Matteo Fraschini

Contrast enhancement of microcalcifications in mammograms using morphological enhancement and non-flat structuring elements

This paper presents an approach to enhancing the contrast of microcalcifications in mammograms using a contrast enhancement algorithm based on a combination of morphological enhancement and non-flat structuring elements. Given that microcalcifications appear as small domes on a 3D relief of a mammogram, enhancement is achieved by using structuring elements which have a 3D form.

An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies have focused mainly on basic features of the Electroencephalography. In this study we propose an approach based on phase synchronization, to investigate personal distinctive brain network organization. To this end, the importance, in terms of centrality, of different regions was determined on the basis of EEG recordings. We hypothesized that nodal centrality enables the accurate identification of individuals. EEG signals from a cohort of 109 64-channels EEGs were band-pass filtered in the classical frequency bands and functional connectivity between the sensors was estimated using the Phase Lag Index. The resulting connectivity matrix was used to construct a weighted network, from which the nodal Eigenvector Centrality was computed. Nodal centrality was successively used as feature vector. Highest recognition rates were observed in the gamma band (equal error rate ( EER) = 0.044) and high beta band ( EER = 0.102). Slightly lower recognition rate was observed in the low beta band ( EER = 0.144), while poor recognition rates were observed for the others frequency bands. The reported results show that resting-state functional brain network topology provides better classification performance than using only a measure of functional connectivity, and may represent an optimal solution for the design of next generation EEG based biometric systems. This study also suggests that results from biometric systems based on high-frequency scalp EEG features should be interpreted with caution.

The effect of epoch length on estimated EEG functional connectivity and brain network organisation

OBJECTIVE Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. APPROACH The aim of this study was to provide a network approach insensitive to the effects that epoch length has on functional connectivity and network reconstruction. Two different measures, the phase lag index (PLI) and the amplitude envelope correlation (AEC) were applied to EEG resting-state recordings for a group of 18 healthy volunteers using non-overlapping epochs with variable length (1, 2, 4, 6, 8, 10, 12, 14 and 16 s). Weighted clustering coefficient (CCw), weighted characteristic path length (L w) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. MAIN RESULTS Results from scalp analysis show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 s for PLI and 6 s for AEC. Moreover, CCw and L w show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1-6 s versus 4-8 s for AEC). At the source-level the results were even more reliable, with stability already at 1 s duration for PLI-based MSTs. SIGNIFICANCE The present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of brain network topology between different studies.

“Physiological” renal regenerating medicine in VLBW preterm infants: could a dream come true?

An emerging hypothesis from the recent literature explain how specific adverse factors related with growth retardation as well as of low birth weight (LBW) might influence renal development during fetal life and then the insurgence of hypertension and renal disease in adulthood. In this article, after introducing a brief overview of human nephrogenesis, the most important factors influencing nephron number at birth will be reviewed, focusing on the “in utero” experiences that lead to an increased risk of developing hypertension and/or kidney disease in adult. Since nephrogenesis in preterm human newborns does not stop at birth, but it continues for 4–6 weeks postnatally, a better knowledge of the mechanisms able to accelerate nephrogenesis in the perinatal period, could represent a powerful tool in the hands of neonatologists. We suggest to define this approach to a possible therapy of a deficient nephrogenesis at birth “physiological renal regenerating medicine”. Our goal in preterm infants, especially VLBW, could be to prolong the nephrogenesis not only for 6 weeks after birth but until 36 weeks of post conceptual age, allowing newborn kidneys to restore their nephron endowment, escaping susceptibility to hypertension and to renal disease later in life.

Brain network analysis of EEG functional connectivity during imagery hand movements.

The characterization of human neural activity during imaginary movement tasks represent an important challenge in order to develop effective applications that allow the control of a machine. Yet methods based on brain network analysis of functional connectivity have been scarcely investigated. As a result we use graph theoretic methods to investigate the functional connectivity and brain network measures in order to characterize imagery hand movements in a set of healthy subjects. The results of the present study show that functional connectivity analysis and minimum spanning tree (MST) parameters allow to successfully discriminate between imagery hand movements (both right and left) and resting state conditions. In conclusion, this paper shows that brain network analysis of EEG functional connectivity could represent an efficient alternative to more classical local activation based approaches. Furthermore, it also suggests the shift toward methods based on the characterization of a limited set of fundamental functional connections that disclose salient network topological features.

The re-organization of functional brain networks in pharmaco-resistant epileptic patients who respond to VNS.

Vagal nerve stimulation (VNS) is a therapeutic add-on treatment for patients with pharmaco-resistant epilepsy. The mechanism of action is still largely unknown. Previous studies have shown that brain network topology during the inter-ictal period in epileptic patients deviates from normal configuration. In the present paper, we investigate the relationship between clinical improvement induced by VNS and alterations in brain network topology. We hypothesize that, as a consequence of the VNS add-on treatment, functional brain network architecture shifts back toward a more efficient configuration in patients responding to VNS. Electroencephalographic (EEG) recordings from ten patients affected by pharmaco-resistant epilepsy were analyzed in the classical EEG frequency bands. The phase lag index (PLI) was used to estimate functional connectivity between EEG channels and the minimum spanning tree (MST) was computed in order to characterize VNS-induced alterations in network topology in a bias-free way. Our results revealed a clear network re-organization, in terms of MST modification, toward a more integrated architecture in patients responding to the VNS. In particular, the results show a significant interaction effect between benefit from VNS (responders/non-responders) and condition (pre/post VNS implantation) in the theta band. This finding suggests that the positive effect induced by VNS add-on treatment in epileptic patients is related to a clear network re-organization and that this network modification can reveal the long debated mechanism of action of VNS. Therefore, MST analysis could be useful in evaluating and monitoring the efficacy of VNS add-on treatment potentially in both epilepsy and psychiatric diseases.

VNS induced desynchronization in gamma bands correlates with positive clinical outcome in temporal lobe pharmacoresistant epilepsy

The vagus nerve stimulation (VNS) represents a diffuse non-pharmacological low-risk surgical option for epilepsy treatment. The aim of this study is to investigate the correlation between variations of global EEG synchronization and the clinical outcome in pharmacoresistant epileptic subjects implanted with VNS. Ten subjects affected by pharmacoresistant epilepsy were recruited on the basis of a clear-cut successful or unsuccessful outcome of the VNS add-on treatment. After five years from VNS surgery we examined the EEG in five subjects in each group. The investigation was led with the method of the phase lag index (PLI), which allows for the study of the global rate of synchronicity among the EEG signals before and after VNS implantation. The results of this study show that after five years from VNS surgery, in subjects whose seizures show a significant reduction, the desynchronization in the gamma frequency band is statistically decreased in comparison with patients who failed to show variations in the frequency and characteristics of their seizures. The other frequency bands are unaffected. This finding suggests that long lasting variations in gamma band desynchronization can be a new tool in assessing the efficacy of VNS. The possibility that GABA-mediated VNS-induced effects can also play a role in this result is discussed.

Thymosin beta 4 expression in normal skin, colon mucosa and in tumor infiltrating mast cells.

Mast cells (MCs) are metachromatic cells that originate from multipotential hemopoietic stem cells in the bone marrow. Two distinct populations of MCs have been characterized: mucosal MCs are tryptase-positive while mast cells in skin contain tryptase and chymase. We now show that a sub-population of MCs is highly immunoreactive for thymosin β4, as revealed by immunohistochemical analyses of normal skin, normal colon mucosa and salivary gland tumors. Four consecutive serial sections from each case were immunostained for thymosin β4 (Tβ4), chymase, tryptase and stained for toluidine blue. In skin biopsies, MCs showed a comparable immunoreactivity for Tβ4, chymase and tryptase. In normal colon mucosa the vast majority of mucosal MCs expressed a strong cytoplasmic immunoreactivity for tryptase and for Tβ4, in the absence of chymase reactivity. A robust expression of Tβ4 was detected in tumor-infiltrating and peritumoral mast cells in salivary gland tumors and breast ductal infiltrating carcinomas. Tumorinfiltrating MCs also showed a strong immunoreactivity for chymase and tryptase. In this paper, we first demonstrate that normal dermal and mucosal mast cells exhibit strong expression of thymosin β4, which could be considered a new marker for the identification of mast cells in skin biopsies as well as in human tumors. The possible relationship between the degree of Tβ4 expression in tumor-infiltrating mast cells and tumor behaviour warrants further consideration in future investigations.

CINtec PLUS Immunocytochemistry as a Tool for the Cytologic Diagnosis of Glandular Lesions of the Cervix Uteri

Cytologic findings of glandular lesions of the cervix uteri are often difficult to evaluate. We studied the usefulness of CINtec PLUS p16/Ki-67 double stain (mtm laboratories, Heidelberg, Germany) for the diagnosis of glandular lesions. The study included 47 abnormal results on liquid-based cytologic tests with a subsequent histologic diagnosis of adenocarcinoma in situ or with early invasion, and 16 samples with negative results on follow-up. All samples were stained with CINtec PLUS p16/Ki-67 double stain. Of the neoplastic samples, 7 were excluded because of insufficient residual cellularity or loss of neoplastic cells. Of the samples that were adequate, 92.5% were stained with CINtec PLUS, whereas 7.5% were judged inconclusive. All inconclusive cases were at least 3 years old. Of the 16 negative samples, 15 (93.8%) stained negative and only 1 (6.2%) showed several positive clusters of cells. Our study shows that CINtec PLUS is a robust and useful tool for the diagnosis of glandular lesions of the cervix uteri.

Changes in MEG resting-state networks are related to cognitive decline in type 1 diabetes mellitus patients.

Objective Integrity of resting-state functional brain networks (RSNs) is important for proper cognitive functioning. In type 1 diabetes mellitus (T1DM) cognitive decrements are commonly observed, possibly due to alterations in RSNs, which may vary according to microvascular complication status. Thus, we tested the hypothesis that functional connectivity in RSNs differs according to clinical status and correlates with cognition in T1DM patients, using an unbiased approach with high spatio-temporal resolution functional network. Methods Resting-state magnetoencephalographic (MEG) data for T1DM patients with (n = 42) and without (n = 41) microvascular complications and 33 healthy participants were recorded. MEG time-series at source level were reconstructed using a recently developed atlas-based beamformer. Functional connectivity within classical frequency bands, estimated by the phase lag index (PLI), was calculated within eight commonly found RSNs. Neuropsychological tests were used to assess cognitive performance, and the relation with RSNs was evaluated. Results Significant differences in terms of RSN functional connectivity between the three groups were observed in the lower alpha band, in the default-mode (DMN), executive control (ECN) and sensorimotor (SMN) RSNs. T1DM patients with microvascular complications showed the weakest functional connectivity in these networks relative to the other groups. For DMN, functional connectivity was higher in patients without microangiopathy relative to controls (all p < 0.05). General cognitive performance for both patient groups was worse compared with healthy controls. Lower DMN alpha band functional connectivity correlated with poorer general cognitive ability in patients with microvascular complications. Discussion Altered RSN functional connectivity was found in T1DM patients depending on clinical status. Lower DMN functional connectivity was related to poorer cognitive functioning. These results indicate that functional connectivity may play a key role in T1DM-related cognitive dysfunction.