, we must embrace future technology and collaborate interdisciplinary to spearhead the next revolution in medicine.

The study of large-scale functional interactions in the human brain with fMRI extends almost to the first applications of this technology. Due to historical reasons and preconceptions about the limitations of this brain imaging method, most studies have focused on assessing connectivity over extended periods of time. It is now clear that fMRI can resolve the temporal dynamics of functional connectivity, like other faster imaging techniques such as EEG and MEG (albeit on a different temporal scale). However, the indirect nature of fMRI measurements can hinder the interpretability of the results. After briefly summarizing recent advances in the field, we discuss how the simultaneous combination of fMRI with electrophysiological activity measurements can contribute to a better understanding of dynamic functional connectivity in humans both during rest and task, wakefulness and other brain states.

A 59-year-old man was admitted with respiratory tract infection, compromised conscience and generalized tonic–clonic seizures. His medical history included schizophrenia diagnosis, for which he had been being treated since he was 27 years old. EEG disclosed non-convulsive status epilepticus. A magnetic resonance image (MRI) acquired 3 days later showed increased left hippocampal volume with hyperintensity on T2-weighted and FLAIR sequences. After being treated with antibiotics and antiepileptic medications, the patient’s condition improved. A follow-up MRI showed reduction of the left hippocampus. The relationship between epilepsy and schizophrenia is not yet clear. This case illustrates this interaction. Hippocampal atrophy may have been caused by environmental aggression in the present patient with schizophrenia, perhaps in association with a predisposing genotype.