Structural Variants at the LMNB1 Locus: Deciphering Pathomechanisms in Autosomal Dominant Adult-Onset Demyelinating Leukodystrophy.

OBJECTIVES: We aimed to elucidate the pathogenic mechanisms underlying autosomal dominant adult-onset demyelinating leukodystrophy (ADLD), and to understand the genotype/phenotype correlation of structural variants (SVs) in the LMNB1 locus. BACKGROUND: Since the discovery of 3D genome architectures and topologically associating domains (TADs), new pathomechanisms have been postulated for SVs, regardless of gene dosage changes. ADLD is a rare genetic disease associated with duplications (classical ADLD) or noncoding deletions (atypical ADLD) in the LMNB1 locus. METHODS: High-throughput chromosome conformation capture, RNA sequencing, histopathological analyses of postmortem brain tissues, and clinical and neuroradiological investigations were performed. RESULTS: We collected data from >20 families worldwide carrying SVs in the LMNB1 locus and reported strong clinical variability, even among patients carrying duplications of the entire LMNB1 gene, ranging from classical and atypical ADLD to asymptomatic carriers. We showed that patients with classic ADLD always carried intra-TAD duplications, resulting in a simple gene dose gain. Atypical ADLD was caused by LMNB1 forebrain-specific misexpression due to inter-TAD deletions or duplications. The inter-TAD duplication, which extends centromerically and crosses the 2 TAD boundaries, did not cause ADLD. Our results provide evidence that astrocytes are key players in ADLD pathology. INTERPRETATION: Our study sheds light on the 3D genome and TAD structural changes associated with SVs in the LMNB1 locus, and shows that a duplication encompassing LMNB1 is not sufficient per se to diagnose ADLD, thereby strongly affecting genetic counseling. Our study supports breaking TADs as an emerging pathogenic mechanism that should be considered when studying brain diseases. ANN NEUROL 2024.

Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis.

Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.

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.

IMPA-Net: Interpretable Multi-Part Attention Network for Trustworthy Brain Tumor Classification from MRI.

Deep learning (DL) networks have shown attractive performance in medical image processing tasks such as brain tumor classification. However, they are often criticized as mysterious "black boxes". The opaqueness of the model and the reasoning process make it difficult for health workers to decide whether to trust the prediction outcomes. In this study, we develop an interpretable multi-part attention network (IMPA-Net) for brain tumor classification to enhance the interpretability and trustworthiness of classification outcomes. The proposed model not only predicts the tumor grade but also provides a global explanation for the model interpretability and a local explanation as justification for the proffered prediction. Global explanation is represented as a group of feature patterns that the model learns to distinguish high-grade glioma (HGG) and low-grade glioma (LGG) classes. Local explanation interprets the reasoning process of an individual prediction by calculating the similarity between the prototypical parts of the image and a group of pre-learned task-related features. Experiments conducted on the BraTS2017 dataset demonstrate that IMPA-Net is a verifiable model for the classification task. A percentage of 86% of feature patterns were assessed by two radiologists to be valid for representing task-relevant medical features. The model shows a classification accuracy of 92.12%, of which 81.17% were evaluated as trustworthy based on local explanations. Our interpretable model is a trustworthy model that can be used for decision aids for glioma classification. Compared with black-box CNNs, it allows health workers and patients to understand the reasoning process and trust the prediction outcomes.

Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset.

The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-the-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical magnetic resonance (MR) images, comparing the network outcomes with traditional up-sampling techniques. We explored possible changes in the model response when different MR sequences were analyzed. T1w and T2w MR brain images of 70 human healthy subjects (F:M, 40:30) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) repository were down-sampled and then up-sampled using EDSR model and BiCubic (BC) interpolation. Several reference metrics were used to quantitatively assess the performance of up-sampling operations (RMSE, pSNR, SSIM, and HFEN). Two-dimensional and three-dimensional reconstructions were evaluated. Different brain tissues were analyzed individually. The EDSR model was superior to BC interpolation on the selected metrics, both for two- and three- dimensional reconstructions. The reference metrics showed higher quality of EDSR over BC reconstructions for all the analyzed images, with a significant difference of all the criteria in T1w images and of the perception-based SSIM and HFEN in T2w images. The analysis per tissue highlights differences in EDSR performance related to the gray-level values, showing a relative lack of outperformance in reconstructing hyperintense areas. The EDSR model, trained on general-purpose images, better reconstructs MR T1w and T2w images than BC, without any retraining or fine-tuning. These results highlight the excellent generalization ability of the network and lead to possible applications on other MR measurements.

The Contribution of Vessel Wall Magnetic Resonance Imaging to the Diagnosis of Primary and Secondary Central Nervous System Vasculitis.

BACKGROUND: To describe high-resolution brain vessel wall MRI (VW-MRI) patterns and morphological brain findings in central nervous system (CNS) vasculitis patients. METHODS: Fourteen patients with confirmed CNS Vasculitis from two tertiary centers underwent VW-MRI using a 3T scanner. The images were reviewed by two neuroradiologists to assess vessel wall enhancement characteristics and locations. RESULTS: Fourteen patients were included (six females; average age 48 ± 19 years). Diagnoses included primary CNS vasculitis (PCNSV) in six patients and secondary CNS vasculitis (SCNSV) in eight, half of which were infection-related. Thirteen patients showed vessel wall enhancement, which was intense in eleven patients (84.6%) and concentric in twelve (92.3%), affecting the anterior circulation in nine patients (69.2%), posterior in two patients (15.4%), and both circulations in two patients (15.4%). The enhancement patterns were similar across different CNS vasculitis types. DWI changes corresponded with areas of vessel wall enhancement in 77% of patients. Conclusions: CNS vasculitis is often associated with intense, concentric vessel wall enhancement in VW-MRI, especially in the anterior circulation. The consistent presence of DWI alterations in affected territories suggests a possible link to microembolization or hypoperfusion. These imaging findings complement parenchymal brain MRI and MRA/DSA data, potentially increasing the possibility of a clinical diagnosis of CNS vasculitis.

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.

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.

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.

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.

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.

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.