Amyotrophic lateral sclerosis phenotypes significantly differ in terms of magnetic susceptibility properties of the precentral cortex

The aim of our study was to investigate whether the magnetic susceptibility varies according to the amyotrophic lateral sclerosis (ALS) phenotypes based on the predominance of upper motor neuron (UMN)/lower motor neuron (LMN) impairment. We retrospectively collected imaging and clinical data of 47 ALS patients (12 with UMN predominance (UMN-ALS), 16 with LMN predominance (LMN-ALS), and 19 with no clinically defined predominance (Np-ALS)). We further enrolled 23 healthy controls (HC) and 15 ALS mimics (ALS-Mim). These participants underwent brain 3-T magnetic resonance imaging (3-T MRI) with T1-weighted and gradient-echo multi-echo sequences. Automatic segmentation and quantitative susceptibility mapping (QSM) were performed. The skewness of the susceptibility values in the precentral cortex (SuscSKEW) was automatically computed, compared among the groups, and correlated to the clinical variables. The Kruskal-Wallis test showed significant differences in terms of SuscSKEW among groups (χ2(3) = 24.2, p < 0.001), and pairwise tests showed that SuscSKEW was higher in UMN-ALS compared to those in LMN-ALS (p < 0.001), HC (p < 0.001), Np-ALS (p = 0.012), and ALS-Mim (p < 0.001). SuscSKEW was highly correlated with the Penn UMN score (Spearman's rho 0.612, p < 0.001). This study demonstrates that the clinical ALS phenotypes based on UMN/LMN sign predominance significantly differ in terms of magnetic susceptibility properties of the precentral cortex. Combined MRI-histopathology investigations are strongly encouraged to confirm whether this evidence is due to iron overload in UMN-ALS, unlike in LMN-ALS. • Magnetic susceptibility in the precentral cortex reflects the prevalence of UMN/LMN impairment in the clinical ALS phenotypes. • The degree of UMN/LMN impairment might be well described by the automatically derived measure of SuscSKEW in the precentral cortex. • Increased SuscSKEW in the precentral cortex is more relevant in UMN-ALS patients compared to those in Np-ALS and LMN-ALS patients

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

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures

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

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Association of Superficial White Matter Alterations with Cerebrospinal Fluid Biomarkers and Cognitive Decline in Neurodegenerative Dementia

BACKGROUND: Superficial white matter (SWM) alterations correlated with cognitive decline have been described in Alzheimer's disease (AD). OBJECTIVE: The study aims to extend the investigation of the SWM alterations to AD and non-AD neurodegenerative dementia (ND) and explore the relationship with cerebrospinal fluid (CSF) biomarkers and clinical data. METHODS: From a database of 323 suspected dementia cases, we retrospectively recruited 55 ND with abnormal amyloid-β42 (AD) and 38 ND with normal amyloid-β42 (non-AD) and collected clinical data, CSF biomarkers, and magnetic resonance images. Ten healthy controls (HC) were recruited for imaging and Mini-Mental State Examination (MMSE). Diffusion tensor imaging (DTI) measurements were performed in the lobar SWM regions and Kruskal Wallis tests were used for among-group comparison. Spearman's correlation tests were performed between DTI measures, CSF biomarkers, and clinical data. RESULTS: AD and non-AD showed significant differences in the DTI measures across the SWM compared to HC. Significant differences between AD and non-AD were detected in the left parietal lobe. DTI measures correlated with amyloid-β42 and MMSE diffusely in the SWM, less extensively with total-tau and phosphorylated tau, and with disease duration in the parietal lobe bilaterally. CONCLUSION: Widespread SWM alterations occur in both AD and non-AD ND and AD shows appreciably more severe alterations in the parietal SWM. Notably, the alterations in the SWM are strongly linked not only to the cognitive decline but also to the diagnostic CSF biomarkers. Further studies are encouraged to evaluate the DTI measures in the SWM as in vivo non-invasive biomarkers in the preclinical phase

Effects of in-utero exposure to chemotherapy on fetal brain growth

OBJECTIVE: Children exposed to chemotherapy in the prenatal period demonstrate normal neurocognitive development at 3 years but concerns regarding fetal brain growth remain high considering its vulnerability to external stimuli. Our aim was to evaluate the impact of in-utero chemotherapy exposure on brain growth and its effects on neurodevelopmental outcome. METHODS: The protocol was approved by the local ethics committee. Brain regional volumes at term postmenstrual age were measured by MRI in children exposed to in-utero chemotherapy and compared with normal MRI controls. Brain segmentation was performed by Advanced Normalization Tools (ANTs)-based transformations of the Neonatal Brain Atlas (ALBERT). Neurodevelopmental assessment (Bayley-III scales) was performed at 18 months corrected age in both exposed infants and in a group of healthy controls. Multiple linear regressions and false discovery rate correction for multiple comparisons were performed. RESULTS: Twenty-one newborns prenatally exposed to chemotherapy (epirubicin administered in 81% of mothers) were enrolled in the study: the mean gestational age was 36.4±2.4 weeks and the mean birthweight was 2,753±622 g. Brain MRI was performed at mean postmenstrual age of 41.1±1.4 weeks. No statistically significant differences were identified between the children exposed to chemotherapy and controls in both the total (398±55 cm3 vs 427±56 cm3, respectively) and regional brain volumes. Exposed children showed normal Bayley-III scores (cognitive 110.2±14.5, language 99.1±11.3, and motor 102.6±7.3), and no significant correlation was identified between the brain volumes and neurodevelopmental outcome. CONCLUSION: Prenatal exposure to anthracycline/cyclophosphamide-based chemotherapy does not impact fetal brain growth, thus supporting the idea that oncological treatment in pregnant women seems to be feasible and safe for the fetus.status: publishe

Effects of in-utero exposure to chemotherapy on fetal brain growth

Objective Children exposed to chemotherapy in the prenatal period demonstrate normal neurocognitive development at 3 years but concerns regarding fetal brain growth remain high considering its vulnerability to external stimuli. Our aim was to evaluate the impact of in-utero chemotherapy exposure on brain growth and its effects on neurodevelopmental outcome. Methods The protocol was approved by the local ethics committee. Brain regional volumes at term postmenstrual age were measured by MRI in children exposed to in-utero chemotherapy and compared with normal MRI controls. Brain segmentation was performed by Advanced Normalization Tools (ANTs)-based transformations of the Neonatal Brain Atlas (ALBERT). Neurodevelopmental assessment (Bayley-III scales) was performed at 18 months corrected age in both exposed infants and in a group of healthy controls. Multiple linear regressions and false discovery rate correction for multiple comparisons were performed. Results Twenty-one newborns prenatally exposed to chemotherapy (epirubicin administered in 81% of mothers) were enrolled in the study: the mean gestational age was 36.4\ub12.4 weeks and the mean birthweight was 2,753\ub1622 g. Brain MRI was performed at mean postmenstrual age of 41.1\ub11.4 weeks. No statistically significant differences were identified between the children exposed to chemotherapy and controls in both the total (398\ub155 cm 3 vs 427\ub156 cm 3, respectively) and regional brain volumes. Exposed children showed normal Bayley-III scores (cognitive 110.2\ub114.5, language 99.1\ub111.3, and motor 102.6\ub17.3), and no significant correlation was identified between the brain volumes and neurodevelopmental outcome. Conclusion Prenatal exposure to anthracycline/cyclophosphamide-based chemotherapy does not impact fetal brain growth, thus supporting the idea that oncological treatment in pregnant women seems to be feasible and safe for the fetus

Magnetic susceptibility as a 1-year predictor of outcome in familial cerebral cavernous malformations: a pilot study

Objectives: To test whether quantitative susceptibility mapping (QSM) of cerebral cavernous malformations (CCMs) assessed at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. Methods: Familial CCM patients were enrolled in the longitudinal multicentre study Treat-CCM. The 3-T MRI scan allowed performing a semi-automatic segmentation of CCMs and computing the maximum susceptibility in each segmented CCM (QSMmax) at baseline. CCMs were classified as haemorrhagic and non-haemorrhagic at baseline and then subclassified according to the 1-year (t1) evolution. Between-group differences were tested, and the diagnostic accuracy of QSMmax in predicting the presence or absence of haemorrhagic signs in CCMs was calculated with ROC analyses. Results: Thirty-three patients were included in the analysis, and a total of 1126 CCMs were segmented. QSMmax was higher in haemorrhagic CCMs than in non-haemorrhagic CCMs (p &lt; 0.001). In haemorrhagic CCMs at baseline, the accuracy of QSMmax in differentiating CCMs that were still haemorrhagic from CCMs that recovered from haemorrhage at t1 calculated as area under the curve (AUC) was 0.78 with sensitivity 62.69%, specificity 82.35%, positive predictive value (PPV) 93.3% and negative predictive value (NPV) 35.9% (QSMmax cut-off ≥ 1462.95 ppb). In non-haemorrhagic CCMs at baseline, AUC was 0.91 in differentiating CCMs that bled at t1 from stable CCMs with sensitivity 100%, specificity 81.9%, PPV 5.1%, and NPV 100% (QSMmax cut-off ≥ 776.29 ppb). Conclusions: The QSMmax in CCMs at baseline showed high accuracy in predicting the presence or absence of haemorrhagic signs at 1-year follow-up. Further effort is required to test the role of QSM in follow-up assessment and therapeutic trials in multicentre CCM studies. Key points: • QSM in semi-automatically segmented CCM was feasible. • The maximum magnetic susceptibility in a single CCM at baseline may predict the presence or absence of haemorrhagic signs at 1-year follow-up. • Multicentric studies are needed to enforce the role of QSM in predicting the CCMs' haemorrhagic evolution in patients affected by familial and sporadic forms

Simultaneous PET-MRI studies of the concordance of atrophy and hypometabolism in syndromic variants of Alzheimer's disease and frontotemporal dementia: an extended case series

Background: Simultaneous PET-MRI is used to compare patterns of cerebral hypometabolism and atrophy in six different dementia syndromes. Objectives: The primary objective was to conduct an initial exploratory study regarding the concordance of atrophy and hypometabolism in syndromic variants of Alzheimer's disease (AD) and frontotemporal dementia (FTD). The secondary objective was to determine the effect of image analysis methods on determination of atrophy and hypometabolism. Method: PET and MRI data were acquired simultaneously on 24 subjects with six variants of AD and FTD (n = 4 per group). Atrophy was rated visually and also quantified with measures of cortical thickness. Hypometabolism was rated visually and also quantified using atlas-and SPM-based approaches. Concordance was measured using weighted Cohen's kappa. Results: Atrophy-hypometabolism concordance differed markedly between patient groups; kappa scores ranged from 0.13 (nonfluent/agrammatic variant of primary progressive aphasia, nfvPPA) to 0.49 (posterior cortical variant of AD, PCA). Heterogeneity was also observed within groups; the confidence intervals of kappa scores ranging from 00.25 for PCA to 0.290.61 for nfvPPA. More widespread MRI and PET changes were identified using quantitative methods than on visual rating. Conclusion: The marked differences in concordance identified in this initial study may reflect differences in the molecular pathologies underlying AD and FTD syndromic variants but also operational differences in the methods used to diagnose these syndromes. The superior ability of quantitative methodologies to detect changes on PET and MRI, if confirmed on larger cohorts, may favor their usage over qualitative visual inspection in future clinical diagnostic practice