Background/Objectives: Response inhibition is the capacity to restrain impulsive actions, representing a pivotal facet of cognitive control. Although several studies report a dynamic relationship between impulsivity and inhibitory control, the neural mechanisms remain unclear. The aim of the present study is to explore neural correlates of response inhibition as a function of impulsive personality traits. Methods: For this purpose, two groups of fMRI studies conducted on subjects with and without impulsive traits were compared. The selected studies were included based on both the impulsivity levels and the performance of the subjects in inhibitory human-computer tasks (e.g., Go/No-go, Stop-signal). This was done to minimize potential differences due to samples' performances. Neuroimaging data were analyzed with an Activation Likelihood Estimation (ALE) meta-analysis approach. Results: Results reveal highly congruent clusters encompassing subcortical and prefrontal brain regions in both impulsive and non-impulsive subjects, albeit with subtle distinctions. Specifically, a direct contrast highlighted different activity in the right Middle and Superior Frontal Gyrus during inhibition tasks in the impulsive group. Conclusions: These findings deepen our comprehension of the neural mechanisms governing inhibitory control in human impulsivity. Understanding such mechanisms is increasingly relevant in today's world, where frequent interactions with artificial systems may challenge or modulate inhibitory control, with potential implications for everyday behavior.

Background Friedreich ataxia (FRDA) is an inherited, progressive neurodegenerative disease. Interindividual heterogeneity in the rate and phenotypic profile of disease progression indicates a biologic variability in the pattern and spatial evolution of underlying changes, but the occurrence of possible FRDA subgroups, which could aid in clinical trial design and treatment, are still unknown. Purpose To obtain a structural MRI-based stratification of participants with FRDA using the Subtype and Stage Inference (SuStaIn) algorithm and determine whether these subgroups are biologically meaningful and clinically relevant. Materials and Methods This multicenter secondary analysis of prospectively acquired data included structural MRI and clinical-demographic data from participants from the ENIGMA-Ataxia working group. MRI biomarkers were analyzed using the SuStaIn algorithm to identify subgroups with distinct patterns and disease stages. The clinical and genetic relevance of these subgroups were assessed within a linear model framework. Results This study included 565 participants (mean age, 32 years ± 13.1 [SD]; 286 women; 275 participants with FRDA and 290 healthy controls). SuStaIn identified three subtypes: (a) a classical subtype (66.5% [183 of 275 participants]), characterized by an ascending gradient of damage from brainstem to cerebellar cortex to cerebrum; (b) an early cerebral subtype (25.8% [71 of 275 participants]) with cerebral atrophy preceding the involvement of cerebellar cortex; and (c) and an early cerebellar subtype (7.64% [21 of 275 participants]) showing cerebellar lobule atrophy before upper brainstem or cerebral involvement. More advanced disease stages (MRI-based SuStaIn stages) correlated with greater symptom duration (unstandardized coefficient B = 0.422, standard error = 0.065, P < .001) and severity (B = 1.404, standard error = 0.201, P < .001), and these relationships were moderated by subtype, with biologic stage progression in the early cerebral subtype mapping less strongly to clinical variables relative to the others (interaction term early cerebral subtype × stage: B = -0.925, standard error = 0.410, P = .02). Conclusion Using the SuStaIn algorithm, three distinct structural MRI-based subtypes of FRDA were identified, with different patterns of brain degeneration and associations with clinical severity. © RSNA, 2026 Supplemental material is available for this article.

Objective: Spinocerebellar ataxia type 1 (SCA1) is a rare, inherited neurodegenerative disease characterised by progressive deterioration of motor and cognitive function. Here, we illustrate the pattern and evolution of brain atrophy in people with SCA1 using a large multisite dataset. Methods: Structural magnetic resonance imaging data from SCA1 (n=152) and healthy control (n=131) participants from seven sites and two consortia were analyzed using voxel-based morphometry. Cross-sectional stratification and correlations were undertaken with ataxia severity and duration to profile disease evolution. Cerebrocerebellar structural covariance analysis was used to understand the relationship between cerebral and cerebellar tissue atrophy. Results: Atrophy in SCA1 first manifests in the lower brainstem and cerebellar white matter (WM), before progressing to the pons, anterior cerebellum, and cerebellar lobule IX. The midbrain and peri-thalamic WM and the remainder of the cerebellar cortex are then affected, with preferential involvement of specific motor and cognitive areas. Finally, degeneration in the striatum and cerebral WM corresponding to the corticospinal tract become apparent. Atrophy and correlations with ataxia severity are most pronounced in the cerebellar WM and pons. Structural covariance analysis showed reduced correlations between cerebellar and cerebral WM volume in SCA1 participants. Interpretation: Cross-sectional stratification of a large SCA1 cohort by ataxia severity indicates a pattern of atrophy spread across the brainstem, cerebellum, and subcortical grey and white matter. Ongoing volume loss throughout the disease course is most evident in a core set of infra-tentorial brain regions. Atrophy of cerebellum spans both motor and cognitive functional zones. Cerebellar degeneration is not directly mirrored by downstream effects in the cerebrum. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by grants from the Australian National Health and Medical Research Council (NHMRC), Friedreich's Ataxia Research Alliance, FAPESP (Sao Paulo Research Foundation), German Research Foundation, German Federal Ministry of Education and Research, Italian Ministry of Health, National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Mental Health (NIMH). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Monash University gave ethical approval for this work (project 12372). Ethics committee of University of Bonn Medical Faculty gave ethical approval for this work (project 176/16). Ethics committee of University of Campinas gave ethical approval for this work (project CAAE 29869520.8.3001.5404). Ethics Committee of University of Duisburg-Essen gave ethical approval for this work (project 15-6404-BO). Ethics Committee of Instituto Neurologico Carlo Besta gave ethical approval for this work (report N.14; 17 December 2014). Ethics committee of University of Minnesota gave ethics approval for this work (study number 0502M67488). Ethics committee of Sorbonne University gave ethics approval for the work (AOM10094, CPP Ile de France VI, Ref: 10510). Ethics committee of University Hospital Tubingen gave ethics approval for this work (project 303/2008BO2). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Introduction Brain structural differences consistent with an older-appearing brain have been reported in people with epilepsy, but the extent to which these differences reflect clinical characteristics vs broader socioeconomic context is unclear. We investigated whether country-level socioeconomic factors are associated with neuroanatomical differences in adults with epilepsy using MRI-based age prediction, along with epilepsy subtype, sex, and clinical factors. Methods Structural MRI and clinical data were collected from 26 epilepsy centres across 12 countries in the Americas, Australia, Europe, Asia and Africa. MRI-based age estimates were estimated using a previously developed prediction model trained on 29,175 healthy subjects. Brain predicted age difference (BrainPAD) was calculated as the difference between MRI-predicted brain age and chronological age. National gross domestic product (GDP) per capita and income inequality (Gini index) were obtained from the World Bank. Associations between BrainPAD and epilepsy subtype (temporal lobe epilepsy, extratemporal epilepsy, and genetic generalised epilepsy), national socioeconomic context (GDP per capita and Gini index), age and sex were assessed using regression models. Results We analyzed 2,109 individuals with epilepsy and 1,041 healthy non-epilepsy controls (57% female; median age = 35; range 17-83). BrainPAD was higher in epilepsy than controls (β 4.2 years, SE 0.4; t=10.6), with increases ranging from 2.5 to 6 years across subtypes. Male sex was associated with 1 year higher BrainPAD relative to females (SE 0.33, t=3.12). There were no main effects of GDP or Gini index; however, significant interactions between were observed. The effect of epilepsy on BrainPAD was greater in countries with lower GDP per capita (t=-2.74) and higher income inequality (t=2.72). Conclusions Clinical factors and socioeconomic context both influence brain structural ageing in epilepsy. These findings highlight the importance of geographic and economic diversity in neuroimaging research and underscore the relevance of global socioeconomic context when interpreting brain health measures.

Low-dose computed tomography (LDCT) screening can reduce lung cancer (LC)-related mortality, but questions remain about the duration of this effect and differences by sex and tumor histology. Extended follow-up data from the ITALUNG and LUSI trials were pooled to examine screening-related tumor stage-shifts and to estimate relative hazards for LC-related mortality, by sex and histology. Findings were compared to, and additionally combined with, those from the US National Lung Screening Trial (NLST). In ITALUNG-LUSI, screening yielded a 30% reduction of overall LC mortality up to 8 years after final screening (dilution-adjusted HR=0.70[0.51-0.96]). This reduction, however, was more pronounced for women (HR=0.49[0.25-0.96]) than men (HR=0.78[0.54-1.11]), which was confirmed in combined data of ITALUNG-LUSI plus NLST (6 years post-screening, women: HR=0.74[0.61-0.90], men: HR=0.93[0.80-1.06]; pheterogeneity=0.06). Analyses of stage-shifts and relative mortality hazards suggested that screening reduced mortality by non-small cell and non-squamous tumors in both sexes. In women (18-20%), more than among men (5-9%), screening also resulted in frequent detection of adenocarcinomas with lepidic growth. Finally, in both ITALUNG-LUSI and NLST, LDCT screening reduced the incidence and mortality for small-cell lung cancer (SCLC) among women (HR=0.63[0.43-0.94], all trials combined) but not among men (pheterogeneity=0.04). LC-related mortality reduction by LDCT screening may last until 8 or more years after cessation, and appears to be stronger for women than men, due to reduced incidence and mortality of SCLC in women only. The latter might be caused by removal of (likely EGFR-mutated, and slowly growing) adenomatous precursor lesions that over time would transform into SCLC (lineage plasticity). These findings may have major implications for the optimization of screening programs in terms of eligibility criteria and screening intervals Rudolf Kaaks, Francisco O. Cortès-Ibañez, Stefan Delorme, Erna Motsch, Verena Katzke, Claus-Peter Heussel, Hans-Ulrich Kauczor, Giulia Picozzi, Giuseppe Gorini, Francesca Maria Carozzi, Laura Carrozzi, Eugenio Paci, Donella Puliti, Mario Mascalchi. Effectiveness of lung cancer screening by sex and tumor histology: Extended, pooled analysis of the ITALUNG and LUSI trials, with comparison to findings in the NLST [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7409.

Purpose:Lesion overlooking and late diagnostic workup can compromise the efficacy of low-dose CT (LDCT) screening of lung cancer (LC), implying more advanced and less curable disease stages. We hypothesized that the azygos esophageal recess (AER) of the right lower lobe (RLL) might be an area prone to lesion overlooking in LC screening.Materials and Methods:Two radiologists reviewed the LDCT examinations of all the screen-detected incident LCs observed in the active arm of 2 randomized clinical trials: ITALUNG and national lung screening trial. Those in the AER were compared with those in the remainder of the RLL for possible differences in diagnostic lag according to the Lung-RADS 1.1 recommendations, size, stage, and mortality.Results:Six (11.7%) of 51 screen-detected incident LCs of the RLL were located in the AER. The diagnostic lag time was significantly longer (P=0.046) in the AER LC (mean 14 +/- 9 mo) than in the LC in the remaining RLL (mean 7.3 +/- 1 mo). Size and stage at diagnosis were not significantly different. All 6 subjects with LC in the AER and 16 (35.5%) of 45 subjects with LC in the remaining RLL (P=0.004) died of LC after a median follow-up of 12 years.Conclusion:Our retrospective study indicates that AER might represent a lung region of the RLL prone to have early LC overlooked due to detection or interpretation errors with possible detrimental consequences for the subject undergoing LC screening.

Lung imaging lacks a standardized reference space, hindering the large-scale, voxel-wise analyses that are routine in neuroimaging. To address this gap, we developed a high-resolution, open-source 3-D lung template and probabilistic lobar atlas from a cohort of 30 subjects from the National Lung Screening Trial (NLST). Created using a fully automatic pipeline based on the Advanced Normalization Tools (ANTs) ecosystem, this template reached convergence (dice similarity coefficient of 0.992 between consecutive iterations) after 11 iterations. We demonstrated its utility by registering 60 subjects with varying emphysema severity, finding that voxel-wise Jacobian analysis could distinguish disease-specific deformation patterns. This work provides a foundational, open resource for standardizing anatomical localization, enabling robust group-level studies in lung cancer screening research.

Background A 5-year screening interval for CT colonography (CTC) and a 2-year screening interval for fecal immunochemical tests (FITs) have been recommended on the basis of the natural history of colorectal cancer (CRC). Purpose To assess whether the recommended 5-year interval for screening CTC is appropriate and whether CTC is associated with earlier diagnosis relative to biennial FIT screening. Materials and Methods This secondary analysis of the SAVE randomized controlled trial was conducted between March 2012 and March 2018; 14 981 participants aged 54-65 years were randomly assigned to groups undergoing a single CTC examination or three biennial FITs for CRC screening. After the trial period ended, all participants aged younger than 70 years were invited to undergo biennial FIT. The incidence rates of CRC and advanced adenoma (AdA) until December 31, 2021 (mean, 8.4 years of follow-up), in the 1286 participants who underwent CTC and 6027 participants who underwent at least one trial FIT were compared using Cox regression models adjusted for age, sex, and socioeconomic status. Results In the CTC arm, one interval CRC was observed during the 5 years following CTC, and no cancers were detected thereafter. Overall, nine CRC cases were diagnosed in the CTC arm and 58 in the FIT arm, with no statistically significant difference in CRC incidence rates between the two groups (adjusted hazard ratio, 0.73 [95% CI: 0.36, 1.47]; P = .38). All stage IV CRCs (n = 7) occurred in the FIT arm. By the end of follow-up, the CTC arm showed a persistently and significantly higher incidence rate of AdA compared with the FIT arm (adjusted hazard ratio, 1.46 [95% CI: 1.11, 1.92]; P = .007). Conclusion The 5-year interval for screening CTC is appropriate and might be associated with earlier diagnosis relative to FIT screening. Clinical trial registration no. NCT01651624 © RSNA, 2025 See also the editorial by Pietryga and Kim in this issue.

BACKGROUND:Spinocerebellar ataxia type 2 (SCA2) is a rare, inherited neurodegenerative disease characterized by progressive deterioration in both motor coordination and cognitive function. Atrophy of the cerebellum, brainstem, and spinal cord are core features of SCA2; however, the evolution and pattern of whole-brain atrophy in SCA2 remain unclear. OBJECTIVE:We undertook a multisite, structural magnetic resonance imaging (MRI) study to comprehensively characterize the neurodegeneration profile of SCA2. METHODS:Voxel-based morphometry analyses of 110 participants with SCA2 and 128 controls were undertaken to assess groupwise differences in whole-brain volume. Correlations with clinical severity and genotype, and cross-sectional profiling of atrophy patterns at different disease stages, were also performed. RESULTS:Atrophy in SCA2 versus controls was greatest (Cohen's d >2.5) in the cerebellar white matter (WM), middle cerebellar peduncle, pons, and corticospinal tract. Very large effects (d >1.5) were also evident in the superior cerebellar, inferior cerebellar, and cerebral peduncles. In the cerebellar gray matter (GM), large effects (d >0.8) were observed in areas related to both motor coordination and cognitive tasks. Strong correlations (|r| > 0.4) between volume and disease severity largely mirrored these groupwise outcomes. Stratification by disease severity exhibited a degeneration pattern beginning in the cerebellar and pontine WM in preclinical subjects; spreading to the cerebellar GM and cerebro-cerebellar/corticospinal WM tracts; and then finally involving the thalamus, striatum, and cortex in severe stages. CONCLUSION:The magnitude and pattern of brain atrophy evolve over the course of SCA2, with widespread, nonuniform involvement across the brainstem, cerebellar tracts, and cerebellar cortex; and late involvement of the cerebral cortex and striatum. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

BACKGROUND AND OBJECTIVES:Temporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of gray and white matter structures. Evidence supports a progressive condition, although the temporal evolution of TLE is poorly defined. In this ENIGMA-Epilepsy study, we aim to investigate structural alterations in gray and white matter across the adult lifespan in patients with TLE by charting both gray and white matter changes and explore the covariance of age-related alterations in both compartments. METHODS:Mega-analysis of parcellated T1-weighted and diffusion MRI data across 18 international sites for patients with TLE was compared against healthy controls. We combined median-age split groupwise comparisons with cross-sectional sliding age-window analyses to explore gray (cortical thickness, subcortical volume) and white matter microstructure (fractional anisotropy, mean diffusivity) age-related changes. Five-year range age windows were constructed from mean z scores of all patients. Covariance analyses examined the coupled correlations of gray and white matter lifespan curves for each region. RESULTS:We studied 769 patients with TLE and 885 healthy controls across an age range of 17-73 years. Robust (pFDR < 0.05) gray matter thickness/volume decline (d < -0.20) was seen across a broad cortico-subcortical territory, extending beyond the mesiotemporal lobe throughout the adult lifespan in patients with TLE. White matter changes were also widespread across multiple fiber tracts with peak effects in temporolimbic fibers in fractional anisotropy (d < -0.3, pFDR < 0.05) and mean diffusivity measures (d > 0.3, pFDR < 0.05). Changes spanned the adult time window and effects exceeded typical aging-related processes in patients at the level of cortical thickness, subcortical volume, and diffusion measures, particularly in patients older than 55 years. Covariance analyses revealed strong associations across multiple white matter tracts, subcortical structures, and cortical regions within and beyond the temporolimbic system. DISCUSSION:This study highlights that patients with TLE exhibit more pronounced and widespread gray and white matter atrophy across the lifespan. The cross-sectional nature of our study limits definitive conclusions on whether the atrophy shown is progressive but emphasizes the importance of prompt diagnosis and intervention in patients. Collectively, our results motivate future longitudinal studies to clarify consequences of drug-resistant epilepsy.

The potential of deep learning for medical imaging is often constrained by limited data availability. Generative models can unlock this potential by generating synthetic data that reproduces the statistical properties of real data while being more accessible for sharing. In this study, we investigated the influence of training set size on the performance of a state-of-the-art generative adversarial network, the StyleGAN2-ADA, trained on a cohort of 3,227 subjects from the OpenBHB dataset to generate 2D slices of brain MR images from healthy subjects. The quality of the synthetic images was assessed through qualitative evaluations and state-of-the-art quantitative metrics, which are provided in a publicly accessible repository. Our results demonstrate that StyleGAN2-ADA generates realistic and high-quality images, deceiving even expert radiologists while preserving privacy, as it did not memorize training images. Notably, increasing the training set size led to slight improvements in fidelity metrics. However, training set size had no noticeable impact on diversity metrics, highlighting the persistent limitation of mode collapse. Furthermore, we observed that diversity metrics, such as coverage and β-recall, are highly sensitive to the number of synthetic images used in their computation, leading to inflated values when synthetic data significantly outnumber real ones. These findings underscore the need to carefully interpret diversity metrics and the importance of employing complementary evaluation strategies for robust assessment. Overall, while StyleGAN2-ADA shows promise as a tool for generating privacy-preserving synthetic medical images, overcoming diversity limitations will require exploring alternative generative architectures or incorporating additional regularization techniques.

In a recent study published in Nature Medicine,Wang,Shao,and colleagues successfully addressed two critical issues of lung cancer(LC)screening with low-dose computed tomography(LDCT)whose widespread implementation,despite its capacity to decrease LC mortality,remains challenging:(1)the difficulty in accurately distinguishing malignant nodules from the far more common benign nodules detected on LDCT,and(2)the insufficient coverage of LC screening in resource-limited areas.

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Background Vascular mild cognitive impairment (VMCI) is a transitional condition that may evolve into Vascular Dementia(VaD). Hippocampal volume (HV) is suggested as an early marker for VaD, the role of white matter lesions (WMLs) in neurodegeneration remains debated. Objectives Evaluate HV and WMLs as predictive markers of VaD in VMCI patients by assessing: (i)baseline differences in HV and WMLs between converters to VaD and non-converters, (ii) predictive power of HV and WMLs for VaD, (iii) associations between HV, WMLs, and cognitive decline, (iv)the role of WMLs on HV. Methods This longitudinal multicenter study included 110 VMCI subjects (mean age:74.33 ± 6.63 years, 60males/50females) from the VMCI-Tuscany Study database. Subjects underwent brain MRI and cognitive testing, with 2-year follow-up data on VaD progression. HV and WMLs were semi-automatically segmented and measured. ANCOVA assessed group differences, while linear and logistic regression models evaluated predictive power. Results After 2 years, 32/110 VMCI patients progressed to VaD. Converting patients had lower HV(p = 0.015) and higher lesion volumes in the posterior thalamic radiation (p = 0.046), splenium of the corpus callosum (p = 0.016), cingulate gyrus (p = 0.041), and cingulum hippocampus(p = 0.038). HV alone did not fully explain progression (p = 0.059), but combined with WMLs volume, the model was significant (p = 0.035). The best prediction model (p = 0.001) included total HV (p = 0.004) and total WMLs volume of the posterior thalamic radiation (p = 0.005) and cingulate gyrus (p = 0.005), achieving 80% precision, 81% specificity, and 74% sensitivity. Lower HV were linked to poorer performance on the Rey Auditory-Verbal Learning Test delayed recall (RAVLT) and Mini Mental State Examination (MMSE). Conclusions HV and WMLs are significant predictors of progression from VMCI to VaD. Lower HV correlate with worse cognitive performance on RAVLT and MMSE tests.

The role of total plasma cell-free DNA (cfDNA) in lung cancer (LC) screening with low-dose computed tomography (LDCT) is uncertain. We hypothesized that cfDNA could support differentiation between malignant and benign nodules observed in LDCT. The baseline cfDNA was measured in 137 subjects of the ITALUNG trial, including 29 subjects with screen-detected LC (17 prevalent and 12 incident) and 108 subjects with benign nodules. The predictive capability of baseline cfDNA to differentiate malignant and benign nodules was compared to that of Lung-RADS classification and Brock score at initial LDCT (iLDCT). Subjects with prevalent LC showed both well-discriminating radiological characteristics of the malignant nodule (16 of 17 were classified as Lung-RADS 4) and markedly increased cfDNA (mean 18.8 ng/mL). The mean diameters and Brock scores of malignant nodules at iLDCT in subjects who were diagnosed with incident LC were not different from those of benign nodules. However, 75% (9/12) of subjects with incident LC showed a baseline cfDNA ≥ 3.15 ng/mL, compared to 34% (37/108) of subjects with benign nodules (p = 0.006). Moreover, baseline cfDNA was correlated (p = 0.001) with tumor growth, measured with volume doubling time. In conclusion, increased baseline cfDNA may help to differentiate subjects with malignant and benign nodules at LDCT.

ABSTRACTObjectivesTemporal lobe epilepsy (TLE) is commonly associated with mesiotemporal pathology and widespread alterations of grey and white matter structures. Evidence supports a progressive condition although the temporal evolution of TLE is poorly defined. This ENIGMA-Epilepsy study utilized multimodal magnetic resonance imaging (MRI) data to investigate structural alterations in TLE patients across the adult lifespan. We charted both grey and white matter changes and explored the covariance of age-related alterations in both compartments.MethodsWe studied 769 TLE patients and 885 healthy controls across an age range of 17-73 years, from multiple international sites. To assess potentially non-linear lifespan changes in TLE, we harmonized data and combined median split assessments with cross-sectional sliding window analyses of grey and white matter age-related changes. Covariance analyses examined the coupling of grey and white matter lifespan curves.ResultsIn TLE, age was associated with a robust grey matter thickness/volume decline across a broad cortico-subcortical territory, extending beyond the mesiotemporal disease epicentre. White matter changes were also widespread across multiple tracts with peak effects in temporo-limbic fibers. While changes spanned the adult time window, changes accelerated in cortical thickness, subcortical volume, and fractional anisotropy (all decreased), and mean diffusivity (increased) after age 55 years. Covariance analyses revealed strong limbic associations between white matter tracts and subcortical structures with cortical regions.ConclusionsThis study highlights the profound impact of TLE on lifespan changes in grey and white matter structures, with an acceleration of aging-related processes in later decades of life. Our findings motivate future longitudinal studies across the lifespan and emphasize the importance of prompt diagnosis as well as intervention in patients.

Objective:Spinocerebellar ataxia type 2 (SCA2) is a rare, inherited neurodegenerative disease characterised by progressive deterioration in both motor coordination and cognitive function. Atrophy of the cerebellum, brainstem, and spinal cord are core features of SCA2, however the evolution and pattern of whole-brain atrophy in SCA2 remain unclear. We undertook a multi-site, structural magnetic resonance imaging (MRI) study to comprehensively characterize the neurodegeneration profile of SCA2. Methods:Voxel-based morphometry analyses of 110 participants with SCA2 and 128 controls were undertaken to assess groupwise differences in whole-brain volume. Correlations with clinical severity and genotype, and cross-sectional profiling of atrophy patterns at different disease stages, were also performed. Results:Atrophy in SCA2 relative to controls was greatest (Cohen's d>2.5) in the cerebellar white matter (WM), middle cerebellar peduncle, pons, and corticospinal tract. Very large effects (d>1.5) were also evident in the superior cerebellar, inferior cerebellar, and cerebral peduncles. In cerebellar grey matter (GM), large effects (d>0.8) mapped to areas related to both motor coordination and cognitive tasks. Strong correlations (|r|>0.4) between volume and disease severity largely mirrored these groupwise outcomes. Stratification by disease severity showed a degeneration pattern beginning in cerebellar and pontine WM in pre-clinical subjects; spreading to the cerebellar GM and cerebro-cerebellar/corticospinal WM tracts; then finally involving the thalamus, striatum, and cortex in severe stages. Interpretation:The magnitude and pattern of brain atrophy evolves over the course of SCA2, with widespread, non-uniform involvement across the brainstem, cerebellar tracts, and cerebellar cortex; and late involvement of the cerebral cortex and striatum.

Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance. The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps. A representative group of 24 subjects (mean age 54 ± 18 years) referred for clinical cardiac MR imaging were enrolled in the study. For each subject, T1 and T2 mapping through MOLLI and T2-prepared TrueFISP acquisition sequences, respectively, were performed at 1.5 T. Then, 98 radiomic features of different classes (shape, first-order, second-order) were extracted from a region of interest encompassing the whole left ventricle myocardium in a short axis slice. The repeatability was assessed performing different and complementary analyses: intraclass correlation coefficient (ICC) and limits of agreement (LOA) (i.e., the interval within which 95% of the percentage differences between two repeated measures are expected to lie). Radiomic features were characterized by a relatively wide range of repeatability degree in terms of both ICC and LOA. Overall, 44.9% and 38.8% of radiomic features showed ICC values > 0.75 for T1 and T2 maps, respectively, while 25.5% and 23.4% of radiomic features showed LOA between ±10%. A subset of radiomic features for T1 (Mean, Median, 10Percentile, 90Percentile, RootMeanSquared, Imc2, RunLengthNonUniformityNormalized, RunPercentage and ShortRunEmphasis) and T2 (MaximumDiameter, RunLengthNonUniformityNormalized, RunPercentage, ShortRunEmphasis) maps presented both ICC > 0.75 and LOA between ±5%. Overall, radiomic features extracted from T1 maps showed better repeatability performance than those extracted from T2 maps, with shape features characterized by better repeatability than first-order and textural features. Moreover, only a limited subset of 9 and 4 radiomic features for T1 and T2 maps, respectively, showed high repeatability degree in terms of both ICC and LOA. These results confirm the importance of assessing test-retest repeatability degree in radiomic feature estimation and might be useful for a more effective/reliable use of myocardial T1 and T2 mapping radiomics in clinical or research studies.