Oncological features and outcomes of laryngeal cancer surgery: a multicentric study.

BACKGROUND: Laryngeal cancer (LC) is among of the most frequent head and neck cancers, associated to a high social impact and mortality. Unfortunately, the current treatment outcomes of LC are often scant, with different factors affecting patient's prognosis (i.e., advanced age, advanced disease stage, lymph node involvement, tumor pathological features, type of intervention). The aims of the present study were: 1) to evaluate the epidemiological and clinical features of patients affected by LC; and 2) to focus on tumor risk factors affecting patient's overall survival (OS) and recurrences. METHODS: A retrospective analysis of all patients affected by LC and surgically treated at two different hospital settings has been performed. RESULTS: Two hundred twenty-five patients were enrolled in the present study; of these 189 were males (84%) and 36 (16%) were females. The most frequently performed surgery was total laryngectomy. Thirty-two (14.2%) patients experienced local recurrence, while 15 patients (6.6%) had regional recurrence and 15 distant metastases. Multivariate analysis showed that locoregional recurrence was associated to the occurrence of distant metastases (P=0.002, HR=25,35). Analyzing OS, the only statistically significant factor that correlated with an increased risk of mortality (P<0.015, HR=2,45) was locoregional recurrence. CONCLUSIONS: The present study confirms the literature data about age and sex distribution of LC, about tumors localization, lymph nodes metastasis and distant metastasis incidence and OS rate, based on T and N stage. Interestingly, within this series, the presence of locoregional recurrence or distant metastasis is related to a worst prognosis and a lower overall survival rate.

Peg3/PW1 Is a Marker of a Subset of Vessel Associated Endothelial Progenitors.

Vascular associated endothelial cell (ECs) progenitors are still poorly studied and their role in the newly forming vasculature at embryonic or postnatal stage remains elusive. In the present work, we first defined a set of genes highly expressed during embryo development and strongly downregulated in the adult mouse. In this group, we then concentrated on the progenitor cell marker Peg3/PW1. By in vivo staining of the vasculature we found that only a subset of cells coexpressed endothelial markers and PW1. These cells were quite abundant in the embryo vasculature but declined in number at postnatal and adult stages. Using a reporter mouse for PW1 expression, we have been able to isolate PW1-positive (PW1posECs) and negative endothelial cells (PW1negECs). PW1-positive cells were highly proliferative in comparison to PW1negECs and were able to form colonies when seeded at clonal dilution. Furthermore, by RNAseq analysis, PW1posECs expressed endothelial cell markers together with mesenchymal and stem cell markers. When challenged by endothelial growth factors in vitro, PW1posECs were able to proliferate more than PW1negECs and to efficiently form new vessels in vivo. Taken together these data identify a subset of vessel associated endothelial cells with characteristics of progenitor cells. Considering their high proliferative potential these cells may be of particular importance to design therapies to improve the perfusion of ischemic tissues or to promote vascular repair. Stem Cells 2017;35:1328-1340.

Sulindac metabolites decrease cerebrovascular malformations in CCM3-knockout mice.

Cerebral cavernous malformation (CCM) is a disease of the central nervous system causing hemorrhage-prone multiple lumen vascular malformations and very severe neurological consequences. At present, the only recommended treatment of CCM is surgical. Because surgery is often not applicable, pharmacological treatment would be highly desirable. We describe here a murine model of the disease that develops after endothelial-cell-selective ablation of the CCM3 gene. We report an early, cell-autonomous, Wnt-receptor-independent stimulation of ß-catenin transcription activity in CCM3-deficient endothelial cells both in vitro and in vivo and a triggering of a ß-catenin-driven transcription program that leads to endothelial-to-mesenchymal transition. TGF-ß/BMP signaling is then required for the progression of the disease. We also found that the anti-inflammatory drugs sulindac sulfide and sulindac sulfone, which attenuate ß-catenin transcription activity, reduce vascular malformations in endothelial CCM3-deficient mice. This study opens previously unidentified perspectives for an effective pharmacological therapy of intracranial vascular cavernomas.

Hippocampal atrophy in people with memory deficits: results from the population-based IPREA study.

BACKGROUND: Clinical studies have shown that hippocampal atrophy is present before dementia in people with memory deficits and can predict dementia development. The question remains whether this association holds in the general population. This is of interest for the possible use of hippocampal atrophy to screen population for preventive interventions. The aim of this study was to assess hippocampal volume and shape abnormalities in elderly adults with memory deficits in a cross-sectional population-based study. METHODS: We included individuals participating in the Italian Project on the Epidemiology of Alzheimer Disease (IPREA) study: 75 cognitively normal individuals (HC), 31 individuals with memory deficits (MEM), and 31 individuals with memory deficits not otherwise specified (MEMnos). Hippocampal volumes and shape were extracted through manual tracing and the growing and adaptive meshes (GAMEs) shape-modeling algorithm. We investigated between-group differences in hippocampal volume and shape, and correlations with memory deficits. RESULTS: In MEM participants, hippocampal volumes were significantly smaller than in HC and were mildly associated with worse memory scores. Memory-associated shape changes mapped to the anterior hippocampus. Shape-based analysis detected no significant difference between MEM and HC, while MEMnos showed shape changes in the posterior hippocampus compared with HC and MEM groups. CONCLUSIONS: These findings support the discriminant validity of hippocampal volumetry as a biomarker of memory impairment in the general population. The detection of shape changes in MEMnos but not in MEM participants suggests that shape-based biomarkers might lack sensitivity to detect Alzheimer's-like pathology in the general population.

Germinal center dysregulation by histone methyltransferase EZH2 promotes lymphomagenesis.

Protection against deadly pathogens requires the production of high-affinity antibodies by B cells, which are generated in germinal centers (GCs). Alteration of the GC developmental program is common in many B cell malignancies. Identification of regulators of the GC response is crucial to develop targeted therapies for GC B cell dysfunctions, including lymphomas. The histone H3 lysine 27 methyltransferase enhancer of zeste homolog 2 (EZH2) is highly expressed in GC B cells and is often constitutively activated in GC-derived non-Hodgkin lymphomas (NHLs). The function of EZH2 in GC B cells remains largely unknown. Herein, we show that Ezh2 inactivation in mouse GC B cells caused profound impairment of GC responses, memory B cell formation, and humoral immunity. EZH2 protected GC B cells against activation-induced cytidine deaminase (AID) mutagenesis, facilitated cell cycle progression, and silenced plasma cell determinant and tumor suppressor B-lymphocyte-induced maturation protein 1 (BLIMP1). EZH2 inhibition in NHL cells induced BLIMP1, which impaired tumor growth. In conclusion, EZH2 sustains AID function and prevents terminal differentiation of GC B cells, which allows antibody diversification and affinity maturation. Dysregulation of the GC reaction by constitutively active EZH2 facilitates lymphomagenesis and identifies EZH2 as a possible therapeutic target in NHL and other GC-derived B cell diseases.

Wnt activation of immortalized brain endothelial cells as a tool for generating a standardized model of the blood brain barrier in vitro.

Reproducing the characteristics and the functional responses of the blood-brain barrier (BBB) in vitro represents an important task for the research community, and would be a critical biotechnological breakthrough. Pharmaceutical and biotechnology industries provide strong demand for inexpensive and easy-to-handle in vitro BBB models to screen novel drug candidates. Recently, it was shown that canonical Wnt signaling is responsible for the induction of the BBB properties in the neonatal brain microvasculature in vivo. In the present study, following on from earlier observations, we have developed a novel model of the BBB in vitro that may be suitable for large scale screening assays. This model is based on immortalized endothelial cell lines derived from murine and human brain, with no need for co-culture with astrocytes. To maintain the BBB endothelial cell properties, the cell lines are cultured in the presence of Wnt3a or drugs that stabilize ß-catenin, or they are infected with a transcriptionally active form of ß-catenin. Upon these treatments, the cell lines maintain expression of BBB-specific markers, which results in elevated transendothelial electrical resistance and reduced cell permeability. Importantly, these properties are retained for several passages in culture, and they can be reproduced and maintained in different laboratories over time. We conclude that the brain-derived endothelial cell lines that we have investigated gain their specialized characteristics upon activation of the canonical Wnt pathway. This model may be thus suitable to test the BBB permeability to chemicals or large molecular weight proteins, transmigration of inflammatory cells, treatments with cytokines, and genetic manipulation.

EndMT contributes to the onset and progression of cerebral cavernous malformations.

Cerebral cavernous malformation (CCM) is a vascular dysplasia, mainly localized within the brain and affecting up to 0.5% of the human population. CCM lesions are formed by enlarged and irregular blood vessels that often result in cerebral haemorrhages. CCM is caused by loss-of-function mutations in one of three genes, namely CCM1 (also known as KRIT1), CCM2 (OSM) and CCM3 (PDCD10), and occurs in both sporadic and familial forms. Recent studies have investigated the cause of vascular dysplasia and fragility in CCM, but the in vivo functions of this ternary complex remain unclear. Postnatal deletion of any of the three Ccm genes in mouse endothelium results in a severe phenotype, characterized by multiple brain vascular malformations that are markedly similar to human CCM lesions. Endothelial-to-mesenchymal transition (EndMT) has been described in different pathologies, and it is defined as the acquisition of mesenchymal- and stem-cell-like characteristics by the endothelium. Here we show that endothelial-specific disruption of the Ccm1 gene in mice induces EndMT, which contributes to the development of vascular malformations. EndMT in CCM1-ablated endothelial cells is mediated by the upregulation of endogenous BMP6 that, in turn, activates the transforming growth factor-ß (TGF-ß) and bone morphogenetic protein (BMP) signalling pathway. Inhibitors of the TGF-ß and BMP pathway prevent EndMT both in vitro and in vivo and reduce the number and size of vascular lesions in CCM1-deficient mice. Thus, increased TGF-ß and BMP signalling, and the consequent EndMT of CCM1-null endothelial cells, are crucial events in the onset and progression of CCM disease. These studies offer novel therapeutic opportunities for this severe, and so far incurable, pathology.

Cerebral atrophy in elderly with subjective memory complaints.

PURPOSE: To evaluate ventricular shape differences along the complete surface of the lateral and third ventricles of persons with subjective memory complaints (MC). MATERIALS AND METHODS: We included 28 controls and 21 persons with MC. FLAIR, T2, and PD-weighted brain MRI scans were acquired at 1.5 Tesla, followed by semi-automated segmentation of the lateral and third ventricles, and local shape difference analysis based on growing and adaptive meshes. Ventricular meshes were used to highlight local areas with significant differences between controls and persons with MC, determined by permutation tests with a predefined threshold (P = 0.01). RESULTS: Compared with control subjects, relevant differences were found in the shape of the ventricular surface adjacent to the thalamus and corona radiata in persons with MC. Before correction for multiple comparisons, relevant differences were also found in the shape of the ventricular surface adjacent to the corpus callosum, hippocampus, and amydala. CONCLUSION: Our findings suggest the presence of localized structural brain differences in patients with subjective memory complaints in the thalamus and the corona radiata.

Non-parametric model selection for subject-specific topological organization of resting-state functional connectivity.

In recent years, graph theory has been successfully applied to study functional and anatomical connectivity networks in the human brain. Most of these networks have shown small-world topological characteristics: high efficiency in long distance communication between nodes, combined with highly interconnected local clusters of nodes. Moreover, functional studies performed at high resolutions have presented convincing evidence that resting-state functional connectivity networks exhibits (exponentially truncated) scale-free behavior. Such evidence, however, was mostly presented qualitatively, in terms of linear regressions of the degree distributions on log-log plots. Even when quantitative measures were given, these were usually limited to the r(2) correlation coefficient. However, the r(2) statistic is not an optimal estimator of explained variance, when dealing with (truncated) power-law models. Recent developments in statistics have introduced new non-parametric approaches, based on the Kolmogorov-Smirnov test, for the problem of model selection. In this work, we have built on this idea to statistically tackle the issue of model selection for the degree distribution of functional connectivity at rest. The analysis, performed at voxel level and in a subject-specific fashion, confirmed the superiority of a truncated power-law model, showing high consistency across subjects. Moreover, the most highly connected voxels were found to be consistently part of the default mode network. Our results provide statistically sound support to the evidence previously presented in literature for a truncated power-law model of resting-state functional connectivity.

Shape abnormalities of the striatum in Alzheimer's disease.

Postmortem studies show pathological changes in the striatum in Alzheimer's disease (AD). Here, we examine the surface of the striatum in AD and assess whether changes of the surface are associated with impaired cognitive functioning. The shape of the striatum (n. accumbens, caudate nucleus, and putamen) was compared between 35 AD patients and 35 individuals without cognitive impairment. The striatum was automatically segmented from 3D T1 magnetic resonance images and automatic shape modeling tools (Growing Adaptive Meshes) were applied for morphometrical analysis. Repeated permutation tests were used to identify locations of consistent shape deformities of the striatal surface in AD. Linear regression models, corrected for age, gender, educational level, head size, and total brain parenchymal volume were used to assess the relation between cognitive performance and local surface deformities. In AD patients, differences of shape were observed on the medial head of the caudate nucleus and on the ventral lateral putamen, but not on the accumbens. The head of the caudate nucleus and ventral lateral putamen are characterized by extensive connections with the orbitofrontal and medial temporal cortices. Severity of cognitive impairment was associated with the degree of deformity of the surfaces of the accumbens, rostral medial caudate nucleus, and ventral lateral putamen. These findings provide evidence for the hypothesis that in AD primarily associative and limbic cerebral networks are affected.

Whole brain resting-state analysis reveals decreased functional connectivity in major depression.

Recently, both increases and decreases in resting-state functional connectivity have been found in major depression. However, these studies only assessed functional connectivity within a specific network or between a few regions of interest, while comorbidity and use of medication was not always controlled for. Therefore, the aim of the current study was to investigate whole-brain functional connectivity, unbiased by a priori definition of regions or networks of interest, in medication-free depressive patients without comorbidity. We analyzed resting-state fMRI data of 19 medication-free patients with a recent diagnosis of major depression (within 6 months before inclusion) and no comorbidity, and 19 age- and gender-matched controls. Independent component analysis was employed on the concatenated data sets of all participants. Thirteen functionally relevant networks were identified, describing the entire study sample. Next, individual representations of the networks were created using a dual regression method. Statistical inference was subsequently done on these spatial maps using voxel-wise permutation tests. Abnormal functional connectivity was found within three resting-state networks in depression: (1) decreased bilateral amygdala and left anterior insula connectivity in an affective network, (2) reduced connectivity of the left frontal pole in a network associated with attention and working memory, and (3) decreased bilateral lingual gyrus connectivity within ventromedial visual regions. None of these effects were associated with symptom severity or gray matter density. We found abnormal resting-state functional connectivity not previously associated with major depression, which might relate to abnormal affect regulation and mild cognitive deficits, both associated with the symptomatology of the disorder.

Morphological hippocampal markers for automated detection of Alzheimer's disease and mild cognitive impairment converters in magnetic resonance images.

In this study, we investigated the use of hippocampal shape-based markers for automatic detection of Alzheimer's disease (AD) and mild cognitive impairment converters (MCI-c). Three-dimensional T1-weighted magnetic resonance images of 50 AD subjects, 50 age-matched controls, 15 MCI-c, and 15 MCI-non-converters (MCI-nc) were taken. Manual delineations of both hippocampi were obtained from normalized images. Fully automatic shape modeling was used to generate comparable meshes for both structures. Repeated permutation tests, run over a randomly sub-sampled training set (25 controls and 25 ADs), highlighted shape-based markers, mostly located in the CA1 sector, which consistently discriminated ADs and controls. Support vector machines (SVMs) were trained, using markers from either one or both hippocampi, to automatically classify control and AD subjects. Leave-1-out cross-validations over the remaining 25 ADs and 25 controls resulted in an optimal accuracy of 90% (sensitivity 92%), for markers in the left hippocampus. The same morphological markers were used to train SVMs for MCI-c versus MCI-nc classification: markers in the right hippocampus reached an accuracy (and sensitivity) of 80%. Due to the pattern recognition framework, our results statistically represent the expected performances of clinical set-ups, and compare favorably to analyses based on hippocampal volumes.

Anatomic considerations of cochlear morphology and its implications for insertion trauma in cochlear implant surgery.

HYPOTHESIS: The goal of this study is to analyze the 3-dimensional anatomy of the cochlear spiral and to investigate the consequences of its course to insertion trauma during cochlear implantation. BACKGROUND: Insertion trauma in cochlear implant surgery is a feared surgical risk, potentially causing neural degeneration and altered performance of the implant. In literature, insertion trauma is reported to occur at specific locations. This has been ascribed to surgical technique and electrode design in relation to the size of the scala tympani. This study investigates whether there is an underlying anatomic substrate serving as a potential source for insertion trauma at these specific locations. METHODS: The 3-dimensional path of the cochlear spiral of 8 human temporal bones was determined by segmentation, skeletonization, distance mapping, and wave propagation technique applied on microcomputer tomography images. Potential pressure points along this path were estimated with linear regression. RESULTS: The cochlear lumen shows a noncontinuous spiraling path leading to potential pressure points during cochlear implantation at the basilar membrane in the region of 180 to 225 (12-14 mm) and 725 degrees (22-26 mm) and at the floor of the scala tympani around 0 to 90, 225 to 270, and 405 to 450 degrees. CONCLUSION: Our data favor the idea that the intrinsic 3-dimensional cochlear morphology contributes to the risk for insertion trauma during cochlear implantation at specific locations.

Hierarchical functional modularity in the resting-state human brain.

Functional magnetic resonance imaging (fMRI) studies have shown that anatomically distinct brain regions are functionally connected during the resting state. Basic topological properties in the brain functional connectivity (BFC) map have highlighted the BFC's small-world topology. Modularity, a more advanced topological property, has been hypothesized to be evolutionary advantageous, contributing to adaptive aspects of anatomical and functional brain connectivity. However, current definitions of modularity for complex networks focus on nonoverlapping clusters, and are seriously limited by disregarding inclusive relationships. Therefore, BFC's modularity has been mainly qualitatively investigated. Here, we introduce a new definition of modularity, based on a recently improved clustering measurement, which overcomes limitations of previous definitions, and apply it to the study of BFC in resting state fMRI of 53 healthy subjects. Results show hierarchical functional modularity in the brain.

Autonomous virtual mobile robot for three-dimensional medical image exploration: application to micro-CT cochlear images.

OBJECTIVE: In this paper, we present an autonomous virtual mobile robot (AVMR) for three-dimensional (3D) exploration of unknown tubular-like structures in 3D images. METHODS AND MATERIALS: The trajectory planning for 3D central navigation is achieved by combining two neuro-fuzzy controllers, and is based on 3D sensory information; a Hough transform is used to locally fit a cylinder during the exploration, estimating the local radius of the tube. Nonholonomic constraints are applied to assure a smooth, continuous and unique final path. When applied to 3D medical images, the AVMR operates as a virtual endoscope, directly providing anatomical measurements of the organ. After a thorough validation on challenging synthetic environments, we applied our method to eight micro-CT datasets of cochleae. RESULTS: Validation on synthetic environments proved the robustness of our method, and highlighted key parameters for the design of the AVMR. When applied to the micro-CT datasets, the AVMR automatically estimated length and radius of the cochleae: results were compared to manual delineations, proving the accuracy of our approach. CONCLUSIONS: The AVMR presents several advantages when used as a virtual endoscope: the nonholonomic constraint guarantees a unique and smooth central path, which can be reliably used both for qualitative and quantitative investigation of 3D medical datasets. Results on the micro-CT cochleae are a significant step towards the validation of more clinical computed tomography (CT) studies.

Ventricular shape biomarkers for Alzheimer's disease in clinical MR images.

The aim of this work was to identify ventricular shape-based biomarkers in MR images to discriminate between patients with Alzheimer's disease (AD) and healthy elderly. Clinical MR images were collected for 58 patients and 28 age-matched healthy controls. After normalizing all the images the ventricular cerebrospinal fluid was semiautomatically extracted for each subject and an innovative technique for fully automatic shape modeling was applied to generate comparable meshes of all ventricles. The search for potential biomarkers was carried out with repeated permutation tests: results highlighted well-defined areas of the ventricular surface being discriminating features for AD: the left inferior medial temporal horn, the right medial temporal horn (superior and inferior), and the areas close to the left anterior part of the corpus callosum and the head of the right caudate nucleus. The biomarkers were then used as features to build an intelligent machine for AD detection: a Support Vector Machine was trained on AD and healthy subjects and subsequently tested with leave-1-out experiments and validation tests on previously unseen cases. The results showed a sensitivity of 76% for AD, with an overall accuracy of 84%, proving that suitable biomarkers for AD can be detected in clinical MR images.

MMSE scores correlate with local ventricular enlargement in the spectrum from cognitively normal to Alzheimer disease.

In this work, we aimed at correlating focal atrophy in periventricular structures with cognitive function, in the spectrum from healthy subjects to severe Alzheimer disease: 28 subjects with normal cognition and 84 patients presenting various degrees of cognitive impairment were included in the study. The cognitive level of each subject was assessed with the Mini-Mental State Examination (MMSE). Atrophy in periventricular structures was inferred by modeling and analyzing local shape variations of brain ventricles: for a given subject, we distinguished between the severity of atrophy, estimated as local enlargement (in mm) of the ventricular surface relative to an average normal subject, and the extent of atrophy, defined as the percentage of the ventricular surface (global or per anatomical region) significantly different from an average control. Linear regression across subjects was performed to evaluate the correlation between atrophy and MMSE score. The severity of atrophy showed good correlation with MMSE score in the left thalamus, the left temporal horn, the left corona radiata, and the right caudate nuclei. The extent of atrophy showed no significant correlations. In conclusion, the MMSE scores correlate with localized depth of atrophy in well-defined periventricular structures.

GAMEs: growing and adaptive meshes for fully automatic shape modeling and analysis.

This paper presents a new framework for shape modeling and analysis, rooted in the pattern recognition theory and based on artificial neural networks. Growing and adaptive meshes (GAMEs) are introduced: GAMEs combine the self-organizing networks which grow when require (SONGWR) algorithm and the Kohonen's self-organizing maps (SOMs) in order to build a mesh representation of a given shape and adapt it to instances of similar shapes. The modeling of a surface is seen as an unsupervised clustering problem, and tackled by using SONGWR (topology-learning phase). The point correspondence between point distribution models is granted by adapting the original model to other instances: the adaptation is seen as a classification task and performed accordingly to SOMs (topology-preserving phase). We thoroughly evaluated our method on challenging synthetic datasets, with different levels of noise and shape variations. Finally, we describe its application to the analysis of a challenging medical dataset. Our method proved to be reproducible, robust to noise, and capable of capturing real variations within and between groups of shapes.

Shape differences of the brain ventricles in Alzheimer's disease.

The brain ventricles are surrounded by gray and white matter structures that are often affected in dementia in general and Alzheimer's disease (AD) in particular. Any change of volume or shape occurring in these structures must affect the volume and shape of the ventricles. It is well known that ventricular volume is significantly higher in AD patients compared to age-matched healthy subjects. However, the large overlap between the two volume distributions makes the measurement unsuitable as a biomarker of the disease. The purpose of this work was to assess whether local shape differences of the ventricles can be detected when comparing AD patients and controls. In this work, we captured the ventricle's shape and shape variations of 29 AD subjects and 25 age-matched controls, using a fully automatic shape modeling technique. By applying permutation tests on every single node of a mesh representation of the shapes, we identified local areas with significant differences. About 22% of an average surface of the ventricles presented significant difference (P < 0.05) ( approximately 14% of the left against approximately 7% of the right side). We found out that in patients with Alzheimer disease, not only the lateral horns were significantly affected, but also the areas adjacent to the anterior corpus callosum, the splenium of the corpus callosum, the amygdala, the thalamus, the tale of the caudate nuclei (especially the left one), and the head of the left caudate nucleus.

Fully automatic shape modelling using growing cell.

In this paper, we present a new framework for shape modelling and analysis: we suggest to look at the problem from a pattern recognition point of view, and claim that under this prospective several advantages are achieved. The modelling of a surface with a point distribution model is seen as an unsupervised clustering problem, and tackled by using growing cell structures. The adaptation of a model to new shapes is studied as a classification task, and provides a straightforward solution to the point correspondence problem in active shape modelling. The method is illustrated and tested in 3D synthetic datasets and applied to the modelling of brain ventricles in an elderly population.