Hemifacial spasm (HFS) is a movement disorder characterized by involuntary contractions of the facial muscles innervated by the seventh cranial nerve. Generally, it is associated with a poor quality of life due to social embarrassment and can lead to functional blindness. Moreover, it is a chronic condition, and spontaneous recovery is rare. Intramuscular injections of Botulinum Toxin (BoNT) are routinely used as HFS treatment. Methods: We reviewed published articles between 1991 and 2021 regarding the effectiveness and safety of BoNT in HFS as well as any reported differences among BoNT formulations. Results: The efficacy of BoNT for HFS treatment ranged from 73% to 98.4%. The mean duration of the effect was around 12 weeks. Effectiveness did not decrease over time. Adverse effects were usually mild and transient. The efficacy and tolerability of the different preparations appeared to be similar. Among the studies, dosage, injected muscles, intervals of treatment, and rating scales were variable, thus leading to challenges in comparing the results. Conclusions: BoNT was the treatment of choice for HFS due to its efficacy and safety profile. Further studies are needed to investigate the factors that influence the outcome, including the optimal timing of treatment, injection techniques, dosage, and the best selection criteria for formulations.

Different psychopathological manifestations, such as affective, psychotic, obsessive-compulsive symptoms, and impulse control disturbances, may occur in most central nervous system (CNS) disorders including neurodegenerative and neuroinflammatory diseases. Psychiatric symptoms often represent the clinical onset of such disorders, thus potentially leading to misdiagnosis, delay in treatment, and a worse outcome. In this review, psychiatric symptoms observed along the course of several neurological diseases, namely Alzheimer’s disease, fronto-temporal dementia, Parkinson’s disease, Huntington’s disease, and multiple sclerosis, are discussed, as well as the involved brain circuits and molecular/synaptic alterations. Special attention has been paid to the emerging role of fluid biomarkers in early detection of these neurodegenerative diseases. The frequent occurrence of psychiatric symptoms in neurological diseases, even as the first clinical manifestations, should prompt neurologists and psychiatrists to share a common clinico-biological background and a coordinated diagnostic approach.

Brain single-photon-emission-computerized tomography (SPECT) with ¹²³I-ioflupane (¹²³I-FP-CIT) is useful to diagnose Parkinson disease (PD). To investigate the diagnostic performance of ¹²³I-FP-CIT brain SPECT with semiquantitative analysis by Basal Ganglia V2 software (BasGan), we evaluated semiquantitative data of patients with suspect of PD by a support vector machine classifier (SVM), a powerful supervised classification algorithm. ¹²³I-FP-CIT SPECT with BasGan analysis was performed in 90 patients with suspect of PD showing mild symptoms (bradykinesia-rigidity and mild tremor). PD was confirmed in 56 patients, 34 resulted non-PD (essential tremor and drug-induced Parkinsonism). A clinical follow-up of at least 6 months confirmed diagnosis. To investigate BasGan diagnostic performance we trained SVM classification models featuring different descriptors using both a “leave-one-out” and a “five-fold” method. In the first study we used as class descriptors the semiquantitative radiopharmaceutical uptake values in the left (L) and right (R) putamen (P) and in the L and R caudate nucleus (C) for a total of 4 descriptors (CL, CR, PL, PR). In the second study each patient was described only by CL and CR, while in the third by PL and PR descriptors. Age was added as a further descriptor to evaluate its influence in the classification performance. ¹²³I-FP-CIT SPECT with BasGan analysis reached a classification performance higher than 73.9% in all the models. Considering the “Leave-one-out” method, PL and PR were better predictors (accuracy of 91% for all patients) than CL and CR descriptors; using PL, PR, CL, and CR diagnostic accuracy was similar to that of PL and PR descriptors in the different groups. Adding age as a further descriptor accuracy improved in all the models. The best results were obtained by using all the 5 descriptors both in PD and non-PD subjects (CR and CL + PR and PL + age = 96.4% and 94.1%, respectively). Similar results were observed for the “five-fold” method. ¹²³I-FP-CIT SPECT with BasGan analysis using SVM classifier was able to diagnose PD. Putamen was the most discriminative descriptor for PD and the patient age influenced the classification accuracy.