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-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 out-performance in reconstructing hyper-intense areas. The EDSR model, trained on general-purpose images, better reconstructs MR T1w and T2w images than BC, without any re-training or fine-tuning. These results highlight the excellent generalization ability of the network and lead to possible applications on other MR measurements.Significance Statement Super resolution applications in biomedical images may help in reducing acquisition scan time and concurrently improving the quality of the exam. Neural networks have been shown to work better than traditional up-sampling techniques, even though ad hoc training experiments need to be performed for specific kind of data. In this work, we used a model previously trained with general-purpose images and we directly applied to magnetic resonance human brain ones; we verified its ability of reconstructing new kind of images, comparing the results with traditional up-sampling techniques. Our analysis highlights the excellent generalization capabilities of the model over the images tested, without need of specific re-training, suggesting that such results might be reproduced on images from other acquisition systems.

Optimizing Screening for Intrastriatal Interventions in Huntington's Disease Using Predictive Models

BACKGROUND

Intrastriatal delivery of potential therapeutics in Huntington's disease (HD) requires sufficient caudate and putamen volumes. Currently, volumetric magnetic resonance imaging is rarely done in clinical practice, and these data are not available in large research cohorts such as Enroll-HD.

OBJECTIVE

The objective of this study was to investigate whether predictive models can accurately classify HD patients who exceed caudate and putamen volume thresholds required for intrastriatal therapeutic interventions.

METHODS

We obtained and merged data for 1374 individuals across three HD cohorts: IMAGE-HD, PREDICT-HD, and TRACK-HD/TRACK-ON. We imputed missing data for clinical variables with >72% non-missing values and used the model-building algorithm BORUTA to identify the 10 most important variables. A random forest algorithm was applied to build a predictive model for putamen volume >2500 mm3 and caudate volume >2000 mm3 bilaterally. Using the same 10 predictors, we constructed a logistic regression model with predictors significant at P < 0.05.

RESULTS

The random forest model with 1000 trees and minimal terminal node size of 5 resulted in 83% area under the curve (AUC). The logistic regression model retaining age, CAG repeat size, and symbol digit modalities test-correct had 85.1% AUC. A probability cutoff of 0.8 resulted in 5.4% false positive and 66.7% false negative rates.

CONCLUSIONS

Using easily obtainable clinical data and machine learning-identified initial predictor variables, random forest, and logistic regression models can successfully identify people with sufficient striatal volumes for inclusion cutoffs. Adopting these models in prescreening could accelerate clinical trial enrollment in HD and other neurodegenerative disorders when volume cutoffs are necessary enrollment criteria. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fracture strength of 3-units fixed partial dentures fabricated with metal-ceramic, graphene doped PMMA and PMMA before and after ageing: An in-vitro study

OBJECTIVES

To evaluate the fracture strength and linear elongation at break of three-units fixed partial dentures (FPDs) fabricated with traditional and new materials for fixed prosthodontics before and after ageing.

METHODS

Sixty models of three-units FPDs were fabricated and cemented onto a Co-Cr model simulating the replacement of a maxillary second premolar. The samples were randomly divided into 3 groups: metal-ceramic (MCR), graphene-doped polymethylmethacrylate (PMMA-GR) and polymethylmethacrylate (PMMA). Half of the samples were directly subjected to fracture test, while the remaining half underwent an ageing process and then a fracture loading test using an electrodynamic testing machine. Fracture load and elongation at break values were taken and statistically analysed.

RESULTS

Significant differences were detected between the different materials (p<0.05). All groups showed a reduction of the fracture load and elongation at break values after ageing, but not statistically significant, except for PMMA group (p = 2.012e-19) (p = 3.8e-11).

CONCLUSIONS

MCR and PMMA-GR three-units FPDs showed higher fracture strength and lower elongation at break compared to PMMA. MCR and PMMA-GR had higher resistance to ageing processes compared to PMMA.

CLINICAL SIGNIFICANCE

PMMA-GR could be considered a material for long-term provisional restorations as its mechanical behaviour and ageing resistance are more like MCR than PMMA.

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.

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.

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.

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.

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.

The contribution of the 1H-MRS lipid signal to cervical cancer prognosis: a preliminary study

Background

The aim of this study was to investigate the role of the lipid peak derived from ¹H magnetic resonance (MR) spectroscopy in assessing cervical cancer prognosis, particularly in assessing response to neoadjuvant chemotherapy (NACT) of locally advanced cervical cancer (LACC).

Methods

We enrolled 17 patients with histologically proven cervical cancer who underwent 3-T MR imaging at baseline. In addition to conventional imaging sequences for pelvic assessment, the protocol included a single-voxel point-resolved spectroscopy (PRESS) sequence, with repetition time of 1,500 ms and echo times of 28 and 144 ms. Spectra were analysed using the LCModel fitting routine, thus extracting multiple metabolites, including lipids (Lip) and total choline (tCho). Patients with LACC were treated with NACT and reassessed by MRI at term. Based on tumour volume reduction, patients were classified as good responder (GR; tumour volume reduction > 50%) and poor responder or nonresponder (PR-or-NR; tumour volume reduction ≤ 50%).

Results

Of 17 patients, 11 were LACC. Of these 11, only 6 had both completed NACT and had good-quality ¹H-MR spectra; 3 GR and 3 PR-or-NR. A significant difference in lipid values was observed in the two groups of patients, particularly with higher Lip values and higher Lip/tCho ratio in PR-NR patients (p =0.040). A significant difference was also observed in choline distribution (tCho), with higher values in GR patients (p = 0.040).

Conclusions

Assessment of lipid peak at ¹H-MR spectroscopy could be an additional quantitative parameter in predicting the response to NACT in patients with LACC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41747-022-00300-1.

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.

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.

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.

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.

The Safety of Deutetrabenazine for Chorea in Huntington Disease: An Open-Label Extension Study

BACKGROUND

Deutetrabenazine is approved in the USA, China, Australia, Israel, Brazil, and South Korea for the treatment of chorea associated with Huntington disease.

OBJECTIVE

We aimed to evaluate the long-term safety and tolerability of deutetrabenazine for the treatment of Huntington disease.

METHODS

This open-label, single-arm, multi-center study included patients who completed a double-blind study (Rollover) and patients who converted overnight from a stable tetrabenazine dose (Switch). Exposure-adjusted incidence rates (adverse events per person-year) were calculated. Efficacy was analyzed using a stable post-titration timepoint (8 weeks). Changes in the Unified Huntington's Disease Rating Scale total motor score and total maximal chorea score from baseline to week 8, as well as those from week 8 to week 145 (or the last visit on the study drug if that occurred earlier), were evaluated as both efficacy and safety endpoints during the study.

RESULTS

Of 119 patients (Rollover, n = 82; Switch, n = 37), 100 (84%) completed ≥ 1 year of treatment. End-of-study exposure-adjusted incidence rates for adverse events in Rollover and Switch, respectively, were: any, 2.57 and 4.02; serious, 0.11 and 0.14; leading to dose suspension, 0.05 and 0.04. Common adverse events (≥ 4% either cohort) included somnolence (Rollover, 20%; Switch, 30%), depression (32%; 22%), anxiety (27%; 35%), insomnia (23%; 16%), and akathisia (6%; 11%). Adverse events of interest included suicidality (9%; 5%) and parkinsonism (4%; 8%). Mean dose at week 8 was 38.1 mg (Rollover) and 36.5 mg (Switch). Mean dose across cohorts after titration was 37.6 mg; at the final visit, mean dose across cohorts was 45.7 mg. Patients showed minimal change in the Unified Huntington's Disease Rating Scale total maximal chorea scores with stable dosing from weeks 8-145 or at the end of treatment, but total motor score increased versus week 8 (mean change [standard deviation]: 8.2 [11.9]). There were no unexpected adverse events upon drug withdrawal, and mean (standard deviation) total maximal chorea scores increased 4.7 (4.6) units from week 8 to 1-week follow-up.

CONCLUSIONS

Adverse events observed with long-term deutetrabenazine exposure were consistent with previous studies. Reductions in chorea persisted over time. Upon treatment cessation, there was no unexpected worsening of chorea.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01897896.

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.

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

Characterization of Structural Bone Properties through Portable Single-Sided NMR Devices: State of the Art and Future Perspectives

Nuclear Magnetic Resonance (NMR) is a well-suited methodology to study bone composition and structural properties. This is because the NMR parameters, such as the T2 relaxation time, are sensitive to the chemical and physical environment of the 1H nuclei. Although magnetic resonance imaging (MRI) allows bone structure assessment in vivo, its cost limits the suitability of conventional MRI for routine bone screening. With difficulty accessing clinically suitable exams, the diagnosis of bone diseases, such as osteoporosis, and the associated fracture risk estimation is based on the assessment of bone mineral density (BMD), obtained by the dual-energy X-ray absorptiometry (DXA). However, integrating the information about the structure of the bone with the bone mineral density has been shown to improve fracture risk estimation related to osteoporosis. Portable NMR, based on low-field single-sided NMR devices, is a promising and appealing approach to assess NMR properties of biological tissues with the aim of medical applications. Since these scanners detect the signal from a sensitive volume external to the magnet, they can be used to perform NMR measurement without the need to fit a sample inside a bore of a magnet, allowing, in principle, in vivo application. Techniques based on NMR single-sided devices have the potential to provide a high impact on the clinical routine because of low purchasing and running costs and low maintenance of such scanners. In this review, the development of new methodologies to investigate structural properties of trabecular bone exploiting single-sided NMR devices is reviewed, and current limitations and future perspectives are discussed.

The Combination of Metabolic Posterior Cingulate Cortical Abnormalities and Structural Asymmetries Improves the Differential Diagnosis Between Primary Progressive Aphasia and Alzheimer's Disease

Differential diagnosis between primary progressive aphasia (PPA) and Alzheimer's disease (AD) could be difficult if based on clinical grounds alone. We evaluated the combination of proton MR spectroscopy of posterior cingulate cortex (PCC) and quantitative structural imaging asymmetries to differentiate PPA from AD patients. A greater left-lateralized temporo-parietal atrophy (higher accuracy for the PCC, 81.4%) and metabolic neurodegenerative changes in PCC (accuracy 76.8%) was demonstrated in PPA versus AD. The combined multiparametric approach increased the accuracy to 94%in the differential diagnosis between these two neurodegenerative diseases.

ESGO/ISUOG/IOTA/ESGE Consensus Statement on preoperative diagnosis of ovarian tumours

The European Society of Gynaecological Oncology (ESGO), the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG), the International Ovarian Tumour Analysis (IOTA) group and the European Society for Gynaecological Endoscopy (ESGE) jointly developed clinically relevant and evidence-based statements on the preoperative diagnosis of ovarian tumours, including imaging techniques, biomarkers and prediction models.

ESGO/ISUOG/IOTA/ESGE nominated a multidisciplinary international group, including expert practising clinicians and researchers who have demonstrated leadership and expertise in the preoperative diagnosis of ovarian tumours and management of patients with ovarian cancer (19 experts across Europe). A patient representative was also included in the group. To ensure that the statements were evidence-based, the current literature was reviewed and critically appraised.

Preliminary statements were drafted based on the review of the relevant literature. During a conference call, the whole group discussed each preliminary statement and a first round of voting was carried out. Statements were removed when a consensus among group members was not obtained. The voters had the opportunity to provide comments/suggestions with their votes. The statements were then revised accordingly. Another round of voting was carried out according to the same rules to allow the whole group to evaluate the revised version of the statements. The group achieved consensus on 18 statements.

This Consensus Statement presents these ESGO/ISUOG/IOTA/ESGE statements on the preoperative diagnosis of ovarian tumours and the assessment of carcinomatosis, together with a summary of the evidence supporting each statement.

On the dependence of quantitative diffusion-weighted imaging on scanner system characteristics and acquisition parameters: A large multicenter and multiparametric phantom study with unsupervised clustering analysis

PURPOSE

The purpose of this multicenter phantom study was to exploit an innovative approach, based on an extensive acquisition protocol and unsupervised clustering analysis, in order to assess any potential bias in apparent diffusion coefficient (ADC) estimation due to different scanner characteristics. Moreover, we aimed at assessing, for the first time, any effect of acquisition plan/phase encoding direction on ADC estimation.

METHODS

Water phantom acquisitions were carried out on 39 scanners. DWI acquisitions (b-value = 0-200-400-600-800-1000 s/mm²) with different acquisition plans (axial, coronal, sagittal) and phase encoding directions (anterior/posterior and right/left, for the axial acquisition plan), for 3 orthogonal diffusion weighting gradient directions, were performed. For each acquisition setup, ADC values were measured in-center and off-center (6 different positions), resulting in an entire dataset of 84 × 39 = 3276 ADC values. Spatial uniformity of ADC maps was assessed by means of the percentage difference between off-center and in-center ADC values (Δ).

RESULTS

No significant dependence of in-center ADC values on acquisition plan/phase encoding direction was found. Ward unsupervised clustering analysis showed 3 distinct clusters of scanners and an association between Δ-values and manufacturer/model, whereas no association between Δ-values and maximum gradient strength, slew rate or static magnetic field strength was revealed. Several acquisition setups showed significant differences among groups, indicating the introduction of different biases in ADC estimation.

CONCLUSIONS

Unsupervised clustering analysis of DWI data, obtained from several scanners using an extensive acquisition protocol, allows to reveal an association between measured ADC values and manufacturer/model of scanner, as well as to identify suboptimal DWI acquisition setups for accurate ADC estimation.

Brain MRS correlates with mitochondrial dysfunction biomarkers in MELAS-associated mtDNA mutations

Objective

The purpose of this study was to investigate correlations between brain proton magnetic resonance spectroscopy (¹H‐MRS) findings with serum biomarkers and heteroplasmy of mitochondrial DNA (mtDNA) mutations. This study enrolled patients carrying mtDNA mutations associated with Mitochondrial Encephalomyopathy, Lactic Acidosis, and Stroke‐like episodes (MELAS), and MELAS‐Spectrum Syndrome (MSS).

Methods

Consecutive patients carrying mtDNA mutations associated with MELAS and MSS were recruited and their serum concentrations of lactate, alanine, and heteroplasmic mtDNA mutant load were evaluated. The brain protocol included single‐voxel ¹H‐MRS (1.5T) in the medial parieto‐occipital cortex (MPOC), left cerebellar hemisphere, parieto‐occipital white matter (POWM), and lateral ventricles. Relative metabolite concentrations of N‐acetyl‐aspartate (NAA), choline (Cho), and myo‐inositol (mI) were estimated relative to creatine (Cr), using LCModel 6.3.

Results

Six patients with MELAS (age 28 ± 13 years, 3 [50%] female) and 17 with MSS (age 45 ± 11 years, 7 [41%] female) and 39 sex‐ and age‐matched healthy controls (HC) were enrolled. These patients demonstrated a lower NAA/Cr ratio in MPOC compared to HC (p = 0.006), which inversely correlated with serum lactate (p = 0.021, rho = −0.68) and muscle mtDNA heteroplasmy (p < 0.001, rho = −0.80). Similarly, in the cerebellum patients had lower NAA/Cr (p < 0.001), Cho/Cr (p = 0.002), and NAA/mI (p = 0.001) ratios, which negatively correlated with mtDNA blood heteroplasmy (p = 0.001, rho = −0.81) and with alanine (p = 0.050, rho = −0.67). Ventricular lactate was present in 78.3% (18/23) of patients, correlating with serum lactate (p = 0.024, rho = 0.58).

Conclusion

Correlations were found between the peripheral and biochemical markers of mitochondrial dysfunction and brain in vivo markers of neurodegeneration, supporting the use of both biomarkers as signatures of MELAS and MSS disease, to evaluate the efficacy of potential treatments.

From Neurosurgical Planning to Histopathological Brain Tumor Characterization: Potentialities of Arcuate Fasciculus Along-Tract Diffusion Tensor Imaging Tractography Measures

Background: Tractography has been widely adopted to improve brain gliomas' surgical planning and guide their resection. This study aimed to evaluate state-of-the-art of arcuate fasciculus (AF) tractography for surgical planning and explore the role of along-tract analyses in vivo for characterizing tumor histopathology.

Methods: High angular resolution diffusion imaging (HARDI) images were acquired for nine patients with tumors located in or near language areas (age: 41 ± 14 years, mean ± standard deviation; five males) and 32 healthy volunteers (age: 39 ± 16 years; 16 males). Phonemic fluency task fMRI was acquired preoperatively for patients. AF tractography was performed using constrained spherical deconvolution diffusivity modeling and probabilistic fiber tracking. Along-tract analyses were performed, dividing the AF into 15 segments along the length of the tract defined using the Laplacian operator. For each AF segment, diffusion tensor imaging (DTI) measures were compared with those obtained in healthy controls (HCs). The hemispheric laterality index (LI) was calculated from language task fMRI activations in the frontal, parietal, and temporal lobe parcellations. Tumors were grouped into low/high grade (LG/HG).

Results: Four tumors were LG gliomas (one dysembryoplastic neuroepithelial tumor and three glioma grade II) and five HG gliomas (two grade III and three grade IV). For LG tumors, gross total removal was achieved in all but one case, for HG in two patients. Tractography identified the AF trajectory in all cases. Four along-tract DTI measures potentially discriminated LG and HG tumor patients (false discovery rate < 0.1): the number of abnormal MD and RD segments, median AD, and MD measures. Both a higher number of abnormal AF segments and a higher AD and MD measures were associated with HG tumor patients. Moreover, correlations (unadjusted p < 0.05) were found between the parietal lobe LI and the DTI measures, which discriminated between LG and HG tumor patients. In particular, a more rightward parietal lobe activation (LI < 0) correlated with a higher number of abnormal MD segments (R = −0.732) and RD segments (R = −0.724).

Conclusions: AF tractography allows to detect the course of the tract, favoring the safer-as-possible tumor resection. Our preliminary study shows that along-tract DTI metrics can provide useful information for differentiating LG and HG tumors during pre-surgical tumor characterization.

Single-sided NMR to estimate morphological parameters of the trabecular bone structure

PURPOSE

Single-sided ¹ H-NMR is proposed for the estimation of morphological parameters of trabecular bone, and potentially the detection of pathophysiological alterations of bone structure. In this study, a new methodology was used to estimate such parameters without using an external reference signal, and to study intratrabecular and intertrabecular porosities, with a view to eventually scanning patients.

METHODS

Animal trabecular bone samples were analyzed by a single-sided device. The Carr-Purcell-Meiboom-Gill sequence of ¹ H nuclei of fluids, including marrow, confined inside the bone, was analyzed by quasi-continuous T₂ distributions and separated into two ¹ H pools: short and long T₂ components. The NMR parameters were estimated using models of trabecular bone structure, and compared with the corresponding micro-CT.

RESULTS

Without any further assumptions, the internal reference parameter (short T₂ signal intensity fraction) enabled prediction of the micro-CT parameters BV/TV (volume of the trabeculae/total sample volume) and BS/TV (external surface of the trabeculae/total sample volume) with linear correlation coefficient >0.80. The assignment of the two pools to intratrabecular and intertrabecular components yielded an estimate of average intratrabecular porosity (33 ± 5)%. Using the proposed models, the NMR-estimated BV/TV and BS/TV were found to be linearly related to the corresponding micro-CT values with high correlation (>0.90 for BV/TV; >0.80 for BS/TV) and agreement coefficients.

CONCLUSION

Low-field, low-cost portable devices that rely on intrinsic magnetic field gradients and do not use ionizing radiation are viable tools for in vitro preclinical studies of pathophysiological structural alterations of trabecular bone.

Clinical and Demographic Characteristics of Upper Limb Dystonia

BACKGROUND

Knowledge of characteristics in upper limb dystonia remains limited, derived primarily from small, single-site studies.

OBJECTIVE

The objective of this study was to characterize demographic and clinical characteristics of upper limb dystonia from the Dystonia Coalition data set, a large, international, multicenter resource.

METHODS

We evaluated clinical and demographic characteristics of 367 participants with upper limb dystonia from onset, comparing across subcategories of focal (with and without dystonia spread) versus nonfocal onset.

RESULTS

Focal onset occurred in 80%; 67% remained focal without spread. Task specificity was most frequent in this subgroup, most often writer's cramp and affecting the dominant limb (83%). Focal onset with spread was more frequent in young onset (<21 years). Focal onset occurred equally in women and men; nonfocal onset affected women disproportionately.

CONCLUSIONS

Upper limb dystonia distribution, focality, and task specificity relate to onset age and likelihood of regional spread. Observations may inform clinical counseling and design, execution, and interpretation of future studies. © 2020 International Parkinson and Movement Disorder Society.

Oncology and Cardiac Rehabilitation: An Underrated Relationship

Cancer and cardiovascular diseases are globally the leading causes of mortality and morbidity. These conditions are closely related, beyond that of sharing many risk factors. The term bidirectional relationship indicates that cardiovascular diseases increase the likelihood of getting cancer and vice versa. The biological and biochemical pathways underlying this close relationship will be analyzed. In this new overlapping scenario, physical activity and exercise are proven protective behaviors against both cardiovascular diseases and cancer. Many observational studies link an increase in physical activity to a reduction in either the development or progression of cancer, as well as to a reduction in risk in cardiovascular diseases, a non-negligible cause of death for long-term cancer survivors. Exercise is an effective tool for improving cardio-respiratory fitness, quality of life, psychological wellbeing, reducing fatigue, anxiety and depression. Finally, it can counteract the toxic effects of cancer therapy. The protection obtained from physical activity and exercise will be discussed in the various stages of the cancer continuum, from diagnosis, to adjuvant therapy, and from the metastatic phase to long-term effects. Particular attention will be paid to the shelter against chemotherapy, radiotherapy, cardiovascular risk factors or new onset cardiovascular diseases. Cardio-Oncology Rehabilitation is an exercise-based multi-component intervention, starting from the model of Cardiac Rehabilitation, with few modifications, to improve care and the prognosis of a patient's cancer. The network of professionals dedicated to Cardiac Rehabilitation is a ready-to-use resource, for implementing Cardio-Oncology Rehabilitation.

Liquid Chromatographic Method for Nicarbazin in Broiler Feeds and Premixtures: Development, Validation, and Interlaboratory Study

A reversed-phase liquid chromatography method for nicarbazin in broiler feeds and premixtures was developed, validated, and interlaboratory studied. The extraction solvent was an acetonitrile–methanol (1 + 1) mixture. For feedingstuffs, water was also added. The 4,4′-dinitrocarbanilide moiety of nicarbazin was detected at a wavelength of 350 nm. Recovery was ≥ 87%. At 20 mg/kg, the repeatability was 0.7% and the within-laboratory reproducibility was 2.7%. The limit of determination was &lt;20 mg/kg. Other feed additives did not interfere in the assay that proved to be applicable to broiler feeds from different European Union countries. In an interlaboratory study, 4 positive broiler feeds, 1 blank pig feed, and 1 broiler premixture were analyzed by 19 laboratories using the method developed in this study. The relative standard deviation for repeatability (RSDr) of the feedingstuffs (20–240 mg/kg) varied between 2.6 and 10.2%. The HORRAT ranged between 0.70 and 1.22. Recoveries were 91–108%. Three laboratories detected small signals in the blind blank samples, ranging from 0.4 to 2 mg/kg. For the premixture, acceptable results for reproducibility could only be obtained after the sample weight and volume of extraction had been doubled. To avoid excessive dilution of the extracts, the range of the calibration curve had also been doubled. With this modified method, the RSDr was 5.7% and the HORRAT was 1.95 (10 laboratories).

L-Dopa Modulation of Brain Connectivity in Parkinson's Disease Patients: A Pilot EEG-fMRI Study

Studies of functional neurosurgery and electroencephalography in Parkinson's disease have demonstrated abnormally synchronous activity between basal ganglia and motor cortex. Functional neuroimaging studies investigated brain dysfunction during motor task or resting state and primarily have shown altered patterns of activation and connectivity for motor areas. L-dopa administration relatively normalized these functional alterations. The aim of this pilot study was to examine the effects of L-dopa administration on functional connectivity in early-stage PD, as revealed by simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) data. Six patients with diagnosis of probable PD underwent EEG-fMRI acquisitions (1.5 T MR scanner and 64-channel cap) before and immediately after the intake of L-dopa. Regions of interest in the primary motor and sensorimotor regions were used for resting state fMRI analysis. From the EEG data, weighted partial directed coherence was computed in the inverse space after the removal of gradient and cardioballistic artifacts. fMRI results showed that the intake of L-dopa increased functional connectivity within the sensorimotor network, and between motor areas and both attention and default mode networks. EEG connectivity among regions of the motor network did not change significantly, while regions of the default mode network showed a strong tendency to increase their outflow toward the rest of the brain. This pilot study provided a first insight into the potentiality of simultaneous EEG-fMRI acquisitions in PD patients, showing for both techniques the analogous direction of increased connectivity after L-dopa intake, mainly involving motor, dorsal attention and default mode networks.

Effects of Light Treatment on Sleep, Cognition, Mood, and Behavior in Alzheimer's Disease: A Systematic Review

BACKGROUND

Bright light treatment is a therapeutic intervention mainly used to treat sleep and circadian disturbances in Alzheimer's disease (AD) patients. Recently, a handful of studies also focused on the effect on cognition and behavior. Conflicting findings are reported in the literature, and no definite conclusions have been drawn about its specific therapeutic effect.

SUMMARY

The aim of this review is to provide a critical evaluation of available evidence in this field, highlighting the specific characteristics of effective bright light treatment. Eligible studies were required to assess at least one of the following outcome measures: sleep, cognition, mood, and/or behavior (e.g., depression, agitation). A total of 32 articles were included in this systematic review and identified as research intervention studies about light treatment in AD. The quality of the papers was evaluated based on the US Preventive Service Task Force guidelines. Key Messages: Overall, the current literature suggests that the effects of light treatment in AD patients are mixed and may be influenced by several factors, but with a general trend toward a positive effect. Bright light seems to be a promising intervention treatment without significant adverse effects; therefore, further well-designed randomized controlled trials are needed taking into account the highlighted recommendations.

Stridor-related gray matter alterations in multiple system atrophy: A pilot study

INTRODUCTION

The neuroanatomical substrate of stridor associated with Multiple System Atrophy (MSA) remains unclear. We evaluated stridor-related gray matter (GM) changes in MSA.

METHODS

36 MSA patients underwent standardized nocturnal video-polysomnography and brain MRI. Differences in GM density between MSA patients with and without stridor and a sample of 22 matched healthy controls were evaluated with Voxel Based Morphometry protocol supplemented by a specific tool (SUIT) for analysing infratentorial structures.

RESULTS

Stridor was confirmed in 14 patients (10 MSA-cerebellar variant; 10 M; mean ± SD age = 61.6 ± 8.9years; disease duration = 5.2 ± 2.9years) and absent in 22 (11 MSA-cerebellar variant; 18 M; age = 61.4 ± 9.9years; disease duration = 4.8 ± 3.4years). Compared to MSA without stridor, patients with stridor showed higher GM density in the cerebellum (p < 0.05, corrected for the MSA-cerebellar variant and uncorrected when considering both MSA-variants) and lower in the striatum (p < 0.05, uncorrected).

CONCLUSIONS

This preliminary study has demonstrated for the first time in MSA stridor-related GM changes in striatal and cerebellar regions. Abnormalities in these regions were previously reported in dystonic disorders affecting laryngeal muscles, suggesting the hypothesis that stridor pathophysiology is dystonia-related. These results need however to be confirmed in a larger sample of patients.

Along-tract analysis of the arcuate fasciculus using the Laplacian operator to evaluate different tractography methods

PURPOSE

We propose a new along-tract algorithm to compare different tractography algorithms in tract curvature mapping and along-tract analysis of the arcuate fasciculus (AF). In particular, we quantified along-tract diffusion parameters and AF spatial distribution evaluating hemispheric asymmetries in a group of healthy subjects.

METHODS

The AF was bilaterally reconstructed in a group of 29 healthy subjects using the probabilistic ball-and-sticks model, and both deterministic and probabilistic constrained spherical deconvolution. We chose cortical ROIs as tractography targets and the developed along-tract algorithm used the Laplacian operator to parameterize the volume of the tract, allowing along-tract analysis and tract curvature mapping independent of the tractography algorithm used.

RESULTS

The Laplacian parameterization successfully described the tract geometry underlying hemispheric asymmetries in the AF curvature. Using the probabilistic tractography methods, we found more tracts branching towards cortical terminations in the left hemisphere. This influenced the left AF curvature and its diffusion parameters, which were significantly different with respect to the right. In particular, we detected projections towards the middle temporal and inferior frontal gyri bilaterally, and towards the superior temporal and precentral gyri in the left hemisphere, with a significantly increased volume and connectivity.

CONCLUSIONS

The approach we propose is useful to evaluate brain asymmetries, assessing the volume, the diffusion properties and the quantitative spatial localization of the AF.

Cognitive Rehabilitation and Transcranial Direct Current Stimulation in a Patient with Posterior Cortical Atrophy: An fMRI Study

BACKGROUND Posterior cortical atrophy (PCA) is a neurodegenerative syndrome that accounts for 5% of the atypical presentation of Alzheimer disease (AD). To date, only a few studies have explored the effect of non-pharmacological treatment in PCA patients and no studies have evaluated the efficacy of transcranial direct current stimulation (tDCS) in this disorder. CASE REPORT A 58-year-old PCA patient underwent a cognitive rehabilitation treatment followed by 2 cycles of tDCS stimulation. The effects of both treatments were monitored over time with a standardized task-based fMRI protocol and with a neuropsychological assessment. Improvements in cognitive abilities, increased fMRI activation in the dorsolateral prefrontal cortex, and deactivation of the default mode network during the Stroop test performance were detected after each session treatment. CONCLUSIONS This combined approach lead to both cognitive improvements and neurophysiological adaptive changes, however, further studies on a larger cohort are needed to confirm these preliminary results.

Cerebral Mitochondrial Microangiopathy Leads to Leukoencephalopathy in Mitochondrial Neurogastrointestinal Encephalopathy

BACKGROUND AND PURPOSE

Mitochondrial neurogastrointestinal encephalopathy is a rare disorder due to recessive mutations in the thymidine phosphorylase gene, encoding thymidine phosphorylase protein required for mitochondrial DNA replication. Clinical manifestations include gastrointestinal dysmotility and diffuse asymptomatic leukoencephalopathy. This study aimed to elucidate the mechanisms underlying brain leukoencephalopathy in patients with mitochondrial neurogastrointestinal encephalopathy by correlating multimodal neuroradiologic features to postmortem pathology.

MATERIALS AND METHODS

Seven patients underwent brain MR imaging, including single-voxel proton MR spectroscopy and diffusion imaging. Absolute concentrations of metabolites calculated by acquiring unsuppressed water spectra at multiple TEs, along with diffusion metrics based on the tensor model, were compared with those of healthy controls using unpaired t tests in multiple white matters regions. Brain postmortem histologic, immunohistochemical, and molecular analyses were performed in 1 patient.

RESULTS

All patients showed bilateral and nearly symmetric cerebral white matter hyperintensities on T2-weighted images, extending to the cerebellar white matter and brain stem in 4. White matter, N-acetylaspartate, creatine, and choline concentrations were significantly reduced compared with those in controls, with a prominent increase in the radial water diffusivity component. At postmortem examination, severe fibrosis of brain vessel smooth muscle was evident, along with mitochondrial DNA replication depletion in brain and vascular smooth-muscle and endothelial cells, without neuronal loss, myelin damage, or gliosis. Prominent periependymal cytochrome C oxidase deficiency was also observed.

CONCLUSIONS

Vascular functional and histologic alterations account for leukoencephalopathy in mitochondrial neurogastrointestinal encephalopathy. Thymidine toxicity and mitochondrial DNA replication depletion may induce microangiopathy and blood-brain-barrier dysfunction, leading to increased water content in the white matter. Periependymal cytochrome C oxidase deficiency could explain prominent periventricular impairment.

Brain functional connectivity in sleep-related hypermotor epilepsy

Objectives

To evaluate functional connectivity (FC) in patients with sleep-related hypermotor epilepsy (SHE) compared to healthy controls.

Methods

Resting state fMRI was performed in 13 patients with a clinical diagnosis of SHE (age = 38.3 ± 11.8 years, 6 M) and 13 matched healthy controls (age = 38.5 ± 10.8 years, 6 M).

Data were first analysed using probabilistic independent component analysis (ICA), then a graph theoretical approach was applied to assess topological and organizational properties at the whole brain level. We evaluated node degree (ND), betweenness centrality (BC), clustering coefficient (CC), local efficiency (LE) and global efficiency (GE). The differences between the two groups were evaluated non-parametrically.

Results

At the group level, we distinguished 16 RSNs (Resting State Networks). Patients showed a significantly higher FC in sensorimotor and thalamic regions (p < 0.05 corrected). Compared to controls, SHE patients showed no significant differences in network global efficiency, while ND and BC were higher in regions of the limbic system and lower in the occipital cortex, while CC and LE were higher in regions of basal ganglia and lower in limbic areas (p < 0.05 uncorrected).

Discussion and conclusions

The higher FC of the sensorimotor cortex and thalamus might be in agreement with the hypothesis of a peculiar excitability of the motor cortex during thalamic K-complexes. This sensorimotor-thalamic hyperconnection might be regarded as a consequence of an alteration of the arousal regulatory system in SHE. An altered topology has been found in structures like basal ganglia and limbic system, hypothesized to be involved in the pathophysiology of the disease as suggested by the dystonic-dyskinetic features and primitive behaviours observed during the seizures.

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Resting state functional connectivity was studied for the first time in SHE.

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SHE patients showed higher connectivity in thalamic and motor regions.

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Motor cortex might show a higher excitability in response to thalamic projections.

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Brain network topology was altered mainly in basal ganglia and limbic system.

Multi-class parkinsonian disorders classification with quantitative MR markers and graph-based features using support vector machines

BACKGROUND AND PURPOSE

In this study we attempt to automatically classify individual patients with different parkinsonian disorders, making use of pattern recognition techniques to distinguish among several forms of parkinsonisms (multi-class classification), based on a set of binary classifiers that discriminate each disorder from all others.

METHODS

We combine diffusion tensor imaging, proton spectroscopy and morphometric-volumetric data to obtain MR quantitative markers, which are provided to support vector machines with the aim of recognizing the different parkinsonian disorders. Feature selection is used to find the most important features for classification. We also exploit a graph-based technique on the set of quantitative markers to extract additional features from the dataset, and increase classification accuracy.

RESULTS

When graph-based features are not used, the MR markers that are most frequently automatically extracted by the feature selection procedure reflect alterations in brain regions that are also usually considered to discriminate parkinsonisms in routine clinical practice. Graph-derived features typically increase the diagnostic accuracy, and reduce the number of features required.

CONCLUSIONS

The results obtained in the work demonstrate that support vector machines applied to multimodal brain MR imaging and using graph-based features represent a novel and highly accurate approach to discriminate parkinsonisms, and a useful tool to assist the diagnosis.

Proton MR Spectroscopy in Patients With Sleep-Related Hypermotor Epilepsy (SHE): Evidence of Altered Cingulate Cortex Metabolism

Study Objectives

To identify structural and/or metabolic alterations in patients with sleep-related hypermotor epilepsy (SHE) using magnetic resonance imaging (MRI) and proton MR spectroscopy (1H-MRS).

Methods

Nineteen SHE patients (seven males; 34.7 ± 9.7 years, mean age ± standard deviation) and 17 matched healthy volunteers (seven males; 34.0 ± 8.9 years) were included in the study. In all patients, the diagnosis of SHE was confirmed by video-polysomnographic recording of seizures. Semiology, seizure frequency, and therapy were assessed for all patients. For each recruited participant, structural MRI and 1H-MRS sequences were acquired. 1H-MRS was performed on two regions of interest: the medial thalamus and the anterior cingulate gyrus.

Results

At examination, five patients were seizure free. In the remainder, seizure frequency ranged from yearly to multiple episodes per night. Brain MRI was normal in all patients but one. The ratio of N-acetyl-aspartate/Creatine (NAA/Cr) was significantly reduced in the anterior cingulate cortex in patients compared to controls (p < .05). Thalamic NAA/Cr showed no differences between patients and controls. Regression analysis showed that NAA/Cr in the anterior cingulate gyrus correlated with seizure frequency (p < .05), being lower in patients with higher seizure frequency.

Conclusions

Given the absence of structural MR changes, our 1H-MRS data point to a functional NAA reduction in the cingulate cortex of SHE patients, more severe in those patients with higher seizure frequency and thus supporting the involvement of the anterior mesial structures in the pathophysiology of SHE.

Metabolic Imaging in Prostate Cancer: Where We Are

In recent years, the development of diagnostic methods based on metabolic imaging has been aimed at improving diagnosis of prostate cancer (PCa) and perhaps at improving therapy. Molecular imaging methods can detect specific biological processes that are different when detected within cancer cells relative to those taking place in surrounding normal tissues. Many methods are sensitive to tissue metabolism; among them, positron emission tomography (PET) and magnetic resonance spectroscopic imaging (MRSI) are widely used in clinical practice and clinical research. There is a rich literature that establishes the role of these metabolic imaging techniques as valid tools for the diagnosis, staging, and monitoring of PCa. Until recently, European guidelines for PCa detection still considered both MRSI/MRI and PET/CT to be under evaluation, even though they had demonstrated their value in the staging of high risk PCa, and in the restaging of patients presenting elevated prostatic-specific antigen levels following radical treatment of PCa, respectively. Very recently, advanced methods for metabolic imaging have been proposed in the literature: multiparametric MRI (mpMRI), hyperpolarized MRSI, PET/CT with the use of new tracers and finally PET/MRI. Their detection capabilities are currently under evaluation, as is the feasibility of using such techniques in clinical studies.

Voxel-based morphometry to detect effect of APOE on brain gray matter changes in Parkinson's Disease

The goal of the study was to determine association between APOE Ɛ4 and gray matter changes in PD patients, with or without dementia. Twenty-five PD patients with the APOE Ɛ4 (13 with dementia), 24 without Ɛ4 (12 with dementia), and 26 controls were selected. We found no significant differences between PD patients and controls, or between PD patients with and without the APOE Ɛ4 allele, with regard to VBM analysis. Our results provide no evidence of an association of the APOE Ɛ4 and gray matter degenerative changes in patients with PD, either with or without dementia.

Voxel-based morphometry study on monozygotic twins discordant for Alzheimer's disease

OBJECTIVES

We set to investigate the possible role of genes and environment in developing Alzheimer's disease (AD) in monozygotic twin pairs discordant for AD.

METHODS

Three pairs of twins discordant for AD, who were enrolled in the Finnish Twin Cohort, were used in the study and compared with 13 controls. Gray matter changes were assessed with magnetic resonance images using voxel-based morphometry with statistical parametric mapping.

RESULTS

In the affected twins, the peaks of volume loss were located bilaterally in the temporal (including the hippocampus), the frontal, and the parietal lobes, while in the unaffected siblings, the peaks were located in the frontal gyri and in the parietal lobule. Thus, in the unaffected twins, the pattern of volume loss overlaps with the neocortical but not with the medial temporal areas.

DISCUSSION

These findings suggest that genetic factors more largely control neocortical regions, whereas environmental factors more strongly affect medial temporal regions.

Accuracy of MR markers for differentiating Progressive Supranuclear Palsy from Parkinson's disease

Background

Advanced brain MR techniques are useful tools for differentiating Progressive Supranuclear Palsy from Parkinson's disease, although time-consuming and unlikely to be used all together in routine clinical work. We aimed to compare the diagnostic accuracy of quantitative morphometric, volumetric and DTI metrics for differentiating Progressive Supranuclear Palsy-Richardson's Syndrome from Parkinson's disease.

Methods

23 Progressive Supranuclear Palsy-Richardson's Syndrome and 42 Parkinson's disease patients underwent a standardized 1.5T brain MR protocol comprising high-resolution T1W1 and DTI sequences. Brainstem and cerebellar peduncles morphometry, automated volumetric analysis of brain deep gray matter and DTI metric analyses of specific brain structures were carried out. We determined diagnostic accuracy, sensitivity and specificity of MR-markers with respect to the clinical diagnosis by using univariate receiver operating characteristics curve analyses. Age-adjusted multivariate receiver operating characteristics analyses were then conducted including only MR-markers with a sensitivity and specificity exceeding 80%.

Results

Morphometric markers (midbrain area, pons to midbrain area ratio and MR Parkinsonism Index), DTI parameters (infratentorial structures) and volumetric analysis (thalamus, putamen and pallidus nuclei) presented moderate to high diagnostic accuracy in discriminating Progressive Supranuclear Palsy-Richardson's Syndrome from Parkinson's disease, with midbrain area showing the highest diagnostic accuracy (99%) (mean ± standard deviation: 75.87 ± 16.95 mm²vs 132.45 ± 20.94 mm², respectively; p < 0.001).

Conclusion

Although several quantitative brain MR markers provided high diagnostic accuracy in differentiating Progressive Supranuclear Palsy-Richardson's Syndrome from Parkinson's disease, the morphometric assessment of midbrain area is the best single diagnostic marker and should be routinely included in the neuroradiological work-up of parkinsonian patients.

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We compared quantitative brain MR markers accuracy to differentiate advanced stages of PSP-RS from PD.

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Quantitative morphometric, DTI and volumetric data showed moderate-high accuracies.

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Midbrain area alone best discriminated advanced PSP-RS from PD (99%).

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Midbrain area evaluation should be added to brain MR protocols for parkinsonisms.

Relationship of white and gray matter abnormalities to clinical and genetic features in myotonic dystrophy type 1

BACKGROUND

Myotonic dystrophy type 1 (DM1) represents a multisystemic disorder in which diffuse brain white and gray matter alterations related to clinical and genetic features have been described. We aimed to evaluate in the brain of adult patients with DM1 (i) white and gray matter differences, including cortical-subcortical gray matter volume and cortical thickness and (ii) their correlation with clinical disability, global neuropsychological performance and triplet expansion.

METHODS

We included 24 adult genetically-confirmed DM1 patients (14 males; age: 38.5 ± 11.8 years) and 25 age- and sex-matched healthy controls (14 males; age: 38.5 ± 11.3 years) who underwent an identical brain MR protocol including high-resolution 3D T1-weighted, axial T2 FLAIR and DTI sequences. All patients underwent an extensive clinical and neuropsychological evaluation. Voxel-wise analyses of white matter, performed by using Tract Based Spatial Statistics, and of gray matter, with Voxel-based Morphometry and Cortical Thickness, were carried out in order to test for differences between patients with DM1 and healthy controls (p < 0.05, corrected). The correlation between MRI measures and clinical-genetic features was also assessed.

RESULTS

Patients with DM1 showed widespread abnormalities of all DTI parameters in the white matter, which were associated with reduced gray matter volume in all brain lobes and thinning in parieto-temporo-occipital cortices, albeit with less extensive cortical alterations when congenital cases were removed from the analyses. White matter alterations correlated with clinical disability, global cognitive performance and triplet expansions.

CONCLUSION

In patients with DM1, the combined smaller overall gray matter volume and white matter alterations seem to be the main morpho-structural substrates of CNS involvement in this condition. The correlation of white matter differences with both clinical and genetic findings lends support to this notion.