Introducing Robust Statistics in the Uncertainty Quantification of Nuclear Safeguards Measurements

The monitoring of nuclear safeguards measurements consists of verifying the coherence between the operator declarations and the corresponding inspector measurements on the same nuclear items. Significant deviations may be present in the data, as consequence of problems with the operator and/or inspector measurement systems. However, they could also be the result of data falsification. In both cases, quantitative analysis and statistical outcomes may be negatively affected by their presence unless robust statistical methods are used. This article aims to investigate the benefits deriving from the introduction of robust procedures in the nuclear safeguards context. In particular, we will introduce a robust estimator for the estimation of the uncertainty components of the measurement error model. The analysis will prove the capacity of robust procedures to limit the bias in simulated and empirical contexts to provide more sounding statistical outcomes. For these reasons, the introduction of robust procedures may represent a step forward in the still ongoing development of reliable uncertainty quantification methods for error variance estimation.

Testing for Benford’s Law in very small samples: Simulation study and a new test proposal

Benford’s Law defines a statistical distribution for the first and higher order digits in many datasets. Under very general condition, numbers are expected to naturally conform to the theorized digits pattern. On the other side, any deviation from the Benford distribution could identify an exogenous modification of the expected pattern, due to data manipulation or even fraud. Many statistical tests are available for assessing the Benford conformity of a sample. However, in some practical applications, the limited number of data to analyze may raise questions concerning their reliability. The first aim of this article is then to analyze and compare the behavior of Benford conformity testing procedures applied to very small samples through an extensive Monte Carlo experiment. Simulations will consider a thorough choice of compliance tests and a very heterogeneous selection of alternative distributions. Secondly, we will use the simulation results for defining a new testing procedure, based on the combination of three tests, that guarantees suitable levels of power in each alternative scenario. Finally, a practical application is provided, demonstrating how a sounding testing Benford compliance test for very small samples is important and profitable in anti-fraud investigations.

Pain and agitation treatment in severe dementia patients: The need for Italian Mobilization-Observation-Behavior-Intensity-Dementia (I-MOBID2) pain scale translation, adaptation and validation with psychometric testing

The 97% of dementia patients develops fluctuant neuropsychiatric symptoms often related to under-diagnosed and unrelieved pain. Up to 80% severe demented nursing home residents experiences chronic pain due to age-related comorbidities. Patients lacking self-report skills risk not to be appropriately treated for pain. Mobilization-Observation-Behavior-Intensity-Dementia (MOBID2) is the sole pain scale to consider the frequent co-occurrence of musculoskeletal and visceral pain and to unravel concealed pain through active guided movements. Accordingly, the Italian real-world setting can benefit from its translation and validation. This clinical study provides a translated, adapted and validated version of the MOBID2, the Italian I-MOBID2. The translation, adaptation and validation of the scale for non-verbal, severe demented patients was conducted according to current guidelines in a cohort of 11 patients over 65 with mini-mental state examination ≤ 12. The I-MOBID2 proves: good face and scale content validity index (0.89); reliable internal consistency (Cronbach's α = 0.751); good to excellent inter-rater (Intraclass correlation coefficient, and test-retest (ICC = 0.902) reliability. The construct validity is high (Rho = 0.748 p < 0.05 for 11 patients, Spearman rank order correlation of the overall pain intensity score with the maximum item score of I-MOBID2 Part 1; rho=0.895 p < 0.01 for 11 patients, for the overall pain intensity score with the maximum item score of I-MOBID2 Part 2) and a good rate of inter-rater and test-retest agreement was demonstrated by Cohen's K = 0.744. The average execution time is of 5.8 min, thus making I-MOBID2 a useful tool suitable also for future development in community setting with administration by caregivers.

Increased functional connectivity within mesocortical networks in open people

Openness is a personality trait reflecting absorption in sensory experience, preference for novelty, and creativity, and is thus considered a driving force of human evolution. At the brain level, a relation between openness and dopaminergic circuits has been proposed, although evidence to support this hypothesis is lacking. Recent behavioral research has also found that people with mania, a psychopathological condition linked to dopaminergic dysfunctions, may display high levels of openness. However, whether openness is related to dopaminergic circuits has not been determined thus far. We addressed this issue via three functional magnetic resonance imaging (fMRI) experiments in n=46 healthy volunteers. In the first experiment participants lied at rest in the scanner while in the other two experiments they performed active tasks that included the presentation of pleasant odors and pictures of food. Individual differences in openness and other personality traits were assessed via the NEO-PI-R questionnaire (NEO-Personality Inventory-Revised), a widely employed measure of the five-factor model personality traits. Correlation between fMRI and personality data was analyzed via state-of-art methods assessing resting-state and task-related functional connectivity within specific brain networks. Openness was positively associated with the functional connectivity between the right substantia nigra/ventral tegmental area, the major source of dopaminergic inputs in the brain, and the ipsilateral dorsolateral prefrontal cortex (DLPFC), a key region in encoding, maintaining, and updating information that is relevant for adaptive behaviors. Of note, the same connectivity pattern was consistently found across all of the three fMRI experiments. Given the critical role of dopaminergic signal in gating information in DLPFC, the increased functional connectivity within mesocortical networks in open people may explain why these individuals display a wide "mental permeability" to salient stimuli and an increased absorption in sensory experience.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy

BACKGROUND

Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP).

METHOD

Morphological T1-weighted Magnetic Resonance Images (MRIs) of PD patients (28), PSP patients (28) and healthy control subjects (28) were used by a supervised machine learning algorithm based on the combination of Principal Components Analysis as feature extraction technique and on Support Vector Machines as classification algorithm. The algorithm was able to obtain voxel-based morphological biomarkers of PD and PSP.

RESULTS

The algorithm allowed individual diagnosis of PD versus controls, PSP versus controls and PSP versus PD with an Accuracy, Specificity and Sensitivity>90%. Voxels influencing classification between PD and PSP patients involved midbrain, pons, corpus callosum and thalamus, four critical regions known to be strongly involved in the pathophysiological mechanisms of PSP.

COMPARISON WITH EXISTING METHODS

Classification accuracy of individual PSP patients was consistent with previous manual morphological metrics and with other supervised machine learning application to MRI data, whereas accuracy in the detection of individual PD patients was significantly higher with our classification method.

CONCLUSIONS

The algorithm provides excellent discrimination of PD patients from PSP patients at an individual level, thus encouraging the application of computer-based diagnosis in clinical practice.

Advanced MRI morphologic study shows no atrophy in healthy individuals with hippocampal hyperintensity

We have already shown that brain MR imaging of healthy individuals frequently reveals either unilateral or bilateral Hh, which is considered a hallmark of hippocampal sclerosis. We performed a follow-up (5-year interval) clinical and advanced imaging study of these individuals to address whether Hh may have masked occult brain atrophy or contributed to a later onset of epilepsy. Subjects with Hh (n = 13) underwent a detailed clinical-imaging protocol, with a 3T scan and were studied with automated hippocampal segmentation (FreeSurfer), whole brain voxel-based morphometry, and shape analysis. All 13 subjects with Hh had normal neurologic examination findings with no cognitive impairment. Multimodal structural neuroimaging methods did not show clear evidence of significant volumetric changes between subjects with or without Hh. We clearly showed that Hh is not associated with any occult brain atrophy; furthermore, none of the healthy subjects with MR imaging evidence of Hh developed epilepsy or trouble with cognition.

Met158 variant of the catechol-O-methyltransferase genotype is associated with thicker cortex in adult brain

Cortical thickness has been proposed as a new promising brain imaging endophenotype in elucidating the nature of gene-brain relationships. Here, we define the morphological impact of the Val(158)Met polymorphism in the catechol-O-methyltransferase (COMT) gene on human brain anatomy. One hundred and forty-nine adult healthy subjects (mean age: 40.7+/-16.1; ranging from 19 to 76 years) were genotyped (38 in the homozygous Val(158) group; 80 in the Val(158)Met group; 31 in the homozygous Met(158) group) for the COMT polymorphism and underwent morphological examination. Surface-based analysis of the cortical mantle showed that the COMT genotype was associated with structural differences in the right superior temporal sulcus and inferior prefrontal sulcus, where the individuals carrying the Met(158) allele had a thicker cortex with respect to their Val(158) counterparts. Our study extends the previous evidence found on pediatric population to the adult population, demonstrating that the higher synaptic dopamine levels associated with the presence of the Met(158) allele may influence neuronal architecture in brain structures important for executive and emotional processing.

Cognitive deficits in multiple sclerosis patients with cerebellar symptoms

Background

Cerebellar dysfunction is common in patients with multiple sclerosis (MS). However, neuropsychological studies of this clinical feature are lacking.

Objective

We investigate the neuropsychological features in relapsing-remitting MS (RR-MS) patients with and without cerebellar dysfunction.

Methods

Twenty-one RR-MS patients with cerebellar dysfunction (RR-MSc), characterized by prevalent ataxic gait and nystagmus, and 21 RR-MS patients without any cerebellar manifestation (RR-MSnc) pair-matched for demographical and clinical variables were studied. All patients from each group underwent an extensive battery of neuropsychological tests. Magnetic resonance imaging analysis included hyperintense fast fluid-attenuated inversion-recovery lesion load in the whole brain as well as in the four lobes separately.

Results

Any significant differences were detected in total and regional lesion load measurements between the two groups. RR-MSc group performed equally as well as the RR-MSnc group on many of the cognitive exploration measures. Nevertheless, the RR-MSc group performed more poorly than the RR-MSnc group on attention tests (Symbol Digit Modalities Test) and verbal fluency tests (Controlled Oral Word Association Test); neither of the test results proved to be affected by regional lesion loads.

Conclusion

These results highlight the importance of considering cognitive deficits associated with the presence of cerebellar symptoms in RR-MS.

Cerebellar atrophy in essential tremor using an automated segmentation method

BACKGROUND AND PURPOSE

Essential tremor (ET) is a slowly progressive disorder characterized by postural and kinetic tremors most commonly affecting the forearms and hands. Several lines of evidence from physiologic and neuroimaging studies point toward a major role of the cerebellum in this disease. Recently, voxel-based morphometry (VBM) has been proposed to quantify cerebellar atrophy in ET. However, VBM was not originally designed to study subcortical structures, and the complicated anatomy of the cerebellum may hamper the automatic processing of VBM. The aim of this study was to determine the efficacy and utility of using automated subcortical segmentation to identify atrophy of the cerebellum and other subcortical structures in patients with ET.

MATERIALS AND METHODS

We used a recently developed automated volumetric method (FreeSurfer) to quantify subcortical atrophy in ET by comparing results obtained with this method with those provided by previous evidence. The study included T1-weighted MR images of 46 patients with ET grouped into those having arm ET (n = 27, a-ET) or head ET (n = 19, h-ET) and 28 healthy controls.

RESULTS

Results revealed the expected reduction of cerebellar volume in patients with h-ET with respect to healthy controls after controlling for intracranial volume. No significant difference was detected in any other subcortical area.

CONCLUSIONS

Volumetric data obtained with automated segmentation of subcortical and cerebellar structures approximate data from a previous study based on VBM. The current findings extend the literature by providing initial validation for using fully automated segmentation to derive cerebellar volumetric information from patients with ET.

Anti-GM1 antibodies are not associated with cerebral atrophy in patients with multiple sclerosis

Objectives

The aim of this study was to correlate the brain atrophy with serum levels of anti-GM1 antibodies in patients with relapsing–remitting multiple sclerosis (RRMS).

Methods

Plasma sample from 52 patients with RRMS and 65 healthy controls were examined for anti-GM1 antibodies. Patients with RRMS underwent to MRI study with automated method called SIENAX that calculated an estimate of gray matter (GMV) and white matter (WMV) volumes.

Results

The percentage of RRMS patients with increased anti-GM1 was 37.8%. Elevated levels of anti-GM1 antibodies did not correlate with brain atrophy.

Conclusions

Anti-GM1 antibodies do not represent a marker of axonal damage in patients with RRMS.

Essential head tremor is associated with cerebellar vermis atrophy: a volumetric and voxel-based morphometry MR imaging study

BACKGROUND AND PURPOSE

Our aim was to investigate the presence of brain gray matter (GM) abnormalities in patients with different forms of essential tremor (ET).

MATERIALS AND METHODS

We used optimized voxel-based morphometry (VBM) and manually traced single region-of-interest analysis in 50 patients with familial ET and in 32 healthy subjects. Thirty patients with ET had tremor of the arms (a-ET), whereas the remaining 20 patients had both arm and head tremor (h-ET).

RESULTS

VBM showed marked atrophy of the cerebellar vermis in the patients with h-ET with respect to healthy subjects (P(corrected) < .001). Patients with a-ET showed a trend toward a vermal GM volume loss that did not reach a significant difference with respect to healthy controls (P(uncorrected) < .01). The region-of-interest analysis showed a reduction of the cerebellar volume (CV) in the h-ET group (98.2 +/- 13.6 mm(3)) compared with healthy controls (110.5 +/- 15.5 mm(3), P < .012) as well as in the entire vermal area (790.3 +/- 94.5 mm(2), 898.6 +/- 170.6 mm(2), P < .04 in h-ET and control groups, respectively).

CONCLUSIONS

Atrophy of the cerebellar vermis detected in patients with h-ET strongly supports the evidence for the involvement of the cerebellum in the pathophysiology of ET. The lack of a significant CV loss observed in patients with a-ET suggests that a-ET and h-ET might represent distinct subtypes of the same disease.

Investigating the role of brain-derived neurotrophic factor in relapsing-remitting multiple sclerosis

Multiple sclerosis (MS) is a common, heterogeneous disorder of the central nervous system with a complex trait composed of both genetic and environmental factors. Recently, scientific interest has increased in defining factors that possibly contribute to brain functional plasticity; the results might be useful to assess the relationship between MS lesion burden and clinical events, as well as explaining the well-known phenotypic heterogeneity of the disease. In this study, we explored the effect of the Val66Met brain-derived neurotrophic factor (BDNF) functional polymorphism on cognitive performances and volumetric measurements obtained by magnetic resonance imaging of the brain in a selected population of relapsing-remitting MS (RRMS) patients, with relatively short disease duration and minimal clinical disability, compared to gender, age and educational-level matched healthy subjects. We found that in the RRMS group, the BDNF Met-allele was significantly associated with the lower volume of cerebral grey matter (GM) (P = 0.005). Furthermore, a significant (P = 0.013) interaction effect between 'MS-status' and the BDNF genotype was found for GM volumes, with the result that patients carrying the BDNF Met-allele showed a higher risk of developing global GM atrophy than the homozygous Val/Val. No BDNF-related impact on global neuropsychological functions resulted in either RRMS patients or controls. Our data seem to be consistent with the reported influence of BDNF in neuronal plasticity, thus suggesting that the Met-allele might have a negative prognostic effect on cortical morphometry in RRMS patients.

Psychological impact of sports activity in spinal cord injury patients

OBJECTIVE

To investigate whether sports activity is associated with better psychological profiles in patients with spinal cord injury (SCI) and to evaluate the effect of demographic factors on psychological benefits.

METHODS

The State-Trait Anxiety Inventory, Form X2 (STAI-X2), the Eysenck Personality Questionnaire for extraversion (EPQ-R (E)) and the questionnaire for depression (QD) were administered in a cross-sectional study of 137 males with spinal cord injury including 52 tetraplegics and 85 paraplegics. The subjects were divided into two groups according to sports activity participation (high frequency vs no sports participation). Moreover, multiple regression analysis was adopted to investigate the influence of demographic variables, such as age, educational level, occupational status and marital status, on psychological variables.

RESULTS

Analysis of variance revealed significant differences among the groups for anxiety (STAI-X2), extraversion (EPQ-R (E)) and depression (QD). In particular, SCI patients who did not practice sports showed higher anxiety and depression scores and lower extraversion scores than sports participants. In addition, with respect to the paraplegics, the tetraplegic group showed the lowest depression scores. Following multiple regression analysis, only the sports activity factor remained as an independent factor of anxiety scores.

CONCLUSION

These findings demonstrate that sports activity is associated with better psychological status in SCI patients, irrespective of tetraplegia and paraplegia, and that psychological benefits are not emphasized by demographic factors.

Evaluation of mixed effects in event-related fMRI studies: impact of first-level design and filtering

With the introduction of event-related designs in fMRI, it has become crucial to optimize design efficiency and temporal filtering to detect activations at the 1st level with high sensitivity. We investigate the relevance of these issues for fMRI population studies, that is, 2nd-level analysis, for a set of event-related fMRI (er-fMRI) designs with different 1st-level efficiencies, adopting three distinct 1st-level filtering strategies as implemented in SPM99, SPM2, and FSL3.0. By theory, experiments, and simulations using physiological fMRI noise, we show that both design and filtering impact the outcome of the statistical analysis, not only at the 1st but also at the 2nd level. There are several reasons behind this finding. First, sensitivity is affected by both design and filtering, since the scan-to-scan variance, that is the fixed effect, is not negligible with respect to the between-subject variance, that is the random effect, in er-fMRI population studies. The impact of the fixed effects error on the sensitivity of the mixed effects analysis can be mitigated by an optimal choice of er-fMRI design and filtering. Moreover, the accuracy of the 1st- and 2nd-level parameter estimates also depend on design and filtering; especially, we show that inaccuracies caused by the presence of residual noise autocorrelations can be constrained by designs that have hemodynamic responses with a Gaussian distribution. In conclusion, designs with both good efficiency and decorrelating properties, for example, such as the geometric or Latin square probability distributions, combined with the "whitening" filters of SPM2 and FSL3.0, give the best result, both for 1st- and 2nd-level analysis of er-fMRI studies.