Clinical validity of the Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB) in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

The identification and staging of Alzheimer's Disease (AD) represent a challenge, especially in the prodromal stage of Mild Cognitive Impairment (MCI), when cognitive changes can be subtle. Worldwide efforts were dedicated to select and harmonize available neuropsychological instruments. In Italy, the Italian Network of Neuroscience and Neuro-Rehabilitation has promoted the adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB), collecting normative data from 433 healthy controls (HC). Here, we aimed to explore the ability of I-UDSNB to differentiate between a) MCI and HC, b) AD and HC, c) MCI and AD.

METHODS

One hundred thirty-seven patients (65 MCI, 72 AD) diagnosed after clinical-neuropsychological assessment, and 137 HC were included. We compared the I-UDSNB scores between a) MCI and HC, b) AD and HC, c) MCI and AD, with t-tests. To identify the test(s) most capable of differentiating between groups, significant scores were entered in binary logistic and in stepwise regressions, and then in Receiver Operating Characteristic curve analyses.

RESULTS

Two episodic memory tests (Craft Story and Five Words test) differentiated MCI from HC subjects; Five Words test, Semantic Fluency (vegetables), and TMT-part B differentiated AD from, respectively, HC and MCI.

CONCLUSIONS

Our findings indicate that the I-UDSNB is a suitable tool for the harmonized and concise assessment of patients with cognitive decline, showing high sensitivity and specificity for the diagnosis of MCI and AD.

Quantitative measurement of dural ectasia: associations with clinical and genetic characteristics in Marfan syndrome

PURPOSE

Dural ectasia (DE) may significantly impact Marfan syndrome (MFS) patients' quality of life due to chronic lower back pain, postural headache and urinary disorders. We aimed to evaluate the association of quantitative measurements of DE, and their evolution over time, with demographic, clinical and genetic characteristics in a cohort of MFS patients.

METHODS

We retrospectively included 88 consecutive patients (39% females, mean age 37.1 ± 14.2 years) with genetically confirmed MFS who underwent at least one MRI or CT examination of the lumbosacral spine. Vertebral scalloping (VS) and dural sac ratio (DSR) were calculated from L3 to S3. Likely pathogenic or pathogenic FBN1 variants were categorized as either protein-truncating or in-frame. The latter were further classified according to their impact on the cysteine content of fibrillin-1.

RESULTS

Higher values of the systemic score (revised Ghent criteria) were associated with greater DSR at lumbar (p < 0.001) and sacral (p = 0.021) levels. Patients with protein-truncating variants exhibited a greater annual increase in lumbar (p = 0.039) and sacral (p = 0.048) DSR. Mutations affecting fibrillin-1 cysteine content were linked to higher VS (p = 0.009) and DSR (p = 0.038) at S1, along with a faster increase in VS (p = 0.032) and DSR (p = 0.001) in the lumbar region.

CONCLUSION

Our study shed further light on the relationship between genotype, dural pathology, and the overall clinical spectrum of MFS. The identification of protein-truncating variants and those impacting cysteine content may therefore suggest closer patient monitoring, in order to address potential complications associated with DE.

Bi-allelic variants in SNF8 cause a disease spectrum ranging from severe developmental and epileptic encephalopathy to syndromic optic atrophy

The endosomal sorting complex required for transport (ESCRT) machinery is essential for membrane remodeling and autophagy and it comprises three multi-subunit complexes (ESCRT I-III). We report nine individuals from six families presenting with a spectrum of neurodevelopmental/neurodegenerative features caused by bi-allelic variants in SNF8 (GenBank: NM_007241.4), encoding the ESCRT-II subunit SNF8. The phenotypic spectrum included four individuals with severe developmental and epileptic encephalopathy, massive reduction of white matter, hypo-/aplasia of the corpus callosum, neurodevelopmental arrest, and early death. A second cohort shows a milder phenotype with intellectual disability, childhood-onset optic atrophy, or ataxia. All mildly affected individuals shared the same hypomorphic variant, c.304G>A (p.Val102Ile). In patient-derived fibroblasts, bi-allelic SNF8 variants cause loss of ESCRT-II subunits. Snf8 loss of function in zebrafish results in global developmental delay and altered embryo morphology, impaired optic nerve development, and reduced forebrain size. In vivo experiments corroborated the pathogenicity of the tested SNF8 variants and their variable impact on embryo development, validating the observed clinical heterogeneity. Taken together, we conclude that loss of ESCRT-II due to bi-allelic SNF8 variants is associated with a spectrum of neurodevelopmental/neurodegenerative phenotypes mediated likely via impairment of the autophagic flux.

Vertebral artery dissection caused by atlantoaxial dislocation in a patient with Marfan syndrome

A small number of case reports have documented a link between atlantoaxial dislocation (AAD) and vertebral artery dissection (VAD), but this association has never been described in patients with hereditary connective tissue disorders. We present a case of an 18-year-old female patient, diagnosed with Marfan syndrome since the age of one, who underwent brain MRA for intracranial aneurysm screening revealing tortuosity of the internal carotid and vertebral arteries as well as atlantoaxial dislocation. Since the patient was asymptomatic, a wait-and-see approach was chosen, but a follow-up MRA after 18 months showed the appearance of a dissecting pseudoaneurysm of the V3 segment of the left vertebral artery. Despite the patient being still asymptomatic, it was decided to proceed with C1-C2 stabilization to prevent further vascular complications. Follow-up imaging showed realignment of the atlantoaxial joint and reduction of the dissecting pseudoaneurysm of the left vertebral artery. In our patient, screening MRA has led to the discovery of asymptomatic arterial and skeletal abnormalities which, if left untreated, might have led to severe cerebrovascular complications. Therefore, AAD correction or close monitoring with MRA should be provided to MFS patients with this craniovertebral junction anomaly, even if asymptomatic.

Magnetic resonance imaging scoring system of the lower limbs in adult patients with suspected idiopathic inflammatory myopathy

PURPOSE

We aim to propose a visual quantitative score for muscle edema in lower limb MRI to contribute to the diagnosis of idiopathic inflammatory myopathy (IIM).

MATERIAL AND METHODS

We retrospectively evaluated 85 consecutive patients (mean age 57.4 ± 13.9 years; 56.5% female) with suspected IIM (muscle weakness and/or persistent hyper-CPK-emia with/without myalgia) who underwent MRI of lower limbs using T2-weighted fast recovery-fast spin echo images and fat-sat T2 echo planar images. Muscle inflammation was evaluated bilaterally in 11 muscles of the thigh and eight muscles of the leg. Edema in each muscle was graded according to a four-point Likert-type scale adding up to 114 points ([11 + 8)] × 3 × 2). Diagnostic accuracy of the total edema score was explored by assessing sensitivity and specificity using the area under the ROC curve. Final diagnoses were made by a multidisciplinary Expert Consensus Panel applying the Bohan and Peter diagnostic criteria whenever possible.

RESULTS

Of the 85 included patients, 34 (40%) received a final diagnosis of IIM (IIM group) while 51 (60%) received an alternative diagnosis (non-IIM group). A cutoff score ≥ 18 was able to correctly classify patients having an IIM with an area under the curve of 0.85, specificity of 96%, and sensitivity of 52.9%.

CONCLUSION

Our study demonstrates that a quantitative MRI score for muscle edema in the lower limbs (thighs and legs) aids in distinguishing IIM from conditions that mimic it.

Emotion dysregulation, impulsivity and anger rumination in borderline personality disorder: the role of amygdala and insula

Borderline Personality Disorder (BPD) is a severe mental disorder, characterized by deficits in emotion regulation, interpersonal dysfunctions, dissociation and impulsivity. Brain abnormalities have been generally explored; however, the specific contribution of different limbic structures to BPD symptomatology is not described. The aim of this study is to cover this gap, exploring functional and structural alterations of amygdala and insula and to highlight their contribution to neuropsychiatric symptoms. Twenty-eight BPD patients (23.7 ± 3.42 years; 6 M/22F) and twenty-eight matched healthy controls underwent a brain MR protocol (1.5 T, including a 3D T1-weighted sequence and resting-state fMRI) and a complete neuropsychiatric assessment. Volumetry, cortical thickness and functional connectivity of amygdala and insula were evaluated, along with correlations with the neuropsychiatric scales. BPD patients showed a lower cortical thickness of the left insula (p = 0.027) that negatively correlated with the Anger Rumination Scale (p = 0.019; r = - 0.450). A focused analysis on female patients showed a significant reduction of right amygdala volumes in BPD (p = 0.037), that correlate with Difficulties in Emotion Regulation Scale (p = 0.031; r =  - 0.415), Beck Depression Inventory (p = 0.009; r =  - 0.50) and Ruminative Response Scale (p = 0.045; r =  - 0.389). Reduced functional connectivity was found in BPD between amygdala and frontal pole, precuneus and temporal pole. This functional connectivity alterations correlated with Anger Rumination Scale (p = .009; r = - 0.491) and Barratt Impulsiveness Scale (p = 0.020; r = - 0.447). Amygdala and insula are altered in BPD patients, and these two limbic structures are implicated in specific neuropsychiatric symptoms, such as difficulty in emotion regulation, depression, anger and depressive rumination.

Distribution of the C9orf72 hexanucleotide repeat expansion in healthy subjects: a multicenter study promoted by the Italian IRCCS network of neuroscience and neurorehabilitation

Introduction

High repeat expansion (HRE) alleles in C9orf72 have been linked to both amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD); ranges for intermediate allelic expansions have not been defined yet, and clinical interpretation of molecular data lacks a defined genotype-phenotype association. In this study, we provide results from a large multicenter epidemiological study reporting the distribution of C9orf72 repeats in healthy elderly from the Italian population.

Methods

A total of 967 samples were collected from neurologically evaluated healthy individuals over 70 years of age in the 13 institutes participating in the RIN (IRCCS Network of Neuroscience and Neurorehabilitation) based in Italy. All samples were genotyped using the AmplideXPCR/CE C9orf72 Kit (Asuragen, Inc.), using standardized protocols that have been validated through blind proficiency testing.

Results

All samples carried hexanucleotide G4C2 expansion alleles in the normal range. All samples were characterized by alleles with less than 25 repeats. In particular, 93.7% of samples showed a number of repeats ≤10, 99.9% ≤20 repeats, and 100% ≤25 repeats.

Conclusion

This study describes the distribution of hexanucleotide G4C2 expansion alleles in an Italian healthy population, providing a definition of alleles associated with the neurological healthy phenotype. Moreover, this study provides an effective model of federation between institutes, highlighting the importance of sharing genomic data and standardizing analysis techniques, promoting translational research. Data derived from the study may improve genetic counseling and future studies on ALS/FTD.

Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions

Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.

Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer's Disease

Background

Being able to differentiate mild cognitive impairment (MCI) patients who would eventually convert (MCIc) to Alzheimer's disease (AD) from those who would not (MCInc) is a key challenge for prognosis.

Objective

This study aimed to investigate the ability of sulcal morphometry to predict MCI progression to AD, dedicating special attention to an accurate identification of sulci.

Methods

Twenty-five AD patients, thirty-seven MCI and twenty-five healthy controls (HC) underwent a brain-MR protocol (1.5T scanner) including a high-resolution T1-weighted sequence. MCI patients underwent a neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 2.3 years. At follow-up, 12 MCI were classified as MCInc and 25 as MCIc. Sulcal morphometry was investigated using the BrainVISA framework. Consistency of sulci across subjects was ensured by visual inspection and manual correction of the automatic labelling in each subject. Sulcal surface, depth, length, and width were retrieved from 106 sulci. Features were compared across groups and their classification accuracy in predicting MCI conversion was tested. Potential relationships between sulcal features and cognitive scores were explored using Spearman's correlation.

Results

The width of sulci in the temporo-occipital region strongly differentiated between each pair of groups. Comparing MCIc and MCInc, the width of several sulci in the bilateral temporo-occipital and left frontal areas was significantly altered. Higher width of frontal sulci was associated with worse performances in short-term verbal memory and phonemic fluency.

Conclusions

Sulcal morphometry emerged as a strong tool for differentiating HC, MCI, and AD, demonstrating its potential prognostic value for the MCI population.

Genomic Profiling of Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Suggests Novel Potential Therapeutic Targets

Primary diffuse large B-cell lymphoma of the primary central nervous system (CNS-DLBCL) is an aggressive disease, with dismal prognosis despite the use of high-dose methotrexate-based polychemotherapy. Our study aimed to expand the biologic profiles of CNS-DLBCL and to correlate them with clinical/imaging findings to gain diagnostic insight and possibly identify new therapeutic targets. We selected 61 CNS-DLBCL whose formalin-fixed paraffin-embedded samples were available at first diagnosis. These were investigated by immunohistochemistry, cMYC rearrangements were explored by fluorescence in situ hybridization, and CNS-DLBCL mutated genes were evaluated by next-generation sequencing. CD10, BCL6, and IRF4 were observed in 16%, 83.6%, and 93% of cases, respectively. As typical of CNS lymphoma, 10 (16.4%) of 61 cases were classified as germinal center (GCB) type and 51 (83.6%) of 61 as non-germinal center (non-GCB) type according to the Hans algorithm. Double-expression status for BCL2 and cMYC was detected in 36 (59%) of 61 cases whereas 25 (41%) of 61 were non-DE. Rearrangement of the cMYC gene was detected in 2 cases, associated with BCL6 translocation only in 1 case MYD88, PIM1, CD79B, and TP53 were mutated in 54.5%, 53.5%, 30.2%, and 18.4% cases, respectively. Novel mutations not previously reported in CNS-DLBCL were found: AIP in 23.1%, PI3KCA in 15%, NOTCH1 in 11.4%, GNAS in 8.1%, CASP8 in 7.9%, EGFR in 6.4%, PTEN in 5.1, and KRAS in 2.6% of cases. Survival was significantly longer for patients with mutated MYD88 (8.7 months vs 1.7 months; log-rank test = 5.43; P = .020) and for patients with mutated CD79B (10.8 months vs 2.5 months; log-rank test = 4.64; P = .031). MYD88 and CD79B predicted a longer survival in patients affected by CNS-DLBCL. Notably, we identified novel mutations that enrich the mutational landscape of CNS-DLBCL, suggest a role of PTEN-PI3K-AKT and receptor tyrosine kinase-RAS-mitogen-activated protein kinase signaling in a subset of CNS-DLBCL, and provide new potential therapeutic targets.

Vessel-wall MRI in primary headaches: The role of neurogenic inflammation

OBJECTIVE

The purpose of this study was to investigate if vessel-wall magnetic resonance imaging (VW-MRI) could differentiate among primary headaches disorders, such as migraine and cluster headache (CH), and detect the presence of neurogenic inflammation.

BACKGROUND

The pathophysiology of primary headaches disorders is complex and not completely clarified. The activation of nociceptive trigeminal afferents through the release of vasoactive neuropeptides, termed "neurogenic inflammation," has been hypothesized. VW-MRI can identify vessel wall changes, reflecting the inflammatory remodeling of the vessel walls despite different etiologies.

METHODS

In this case series, we enrolled seven patients with migraine and eight patients with CH. They underwent a VW-MRI study before and after the intravenous administration of contrast medium, during and outside a migraine attack or cluster period. Two expert neuroradiologists analyzed the magnetic resonance imaging (MRI) studies to identify the presence of vessel wall enhancement or other vascular abnormalities.

RESULTS

Fourteen out of 15 patients had no enhancement. One out of 15, with migraine, showed a focal parietal enhancement in the intracranial portion of a vertebral artery, unmodified during and outside the attack, thus attributable to atherosclerosis. No contrast enhancement attributable to neurogenic inflammation was observed in VW-MRI, both during and outside the attack/cluster in all patients. Moreover, MRI angiography registered slight diffuse vasoconstriction in one of seven patients with migraine during the attack and in one of eight patients with cluster headache during the cluster period; both patients had taken triptans as symptomatic therapy for pain.

CONCLUSIONS

These preliminary results suggest that VW-MRI studies are negative in patients with primary headache disorders even during migraine attacks or cluster periods. The VW-MRI studies did not detect signs of neurogenic inflammation in the intracranial intradural vessels of patients with migraine or CH.

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.

Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.

Methods of diffusion MRI tractography for localization of the anterior optic pathway: A systematic review of validated methods

The anterior optic pathway (AOP) is a system of three structures (optic nerves, optic chiasma, and optic tracts) that convey visual stimuli from the retina to the lateral geniculate nuclei. A successful reconstruction of the AOP using tractography could be helpful in several clinical scenarios, from presurgical planning and neuronavigation of sellar and parasellar surgery to monitoring the stage of fiber degeneration both in acute (e.g., traumatic optic neuropathy) or chronic conditions that affect AOP structures (e.g., amblyopia, glaucoma, demyelinating disorders or genetic optic nerve atrophies). However, its peculiar anatomy and course, as well as its surroundings, pose a serious challenge to obtaining successful tractographic reconstructions. Several AOP tractography strategies have been adopted but no standard procedure has been agreed upon. We performed a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) 2020 guidelines in order to find the combinations of acquisition and reconstruction parameters that have been performed previously and have provided the highest rate of successful reconstruction of the AOP, in order to promote their routine implementation in clinical practice. For this purpose, we reviewed data regarding how the process of anatomical validation of the tractographies was performed. The Cochrane Handbook for Systematic Reviews of Interventions was used to assess the risk of bias and thus the study quality We identified thirty-nine studies that met our inclusion criteria, and only five were considered at low risk of bias and achieved over 80% of successful reconstructions. We found a high degree of heterogeneity in the acquisition and analysis parameters used to perform AOP tractography and different combinations of them can achieve satisfactory levels of anterior optic tractographic reconstruction both in real-life research and clinical scenarios. One thousand s/mm2 was the most frequently used b value, while both deterministic and probabilistic tractography algorithms performed morphological reconstruction of the tract satisfactorily, although probabilistic algorithms estimated a more realistic percentage of crossing fibers (45.6%) in healthy subjects. A wide heterogeneity was also found regarding the method used to assess the anatomical fidelity of the AOP reconstructions. Three main strategies can be found: direct visual direct visual assessment of the tractography superimposed to a conventional MR image, surgical evaluation, and computational methods. Because the latter is less dependent on a priori knowledge of the anatomy by the operator, computational methods of validation of the anatomy should be considered whenever possible.

The angio-architectural features of brain arteriovenous malformations: is it possible to predict the probability of rupture?

BACKGROUND

Hemorrhage is the most devastating complication of brain arteriovenous malformations (bAVMs), and to date, there is still concern about the needing for treatment in case of unruptured and asymptomatic bAVM. In fact, the morbidity and mortality of treatments may exceed that of the AVM's natural history. None of the classifications and scores for bAVM allows to predict the risk of bleeding. In this study, we aimed to identify the angio-architectural characteristics of brain AVMs associated with bleeding.

METHODS

We retrospectively evaluated all consecutive patients diagnosed with cerebral AVMs, between January 2010 and December 2019 from our prospective bAVM database. Univariate and multivariate logistic regression analysis were used to evaluate relationships between angio-architectural features of ruptured and unruptured bAVMs.

RESULTS

Of the 143 retrieved bAVMs, 65 were unruptured and 78 were ruptured. The univariate logistic regression analysis demonstrated statistically significant differences into angio-architectural features of unruptured and ruptured bAVMs. The multivariate logistic regression analysis fitted well (p =.113) with a good discrimination capacity (ROC = 0.83) of three independent angio-architectural features mainly related to bleeding in bAVMs: a smaller diameter of the nidus (p < .001), the absence of venous drainage alterations (p = .047), of the presence of prenidal aneurysms (p = .005).

CONCLUSIONS

In our study, several features resulted related to an increased probability of rupture for bAVMs, among which the more relevant were a small diameter of the nidus, the absence of venous drainage alterations, and the presence of prenidal aneurysms.

Prevalence of unruptured intracranial aneurysms in patients with Marfan syndrome: A cross-sectional study and meta-analysis

INTRODUCTION

Marfan syndrome (MFS) is the most common inherited connective tissue disorder and its association with intracranial aneurysms (ICAs) has been debated for more than two decades. Here, we report the prevalence of ICAs at screening neuroimaging in a population of genetically confirmed MFS patients and present the results of a meta-analysis including our cohort of patients and those of previous studies.

PATIENTS AND METHODS

We enrolled 100 consecutive MFS patients, who underwent screening with brain magnetic resonance angiography at our tertiary center between August 2018 and May 2022. We did a PubMed and Web of Science search to retrieve all studies on the prevalence of ICAs in patients with MFS published before November, 2022.

RESULTS

Of the 100 patients included in this study (94% Caucasians, 40% females, mean age 38.6 ± 14.6 years), three had an ICA. We pooled the current study with five previously published studies, including a total of 465 patients, 43 of which harbored at least one unruptured ICA, leading to an overall ICA prevalence of 8.9% (95% CI 5.8%-13.3%).

DISCUSSION AND CONCLUSION

In our cohort of genetically confirmed MFS patients, the prevalence of ICAs was 3%, which is substantially lower compared to previous studies based on neuroimaging. The high frequency of ICA found in previous studies could be explained by selection bias and lack of genetic testing, which may have led to the inclusion of patients with different connective tissue disorders. Further studies, including several centers and a large number of patients with genetically confirmed MFS, are needed to confirm our results.

Multimodal investigation of melanopsin retinal ganglion cells in Alzheimer's disease

OBJECTIVE

In Alzheimer's disease (AD), the presence of circadian dysfunction is well-known and may occur early in the disease course. The melanopsin retinal ganglion cell (mRGC) system may play a relevant role in contributing to circadian dysfunction. In this study, we aimed at evaluating, through a multimodal approach, the mRGC system in AD at an early stage of disease.

METHODS

We included 29 mild-moderate AD (70.9 ± 11 years) and 26 (70.5 ± 8 years) control subjects. We performed an extensive neurophtalmological evaluation including optical coherence tomography with ganglion cell layer segmentation, actigraphic evaluation of the rest-activity rhythm, chromatic pupillometry analyzed with a new data-fitting approach, and brain functional MRI combined with light stimuli assessing the mRGC system.

RESULTS

We demonstrated a significant thinning of the infero-temporal sector of the ganglion cell layer in AD compared to controls. Moreover, we documented by actigraphy the presence of a circadian-impaired AD subgroup. Overall, circadian measurements worsened by age. Chromatic pupillometry evaluation highlighted the presence of a pupil-light response reduction in the rod condition pointing to mRGC dendropathy. Finally, brain fMRI showed a reduced occipital cortex activation with blue light particularly for the sustained responses.

INTERPRETATION

Overall, the results of this multimodal innovative approach clearly document a dysfunctional mRGC system at early stages of disease as a relevant contributing factor for circadian impairment in AD providing also support to the use of light therapy in AD.

Phospholipases in Gliomas: Current Knowledge and Future Perspectives from Bench to Bedside

Phospholipases are essential intermediaries that work as hydrolyzing enzymes of phospholipids (PLs), which represent the most abundant species contributing to the biological membranes of nervous cells of the healthy human brain. They generate different lipid mediators, such as diacylglycerol, phosphatidic acid, lysophosphatidic acid, and arachidonic acid, representing key elements of intra- and inter-cellular signaling and being involved in the regulation of several cellular mechanisms that can promote tumor progression and aggressiveness. In this review, it is summarized the current knowledge about the role of phospholipases in brain tumor progression, focusing on low- and high-grade gliomas, representing promising prognostic or therapeutic targets in cancer therapies due to their influential roles in cell proliferation, migration, growth, and survival. A deeper understanding of the phospholipases-related signaling pathways could be necessary to pave the way for new targeted therapeutic strategies.

Cognitive and functional connectivity impairment in post-COVID-19 olfactory dysfunction

OBJECTIVES

To explore the neuropsychological profile and the integrity of the olfactory network in patients with COVID-19-related persistent olfactory dysfunction (OD).

METHODS

Patients with persistent COVID-19-related OD underwent olfactory assessment with Sniffin' Sticks and neuropsychological evaluation. Additionally, both patients and a control group underwent brain MRI, including T1-weighted and resting-state functional MRI (rs-fMRI) sequences on a 3 T scanner. Morphometrical properties were evaluated in olfaction-associated regions; the rs-fMRI data were analysed using graph theory at the whole-brain level and within a standard parcellation of the olfactory functional network. All the MR-derived quantities were compared between the two groups and their correlation with clinical scores in patients were explored.

RESULTS

We included 23 patients (mean age 37 ± 14 years, 12 females) with persistent (mean duration 11 ± 5 months, range 2-19 months) COVID-19-related OD (mean score 23.63 ± 5.32/48, hyposmia cut-off: 30.75) and 26 sex- and age-matched healthy controls. Applying population-derived cut-off values, the two cognitive domains mainly impaired were visuospatial memory and executive functions (17 % and 13 % of patients). Brain MRI did not show gross morphological abnormalities. The lateral orbital cortex, hippocampus, and amygdala volumes exhibited a reduction trend in patients, not significant after the correction for multiple comparisons. The olfactory bulb volumes did not differ between patients and controls. Graph analysis of the functional olfactory network showed altered global and local properties in the patients' group (n = 19, 4 excluded due to artifacts) compared to controls. Specifically, we detected a reduction in the global modularity coefficient, positively correlated with hyposmia severity, and an increase of the degree and strength of the right thalamus functional connections, negatively correlated with short-term verbal memory scores.

DISCUSSION

Patients with persistent COVID-19-related OD showed an altered olfactory network connectivity correlated with hyposmia severity and neuropsychological performance. No significant morphological alterations were found in patients compared with controls.

Non-Pharmacological Treatments in Lewy Body Disease: A Systematic Review

INTRODUCTION

Lewy body disease (LBD) is the second most common neurodegenerative disorder in patients older than 65 years. LBD is characterized by heterogeneous symptoms like fluctuation in attention, visual hallucinations, Parkinsonism, and REM sleep behaviour disorders. Considering the relevant social impact of the disease, identifying effective non-pharmacological treatments is becoming a priority. The aim of this systematic review was to provide an up-to-date literature review of the most effective non-pharmacological treatments in patients with LBD, focussing on evidence-based interventions.

METHODS

Following PRISMA criteria, we carried out a systematic search through three databases (PubMed, Cochrane Libraries, and PEDro) including physical therapy (PT), cognitive rehabilitation (CR), light therapy (LT), transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), deep brain stimulation (DBS). All studies were qualitatively assessed using standardized tools (CARE and EPHPP).

RESULTS

We obtained a total of 1,220 studies of which 23 original articles met eligibility criteria for inclusion. The total number of LBD patients included was 231; mean age was 69.98, predominantly men (68%). Some PT studies highlighted improvements in motor deficits. CR produced significant improvements in mood, cognition, and patient's quality of life and satisfaction. LT outlined a partial trend of improvements in mood and sleep quality. DBS, ECT, and TMS showed some partial improvements mainly on neuropsychiatric symptoms, whereas tDCS provided partial improvements in attention.

CONCLUSION

This review highlights the efficacy of some evidence-based rehabilitation studies in LBD; however, further randomized controlled trials with larger samples are needed to provide definitive recommendations.

Neurological Manifestations of Long COVID: A Single-Center One-Year Experience

PURPOSE

We report our single-center experience on the neurological manifestations of long COVID.

PATIENTS AND METHODS

This is a retrospective observational study. All consecutive patients referred to the neurological long COVID outpatient clinic of our institute from January 21 2021 to December 9 2021 underwent a general neurological objective examination. Treatments and investigations (brain MRI, neuropsychological evaluation, or others) were prescribed on an individual basis as per standard clinical practice. A follow-up visit was performed when appropriate. Descriptive statistics were presented as absolute and relative frequencies for categorical variables and as means, median, and ranges for continuous variables.

RESULTS

One hundred and three patients were visited (mean age 50.5 ±36 years, 62 females). The average time from acute COVID-19 infection to the first visit to our outpatient clinic was 243 days. Most patients presented with a mild form of acute COVID-19, with only 24 cases requiring hospitalization. The neurological symptoms mostly (n=70/103, 68%) started during the acute phase (before a negative swab for SARS-CoV-2). The most frequent acute manifestations reported, which lately became persistent, were fatigue (n=58/103, 56%), olfactory/taste dysfunction (n=58/103, 56%), headache (n=47/103, 46%), cognitive disorders (n=46/103, 45%), sleep disorders (n=30/103, 29%), sensitivity alterations (n=29/103, 28%), and dizziness (n=7/103, 7%). Tremor was also reported (n=8/103, 7%). Neuropsychological evaluation was performed in 30 patients and revealed alterations in executive functions (n=6/30, 20%), memory (n=11/30, 37%), with pathological depressive (n=9/30, 30%) and anxiety (n=8/30, 27%) scores. Brain MRIs have been performed in 41 cases, revealing nonspecific abnormal findings only in 4 cases. Thirty-six patients underwent a follow-up, where a general improvement was observed but rarely (n=2/36) a complete recovery.

CONCLUSION

The majority of patients presenting persistent neurological symptoms (most frequently fatigue, cognitive disorders, and olfactory dysfunctions) developed a previous mild form of COVID-19. Further studies are required to develop therapeutic strategies.

Italian, European, and international neuroinformatics efforts: An overview

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago. To address this phenomenon, several neuroimaging-focussed neuroinformatics platforms have emerged, funded by national or transnational agencies, with the following goals: (i) development of tools for archiving and organising analytical data (XNAT, REDCap and LabKey); (ii) development of data-driven models evolving from reductionist approaches to multidimensional models (RIN, IVN, HBD, EuroPOND, E-DADS and GAAIN BRAIN); and (iii) development of e-infrastructures to provide sufficient computational power and storage resources (neuGRID, HBP-EBRAINS, LONI and CONP). Although the scenario is still fragmented, there are technological and economical attempts at both national and international levels to introduce high standards for open and Findable, Accessible, Interoperable and Reusable (FAIR) neuroscience worldwide.

In Vivo Parieto-Occipital White Matter Metabolism Is Correlated with Visuospatial Deficits in Adult DM1 Patients

Myotonic dystrophy type 1 (DM1) is a genetic disorder caused by a (CTG) expansion in the DM protein kinase (DMPK) gene, representing the most common adult muscular dystrophy, characterized by a multisystem involvement with predominantly skeletal muscle and brain affection. Neuroimaging studies showed widespread white matter changes and brain atrophy in DM1, but only a few studies investigated the role of white matter metabolism in the pathophysiology of central nervous system impairment. We aim to reveal the relationship between the metabolic profile of parieto-occipital white matter (POWM) as evaluated with proton MR spectroscopy technique, with the visuoperceptual and visuoconstructional dysfunctions in DM1 patients. MR spectroscopy (3 Tesla) and neuropsychological evaluations were performed in 34 DM1 patients (19 F, age: 46.4 ± 12.1 years, disease duration: 18.7 ± 11.6 years). The content of neuro-axonal marker N-acetyl-aspartate, both relative to Creatine (NAA/Cr) and to myo-Inositol (NAA/mI) resulted significantly lower in DM1 patients compared to HC (p-values < 0.0001). NAA/Cr and NAA/mI correlated with the copy of the Rey-Osterrieth complex figure (r = 0.366, p = 0.033; r = 0.401, p = 0.019, respectively) and with Street’s completion tests scores (r = 0.409, p = 0.016; r = 0.341, p = 0.048 respectively). The proportion of white matter hyperintensities within the MR spectroscopy voxel did not correlate with the metabolite content. In this study, POWM metabolic alterations in DM1 patients were not associated with the white matter morphological changes and correlated with specific neuropsychological deficits.

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.

Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data

BACKGROUND

Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer's disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue.

METHODS

Following the initiative of the University of Washington's National Alzheimer's Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms.

RESULTS

Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward.

CONCLUSIONS

The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings.

Convolutional Neural Network Techniques for Brain Tumor Classification (from 2015 to 2022): Review, Challenges, and Future Perspectives

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. The main objective of this work is to present a comprehensive review of studies using CNN architectures to classify brain tumors using MR images with the aim of identifying useful strategies for and possible impediments in the development of this technology. Relevant articles were identified using a predefined, systematic procedure. For each article, data were extracted regarding training data, target problems, the network architecture, validation methods, and the reported quantitative performance criteria. The clinical relevance of the studies was then evaluated to identify limitations by considering the merits of convolutional neural networks and the remaining challenges that need to be solved to promote the clinical application and development of CNN algorithms. Finally, possible directions for future research are discussed for researchers in the biomedical and machine learning communities. A total of 83 studies were identified and reviewed. They differed in terms of the precise classification problem targeted and the strategies used to construct and train the chosen CNN. Consequently, the reported performance varied widely, with accuracies of 91.63–100% in differentiating meningiomas, gliomas, and pituitary tumors (26 articles) and of 60.0–99.46% in distinguishing low-grade from high-grade gliomas (13 articles). The review provides a survey of the state of the art in CNN-based deep learning methods for brain tumor classification. Many networks demonstrated good performance, and it is not evident that any specific methodological choice greatly outperforms the alternatives, especially given the inconsistencies in the reporting of validation methods, performance metrics, and training data encountered. Few studies have focused on clinical usability.

Role of endoscopic endonasal approach for craniopharyngiomas extending into the third ventricle in adults

•EAA is an innovative, promising, safe and effective approach for 3VCPs.•Key of success is surgeon learning curve in endoscopy and patients selection.•With correct indications, EEA gives GTR and morbidity rate similar to other routes.•Clinical, tumoral and anatomical features should be considered for EEA selection.

Follow-Up Assessment of Intracranial Aneurysms Treated with Endovascular Coiling: Comparison of Compressed Sensing and Parallel Imaging Time-of-Flight Magnetic Resonance Angiography

The aim of our study was to compare compressed sensing (CS) time-of-flight (TOF) magnetic resonance angiography (MRA) with parallel imaging (PI) TOF MRA in the evaluation of patients with intracranial aneurysms treated with coil embolization or stent-assisted coiling. We enrolled 22 patients who underwent follow-up imaging after intracranial aneurysm coil embolization. All patients underwent both PI TOF and CS TOF MRA during the same examination. Image evaluation aimed to compare the performance of CS to PI TOF MRA in determining the degree of aneurysm occlusion, as well as the depiction of parent vessel and vessels adjacent to the aneurysm dome. The reference standard for the evaluation of aneurysm occlusion was PI TOF MRA. The inter-modality agreement between CS and PI TOF MRA in the evaluation of aneurysm occlusion was almost perfect (κ  =  0.98, p  <  0.001) and the overall inter-rater agreement was substantial (κ  =  0.70, p  <  0.001). The visualization of aneurysm parent vessel in CS TOF images compared with PI TOF images was evaluated to be better in 11.4%, equal in 86.4%, and worse in 2.3%. CS TOF MRA, with almost 70% scan time reduction with respect to PI TOF MRA, yields comparable results for assessing the occlusion status of coiled intracranial aneurysms. Short scan times increase patient comfort, reduce the risk of motion artifacts, and increase patient throughput, with a resulting reduction in costs. CS TOF MRA may therefore be a potential replacement for PI TOF MRA as a first-line follow-up examination in patients with intracranial aneurysms treated with coil embolization.

Multishell Diffusion MR Tractography Yields Morphological and Microstructural Information of the Anterior Optic Pathway: A Proof-of-Concept Study in Patients with Leber’s Hereditary Optic Neuropathy

Tractography based on multishell diffusion-weighted magnetic resonance imaging (DWI) can be used to estimate the course of myelinated white matter tracts and nerves, yielding valuable information regarding normal anatomy and variability. DWI is sensitive to the local tissue microstructure, so tractography can be used to estimate tissue properties within nerve tracts at a resolution of millimeters. This study aimed to test the applicability of the method using a disease with a well-established pattern of myelinated nerve involvement. Eight patients with LHON and 13 age-matched healthy controls underwent tractography of the anterior optic pathway. Diffusion parameters were compared between groups, and for the patient group correlated with clinical/ophthalmological parameters. Tractography established the course of the anterior optic pathway in both patients and controls. Localized changes in fractional anisotropy were observed, and related to estimates of different tissue compartments within the nerve and tract. The proportion of different compartments correlated with markers of disease severity. The method described allows both anatomical localization and tissue characterization in vivo, permitting both visualization of variation at the individual level and statistical inference at the group level. It provides a valuable adjunct to ex vivo anatomical and histological study of normal variation and disease processes.

Case Report: Optic Atrophy and Nephropathy With m.13513G>A/MT-ND5 mtDNA Pathogenic Variant

Isolated complex I deficiency represents the most common mitochondrial respiratory chain defect involved in mitochondrial disorders. Among these, the mitochondrial DNA (mtDNA) m.13513G>A pathogenic variant in the NADH dehydrogenase 5 subunit gene (MT-ND5) has been associated with heterogenous manifestations, including phenotypic overlaps of mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes, Leigh syndrome, and Leber’s hereditary optic neuropathy (LHON). Interestingly, this specific mutation has been recently described in patients with adult-onset nephropathy. We, here, report the unique combination of LHON, nephropathy, sensorineural deafness, and subcortical and cerebellar atrophy in association with the m.13513G>A variant.

Neuroplasticity Mechanisms in Frontal Brain Gliomas: A Preliminary Study

Background

Pathological brain processes may induce adaptive cortical reorganization, however, the mechanisms underlying neuroplasticity that occurs in the presence of lesions in eloquent areas are not fully explained. The aim of this study was to evaluate functional compensatory cortical activations in patients with frontal brain gliomas during a phonemic fluency task and to explore correlations with cognitive performance, white matter tracts microstructural alterations, and tumor histopathological and molecular characterization.

Methods

Fifteen patients with frontal glioma were preoperatively investigated with an MRI study on a 3T scanner and a subgroup underwent an extensive neuropsychological assessment. The hemispheric laterality index (LI) was calculated through phonemic fluency task functional MRI (fMRI) activations in the frontal, parietal, and temporal lobe parcellations. Diffusion-weighted images were acquired for all patients and for a group of 24 matched healthy volunteers. Arcuate Fasciculus (AF) and Frontal Aslant Tract (FAT) tractography was performed using constrained spherical deconvolution diffusivity modeling and probabilistic fiber tracking. All patients were operated on with a resective aim and underwent adjuvant therapies, depending on the final diagnosis.

Results

All patients during the phonemic fluency task fMRI showed left hemispheric dominance in temporal and parietal regions. Regarding frontal regions (i.e., frontal operculum) we found right hemispheric dominance that increases when considering only those patients with tumors located on the left side. These latter activations positively correlate with verbal and visuo-spatial short-term memory, and executive functions. No correlations were found between the left frontal operculum and cognitive performance. Furthermore, patients with IDH-1 mutation and without TERT mutation, showed higher rightward frontal operculum fMRI activations and better cognitive performance in tests measuring general cognitive abilities, semantic fluency, verbal short-term memory, and executive functions. As for white matter tracts, we found left and right AF and FAT microstructural alterations in patients with, respectively, left-sided and right-side glioma compared to controls.

Conclusions

Compensatory cortical activation of the corresponding region in the non-dominant hemisphere and its association with better cognitive performance and more favorable histopathological and molecular tumor characteristics shed light on the neuroplasticity mechanisms that occur in the presence of a tumor, helping to predict the rate of post-operative deficit, with the final goal of improving patients'quality of life.

Cognitive profile in idiopathic autonomic failure: relation with white matter hyperintensities and neurofilament levels

OBJECTIVE

To disclose the nature of cognitive deficits in a cohort of patients with idiopathic autonomic failure (IAF) by exploring the relation among cognitive functions, cardiovascular autonomic failure (AF) and clinical progression to another α-synucleinopathy (phenoconversion).

METHODS

We retrospectively identified all patients with a clinical diagnosis of IAF who underwent a comprehensive neuropsychological evaluation, clinical examination and cardiovascular autonomic tests from the IAF-BO cohort. Brain magnetic resonance imaging (MRI) studies and cerebrospinal fluid (CSF) analysis, including neurofilament light chain (NfL), Alzheimer disease core biomarkers, and α-synuclein seeding activity were further evaluated when available. Correlations among cognitive functions, clinical features, cardiovascular AF, cerebral white matter hyperintensities (WMH) load, and CSF biomarkers were estimated using Spearman correlation coefficient.

RESULTS

Thirteen out of 30 (43%) patients with IAF displayed cognitive deficits (CI) mainly concerning executive functioning. Seven out of 30 (23%) met the criteria for mild cognitive impairment (MCI). The diagnosis of CI and MCI was not associated with phenoconversion or autonomic function parameters, including duration and severity of neurogenic orthostatic hypotension, presence and severity of supine hypertension, and nocturnal dipper profile. Twenty patients underwent a brain MRI and CSF analysis. MCI was related to WMH load (r = 0.549) and NfL levels (r = 0.656), while autonomic function parameters were not associated with either WMH or NfL levels.

INTERPRETATION

Cardiovascular AF and phenoconversion, underlying the spreading of neurodegeneration to the central nervous system, were not independent drivers of cognitive dysfunction in IAF. We identified WMH load and NfL levels as potential biomarkers of the neural network disruption associated with cognitive impairment in patients with IAF.

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.

Vessel Wall MRI: clinical implementation in cerebrovascular disorders—technical aspects

Vessel Wall MRI (VW-MRI) is an emerging MR sequence used for diagnosis, characterization, and treatment planning of cerebrovascular diseases. Although VW-MRI is not yet routinely used, most papers have emphasized its role in several aspects of the management of cerebrovascular diseases. Nowadays, no VW-MRI sequence optimized for the intracranial imaging is commercially available, thus the Spin Echo sequences are the more effective sequences for this purpose. Moreover, as one of the principal technical requirements for intracranial VW-MR imaging is to achieve both the suppression of blood in vessel lumen and of the outer cerebrospinal fluid, different suppression techniques have been developed. This short report provides the technical parameters of our VW-MR sequence developed over 3-years’ experience.

Predictive value of Tmax perfusion maps on final core in acute ischemic stroke: an observational single-center study

PURPOSE

To assess utility of computed tomography perfusion (CTP) protocols for selection of patients with acute ischemic stroke (AIS) for reperfusive treatments and compare the diagnostic accuracy (ACC) in predicting follow-up infarction, using time-to-maximum (Tmax) maps.

METHODS

We retrospectively reviewed consecutive AIS patients evaluated for reperfusive treatments at comprehensive stroke center, employing a multimodal computed tomography. To assess prognostic accuracy of CTP summary maps in predicting final infarct area (FIA) in AIS patients, we assumed the best correlation between non-viable tissue (NVT) and FIA in early and fully recanalized patients and/or in patients with favorable clinical response (FCR). On the other hand, the tissue at risk (TAR) should better correlate with FIA in untreated patients and in treatment failure.

RESULTS

We enrolled 158 patients, for which CTP maps with Tmax thresholds of 9.5 s and 16 s, presented sensitivity of 82.5%, specificity of 74.6%, and ACC of 75.9%. In patients selected for perfusion deficit in anterior circulation territory, CTP-Tmax > 16 s has proven relatively reliable to identify NVT in FCR patients, with a tendency to overestimate NVT. Similarly, CTP-Tmax > 9.5 s was reliable for TAR, but it was overestimated comparing to FIA, in patients with unfavorable outcomes.

CONCLUSIONS

In our experience, Tmax thresholds have proven sufficiently reliable to identify global hypoperfusion, with tendency to overestimate both NVT and TAR, not yielding satisfactory differentiation between true penumbra and benign oligoemia. In particular, the overestimation of NVT could have serious consequences in not selecting potential candidates for a reperfusion treatment.

Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach

Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B₁ , and IR-bSSFP-B₁ , the latter two designed to be more specific for B1+ parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T₁ ,  T₂ , and M₀ maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.

Molecular biomarkers correlate with brain grey and white matter changes in patients with mitochondrial m.3243A > G mutation

INTRODUCTION

The mitochondrial DNA (mtDNA) m.3243A > G mutation in the MT-TL1 gene results in a multi-systemic disease, that is commonly associated with neurodegenerative changes in the brain.

METHODS

Seventeen patients harboring the m3243A > G mutation were enrolled (age 43.1 ± 11.4 years, 10 M/7F). A panel of plasma biomarkers including lactate acid, alanine, L-arginine, fibroblast growth factor 21 (FGF-21), growth/differentiation factor 15 (GDF-15) and circulating cell free -mtDNA (ccf-mtDNA), as well as blood, urine and muscle mtDNA heteroplasmy were evaluated. Patients also underwent a brain standardized MR protocol that included volumetric T1-weighted images and diffusion-weighted MRI. Twenty sex- and age-matched healthy controls were included. Voxel-wise analysis was performed on T1-weighted and diffusion imaging, respectively with VBM (voxel-based morphometry) and TBSS (Tract-based Spatial Statistics). Ventricular lactate was also evaluated by ¹H-MR spectroscopy.

RESULTS

A widespread cortical gray matter (GM) loss was observed, more severe (p < 0.001) in the bilateral calcarine, insular, frontal and parietal cortex, along with infratentorial cerebellar cortex. High urine mtDNA mutation load, high levels of plasma lactate and alanine, low levels of plasma arginine, high levels of serum FGF-21 and ventricular lactate accumulation significantly (p < 0.05) correlated with the reduced brain GM density. Widespread microstructural alterations were highlighted in the white matter, significantly (p < 0.05) correlated with plasma alanine and arginine levels, with mtDNA mutation load in urine, with high level of serum GDF-15 and with high content of plasma ccf-mtDNA.

CONCLUSIONS

Our results suggest that the synergy of two pathogenic mechanisms, mtDNA-related mitochondrial respiratory deficiency and defective nitric oxide metabolism, contributes to the brain neurodegeneration in m.3243A > G patients.

Immune-checkpoint inhibitors in pituitary malignancies

To date, there are no standardized systemic treatment options for patients with metastatic pituitary carcinoma progressed to chemo and radiation therapy. Immune-checkpoint inhibitors (ICIs) have been successfully assessed in other solid malignancies and could be a concrete hope for these patients. We performed a critical review of the literature aimed to evaluate studies assessing ICIs in pituitary malignancies. We also conducted research about published translational data assessing immune-contexture in these malignancies. Some preliminary reports reported a successful administration of pembrolizumab or the combination between nivolumab and ipilimumab in patients with metastatic ACTH-secreting pituitary carcinomas. Translational data suggest that adenomas secreting growth hormone and ACTH have a suppressed immune-microenvironment, which could be more likely to benefit from ICIs. Immune-checkpoint inhibitors can be an effective treatment in patients with pituitary carcinoma and maybe also recurrent adenoma. Tumors secreting growth hormone and ACTH are more likely to benefit from ICIs due to a different immune-microenvironment.

Engineered CAR-T and novel CAR-based therapies to fight the immune evasion of glioblastoma: gutta cavat lapidem

INTRODUCTION

The field of cancer immunotherapy has achieved great advancements through the application of genetically engineered T cells with chimeric antigen receptors (CAR), that have shown exciting success in eradicating hematologic malignancies and have proved to be safe with promising early signs of antitumoral activity in the treatment of glioblastoma (GBM).

AREAS COVERED

We discuss the use of CAR T cells in GBM, focusing on limitations and obstacles to advancement, mostly related to toxicities, hostile tumor microenvironment, limited CAR T cells infiltration and persistence, target antigen loss/heterogeneity and inadequate trafficking. Furthermore, we introduce the refined strategies aimed at strengthening CAR T activity and offer insights in to novel immunotherapeutic approaches, such as the potential use of CAR NK or CAR M to optimize anti-tumor effects for GBM management.

EXPERT OPINION

With the progressive wide use of CAR T cell therapy, significant challenges in treating solid tumors, including central nervous system (CNS) tumors, are emerging, highlighting early disease relapse and cancer cell resistance issues, owing to hostile immunosuppressive microenvironment and tumor antigen heterogeneity. In addition to CAR T cells, there is great interest in utilizing other types of CAR-based therapies, such as CAR natural killer (CAR NK) or CAR macrophages (CAR M) cells for CNS tumors.

Discovering the Molecular Landscape of Meningioma: The Struggle to Find New Therapeutic Targets

Meningiomas are the most common primary CNS tumors. They are usually benign but can present aggressive behavior in about 20% of cases. The genetic landscape of meningioma is characterized by the presence (in about 60% of cases) or absence of NF2 mutation. Low-grade meningiomas can also present other genetic alterations, particularly affecting SMO, TRAF7, KLF4 AKT1 and PI3KCA. In higher grade meningiomas, mutations of TERT promoter and deletion of CDKN2A/B seem to have a prognostic value. Furthermore, other genetic alterations have been identified, such as BAP1, DMD and PBRM1. Different subgroups of DNA methylation appear to be correlated with prognosis. In this review, we explored the genetic landscape of meningiomas and the possible therapeutic implications.

Liquid Biopsy in Glioblastoma Management: From Current Research to Future Perspectives

Glioblastoma (GBM) is the most common primary tumor of the central nervous system. Arising from neuroepithelial glial cells, GBM is characterized by invasive behavior, extensive angiogenesis, and genetic heterogeneity that contributes to poor prognosis and treatment failure. Currently, there are several molecular biomarkers available to aid in diagnosis, prognosis, and predicting treatment outcomes; however, all require the biopsy of tumor tissue. Nevertheless, a tissue sample from a single location has its own limitations, including the risk related to the procedure and the difficulty of obtaining longitudinal samples to monitor treatment response and to fully capture the intratumoral heterogeneity of GBM. To date, there are no biomarkers in blood or cerebrospinal fluid for detection, follow-up, or prognostication of GBM. Liquid biopsy offers an attractive and minimally invasive solution to support different stages of GBM management, assess the molecular biology of the tumor, identify early recurrence and longitudinal genomic evolution, predict both prognosis and potential resistance to chemotherapy or radiotherapy, and allow patient selection for targeted therapies. The aim of this review is to describe the current knowledge regarding the application of liquid biopsy in glioblastoma, highlighting both benefits and obstacles to translation into clinical care. IMPLICATIONS FOR PRACTICE: To translate liquid biopsy into clinical practice, further prospective studies are required with larger cohorts to increase specificity and sensitivity. With the ever-growing interest in RNA nanotechnology, microRNAs may have a therapeutic role in brain tumors.

Brain Structure and Degeneration Staging in Friedreich Ataxia: Magnetic Resonance Imaging Volumetrics from the ENIGMA-Ataxia Working Group

Objective

Friedreich ataxia (FRDA) is an inherited neurological disease defined by progressive movement incoordination. We undertook a comprehensive characterization of the spatial profile and progressive evolution of structural brain abnormalities in people with FRDA.

Methods

A coordinated international analysis of regional brain volume using magnetic resonance imaging data charted the whole‐brain profile, interindividual variability, and temporal staging of structural brain differences in 248 individuals with FRDA and 262 healthy controls.

Results

The brainstem, dentate nucleus region, and superior and inferior cerebellar peduncles showed the greatest reductions in volume relative to controls (Cohen d = 1.5–2.6). Cerebellar gray matter alterations were most pronounced in lobules I–VI (d = 0.8), whereas cerebral differences occurred most prominently in precentral gyri (d = 0.6) and corticospinal tracts (d = 1.4). Earlier onset age predicted less volume in the motor cerebellum (r_max = 0.35) and peduncles (r_max = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (r_max = −0.49); subgrouping showed these to be robust and early features of FRDA, and strong candidates for further biomarker validation. Cerebral white matter abnormalities, particularly in corticospinal pathways, emerge as intermediate disease features. Cerebellar and cerebral gray matter loss, principally targeting motor and sensory systems, preferentially manifests later in the disease course.

Interpretation

FRDA is defined by an evolving spatial profile of neuroanatomical changes beyond primary pathology in the cerebellum and spinal cord, in line with its progressive clinical course. The design, interpretation, and generalization of research studies and clinical trials must consider neuroanatomical staging and associated interindividual variability in brain measures. ANN NEUROL 2021;90:570–583

Is Molecular Tailored-Therapy Changing the Paradigm for CNS Metastases in Breast Cancer?

Breast cancer (BC) is the second most common tumour spreading to the central nervous system (CNS). The prognosis of patients with CNS metastases depends on several parameters including the molecular assessment of the disease. Although loco-regional treatment remains the best approach, systemic therapies are acquiring a role leading to remarkable long-lasting responses. The efficacy of these compounds diverges between tumours with different molecular assessments. Promising agents under investigation are drugs targeting the HER2 pathways such as tucatinib, neratinib, pyrotinib, trastuzumab deruxtecan. In addition, there are several promising agents under investigation for patients with triple-negative brain metastases (third-generation taxane, etirinotecan, sacituzumab, immune-checkpoint inhibitors) and hormone receptor-positive brain metastases (CDK 4/5, phosphoinositide-3-kinase-mammalian target of rapamycin [PI3K/mTOR] inhibitors). Also, the systemic treatment of leptomeningeal metastases, which represents a very negative prognostic site of metastases, is likely to change as several compounds are under investigation, some with interesting preliminary results. Here we performed a comprehensive review focusing on the current management of CNS metastases according to molecular subtypes, site of metastases (leptomeningeal vs brain), and systemic treatments under investigation.

Distinct MRI pattern of "pseudoresponse" in recurrent glioblastoma multiforme treated with regorafenib: Case report and literature review

Antiangiogenic agents can induce a distinct MRI pattern in glioblastoma, characterized by a decrease in the contrast enhancement on T1-weighted images and a simultaneous hyperintensity on T2-weighted or fluid-attenuated inversion recovery images.