Facemask headache: a new nosographic entity among healthcare providers in COVID-19 era.

BACKGROUND: SARS-CoV-2 is a novel infectious agent causing coronavirus disease 2019, which has been declared as pandemic in March 2020. Personal protective equipment has been mandatory for healthcare workers in order to contain the outbreak of pandemic disease. Mild neurological disturbances such as headache have been related to the extensive utilization of facemask. This study aims to examine headache variations related to the intensive utilization of facemask among a cohort of healthcare professionals in a setting of low-medium risk of exposure to SARS-CoV-2. METHODS: This is a cross-sectional study among healthcare providers from different hospital and clinics in Italy. Each participant completed a specifically designed self-administered questionnaire. Headache features and outcome measures' change from baseline were evaluated over a 4-month period, in which wearing facemask has become mandatory for Italian healthcare workers. RESULTS: A total of 400 healthcare providers completed the questionnaire, 383 of them met the inclusion criteria. The majority were doctors, with a mean age of 33.4 ± 9.2 years old. Among 166/383 subjects, who were headache free at baseline, 44 (26.5%) developed de novo headache. Furthermore, 217/383 reported a previous diagnosis of primary headache disorder: 137 were affected by migraine and 80 had tension-type headache. A proportion (31.3%) of these primary headache sufferers experienced worsening of their pre-existing headache disorder, mainly for migraine frequency and attack mean duration. CONCLUSIONS: Our data showed the appearance of de novo associated facemask headache in previous headache-free subjects and an exacerbation of pre-existing primary headache disorders, mostly experienced by people with migraine disease.

Automated MRI Classification in Progressive Supranuclear Palsy: A Large International Cohort Study.

BACKGROUND: The Magnetic Resonance Parkinsonism Index is listed as one of the most reliable imaging morphometric markers for diagnosis of progressive supranuclear palsy (PSP). However, the use of this index in diagnostic workup has been limited until now by the low generalizability of published results because of small monocentric patient cohorts, the lack of data validation in independent patient series, and manual measurements used for index calculation. The objectives of this study were to investigate the generalizability of Magnetic Resonance Parkinsonism Index performance validating previously established cutoff values in a large international cohort of PSP patients subclassified into PSP-Richardson's syndrome and PSP-parkinsonism and to standardize the use of the automated Magnetic Resonance Parkinsonism Index by providing a web-based platform to obtain homogenous measures around the world. METHODS: In a retrospective international multicenter study, a total of 173 PSP patients and 483 non-PSP participants were enrolled. A web-based platform (https://mrpi.unicz.it) was used to calculate automated Magnetic Resonance Parkinsonism Index values. RESULTS: Magnetic Resonance Parkinsonism Index values showed optimal performance in differentiating PSP-Richardson's syndrome and PSP-parkinsonism patients from non-PSP participants (93.6% and 86.5% of accuracy, respectively). The Magnetic Resonance Parkinsonism Index was also able to differentiate PSP-Richardson's syndrome and PSP-parkinsonism patients in an early stage of the disease from non-PSP participants (90.1% and 85.9%, respectively). The web-based platform provided the automated Magnetic Resonance Parkinsonism Index calculation in 94% of cases. CONCLUSIONS: Our study provides the first evidence on the generalizability of automated Magnetic Resonance Parkinsonism Index measures in a large international cohort of PSP-Richardson's syndrome and PSP-parkinsonism patients. The web-based platform enables widespread applicability of the automated Magnetic Resonance Parkinsonism Index to different clinical and research settings. © 2020 International Parkinson and Movement Disorder Society.

Track density imaging in progressive supranuclear palsy: A pilot study.

Progressive supranuclear palsy (PSP) is a neurodegenerative disorder characterized by white matter (WM) changes in different supra- and infratentorial brain structures. We used track density imaging (TDI) to characterize WM microstructural alterations in patients with PSP-Richardson's Syndrome (PSP-RS). Moreover, we investigated the diagnostic utility of TDI in distinguishing patients with PSP-RS from those with Parkinson's disease and healthy controls (HC). Twenty PSP-RS patients, 21 PD patients, and 23 HC underwent a 3 T MRI diffusion-weighted (DW) imaging. Then, we combined constrained spherical deconvolution and WM probabilistic tractography to reconstruct track density maps by calculating the number of WM streamlines traversing each voxel. Voxel-wise analysis was performed to assess group differences in track density maps. A support vector machine (SVM) approach was also used to evaluate the performance of TDI for discriminating between groups. Relative to PD patients, decreases in track density in PSP-RS patients were found in brainstem, cerebellum, thalamus, corpus callosum, and corticospinal tract. Similar findings were obtained between PSP-RS patients and HC. No differences in TDI were observed between PD and HC. SVM approach based on whole-brain analysis differentiated PD patients from PSP-RS with an area under the curve (AUC) of 0.82. The AUC reached a value of 0.98 considering only the voxels belonging to the superior cerebellar peduncle. This study shows that TDI may represent a useful approach for characterizing WM alterations in PSP-RS patients. Moreover, track density decrease in PSP could be considered a new feature for the differentiation of patients with PSP-RS from those with PD.

Assessment of Snaith-Hamilton Pleasure Scale (SHAPS): the dimension of anhedonia in Italian healthy sample.

The Snaith-Hamilton Pleasure Scale (SHAPS) is a rapid screening battery created for assessing the presence of anhedonia, namely the inability to experience pleasure. Although, this symptom has widely been investigated in clinical settings, individual differences in anhedonia are also present in healthy population. The aim of present study was to validate the translated Italian version of this test. One thousand six hundred ninety-seven consecutive healthy subjects (55% female) of different ages (age 18-82 years) underwent SHAPS. Participants who showed mild level of anhedonia also completed the Apathy Evaluation Scale (AES), Beck Depression Inventory (BDI), Toronto Alexithymia Scale-20 (TAS), Mood Disorders Insight Scale (MDIS), and Beck Hopelessness Scale (BHS). The SHAPS showed good internal consistency and discriminant validity; moreover, the factorial analysis highlighted that SHAPS had a three-factor structure for explaining the anhedonic construct. 14.9% showed a significant reduction of hedonic tone (SHAPS ≥ 3). Finally, the degree of anhedonia was significantly correlated with BDI and BHS scores, but not with age or gender. Although anhedonia is a prominent feature of many psychiatric and neurological disorders, the presence of this symptom in the healthy population highlighted the importance to develop reliable tool. SHAPS shows good psychometric properties to assess multidimensional anhedonia symptoms also in Italian healthy population.

Neuroticism modulates brain visuo-vestibular and anxiety systems during a virtual rollercoaster task.

Different lines of research suggest that anxiety-related personality traits may influence the visual and vestibular control of balance, although the brain mechanisms underlying this effect remain unclear. To our knowledge, this is the first functional magnetic resonance imaging (fMRI) study that investigates how individual differences in neuroticism and introversion, two key personality traits linked to anxiety, modulate brain regional responses and functional connectivity patterns during a fMRI task simulating self-motion. Twenty-four healthy individuals with variable levels of neuroticism and introversion underwent fMRI while performing a virtual reality rollercoaster task that included two main types of trials: (1) trials simulating downward or upward self-motion (vertical motion), and (2) trials simulating self-motion in horizontal planes (horizontal motion). Regional brain activity and functional connectivity patterns when comparing vertical versus horizontal motion trials were correlated with personality traits of the Five Factor Model (i.e., neuroticism, extraversion-introversion, openness, agreeableness, and conscientiousness). When comparing vertical to horizontal motion trials, we found a positive correlation between neuroticism scores and regional activity in the left parieto-insular vestibular cortex (PIVC). For the same contrast, increased functional connectivity between the left PIVC and right amygdala was also detected as a function of higher neuroticism scores. Together, these findings provide new evidence that individual differences in personality traits linked to anxiety are significantly associated with changes in the activity and functional connectivity patterns within visuo-vestibular and anxiety-related systems during simulated vertical self-motion. Hum Brain Mapp 38:715-726, 2017. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The movement time analyser task investigated with functional near infrared spectroscopy: an ecologic approach for measuring hemodynamic response in the motor system.

AIMS: Movement time analyzer (MTA) is an objective instrument to evaluate the degree of motor impairment as well as to investigate the dopaminergic drug effect in Parkinson's disease patients. The aim of this study is to validate a new ecologic neuroimaging tool for quantifying MTA-related hemodynamic response of the cortical motor system by means of functional near-infrared spectroscopy (fNIRS). MATERIALS: 11 right-handed healthy volunteers (six male and five female, age range 27-64 years) were studied with fNIRS and functional magnetic resonance imaging (fMRI) while performing MTA task for each hand. RESULTS: MTA performance was better for the dominant hand and younger participants. Both fNIRS and fMRI analyses revealed MTA-related increase of haemoglobin levels in the primary motor and premotor cortices contralateral to the moving hand. This response progressively increased with aging. CONCLUSION: These findings supported the translation of fNIRS-based MTA behavioural tool in clinical practice.

A network centred on the inferior frontal cortex is critically involved in levodopa-induced dyskinesias.

Levodopa-induced dyskinesias are disabling motor complications of long-term dopamine replacement in patients with Parkinson's disease. In recent years, several alternative models have been proposed to explain the pathophysiological mechanisms underlying this hyperkinetic motor disorder. In particular, our group has shed new light on the role of the prefrontal cortex as a key site of interest, demonstrating that, among other areas, the inferior frontal cortex is particularly characterized by altered patterns of anatomical and functional changes. However, how neural activity varies depending on levodopa treatment in patients with dyskinesias and whether the reported prefrontal abnormalities may have a critical role in dyskinesias is debated. To answer these questions we performed independent functional magnetic resonance imaging and repetitive transcranial magnetic stimulation studies. In the first experiment we applied resting state functional magnetic resonance imaging on 12 patients with Parkinson's disease with levodopa-induced dyskinesias and 12 clinically matched patients without dyskinesias, before and after administration of levodopa. Functional connectivity of brain networks in the resting state was assessed in both groups. We chose the right inferior frontal cortex as the seed region given the evidence highlighting the role of this region in motor control. In a second experiment, we applied different forms of repetitive transcranial magnetic stimulation over the right inferior frontal cortex in a new group of dyskinetic patients who were taking a supramaximal dose of levodopa, to verify the clinical relevance of this area in controlling the development of hyperkinetic movements. The resting state functional imaging analysis revealed that in patients with levodopa-induced dyskinesias connectivity of the right inferior frontal cortex was decreased with the left motor cortex and increased with the right putamen when compared to patients without levodopa-induced dyskinesias. This abnormal pattern of connectivity was evident only during the ON phase of levodopa treatment and the degree of such alteration correlated with motor disability. The repetitive TMS experiments showed that a session of continuous but not intermittent or sham theta burst stimulation applied over the inferior frontal cortex was able to reduce the amount of dyskinesias induced by a supramaximal single dose of levodopa, suggesting that this area may play a key role in controlling the development of dyskinesias. Our combined resting state functional magnetic resonance and transcranial magnetic stimulation studies demonstrate that pathophysiological mechanisms underlying levodopa-induced dyskinesias may extend beyond the 'classical' basal ganglia dysfunctions model, including the modulation performed by the neural network centred on the inferior frontal cortex.

The motor inhibition system in Parkinson's disease with levodopa-induced dyskinesias.

BACKGROUND: Parkinson's disease is primarily a disorder of response initiation characterized by an excessive motor inhibition, whereas levodopa-induced dyskinesias are clearly a clinical expression of disinhibition of movements. OBJECTIVE: That levodopa-induced dyskinesias are linked to dysfunctions of inhibitory brain network has recently been proposed, but no investigation of behavioral performance during action inhibition task in these patients has been published. METHODS: Twenty-four Parkinson's disease patients with or without levodopa-induced dyskinesias tested on or off their medications underwent functional magnetic resonance imaging investigation during the execution of a stop-signal inhibition task. In particular, we were interested in evaluating the neural correlates of stop-related conditions: StopInhibit task (in which patients had to successfully inhibit their responses) and StopRespond task (Stop trials with erroneous button press). Both tasks were compared against Go trials. RESULTS: Levodopa intake in dyskinetic patients tended to worsen inhibitory control during the StopInhibit task, while significantly affecting the ability to monitor motor responses when patients failed to stop (StopRespond task). Functional analysis showed that, during the StopInhibit task, dyskinetic patients were characterized by decreased activity of the right inferior frontal cortex after levodopa intake, whereas patients without dyskinesias showed a reverse effect. A similar group × levodopa interaction effect was detected in the medial frontal cortex during the execution of the StopRespond task, in which dyskinetic patients showed increased activity after dopaminergic therapy CONCLUSIONS: Our study demonstrated that levodopa intake in dyskinetic patients tends to alter the functioning of some parts of the neural network involved in motor inhibition.

Magnetic resonance support vector machine discriminates between Parkinson disease and progressive supranuclear palsy.

BACKGROUND: The aim of the current study was to distinguish patients with Parkinson disease (PD) from those with progressive supranuclear palsy (PSP) at the individual level using pattern recognition of magnetic resonance imaging data. METHODS: We combined diffusion tensor imaging and voxel-based morphometry in a support vector machine algorithm to evaluate 21 patients with PSP and 57 patients with PD. RESULTS: The automated algorithm correctly distinguished patients who had PD from those who had PSP with 100% accuracy. This accuracy value was obtained when white matter atrophy was considered. Diffusion parameters combined with gray matter atrophy exhibited 90% sensitivity and 96% specificity. CONCLUSIONS: Our findings demonstrate that automated pattern recognition can help distinguish patients with PSP from those with PD on an individual basis.

Development and Implementation of an Innovative Framework for Automated Radiomics Analysis in Neuroimaging.

Radiomics represents an innovative approach to medical image analysis, enabling comprehensive quantitative evaluation of radiological images through advanced image processing and Machine or Deep Learning algorithms. This technique uncovers intricate data patterns beyond human visual detection. Traditionally, executing a radiomic pipeline involves multiple standardized phases across several software platforms. This could represent a limit that was overcome thanks to the development of the matRadiomics application. MatRadiomics, a freely available, IBSI-compliant tool, features its intuitive Graphical User Interface (GUI), facilitating the entire radiomics workflow from DICOM image importation to segmentation, feature selection and extraction, and Machine Learning model construction. In this project, an extension of matRadiomics was developed to support the importation of brain MRI images and segmentations in NIfTI format, thus extending its applicability to neuroimaging. This enhancement allows for the seamless execution of radiomic pipelines within matRadiomics, offering substantial advantages to the realm of neuroimaging.

Combined blood Neurofilament light chain and third ventricle width to differentiate Progressive Supranuclear Palsy from Parkinson's Disease: A machine learning study.

INTRODUCTION: Differentiating Progressive Supranuclear Palsy (PSP) from Parkinson's Disease (PD) may be clinically challenging. In this study, we explored the performance of machine learning models based on MR imaging and blood molecular biomarkers in distinguishing between these two neurodegenerative diseases. METHODS: Twenty-eight PSP patients, 46 PD patients and 60 control subjects (HC) were consecutively enrolled in the study. Serum concentration of neurofilament light chain protein (Nf-L) was assessed by single molecule array (SIMOA), while an automatic segmentation algorithm was employed for T1-weighted measurements of third ventricle width/intracranial diameter ratio (3rdV/ID). Machine learning (ML) models with Logistic Regression (LR), Random Forest (RF), and XGBoost algorithms based on 3rdV/ID and serum Nf-L levels were tested in distinguishing among PSP, PD and HC. RESULTS: PSP patients showed higher serum Nf-L levels and larger 3rdV/ID ratio in comparison with both PD and HC groups (p < 0.005). All ML algorithms (LR, RF and XGBoost) showed that the combination of MRI and blood biomarkers had excellent classification performances in differentiating PSP from PD (AUC ≥0.92), outperforming each biomarker used alone (AUC: 0.85-0.90). Among the different algorithms, XGBoost was slightly more powerful than LR and RF in distinguishing PSP from PD patients, reaching AUC of 0.94 ± 0.04. CONCLUSION: Our findings highlight the usefulness of combining blood and simple linear MRI biomarkers to accurately distinguish between PSP and PD patients. This multimodal approach may play a pivotal role in patient management and clinical decision-making, paving the way for more effective and timely interventions in these neurodegenerative diseases.

Video-oculographic biomarkers for evaluating vertical ocular dysfunction in progressive supranuclear palsy.

INTRODUCTION: Progressive supranuclear palsy (PSP) patients show reduced amplitude and velocity of vertical saccades, but saccadic abnormalities have also been reported in Parkinson's disease (PD). We investigated amplitude and velocity of vertical saccades in PSP and PD patients, to establish the best video-oculographic (VOG) parameters for PSP diagnosis. METHODS: Fifty-one PSP patients, 113 PD patients and 40 controls were enrolled. The diagnosis was performed on a clinico-radiological basis (MR Parkinsonism index [MRPI] and MRPI 2.0). We used VOG to assess the diagnostic performances of saccadic amplitude, peak velocity, and their product (AxV) in upward or downward direction and in vertical gaze (upward and downward averaged) in distinguishing PSP from PD patients. The vestibulo-ocular reflex, necessary to establish the supranuclear nature of ocular dysfunction, was evaluated clinically. RESULTS: PSP patients showed significantly reduced amplitude and peak velocity of ocular saccades in upward and downward directions compared to PD and healthy subjects. In PD patients, upward gaze amplitude was lower than in controls. In vertical gaze, the peak velocity showed 99.1% specificity and 54.7% sensitivity for PSP classification. The AxV product showed high specificity (94.7%) and sensitivity (84.3%) and yielded higher accuracy (91.5%) than velocity and amplitude used alone in distinguishing PSP from PD. CONCLUSION: Our study demonstrates that the peak velocity of vertical saccades was a very low sensitive parameter and cannot be used alone for PSP diagnosis. A new index combining amplitude and peak velocity in vertical gaze seems the most suitable video-oculographic biomarker for differentiating PSP from PD and controls.

Magnetic Resonance Planimetry in the Differential Diagnosis between Parkinson's Disease and Progressive Supranuclear Palsy.

The clinical differential diagnosis between Parkinson's disease (PD) and progressive supranuclear palsy (PSP) is often challenging. The description of milder PSP phenotypes strongly resembling PD, such as PSP-Parkinsonism, further increased the diagnostic challenge and the need for reliable neuroimaging biomarkers to enhance the diagnostic certainty. This review aims to summarize the contribution of a relatively simple and widely available imaging technique such as MR planimetry in the differential diagnosis between PD and PSP, focusing on the recent advancements in this field. The development of accurate MR planimetric biomarkers, together with the implementation of automated algorithms, led to robust and objective measures for the differential diagnosis of PSP and PD at the individual level. Evidence from longitudinal studies also suggests a role of MR planimetry in predicting the development of the PSP clinical signs, allowing to identify PSP patients before they meet diagnostic criteria when their clinical phenotype can be indistinguishable from PD. Finally, promising evidence exists on the possible association between MR planimetric measures and the underlying pathology, with important implications for trials with new disease-modifying target therapies.

Development and Validation of a New Wearable Mobile Device for the Automated Detection of Resting Tremor in Parkinson's Disease and Essential Tremor.

Involuntary tremor at rest is observed in patients with Parkinson's disease (PD) or essential tremor (ET). Electromyography (EMG) studies have shown that phase displacement between antagonistic muscles at prevalent tremor frequency can accurately differentiate resting tremor in PD from that detected in ET. Currently, phase evaluation is qualitative in most cases. The aim of this study is to develop and validate a new mobile tool for the automated and quantitative characterization of phase displacement (resting tremor pattern) in ambulatory clinical settings. A new low-cost, wearable mobile device, called µEMG, is described, based on low-end instrumentation amplifiers and simple digital signal processing (DSP) capabilities. Measurements of resting tremor characteristics from this new device were compared with standard EMG. A good level of agreement was found in a sample of 21 subjects (14 PD patients with alternating resting tremor pattern and 7 ET patients with synchronous resting tremor pattern). Our results demonstrate that tremor analysis using µEMG is easy to perform and it can be used in routine clinical practice for the automated quantification of resting tremor patterns. Moreover, the measurement process is handy and operator-independent.

Apomorphine-induced reorganization of striato-frontal connectivity in patients with tremor-dominant Parkinson's disease.

INTRODUCTION: Apomorphine is a dopamine agonist used in Parkinson's disease (PD), which matches levodopa in terms of the magnitude of effect on the cardinal motor features, such as tremor and bradykinesia. The beneficial effect of this treatment on PD patients with tremor-dominant has widely been demonstrated, although the underlying neural correlates are unknown. We sought to examine the effects of apomorphine on topological characteristics of resting-state functional connectivity networks in tremor-dominant PD (tdPD) patients. METHODS: Sixteen tdPD patients were examined using a combined electromyography-functional magnetic resonance imaging approach. Patients were scanned twice following either placebo (subcutaneous injection of 1 mL saline solution) or 1 mg of apomorphine injection. Graph analysis methods were employed to investigate the modular organization of functional connectivity networks before and after drug treatment. RESULTS: After injection of apomorphine, evident reduction of tremor symptoms was mirrored by a significant increase in overall connectivity strength and reorganization of the modular structure of the basal ganglia and of the fronto-striatal module. Moreover, we found an increase in the centrality of motor and premotor regions. No differences were found between pre- and post-placebo sessions. CONCLUSION: These results provide new evidence about the effects of apomorphine at a large-scale neural network level showing that drug treatment modifies the brain functional organization of tdPD, increasing the overall resting-state functional connectivity strength, the segregation of striato-frontal regions and the integrative role of motor areas.

The placebo effect on resting tremor in Parkinson's disease: an electrophysiological study.

INTRODUCTION: The aim of our study was to investigate the effect of apomorphine and placebo on resting tremor in tremor-dominant Parkinson's disease (tPD) patients. METHODS: Fifteen tPD patients were enrolled. Each patient underwent two treatments on two consecutive days: on day one the patients received a subcutaneous injection of placebo, while on day two they received apomorphine. On each day, the patients underwent three electrophysiological recording sessions: T0, T1, and T2: before, 30 min, and 60 min after the treatment respectively. Electrophysiological changes in tremor amplitude were evaluated using a triaxial accelerometer. RESULTS: Placebo was effective in improving resting tremor in all tPD patients (p = 0.009) at T1, but not at T2. Eight out of 15 tPD patients (53.3%) responded to placebo with an at least 70% reduction in tremor amplitude compared to the basal condition (responders). By contrast, seven out of 15 tPD patients (46.7%) did not show any variation in tremor amplitude after placebo administration (non-responders). Apomorphine induced a marked reduction in tremor amplitude at 30 min and 60 min in all investigated tPD patients. Of note, the decrease in tremor amplitude in placebo responders was similar to that achieved with dopaminergic stimulation induced by apomorphine. CONCLUSIONS: Our study demonstrates that placebo was very effective in reducing resting tremor in about half of patients with tPD. The decrease in tremor amplitude in placebo responders was similar to that induced by apomorphine. The cerebral mechanisms underlying the placebo effect on resting tremor need further investigations.

Validation Study of Italian Version of Inventory for Déjà Vu Experiences Assessment (I-IDEA): A Screening Tool to Detect Déjà Vu Phenomenon in Italian Healthy Individuals.

The Inventory Déjà Vu Experiences Assessment (IDEA) is the only screening instrument proposed to evaluate the Déjà vu (DV) experience. Here, we intended to validate the Italian version of IDEA (I-IDEA) and at the same time to investigate the incidence and subjective qualities of the DV phenomenon in healthy Italian adult individuals on basis of an Italian multicentre observational study. In this study, we report normative data on the I-IDEA, collected on a sample of 542 Italian healthy subjects aging between 18-70 years (average age: 40) with a formal educational from 1-19 years. From September 2013 to March 2016, we recruited 542 healthy volunteers from 10 outpatient neurological clinics in Italy. All participants (i.e., family members of neurological patients enrolled, medical students, physicians) had no neurological or psychiatric illness and gave their informed consent to participate in the study. All subjects enrolled self-administered the questionnaire and they were able to complete I-IDEA test without any support. In total, 396 (73%) of the 542 healthy controls experienced the DV phenomenon. The frequency of DV was inversely related to age as well as to derealisation, jamais vu, precognitive dreams, depersonalization, paranormal activity, remembering dreams, travel frequency, and daydreams (all p < 0.012). The Italian version of IDEA maintains good properties, thus confirming that this instrument is reliable for detecting and characterising the DV phenomenon.

CADA-computer-aided DaTSCAN analysis.

BACKGROUND: Dopamine transporter (DaT) imaging (DaTSCAN) is useful for the differential diagnosis of parkinsonian syndromes. Visual evaluation of DaTSCAN images represents the generally accepted diagnostic method, but it is strongly dependent on the observer's experience and shows inter- and intra-observer variability. A reliable and automatic method for DaTSCAN evaluation can provide objective quantification; it is desirable for longitudinal studies, and it allows for a better follow-up control. Moreover, it is crucial for an automated method to produce coherent measures related to the severity of motor symptoms. METHODS: In this work, we propose a novel fully automated technique for DaTSCAN analysis that generates quantitative measures based on striatal intensity, shape, symmetry and extent. We tested these measures using a support vector machine (SVM) classifier. RESULTS: The proposed measures reached 100 % accuracy in distinguishing between patients with Parkinson's disease (PD) and control subjects. We also demonstrate the existence of a linear relationship and an exponential trend between pooled structural and functional striatal characteristics and the Unified Parkinson's disease Rating Scale (UPDRS) motor score. CONCLUSIONS: We present a novel, highly reproducible, user-independent technique for DaTSCAN analysis producing quantitative measures directly connected to striatum uptake and shape. In our method, no a priori assumption is required on the spatial conformation and localization of striatum, and both uptake and symmetry contribute to the index quantification. These measures can reliably support a computer-assisted decision system.

Hippocampal Subfield Atrophies in Converted and Not-Converted Mild Cognitive Impairments Patients by a Markov Random Fields Algorithm.

Although measurement of total hippocampal volume is considered as an important hallmark of Alzheimer's disease (AD), recent evidence demonstrated that atrophies of hippocampal subregions might be more sensitive in predicting this neurodegenerative disease. The vast majority of neuroimaging papers investigating this topic are focused on the difference between AD and patients with mild cognitive impairment (MCI), not considering the impact of MCI patients who will or not convert in AD. For this reason, the aim of this study was to determine if measurements of hippocampal subfields provide advantages over total hippocampal volume for discriminating these groups. Hippocampal subfields volumetry was extracted in 55 AD, 32 converted and 89 not-converted MCI (c/nc-MCI) and 47 healthy controls, using an atlas-based automatic algorithm based on Markov random fields embedded in the Freesurfer framework. To evaluate the impact of hippocampal atrophy in discriminating the insurgence of AD-like phenotypes we used three classification methods: Support Vector Machine, Naïve Bayesian Classifier and Neural Networks Classifier. Taking into account only the total hippocampal volume, all classification models, reached a sensitivity of about 66% in discriminating between c-MCI and nc-MCI. Otherwise, classification analysis considering all segmenting subfields increased accuracy to diagnose c-MCI from 68% to 72%. This effect resulted to be strongly dependent upon atrophies of the subiculum and presubiculum. Our multivariate analysis revealed that the magnitude of the difference considering hippocampal subfield volumetry, as segmented by the considered atlas-based automatic algorithm, offers an advantage over hippocampal volume in distinguishing early AD from nc-MCI.