A Method for Manufacturing Oncological Phantoms for the Quantification of 18F-FDG PET and DW-MRI Studies

The aim of this work was to develop a method to manufacture oncological phantoms for quantitation purposes in 18F-FDG PET and DW-MRI studies. Radioactive and diffusion materials were prepared using a mixture of agarose and sucrose radioactive gels. T2 relaxation and diffusion properties of gels at different sucrose concentrations were evaluated. Realistic oncological lesions were created using 3D-printed plastic molds filled with the gel mixture. Once solidified, gels were extracted from molds and immersed in a low-radioactivity gel simulating normal background tissue. A breast cancer phantom was manufactured using the proposed method as an exploratory feasibility study, including several realistic oncological configurations in terms of both radioactivity and diffusion. The phantom was acquired in PET with 18F-FDG, immediately after solidification, and in DW-MRI the following day. Functional volumes characterizing the simulated BC lesions were segmented from PET and DW-MRI images. Measured radioactive uptake and ADC values were compared with gold standards. Phantom preparation was straightforward, and the time schedule was compatible with both PET and MRI measurements. Lesions appeared on 18F-FDG PET and DW-MRI images as expected, without visible artifacts. Lesion functional parameters revealed the phantom’s potential for validating quantification methods, in particular for new generation hybrid PET-MRI systems

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN-Neuroimaging Network case study

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RINNeuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.7 +/- 5.0 years), collected in 15 sites with MRI scanners of three different vendors, was considered. Parallelly, a dataset of 7 "traveling" subjects, each undergoing three acquisitions with scanners from different vendors, was also used. Intra-site, intra-vendor, and inter-site variabilities were evaluated in terms of the percentage standard deviation of volumetric and cortical thickness measures. Image quality metrics such as contrast-to-noise and signal-to-noise ratio in gray and white matter were also assessed for all sites and vendors. The results showed a measured global variability that ranges from 11% to 19% for subcortical volumes and from 3% to 10% for cortical thicknesses. Univariate distributions of the normalized volumes of subcortical regions, as well as the distributions of the thickness of cortical parcels appeared to be significantly different among sites in 8 subcortical (out of 17) and 21 cortical (out of 68) regions of i nterest in the multicentric study. The Bland-Altman analysis on "traveling" brain measurements did not detect systematic scanner biases even though a multivariate classification approach was able to classify the scanner vendor from brain measures with an accuracy of 0.60 +/- 0.14 (chance level 0.33)

Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T

: 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

Normative values of the topological metrics of the structural connectome: a multi-site reproducibility study across the italian neuroscience network

Purpose: 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

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

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 and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

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 discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

L’influenza della personalità degli elettori e dei candidati sull’impegno politico.

Il presente studio applica al marketing politico la teoria psico-sociale che descrive la personalità degli individui identificando, con il Modello dei Big Five, i tratti della personalità di un elettore e del suo candidato politico ideale. Le differenze significative tra le personalità sono state esaminate come possibili predittori dell’impegno politico (political engagement) del votante. Attraverso l’analisi di un campione di 121 partecipanti, a cui è stato somministrato un questionario strutturato, è stato possibile affermare che l’Estroversione accomuna la personalità degli elettori a quella del candidato politico ideale più degli altri tratti. Inoltre, la Coscienziosità dell’elettore e l’Estroversione del candidato politico ideale sono predittori dell’impegno politico. Le implicazioni teoriche e manageriali sono discusse al termine della ricerca

Effects of active music therapy on the normal brain: fMRI based evidence

Abstract The aim of this study was to investigate the neurophysiological bases of Active Music Therapy (AMT) and its effects on the normal brain. Twelve right-handed, healthy, non-musician volunteers were recruited. The subjects underwent 2 AMT sessions based on the free sonorousmusic improvisation using rhythmic and melodic instruments. After these sessions, each subject underwent 2 fMRI scan acquisitions while listening to a Syntonic (SP) and an ASyntonic (AP) Production from the AMT sessions. A 3 T Discovery MR750 scanner with a 16-channel phased array head coil was used, and the image analysis was performed with Brain Voyager QX 2.8. The listening to SP vs AP excerpts mainly activated: (1) the right middle temporal gyrus and right superior temporal sulcus, (2) the right middle frontal gyrus and in particular the right precentral gyrus, (3) the bilateral precuneus, (4) the left superior temporal sulcus and (5) the left middle temporal gyrus. These results are consistent with the psychological bases of the AMT approach and with the activation of brain areas involved in memory and autobiographical processes, and also in personal or interpersonal significant experiences. Further studies are required to confirm these findings and to explain possible effects of AMT in clinical settings

In Vivo MR Microneurography of the Tibial and Common Peroneal Nerves

MR microneurography is a noninvasive technique that provides visualization of the microanatomy of peripheral nerves, otherwise available only with histopathology. The objective of this study was to present a protocol to visualize the microstructure of peripheral nerves in vivo, using a 3T MRI scanner with a clinical set of coils and sequences. The tibial and the common peroneal nerves of healthy volunteers were imaged above the medial malleolus and at the level of the fibular head, respectively. The acquired images provided details about the internal structure of peripheral nerves, with visualization of the fascicles, the interfascicular fat, the epineurium, and the perineurium. MR microneurography can be performed in a clinical setting with acceptable imaging times and can be a potentially powerful tool that complements standard MR neurography

Nerve Fascicles and Epineurium Volume Segmentation of Peripheral Nerve Using Magnetic Resonance Micro-neurography

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