Irene Carne - Academia.edu (original) (raw)

Papers by Irene Carne

Zenodo (CERN European Organization for Nuclear Research), Feb 20, 2023

Scientific Reports, Jan 17, 2024

Journal of Instrumentation, Jan 29, 2008

We present the results of our recent studies of a Thick Gaseous Electron Multiplier (THGEM)-based... more We present the results of our recent studies of a Thick Gaseous Electron Multiplier (THGEM)-based detector, operated in Ar, Xe and Ar:Xe (95:5) at various gas pressures. Avalanche-multiplication properties and energy resolution were investigated with soft x-rays for different detector configurations and parameters. Gains above 10 4 were reached in a double-THGEM detector, at atmospheric pressure, in all gases, in almost all the tested conditions; in Ar:Xe (95:5) similar gains were reached at pressures up to 2 bar. The energy resolution dependence on the gas, pressure, hole geometry and electric fields was studied in detail, yielding in some configurations values below 20% FWHM with 5.9 keV x-rays.

Behavioural Brain Research, Feb 1, 2021

We have previously shown that activity and connectivity within and between the action observation... more We have previously shown that activity and connectivity within and between the action observation and mentalizing brain systems reflect the degree of positive dimensions expressed by social interactions such as cooperativity and affectivity, respectively. Here we aim to extend this evidence by investigating the neural bases of processing negative dimensions of observed interactions, such as competition and affective conflict, possibly representing a benchmark for different pathological conditions. In this fMRI study 34 healthy participants were shown pictures depicting interactions characterized by two crossed dimensions, i.e. positively- vs. negatively- connotated social intentions mainly expressed in terms of motor acts vs. mental states, i.e. cooperative, competitive, affective and conflicting interactions. We confirmed the involvement of the action observation and mentalizing networks in processing intentions mainly expressed through motor acts (cooperative/competitive) vs. mental states (affective/conflicting), respectively. Results highlighted the selective role of the left pSTS/TPJ in decoding social interactions, even when compared with parallel actions by non-interacting individuals. Its right-hemispheric homologue displayed stronger responses to negative than positive social intentions, regardless of their motor/mental status, and decreased connectivity with the medial prefrontal cortex (mPFC) when processing negative interactions. The resulting mPFC downregulation by negative social scenes might reflect an adaptive response to socio-affective threats, via decreased mentalizing when facing negative social stimuli. This evidence on the brain mechanisms underlying the decoding of real complex interactions represents a baseline for assessing both the neural correlates of impaired social cognition, and the effects of rehabilitative treatments, in neuro-psychiatric diseases or borderline conditions such as loneliness.

Academic Radiology, Aug 1, 2016

Rationale and Objectives: The aims of this study were to propose a semiautomated technique to seg... more Rationale and Objectives: The aims of this study were to propose a semiautomated technique to segment and measure the volume of different nerve components of the tibial nerve, such as the nerve fascicles and the epineurium, based on magnetic resonance microneurography and a segmentation tool derived from brain imaging; and to assess the reliability of this method by measuring interobserver and intraobserver agreement. Materials and Methods: The tibial nerve of 20 healthy volunteers (age range = 23-69; mean = 47; standard deviation = 15) was investigated at the ankle level. High-resolution images were obtained through tailored microneurographic sequences, covering 28 mm of nerve length. Two operators manually segmented the nerve using the in-phase image. This region of interest was used to mask the nerve in the water image, and two-class segmentation was performed to measure the fascicular volume, epineurial volume, nerve volume, and fascicular to nerve volume ratio (FNR). Interobserver and intraobserver agreements were calculated. Results: The nerve structure was clearly visualized with distinction of the fascicles and the epineurium. Segmentation provided absolute volumes for nerve volume, fascicular volume, and epineurial volume. The mean FNR resulted in 0.69 with a standard deviation of 0.04 and appeared to be not correlated with age and sex. Interobserver and intraobserver agreements were excellent with alpha values >0.9 for each parameter investigated, with measurements free of systematic errors at the Bland-Altman analysis. Conclusions: We concluded that the method is reproducible and the parameter FNR is a novel feature that may help in the diagnosis of neuropathies detecting changes in volume of the fascicles or the epineurium.

Physica Medica, Aug 1, 2023

The use of topological metrics to derive quantitative descriptors from structural connectomes is ... more The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers. Methods: Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.g. 3 T) Magnetic Resonance Imaging scanners in 13 different centers, following the harmonization of the acquisition protocol, on young and healthy adults. A "traveling brains" dataset acquired on a subgroup of subjects at 3 different centers was also analyzed as reference data. All data were processed following a common processing pipeline that includes data pre-processing, tractography, generation of structural connectomes and calculation of graph-based metrics. The results were evaluated both with statistical analysis of variability and consistency among sites with the traveling brains range. In addition, inter-site reproducibility was assessed in terms of intra-class correlation variability. Results: The results show an inter-center and inter-subject variability of <10%, except for "clustering coefficient" (variability of 30%). Statistical analysis identifies significant differences among sites, as expected given the wide range of scanners' hardware. Conclusions: The results show low variability of connectivity topological metrics across sites running a harmonised protocol.

Scientific Reports

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasin... more Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of ...

IEEE Conference Proceedings, 2017

Physica Medica

Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive qua... more Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive quantification of iron content and myelination in the brain. The RIN-Neuroimaging Network established an optimized and harmonized protocol for QSM across ten sites with 3T MRI systems from three different vendors to enable multicentric studies. The assessment of the reproducibility of this protocol is crucial to establish susceptibility as a quantitative biomarker. In this work, we evaluated cross-vendor reproducibility in a group of six traveling brains. Then, we recruited fifty-one volunteers and measured the variability of QSM values in a cohort of healthy subjects scanned at different sites, simulating a multicentric study. Both voxelwise and Region of Interest (ROI)based analysis on cortical and subcortical gray matter were performed. The traveling brain study yielded high structural similarity (~0.8) and excellent reproducibility comparing maps acquired on scanners from two different vendors. Depending on the ROI, we reported a quantification error ranging from 0.001 to 0.017 ppm for the traveling brains. In the cohort of fifty-one healthy subjects scanned at nine different sites, the ROI-dependent variability of susceptibility values, of the order of 0.005-0.025 ppm, was comparable to the result of the traveling brain experiment. The harmonized QSM protocol of the RIN-Neuroimaging Network provides a reliable quantification of susceptibility in both cortical and subcortical gray matter regions and it is ready for multicentric and longitudinal clinical studies in neurological and pychiatric diseases.

2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2017

Physical and digital phantoms are useful instruments for the validation of image processing metho... more Physical and digital phantoms are useful instruments for the validation of image processing methods for oncology allowing the simulation of various realistic scenarios with the knowledge of gold standard (GS) parameters, such as oncological lesion characteristics. This work aims presenting a strategy to create disposable realistic breast phantoms, suitable for Magnetic Resonance (MR) acquisitions by using Diffusion Weighted Imaging (DWI). Diffusion materials were prepared using agarose/sucrose gels. Gel diffusion characteristics were evaluated in cylindrical calibration phantoms in order to obtain GS for Apparent Diffusion Coefficients (ADCs). Realistic oncological lesions with irregular shapes were manufactured using 3Dprinted plastic molds filled with the gel mixture at a sucrose concentration mimicking the diffusion characteristics of high cellularity tissues. Breast cancer phantoms, simulating realistic oncological conditions, were manufactured suspending synthetic lesion in a u...

Frontiers in Neurology

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific m... more Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization...

Behavioural Brain Research