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Muscular dystrophies present diagnostic challenges, requiring accurate classification for effective diagnosis and treatment. This study investigates the efficacy of deep learning methodologies in classifying these disorders using skeletal muscle MRI scans. Specifically, we assess the performance of the Swin Transformer (SwinT) architecture against traditional convolutional neural networks (CNNs) in distinguishing between healthy individuals, Becker muscular dystrophy (BMD), and limb-girdle muscular Dystrophy type 2 (LGMD2) patients. Moreover, 3T MRI scans from a retrospective dataset of 75 scans (from 54 subjects) were utilized, with multiparametric protocols capturing various MRI contrasts, including T1-weighted and Dixon sequences. The dataset included 17 scans from healthy volunteers, 27 from BMD patients, and 31 from LGMD2 patients. SwinT and CNNs were trained and validated using a subset of the dataset, with the performance evaluated based on accuracy and F-score. Results indicate the superior accuracy of SwinT (0.96), particularly when employing fat fraction (FF) images as input; it served as a valuable parameter for enhancing classification accuracy. Despite limitations, including a modest cohort size, this study provides valuable insights into the application of AI-driven approaches for precise neuromuscular disorder classification, with potential implications for improving patient care.
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BACKGROUND: An intronic deletion within intron 2 of the DCDC2 gene encompassing the entire READ1 (hereafter, READ1d) has been associated in both children with developmental dyslexia (DD) and typical readers (TRs), with interindividual variation in reading performance and motion perception as well as with structural and functional brain alterations. Visual motion perception -- specifically processed by the magnocellular (M) stream -- has been reported to be a solid and reliable endophenotype of DD. Hence, we predicted that READ1d should affect neural activations in brain regions sensitive to M stream demands as reading proficiency changes. METHODS: We investigated neural activations during two M-eliciting fMRI visual tasks (full-field sinusoidal gratings controlled for spatial and temporal frequencies and luminance contrast, and sensitivity to motion coherence at 6%, 15% and 40% dot coherence levels) in four subject groups: children with DD with/without READ1d, and TRs with/without READ1d. RESULTS: At the Bonferroni-corrected level of significance, reading skills showed a significant effect in the right polar frontal cortex during the full-field sinusoidal gratings-M task. Regardless of the presence/absence of the READ1d, subjects with poor reading proficiency showed hyperactivation in this region of interest (ROI) compared to subjects with better reading scores. Moreover, a significant interaction was found between READ1d and reading performance in the left frontal opercular area 4 during the 15% coherent motion sensitivity task. Among subjects with poor reading performance, neural activation in this ROI during this specific task was higher for subjects without READ1d than for READ1d carriers. The difference vanished as reading skills increased. CONCLUSIONS: Our findings showed a READ1d-moderated genetic vulnerability to alterations in neural activation in the ventral attentive and salient networks during the processing of relevant stimuli in subjects with poor reading proficiency.
Subject(s)
Dyslexia , Frontal Lobe , Magnetic Resonance Imaging , Motion Perception , Parietal Lobe , Reading , Humans , Dyslexia/physiopathology , Dyslexia/genetics , Male , Child , Female , Magnetic Resonance Imaging/methods , Parietal Lobe/physiopathology , Motion Perception/physiology , Frontal Lobe/physiopathology , Frontal Lobe/diagnostic imaging , Microtubule-Associated Proteins/genetics , Brain Mapping/methods , Nerve Net/physiopathology , Nerve Net/diagnostic imaging , Photic Stimulation/methodsABSTRACT
Magnetic resonance imaging (MRI) and cognitive profiles in patients with mild traumatic brain injury (mTBI) are often discordant. Conventional MRI seldom captures the full extent of pathological changes in the normal-appearing white matter (NAWM). The divided subtracted inversion recovery (dSIR) technique may enhance T1 differences in NAWM, making them easily visible. We aimed to implement dSIR on a clinical scanner and tested results in mTBI patients. To produce dSIR images, Inversion Recovery-Turbo Spin Echo sequences were modified using six different inversion times (TI) on a 3-T scanner in healthy participants and patients with mTBI. The multiple TIs determined normal white (TIshort) and gray matter (TIlong) nulling points in healthy subjects, which were used to create dSIR images. In one patient, the protocol was repeated at 3 months to identify changes after rehabilitation. Diffusion tensor imaging (DTI)-derived mean diffusivity (MD) and fractional anisotropy (FA) maps were aligned to dSIR images to ensure that signal was not artefactual. Ten healthy participants (five females; age 24 ± 3 [95% CI: 21, 26] years) were included. TIshort and TIlong were set at 450 and 750 ms, respectively. In both patients (one male, age 17 years; one female, age 14 years), dSIR images revealed areas with increased T1 in the NAWM not visible on conventional MRI. dSIR-based hyperintensities corresponded to elevated MD and reduced FA. Substantial changes were found at follow-up with improvement in DTI-based parameters. dSIR images enhance subtle changes in the NAWM of patients with mTBI by amplifying their intrinsic T1 signal.
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Fetal brain development is a complex process involving different stages of growth and organization which are crucial for the development of brain circuits and neural connections. Fetal atlases and labeled datasets are promising tools to investigate prenatal brain development. They support the identification of atypical brain patterns, providing insights into potential early signs of clinical conditions. In a nutshell, prenatal brain imaging and post-processing via modern tools are a cutting-edge field that will significantly contribute to the advancement of our understanding of fetal development. In this work, we first provide terminological clarification for specific terms (i.e., "brain template" and "brain atlas"), highlighting potentially misleading interpretations related to inconsistent use of terms in the literature. We discuss the major structures and neurodevelopmental milestones characterizing fetal brain ontogenesis. Our main contribution is the systematic review of 18 prenatal brain atlases and 3 datasets. We also tangentially focus on clinical, research, and ethical implications of prenatal neuroimaging.
Subject(s)
Atlases as Topic , Brain , Magnetic Resonance Imaging , Neuroimaging , Female , Humans , Pregnancy , Brain/diagnostic imaging , Brain/embryology , Datasets as Topic , Fetal Development/physiology , Fetus/diagnostic imaging , Magnetic Resonance Imaging/methods , Neuroimaging/methodsABSTRACT
Background: Duchenne Muscular Dystrophy (DMD) is a genetic disease in which lack of the dystrophin protein causes progressive muscular weakness, cardiomyopathy and respiratory insufficiency. DMD is often associated with other cognitive and behavioral impairments, however the correlation of abnormal dystrophin expression in the central nervous system with brain structure and functioning remains still unclear. Objective: To investigate brain involvement in patients with DMD through a multimodal and multivariate approach accounting for potential comorbidities. Methods: We acquired T1-weighted and Diffusion Tensor Imaging data from 18 patients with DMD and 18 age- and sex-matched controls with similar cognitive and behavioral profiles. Cortical thickness, structure volume, fractional anisotropy and mean diffusivity measures were used in a multivariate analysis performed using a Support Vector Machine classifier accounting for potential comorbidities in patients and controls. Results: the classification experiment significantly discriminates between the two populations (97.2% accuracy) and the forward model weights showed that DMD mostly affects the microstructural integrity of long fiber bundles, in particular in the cerebellar peduncles (bilaterally), in the posterior thalamic radiation (bilaterally), in the fornix and in the medial lemniscus (bilaterally). We also reported a reduced cortical thickness, mainly in the motor cortex, cingulate cortex, hippocampal area and insula. Conclusions: Our study identified a small pattern of alterations in the CNS likely associated with the DMD diagnosis.
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Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2 = 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.
Subject(s)
Diffusion Magnetic Resonance Imaging , Humans , Diffusion Magnetic Resonance Imaging/methods , Male , Adult , Female , Brain/diagnostic imaging , Diffusion Tensor Imaging/methods , Young Adult , White Matter/diagnostic imaging , AlgorithmsABSTRACT
Brain segmentation is often the first and most critical step in quantitative analysis of the brain for many clinical applications, including fetal imaging. Different aspects challenge the segmentation of the fetal brain in magnetic resonance imaging (MRI), such as the non-standard position of the fetus owing to his/her movements during the examination, rapid brain development, and the limited availability of imaging data. In recent years, several segmentation methods have been proposed for automatically partitioning the fetal brain from MR images. These algorithms aim to define regions of interest with different shapes and intensities, encompassing the entire brain, or isolating specific structures. Deep learning techniques, particularly convolutional neural networks (CNNs), have become a state-of-the-art approach in the field because they can provide reliable segmentation results over heterogeneous datasets. Here, we review the deep learning algorithms developed in the field of fetal brain segmentation and categorize them according to their target structures. Finally, we discuss the perceived research gaps in the literature of the fetal domain, suggesting possible future research directions that could impact the management of fetal MR images.
Subject(s)
Deep Learning , Female , Male , Humans , Fetus/diagnostic imaging , Magnetic Resonance Imaging , Algorithms , Brain/diagnostic imagingABSTRACT
Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.
Subject(s)
Imaging, Three-Dimensional , Magnetic Resonance Imaging , Female , Humans , Pregnancy , Pregnancy Trimester, Second , Imaging, Three-Dimensional/methods , Reproducibility of Results , Magnetic Resonance Imaging/methods , Brain/diagnostic imagingABSTRACT
PURPOSE: Morphometric studies on idiopathic Chiari malformation type 1 (CM1) pathogenesis have been mainly based on post-natal neuroimaging. Prenatal clues related to CM1 development are lacking. We present pre- and post-natal imaging time course in idiopathic CM1 and assess fetal skull and brain biometry to establish if clues about CM1 development are present at fetal age. METHODS: Multicenter databases were screened to retrieve intrauterine magnetic resonance (iuMR) of children presenting CM1 features at post-natal scan. Syndromes interfering with skull-brain growth were excluded. Twenty-two morphometric parameters were measured at fetal (average 24.4 weeks; range 21 to 32) and post-natal (average 15.4 months; range 1 to 45) age; matched controls were included. RESULTS: Among 7000 iuMR cases, post-natal scans were available for 925, with postnatal CM1 features reported in seven. None of the fetuses presented CM1 features. Tonsillar descent was clear at a later post-natal scan in all seven cases. Six fetal parameters resulted to be statistically different between CM1 and controls: basal angle (p = 0.006), clivo-supraoccipital angle (p = 0.044), clivus' length (p = 0.043), posterior cranial fossa (PCF) width (p = 0.009), PCF height (p = 0.045), and PCFw/BPDb (p = 0.013). Postnatally, only the clivus' length was significant between CM1 cases and controls. CONCLUSION: Pre- and post-natal CM1 cases did not share striking common features, making qualitative prenatal assessment not predictive; however, our preliminary results support the view that some of the pathogenetic basis of CM1 may be embedded to some extent already in intrauterine life.
Subject(s)
Arnold-Chiari Malformation , Child , Humans , Arnold-Chiari Malformation/diagnostic imaging , Arnold-Chiari Malformation/pathology , Magnetic Resonance Imaging , Brain/pathology , Neuroimaging , Cranial Fossa, Posterior/diagnostic imaging , Cranial Fossa, Posterior/pathologyABSTRACT
Beyond classical aspects related to locomotion (biomechanics), it has been hypothesized that walking pattern is influenced by a combination of distinct computations including online sensory/perceptual sampling and the processing of expectations (neuromechanics). Here, we aimed to explore the potential impact of contrasting scenarios ("risky and potentially dangerous" scenario; "safe and comfortable" scenario) on walking pattern in a group of healthy young adults. Firstly, and consistently with previous literature, we confirmed that the scenario influences gait pattern when it is recalled concurrently to participants' walking activity (motor interference). More intriguingly, our main result showed that participants' gait pattern is also influenced by the contextual scenario when it is evoked only before the start of walking activity (motor expectation). This condition was designed to test the impact of expectations (risky scenario vs. safe scenario) on gait pattern, and the stimulation that preceded walking activity served as prior. Noteworthy, we combined statistical and machine learning (Support-Vector Machine classifier) approaches to stratify distinct levels of analyses that explored the multi-facets architecture of walking. In a nutshell, our combined statistical and machine learning analyses converge in suggesting that walking before steps is not just a paradox.
Subject(s)
Gait , Motivation , Young Adult , Humans , Biomechanical Phenomena , Gait/physiology , Walking/physiology , JointsABSTRACT
BACKGROUND: Spinal cord damage is a hallmark of Friedreich's ataxia (FRDA), but its progression and clinical correlates remain unclear. OBJECTIVE: The objective of this study was to perform a characterization of cervical spinal cord structural damage in a large multisite FRDA cohort. METHODS: We performed a cross-sectional analysis of cervical spinal cord (C1-C4) cross-sectional area (CSA) and eccentricity using magnetic resonance imaging data from eight sites within the ENIGMA-Ataxia initiative, including 256 individuals with FRDA and 223 age- and sex-matched control subjects. Correlations and subgroup analyses within the FRDA cohort were undertaken based on disease duration, ataxia severity, and onset age. RESULTS: Individuals with FRDA, relative to control subjects, had significantly reduced CSA at all examined levels, with large effect sizes (d > 2.1) and significant correlations with disease severity (r < -0.4). Similarly, we found significantly increased eccentricity (d > 1.2), but without significant clinical correlations. Subgroup analyses showed that CSA and eccentricity are abnormal at all disease stages. However, although CSA appears to decrease progressively, eccentricity remains stable over time. CONCLUSIONS: Previous research has shown that increased eccentricity reflects dorsal column (DC) damage, while decreased CSA reflects either DC or corticospinal tract (CST) damage, or both. Hence our data support the hypothesis that damage to the DC and damage to CST follow distinct courses in FRDA: developmental abnormalities likely define the DC, while CST alterations may be both developmental and degenerative. These results provide new insights about FRDA pathogenesis and indicate that CSA of the cervical spinal cord should be investigated further as a potential biomarker of disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Subject(s)
Friedreich Ataxia , Movement Disorders , Humans , Friedreich Ataxia/complications , Friedreich Ataxia/pathology , Ataxia , Magnetic Resonance Imaging/methods , Pyramidal TractsABSTRACT
PURPOSE: To describe the neuroanatomical correlates of unilateral congenital isolated oculomotor palsy by means of high-resolution MRI. METHODS: Children with a clinical diagnosis of congenital isolated oculomotr palsy and with a high-resolution MRI acquisition targeted on the orbits and cranial nerves were selected and included in the study. An experienced pediatric neuroradiologist evaluated all the exams, assessing the integrity and morphology of extraocular muscles, oculomotor, trochlear and abducens nerves as well as optic nerves and globes. Clinical data and ophthalmologic evaluations were also collected. RESULTS: Six children (age range: 1-16 years; males: 3) were selected. All patients showed, on the affected side (left:right = 5:1), anomalies of the III nerve and extraocular muscles innervated by the pathological nerve. One patient had complete nerve agenesis, two patients showed a diffuse thinning of the nerve, from the brainstem to the orbit and 3 patients showed a distal thinning of the oculomotor nerve, starting at the level of the cavernous sinus. In all cases atrophy of corresponding muscles was noticed, but the involvement of the affected muscles varied with the nervous pattern of injury. CONCLUSIONS: High-resolution MRI represents a valuable tool for the diagnosis of III nerve anomalies in unilateral congenital IOP, showing different patterns of nerve involvement and muscular atrophy.
Subject(s)
Oculomotor Nerve Diseases , Ophthalmoplegia , Male , Humans , Child , Infant , Child, Preschool , Adolescent , Oculomotor Nerve Diseases/diagnostic imaging , Oculomotor Nerve/diagnostic imaging , Oculomotor Nerve/abnormalities , Cranial Nerves , Ophthalmoplegia/pathology , Magnetic Resonance Imaging/methodsABSTRACT
T1-weighted magnetic resonance images provide a comprehensive view of the morphology of the human brain at the macro scale. These images are usually the input of a segmentation process that aims detecting the anatomical structures labeling them according to a predefined set of target tissues. Automated methods for brain tissue segmentation rely on anatomical priors of the human brain structures. This is the reason why their performance is quite accurate on healthy individuals. Nevertheless model-based tools become less accurate in clinical practice, specifically in the cases of severe lesions or highly distorted cerebral anatomy. More recently there are empirical evidences that a data-driven approach can be more robust in presence of alterations of brain structures, even though the learning model is trained on healthy brains. Our contribution is a benchmark to support an open investigation on how the tissue segmentation of distorted brains can be improved by adopting a supervised learning approach. We formulate a precise definition of the task and propose an evaluation metric for a fair and quantitative comparison. The training sample is composed of almost one thousand healthy individuals. Data include both T1-weighted MR images and their labeling of brain tissues. The test sample is a collection of several tens of individuals with severe brain distortions. Data and code are openly published on BrainLife, an open science platform for reproducible neuroscience data analysis.
Subject(s)
Benchmarking , Image Processing, Computer-Assisted , Brain/anatomy & histology , Child , Humans , Image Processing, Computer-Assisted/methods , Magnetic Resonance Imaging/methodsABSTRACT
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 (rmax = 0.35) and peduncles (rmax = 0.36). Disease duration and severity correlated with volume deficits in the dentate nucleus region, brainstem, and superior/inferior cerebellar peduncles (rmax = -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.
Subject(s)
Brain/pathology , Friedreich Ataxia/diagnostic imaging , Image Processing, Computer-Assisted , Adult , Age of Onset , Brain/anatomy & histology , Disease Progression , Female , Humans , Magnetic Resonance Imaging/methods , Male , Middle Aged , Pyramidal Tracts/pathology , Young AdultABSTRACT
As fathers are increasingly involved in childcare, understanding the neurological underpinnings of fathering has become a key research issue in developmental psychobiology research. This systematic review specifically focused on (1) highlighting methodological issues of paternal brain research using functional magnetic resonance imaging (fMRI) and (2) summarizing findings related to paternal brain responses to auditory and visual infant stimuli. Sixteen papers were included from 157 retrieved records. Sample characteristics (e.g., fathers' and infant's age, number of kids, and time spent caregiving), neuroimaging information (e.g., technique, task, stimuli, and processing), and main findings were synthesized by two independent authors. Most of the reviewed works used different stimuli and tasks to test fathers' responses to child visual and/or auditory stimuli. Pre-processing and first-level analyses were performed with standard pipelines. Greater heterogeneity emerged in second-level analyses. Three main cortical networks (mentalization, embodied simulation, and emotion regulation) and a subcortical network emerged linked with fathers' responses to infants' stimuli, but additional areas (e.g., frontal gyrus, posterior cingulate cortex) were also responsive to infants' visual or auditory stimuli. This review suggests that a distributed and complex brain network may be involved in facilitating fathers' sensitivity and responses to infant-related stimuli. Nonetheless, specific methodological caveats, the exploratory nature of large parts of the literature to date, and the presence of heterogeneous tasks and measures also demonstrate that systematic improvements in study designs are needed to further advance the field.
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Increasing evidence supports the presence of deficits in the visual magnocellular (M) system in developmental dyslexia (DD). The M system is related to the fronto-parietal attentional network. Previous neuroimaging studies have revealed reduced/absent activation within the visual M pathway in DD, but they have failed to characterize the extensive brain network activated by M stimuli. We performed a multivariate pattern analysis on a Region of Interest (ROI) level to differentiate between children with DD and age-matched typical readers (TRs) by combining full-field sinusoidal gratings, controlled for spatial and temporal frequencies and luminance contrast, and a coherent motion (CM) sensitivity task at 6%-CML6, 15%-CML15 and 40%-CML40. ROIs spanning the entire visual dorsal stream and ventral attention network (VAN) had higher discriminative weights and showed higher act1ivation in TRs than in children with DD. Of the two tasks, CM had the greatest weight when classifying TRs and children with DD in most of the ROIs spanning these streams. For the CML6, activation within the right superior parietal cortex positively correlated with reading skills. Our approach highlighted the dorsal stream and the VAN as highly discriminative areas between children with DD and TRs and allowed for a better characterization of the "dorsal stream vulnerability" underlying DD.
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DNA methylation plays a key role in neural cell fate and provides a molecular link between early life stress and later-life behavioral phenotypes. Here, studies that combine neuroimaging methods and DNA methylation analysis in pediatric population with a history of adverse experiences were systematically reviewed focusing on: targeted genes and neural correlates; statistical models used to examine the link between DNA methylation and neuroimaging data also considering early life stress and behavioral outcomes. We identified 8 studies that report associations between DNA methylation and brain structure/functions in infants, school age children and adolescents faced with early life stress condition (e.g., preterm birth, childhood maltreatment, low socioeconomic status, and less-than optimal caregiving). Results showed that several genes were investigated (e.g., OXTR, SLC6A4, FKBP5, and BDNF) and different neuroimaging techniques were performed (MRI and f-NIRS). Statistical model used ranged from correlational to more complex moderated mediation models. Most of the studies (n = 5) considered DNA methylation and neural correlates as mediators in the relationship between early life stress and behavioral phenotypes. Understanding what role DNA methylation and neural correlates play in interaction with early life stress and behavioral outcomes is crucial to promote theory-driven studies as the future direction of this research fields.
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PURPOSE: To study a robust and reproducible procedure to investigate a relation between focal brain radiotherapy (RT) low doses, neurocognitive impairment and late White Matter and Gray Matter alterations, as shown by Diffusion Tensor Imaging (DTI), in children. METHODS AND MATERIALS: Forty-five patients (23 males and 22 females, median age at RT 6.2 years, median age at evaluations 11.1 years) who had received focal RT for brain tumors were recruited for DTI exams and neurocognitive tests. Patients' brains were parceled in 116 regions of interest (ROIs) using an available segmented atlas. After the development of an ad hoc, home-made, multimodal and highly deformable registration framework, we collected mean RT doses and DTI metrics values for each ROI. The pattern of association between cognitive scores or domains and dose or DTI values was assessed in each ROI through both considering and excluding ROIs with mean doses higher than 75% of the prescription. Subsequently, a preliminary threshold value of dose discriminating patients with and without neurocognitive impairment was selected for the most relevant associations. RESULTS: The workflow allowed us to identify 10 ROIs where RT dose and DTI metrics were significantly associated with cognitive tests results (p<0.05). In 5/10 ROIs, RT dose and cognitive tests were associated with p<0.01 and preliminary RT threshold dose values, implying a possible cognitive or neuropsychological damage, were calculated. The analysis of domains showed that the most involved one was the "school-related activities". CONCLUSION: This analysis, despite being conducted on a retrospective cohort of children, shows that the identification of critical brain structures and respective radiation dose thresholds is achievable by combining, with appropriate methodological tools, the large amount of data arising from different sources. This supported the design of a prospective study to gain stronger evidence.
Subject(s)
Abnormalities, Radiation-Induced/diagnostic imaging , Brain Neoplasms/radiotherapy , Gray Matter/diagnostic imaging , Gray Matter/radiation effects , White Matter/diagnostic imaging , White Matter/radiation effects , Child , Diffusion Tensor Imaging/methods , Female , Follow-Up Studies , Humans , Male , Mental Status and Dementia Tests , Neurocognitive Disorders , Retrospective StudiesABSTRACT
Friedreich's ataxia (FRDA) is an inherited neurodegenerative movement disorder with early onset, widespread cerebral and cerebellar pathology, and no cure still available. Functional MRI (fMRI) studies, although currently limited in number, have provided a better understanding of brain changes in people with FRDA. This systematic review aimed to provide a critical overview of the findings and methodologies of all fMRI studies conducted in genetically confirmed FRDA so far, and to offer recommendations for future study designs. About 12 cross-sectional and longitudinal fMRI studies, included 198 FRDA children and young adult patients and, 205 healthy controls (HCs), according to the inclusion criteria. Details regarding GAA triplet expansion and demographic and clinical severity measures were widely reported. fMRI designs included motor and cognitive task paradigms, and resting-state studies, with widespread changes in functionally activated areas and extensive variability in study methodologies. These studies highlight a mixed picture of both hypoactivation and hyperactivation in different cerebral and cerebellar brain regions depending on fMRI design and cohort characteristics. Functional changes often correlate with clinical variables. In aggregate, the findings provide support for cerebro-cerebellar loop damage and the compensatory mechanism hypothesis. Current literature indicates that fMRI is a valuable tool for gaining in vivo insights into FRDA pathology, but addressing that its limitations would be a key to improving the design, interpretation, and generalizability of studies in the future.