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Background: Artificial intelligence (AI) is increasingly finding its way into routine radiological work., Objective: Presentation of the current advances and applications of AI along the entire radiological patient journey., Methods: Systematic literature review of established AI techniques and current research projects, with reference to consensus recommendations., Results: The applications of AI in radiology cover a wide range, starting with AI-supported scheduling and indications assessment, extending to AI-enhanced image acquisition and reconstruction techniques that have the potential to reduce radiation doses in computed tomography (CT) or acquisition times in magnetic resonance imaging (MRI), while maintaining comparable image quality. These include computer-aided detection and diagnosis, such as fracture recognition or nodule detection. Additionally, methods such as worklist prioritization and structured reporting facilitated by large language models enable a rethinking of the reporting process. The use of AI promises to increase the efficiency of all steps of the radiology workflow and an improved diagnostic accuracy. To achieve this, seamless integration into technical workflows and proven evidence of AI systems are necessary., Conclusion: Applications of AI have the potential to profoundly influence the role of radiologists in the future., (© 2024. The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.)

This systematic review considered evidence of children's and adolescents' typical brain connectivity development studied through resting-state functional magnetic resonance imaging (rs-fMRI). With aim of understanding the state of the art, what has been researched thus far and what remains unknown, this paper reviews 58 studies from 2013 to 2023. Considering the results, rs-fMRI stands out as an appropriate technique for studying language and attention within cognitive domains, and personality traits such as impulsivity and empathy. The most used analyses encompass seed-based, independent component analysis (ICA), the amplitude of the low frequency fluctuations (ALFF), and fractional ALFF (fALFF). The findings highlight key themes, including age-related changes in intrinsic connectivity, sex-specific patterns, and the relevance of the Default Mode Network (DMN). Overall, there is a need for longitudinal approaches to trace the typical developmental trajectory of neural networks from childhood through adolescence with fMRI at rest., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Cervical spine (c-spine) evaluation is a critical component in trauma evaluation, and although several pediatric c-spine evaluation algorithms have been developed, none have been widely implemented. Here, we assess rates of c-spine imaging use across children's hospitals, specifically temporal trends in imaging use, variation across hospitals in imaging used, and timing of magnetic resonance imaging in admitted patients., Methods: Data from the Children's Hospital Associations Pediatric Health Information System were abstracted from 2015 to 2020. Patients younger than 18 years seen in the emergency department with an International Classification of Diseases, Tenth Revision , code indicative of trauma and c-spine plain radiograph or computed tomography (CT) in the emergency department were included. Data visualization and descriptive statistics were used to assess rates of imaging use by age, year, hospital, injury severity, and day of service. Changes in rates of imaging use over time were evaluated via simple linear regression., Results: Across 25,238 patient encounters at 35 children's hospitals, there was an increase in use of c-spine CT from 2015 to 2020 (28.5-36.5%). There was substantial interinstitutional variation in rates of use of plain radiographs versus CT for initial evaluation of the c-spine across all age groups. Magnetic resonance imaging was obtained more than 3 days after admission in 31.5% of intensive care patients who received this imaging., Conclusion: Increasing use of CT, substantial interinstitutional variation in rates of use of plain radiographs versus CT, and heterogenous timing of magnetic resonance imaging for evaluation of the pediatric c-spine demonstrate the growing need for development and implementation of an age-specific c-spine evaluation algorithm to guide judicious use of diagnostic resources., Level of Evidence: Prognostic and Epidemiological; Level III., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Purpose: The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain., Methods: All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023., Results: A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain., Conclusions: This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.)

Objective: To develop and validate a multimodal combinatorial model based on whole-brain magnetic resonance imaging (MRI) radiomic features for predicting cognitive decline in patients with Parkinson's disease (PD)., Methods: This study included a total of 222 PD patients with normal baseline cognition, of whom 68 had cognitive impairment during a 4-year follow-up period. All patients underwent MRI scans, and radiomic features were extracted from the whole-brain MRI images of the training set, and dimensionality reduction was performed to construct a radiomics model. Subsequently, Screening predictive factors for cognitive decline from clinical features and then combining those with a radiomics model to construct a multimodal combinatorial model for predicting cognitive decline in PD patients. Evaluate the performance of the comprehensive model using the receiver-operating characteristic curve, confusion matrix, F1 score, and survival curve. In addition, the quantitative characteristics of diffusion tensor imaging (DTI) from corpus callosum were selected from 52 PD patients to further validate the clinical efficacy of the model., Results: The multimodal combinatorial model has good classification performance, with areas under the curve of 0.842, 0.829, and 0.860 in the training, test, and validation sets, respectively. Significant differences were observed in the number of cognitive decline PD patients and corpus callosum-related DTI parameters between the low-risk and high-risk groups distinguished by the model (p < 0.05). The survival curve analysis showed a statistically significant difference in the progression time of mild cognitive impairment between the low-risk and the high-risk groups., Conclusions: The building of a multimodal combinatorial model based on radiomic features from MRI can predict cognitive decline in PD patients, thus providing adaptive strategies for clinical practice., (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Cerebrovascular disease (CVD) manifests through a broad spectrum of mechanisms that negatively impact brain and cognitive health. Oftentimes, CVD changes (excluding acute stroke) are insufficiently considered in aging and dementia studies which can lead to an incomplete picture of the etiologies contributing to the burden of cognitive impairment. Our goal with this focused review is 3-fold. First, we provide a research update on the current magnetic resonance imaging methods that can measure CVD lesions as well as early CVD-related brain injury specifically related to small vessel disease. Second, we discuss the clinical implications and relevance of these CVD imaging markers for cognitive decline, incident dementia, and disease progression in Alzheimer disease, and Alzheimer-related dementias. Finally, we present our perspective on the outlook and challenges that remain in the field. With the increased research interest in this area, we believe that reliable CVD imaging biomarkers for aging and dementia studies are on the horizon.

To further advance functional MRI (fMRI)-based brain science, it is critical to dissect fMRI activity at the circuit level. To achieve this goal, we combined brain-wide fMRI with neuronal silencing in well-defined regions. Since focal inactivation suppresses excitatory output to downstream pathways, intact input and suppressed output circuits can be separated. Highly specific cerebral blood volume-weighted fMRI was performed with optogenetic stimulation of local GABAergic neurons in mouse somatosensory regions. Brain-wide spontaneous somatosensory networks were found mostly in ipsilateral cortical and subcortical areas, which differed from the bilateral homotopic connections commonly observed in resting-state fMRI data. The evoked fMRI responses to somatosensory stimulation in regions of the somatosensory network were successfully dissected, allowing the relative contributions of spinothalamic (ST), thalamocortical (TC), corticothalamic (CT), corticocortical (CC) inputs, and local intracortical circuits to be determined. The ventral posterior thalamic nucleus receives ST inputs, while the posterior medial thalamic nucleus receives CT inputs from the primary somatosensory cortex (S1) with TC inputs. The secondary somatosensory cortex (S2) receives mostly direct CC inputs from S1 and a few TC inputs from the ventral posterolateral nucleus. The TC and CC input layers in cortical regions were identified by laminar-specific fMRI responses with a full width at half maximum of <150 µm. Long-range synaptic inputs in cortical areas were amplified approximately twofold by local intracortical circuits, which is consistent with electrophysiological recordings. Overall, whole-brain fMRI with optogenetic inactivation revealed brain-wide, population-based, long-range circuits, which could complement data typically collected in conventional microscopic functional circuit studies., Competing Interests: The authors declare no competing interest., (Copyright © 2022 the Author(s). Published by PNAS.)

Background: Stereotactic needle brain biopsy is a commonly used neurosurgical procedure. However, up to 15% of biopsies result in undiagnostic pathology reports. Repeat biopsy or continued management without a diagnosis are often considered after undiagnostic biopsies. There have been no reports about the role of postoperative imaging in predicting the diagnostic yield of stereotactic biopsies., Methods: We retrospectively assessed all stereotactic biopsies performed over an 11-year period. We performed fusion of immediate postoperative computed tomography (CT) with preoperative MRI, to document whether the air bubble in the postoperative CT was located within the targeted lesion. We then evaluated the association of this fusion-based accuracy assessment with the diagnostic yield of the biopsy., Results: Fewer than 5% of biopsies did not have an air bubble on postoperative CT. A total of 226 biopsies were performed for 219 patients. In our sample, 213 of 226 biopsies were accurate (94.2% accuracy rate), and 203 of 226 biopsies gave a definitive diagnosis (89.8% diagnostic rate). In those cases where the fusion was accurate, the diagnostic rate was 93.9%. When the fusion was inaccurate, the diagnostic rate was only 23.1% (odds ratio 51.5, 95% confidence interval 12.6-210.44, P < 0.001). Of all patient, imaging, surgical, and admission parameters, the only parameter that correlated with diagnostic outcome of the biopsy was the fusion construct accuracy., Conclusions: Fusion of immediate postoperative CT with preoperative imaging is predictive of the diagnostic rate. In cases where the pathology report following a biopsy is not diagnostic, this fusion may be useful in making decisions regarding repeat biopsy or considering other diagnostic options., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The objective of the study is to evaluate the clinical and neuroradiological findings, the risk factors for recurrence and the prognosis in patients with posterior reversible encephalopathy syndrome developed secondary to acute hypertension in children. The study was conducted between 2008 and 2019 at Mersin University Faculty of Medicine. A total of 49 episodes were evaluated retrospectively in 38 patients with PRES secondary to acute hypertension. The demographic data, etiology, and clinical and neuroradiological findings were recorded. Twenty-one (55.3%) patients were female; the mean age was 11.8 years. The etiology of acute hypertension in 29 (76.3%) patients was end-stage renal disease (ESRD). The most common clinical findings were seizure (81.6%) and altered consciousness (79.6%). Status epilepticus developed in eight (16.3%) episodes. MRI lesions were atypical in 33 episodes (67.3%). In eight (21%) patients, PRES recurred. Irreversible brain damage was detected after PRES in three (7.8%) patients. C-reactive protein and erythrocyte sedimentation rate were elevated in 82.2% and 71.4% of the episodes, respectively. A statistically significant relationship was found between the recurrence, the duration of hospitalization at the PICU, SE and the occurrence of irreversible lesion (p = 0.013, p = 0.015, p = 0.001 respectively). Also, there were statistically significant relationships between recurrence and ESRD; epilepsy and recurrences; SE and irreversible brain damage (p = 0.02, p = 0.012, p = 0.025 respectively). Although PRES is usually known to have a good prognosis, the mortality and morbidity rates may increase in the long-term follow-up as in our study. In this study, the etiology, the presence of status epilepticus, PICU history, atypical MRI lesions and increased inflammatory markers were found to be important for the prognosis in PRES., (© 2020. Belgian Neurological Society.)

Objective: Effective image segmentation of cerebral structures is fundamental to 3-dimensional techniques such as augmented reality. To be clinically viable, segmentation algorithms should be fully automatic and easily integrated in existing digital infrastructure. We created a fully automatic adaptive-meshing-based segmentation system for T1-weighted magnetic resonance images (MRI) to automatically segment the complete ventricular system, running in a cloud-based environment that can be accessed on an augmented reality device. This study aims to assess the accuracy and segmentation time of the system by comparing it to a manually segmented ground truth dataset., Methods: A ground truth (GT) dataset of 46 contrast-enhanced and non-contrast-enhanced T1-weighted MRI scans was manually segmented. These scans also were uploaded to our system to create a machine-segmented (MS) dataset. The GT data were compared with the MS data using the Sørensen-Dice similarity coefficient and 95% Hausdorff distance to determine segmentation accuracy. Furthermore, segmentation times for all GT and MS segmentations were measured., Results: Automatic segmentation was successful for 45 (98%) of 46 cases. Mean Sørensen-Dice similarity coefficient score was 0.83 (standard deviation [SD] = 0.08) and mean 95% Hausdorff distance was 19.06 mm (SD = 11.20). Segmentation time was significantly longer for the GT group (mean = 14405 seconds, SD = 7089) when compared with the MS group (mean = 1275 seconds, SD = 714) with a mean difference of 13,130 seconds (95% confidence interval 10,130-16,130)., Conclusions: The described adaptive meshing-based segmentation algorithm provides accurate and time-efficient automatic segmentation of the ventricular system from T1 MRI scans and direct visualization of the rendered surface models in augmented reality., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. Early detection of HCC enables patients to avail curative therapies that can improve patient survival. Current international guidelines advocate for the enrollment of patients at high risk for HCC, like those with cirrhosis, in surveillance programs that perform ultrasound every 6 months. In recent years, many studies have further characterized the utility of established screening strategies and have introduced new promising tools for HCC surveillance. In this review, we provide an overview of the most promising new imaging modalities and biomarkers for the detection of HCC. We discuss the role of imaging tools like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) in the early detection of HCC, and describe recent innovations which can potentially enhance their applicability, including contrast enhanced ultrasound, low-dose CT scans, and abbreviated MRI. Next, we outline the data supporting the use of three circulating biomarkers (i.e., alpha-fetoprotein [AFP], AFP lens culinaris agglutinin-reactive fraction, and des-gamma-carboxy prothrombin) in HCC surveillance, and expand on multiple emerging liquid biopsy biomarkers, including methylated cell-free DNA (cfDNA), cfDNA mutations, extracellular vesicles, and circulating tumor cells. These promising new imaging modalities and biomarkers have the potential to improve early detection, and thus improve survival, in patients with HCC., (© 2021 The Authors. Hepatology Communications published by Wiley Periodicals LLC on behalf of American Association for the Study of Liver Diseases.)

In Parkinson's disease, there is a progressive reduction in striatal dopaminergic function, and loss of neuromelanin-containing dopaminergic neurons and increased iron deposition in the substantia nigra. We tested the hypothesis of a relationship between impairment of the dopaminergic system and changes in the iron metabolism. Based on imaging data of patients with prodromal and early clinical Parkinson's disease, we assessed the spatiotemporal ordering of such changes and relationships in the sensorimotor, associative and limbic territories of the nigrostriatal system. Patients with Parkinson's disease (disease duration < 4 years) or idiopathic REM sleep behaviour disorder (a prodromal form of Parkinson's disease) and healthy controls underwent longitudinal examination (baseline and 2-year follow-up). Neuromelanin and iron sensitive MRI and dopamine transporter single-photon emission tomography were performed to assess nigrostriatal levels of neuromelanin, iron, and dopamine. For all three functional territories of the nigrostriatal system, in the clinically most and least affected hemispheres separately, the following was performed: cross-sectional and longitudinal intergroup difference analysis of striatal dopamine and iron, and nigral neuromelanin and iron; in Parkinson's disease patients, exponential fitting analysis to assess the duration of the prodromal phase and the temporal ordering of changes in dopamine, neuromelanin or iron relative to controls; and voxel-wise correlation analysis to investigate concomitant spatial changes in dopamine-iron, dopamine-neuromelanin and neuromelanin-iron in the substantia nigra pars compacta. The temporal ordering of dopaminergic changes followed the known spatial pattern of progression involving first the sensorimotor, then the associative and limbic striatal and nigral regions. Striatal dopaminergic denervation occurred first followed by abnormal iron metabolism and finally neuromelanin changes in the substantia nigra pars compacta, which followed the same spatial and temporal gradient observed in the striatum but shifted in time. In conclusion, dopaminergic striatal dysfunction and cell loss in the substantia nigra pars compacta are interrelated with increased nigral iron content., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Multiple sclerosis is a highly heterogeneous disease, and the detection of neuroaxonal damage as well as its quantification is a critical step for patients. Blood-based serum neurofilament light chain (sNfL) is currently under close investigation as an easily accessible biomarker of prognosis and treatment response in patients with multiple sclerosis. There is abundant evidence that sNfL levels reflect ongoing inflammatory-driven neuroaxonal damage (e.g. relapses or MRI disease activity) and that sNfL levels predict disease activity over the next few years. In contrast, the association of sNfL with long-term clinical outcomes or its ability to reflect slow, diffuse neurodegenerative damage in multiple sclerosis is less clear. However, early results from real-world cohorts and clinical trials using sNfL as a marker of treatment response in multiple sclerosis are encouraging. Importantly, clinical algorithms should now be developed that incorporate the routine use of sNfL to guide individualized clinical decision-making in people with multiple sclerosis, together with additional fluid biomarkers and clinical and MRI measures. Here, we propose specific clinical scenarios where implementing sNfL measures may be of utility, including, among others: initial diagnosis, first treatment choice, surveillance of subclinical disease activity and guidance of therapy selection., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Background: Metabolic disorders associated with obesity could lead to alterations in brain structure and function. Whether these changes can be reversed after weight loss is unclear. Bariatric surgery provides a unique opportunity to address these questions because it induces marked weight loss and metabolic improvements which in turn may impact the brain in a longitudinal fashion. Previous studies found widespread changes in grey matter (GM) and white matter (WM) after bariatric surgery. However, findings regarding changes in spontaneous neural activity following surgery, as assessed with the fractional amplitude of low frequency fluctuations (fALFF) and regional homogeneity of neural activity (ReHo), are scarce and heterogenous. In this study, we used a longitudinal design to examine the changes in spontaneous neural activity after bariatric surgery (comparing pre- to post-surgery), and to determine whether these changes are related to cardiometabolic variables., Methods: The study included 57 participants with severe obesity (mean BMI=43.1 ± 4.3 kg/m 2 ) who underwent sleeve gastrectomy (SG), biliopancreatic diversion with duodenal switch (BPD), or Roux-en-Y gastric bypass (RYGB), scanned prior to bariatric surgery and at follow-up visits of 4 months (N = 36), 12 months (N = 29), and 24 months (N = 14) after surgery. We examined fALFF and ReHo measures across 1022 cortical and subcortical regions (based on combined Schaeffer-Xiao parcellations) using a linear mixed effect model. Voxel-based morphometry (VBM) based on T1-weighted images was also used to measure GM density in the same regions. We also used an independent sample from the Human Connectome Project (HCP) to assess regional differences between individuals who had normal-weight (N = 46) or severe obesity (N = 46)., Results: We found a global increase in the fALFF signal with greater increase within dorsolateral prefrontal cortex, precuneus, inferior temporal gyrus, and visual cortex. This effect was more significant 4 months after surgery. The increase within dorsolateral prefrontal cortex, temporal gyrus, and visual cortex was more limited after 12 months and only present in the visual cortex after 24 months. These increases in neural activity measured by fALFF were also significantly associated with the increase in GM density following surgery. Furthermore, the increase in neural activity was significantly related to post-surgery weight loss and improvement in cardiometabolic variables, such as blood pressure. In the independent HCP sample, normal-weight participants had higher global and regional fALFF signals, mainly in dorsolateral/medial frontal cortex, precuneus and middle/inferior temporal gyrus compared to the obese participants. These BMI-related differences in fALFF were associated with the increase in fALFF 4 months post-surgery especially in regions involved in control, default mode and dorsal attention networks., Conclusions: Bariatric surgery-induced weight loss and improvement in metabolic factors are associated with widespread global and regional increases in neural activity, as measured by fALFF signal. These findings alongside the higher fALFF signal in normal-weight participants compared to participants with severe obesity in an independent dataset suggest an early recovery in the neural activity signal level after the surgery., (Copyright © 2021. Published by Elsevier Inc.)

Neurodegenerative diseases (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD) and multiple sclerosis (MS), are relatively common and devastating neurological disorders. For example, there are 6 million individuals living with AD in the United States, a number that is projected to grow to 14 million by the year 2030. Importantly, AD, PD and MS are all characterized by the lack of a true disease-modifying therapy that is able to reverse or halt disease progression. In addition, the existing standard of care for most NDs only addresses the symptoms of the disease. Therefore, alternative strategies that target mechanisms underlying the neuropathogenesis of disease are much needed. Recent studies have indicated that metabolic alterations in neurons and glia are commonly observed in AD, PD and MS and lead to changes in cell function that can either precede or protect against disease onset and progression. Specifically, single-cell RNAseq studies have shown that AD progression is tightly linked to the metabolic phenotype of microglia, the key immune effector cells of the brain. However, these analyses involve removing cells from their native environment and performing measurements in vitro, influencing metabolic status. Therefore, technical approaches that can accurately assess cell-specific metabolism in situ have the potential to be transformative to our understanding of the mechanisms driving AD. Here, we review our current understanding of metabolism in both neurons and glia during homeostasis and disease. We also evaluate recent advances in metabolic imaging, and discuss how emerging modalities, such as fluorescence lifetime imaging microscopy (FLIM) have the potential to determine how metabolic perturbations may drive the progression of NDs. Finally, we propose that the temporal, regional, and cell-specific characterization of brain metabolism afforded by FLIM will be a critical first step in the rational design of metabolism-focused interventions that delay or even prevent NDs., (© 2021. The Author(s).)

Quantitative susceptibility mapping (QSM) and R2* mapping are MRI post-processing methods that quantify tissue magnetic susceptibility and transverse relaxation rate distributions. However, QSM and R2* acquisitions are relatively slow, even with parallel imaging. Incoherent undersampling and compressed sensing reconstruction techniques have been used to accelerate traditional magnitude-based MRI acquisitions; however, most do not recover the full phase signal, as required by QSM, due to its non-convex nature. In this study, a learning-based Deep Complex Residual Network (DCRNet) is proposed to recover both the magnitude and phase images from incoherently undersampled data, enabling high acceleration of QSM and R2* acquisition. Magnitude, phase, R2*, and QSM results from DCRNet were compared with two iterative and one deep learning methods on retrospectively undersampled acquisitions from six healthy volunteers, one intracranial hemorrhage and one multiple sclerosis patients, as well as one prospectively undersampled healthy subject using a 7T scanner. Peak signal to noise ratio (PSNR), structural similarity (SSIM), root-mean-squared error (RMSE), and region-of-interest susceptibility and R2* measurements are reported for numerical comparisons. The proposed DCRNet method substantially reduced artifacts and blurring compared to the other methods and resulted in the highest PSNR, SSIM, and RMSE on the magnitude, R2*, local field, and susceptibility maps. Compared to two iterative and one deep learning methods, the DCRNet method demonstrated a 3.2% to 9.1% accuracy improvement in deep grey matter susceptibility when accelerated by a factor of four. The DCRNet also dramatically shortened the reconstruction time of single 2D brain images from 36-140 seconds using conventional approaches to only 15-70 milliseconds., (Copyright © 2021. Published by Elsevier Inc.)

Purpos e. We investigated the disparate influence of lesion location on functional damage and reorganization of the sensorimotor brain network in patients with thalamic infarction and pontine infarction. Methods . Fourteen patients with unilateral infarction of the thalamus and 14 patients with unilateral infarction of the pons underwent longitudinal fMRI measurements and motor functional assessment five times during a 6-month period (<7 days, at 2 weeks, 1 month, 3 months, and 6 months after stroke onset). Twenty-five age- and sex-matched controls underwent MRI examination across five consecutive time points in 6 months. Functional images from patients with left hemisphere lesions were first flipped from the left to the right side. The voxel-wise connectivity analyses between the reference time course of each ROI (the contralateral dorsal lateral putamen (dl-putamen), pons, ventral anterior (VA), and ventral lateral (VL) nuclei of the thalamus) and the time course of each voxel in the sensorimotor area were performed for all five measurements. One-way ANOVA was used to identify between-group differences in functional connectivity (FC) at baseline stage (<7 days after stroke onset), with infarction volume included as a nuisance variable. The family-wise error (FWE) method was used to account for multiple comparison issues using SPM software. Post hoc repeated-measure ANOVA was applied to examine longitudinal FC reorganization. Results . At baseline stage, significant differences were detected between the contralateral VA and ipsilateral postcentral gyrus (cl&#95;VA-ip&#95;postcentral), contralateral VL and ipsilateral precentral gyrus (cl&#95;VL-ip&#95;precentral). Repeated measures ANOVA revealed that the FC change of cl&#95;VA-ip&#95;postcentral differ significantly among the three groups over time. The significant changes of FC between cl&#95;VA and ip&#95;postcentral at different time points in the thalamic infarction group showed that compared with 7 days after stroke onset, there was significantly increased FC of cl&#95;VA-ip&#95;postcentral at 1 month, 3 months, and 6 months after stroke onset. Conclusions . The different patterns of sensorimotor functional damage and reorganization in patients with pontine infarction and thalamic infarction may provide insights into the neural mechanisms underlying functional recovery after stroke., Competing Interests: The authors have no conflict of interest to declare., (Copyright © 2021 Peipei Wang et al.)

Children born extremely preterm (EP, <28 weeks' gestation) or extremely low birth weight (ELBW, <1,000 g) are a vulnerable population at high risk of working memory impairments. We aimed to examine changes in the brain structural connectivity networks thought to underlie working memory performance, after completion of a working memory training program (Cogmed) compared with a placebo program in EP/ELBW children. This was a double-blind, placebo-controlled randomized trial (the Improving Memory in a Preterm Randomised Intervention Trial). Children born EP/ELBW received either the Cogmed or placebo program at 7 years of age (n = 91). A subset of children had magnetic resonance imaging of the brain immediately pre- and 2 weeks post-training (Cogmed n = 28; placebo n = 27). T 1 -weighted and diffusion-weighted images were used to perform graph theoretical analysis of structural connectivity networks. Changes from pre-training to post-training in structural connectivity metrics were generally similar between randomized groups. There was little evidence that changes in structural connectivity metrics were related to changes in working memory performance from pre- to post-training. Overall, our results provide little evidence that the Cogmed working memory training program has training-specific effects on structural connectivity networks in EP/ELBW children., (© 2021 Wiley Periodicals LLC.)

Background: Lumbar Spine MRI Use for Low Back Pain (OP-8) is calculated by dividing the number of patients who received lumbar magnetic resonance imaging (MRI-L) before receiving alternative treatments (e.g., physical therapy) by the total number of patients receiving MRI-L in the outpatient setting at a given institution. Since the passage of the Post-Medicare Access and CHIP Reauthorization Act of 2015 (MACRA), OP-8 scores became tied to hospital finances. This study aims to determine how MACRA has impacted OP-8 scores since its implementation. We also aim to investigate how regional designation, profit status (for-profit, government, and nonprofit), and hospital setting (critical access, non-critical access) affect OP-8 scores., Methods: Data from the Centers for Medicare and Medicaid Services Hospital Compare database were used to extract information on the national trends in OP-8 scores from 2014 to 2020. A multivariable linear regression model was fit to isolate the impact of hospital characteristics on OP-8 scores., Results: After a decrease from 2015 to 2016, the mean national OP-8 score plateaued, staying around 40% from 2017 through 2020. A critical access setting increased OP-8 scores by 5.41 (95% confidence interval, 3.51-6.77; P ≤ 0.001), compared with a non-critical access setting. Governmental status increased scores by 1.27 (95% confidence interval, 0.28-2.27; P = 0.012), compared with a nonprofit status., Conclusions: The implementation of MACRA seems to have been unsuccessful in altering practice patterns, given the minimal change in OP-8 scores over the last 4 years. Furthermore, institutional factors are clearly correlated with a lack of adherence to magnetic resonance imaging guidelines. Given these findings, there is a need to modify health policies., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Although the year 2020 was different from other years in many respects, the Journal of Nuclear Cardiology published excellent articles pertaining to imaging in patients with cardiovascular disease due to the dedication of the investigators in our field all over the world. In this review, we will summarize a selection of these articles to provide a concise review of the main advancements that have recently occurred in the field and provide the reader with an opportunity to review a wide selection of articles. We will focus on publications dealing with positron emission tomography, computed tomography, and magnetic resonance and hope that you will find this review helpful., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

The hippocampus (Hc) is composed of cytoarchitectonically distinct subfields: dentate gyrus (DG), cornu ammonis sectors 1-3 (CA1-3), and subiculum. Limited evidence suggests differential maturation rates across the Hc subfields. While longitudinal studies are essential in demonstrating differential development of Hc subfields, a prerequisite for interpreting meaningful longitudinal effects is establishing test-retest consistency of Hc subfield volumes measured in vivo over time. Here, we examined test-retest consistency of Hc subfield volumes measured from structural MR images in two independent developmental samples. Sample One (n = 28, ages 7-20 years, M = 12.64, SD = 3.35) and Sample Two (n = 28, ages 7-17 years, M = 11.72, SD = 2.88) underwent MRI twice with a 1-month and a 2-year delay, respectively. High-resolution PD-TSE-T 2 -weighted MR images (0.4 × 0.4 × 2 mm 3 ) were collected and manually traced using a longitudinal manual demarcation protocol. In both samples, we found excellent consistency of Hc subfield volumes between the two visits, assessed by two-way mixed intraclass correlation (ICC (3) single measures ≥ 0.87), and no difference between children and adolescents. The results further indicated that discrepancies between repeated measures were not related to Hc subfield volumes, or visit number. In addition to high consistency, with the applied longitudinal protocol, we detected significant variability in Hc subfield volume changes over the 2-year delay, implying high sensitivity of the method in detecting individual differences. Establishing unbiased, high longitudinal consistency of Hc subfield volume measurements optimizes statistical power of a hypothesis test and reduces standard error of the estimate, together improving external validity of the measures in constructing theoretical models of memory development., (© 2021 Wiley Periodicals LLC.)

B-cells contribute to MS pathogenesis. The association of circulating B-cell phenotypes with combined unique active lesions (CUA) on MRI at 48 weeks follow-up was investigated in 50 interferon beta-treated MS patients. Transitional B-cell proportions were lower in participants with CUA at week 0 and 48 [p = 0.004, p = 0.002]. A decrease in circulating anti-EBNA-1 IgG levels between week 0 and 48 associated with absence of CUA [p = 0.047], but not with B-cell profiles. In a multi-factor model for CUA-risk, transitional B-cell proportions contributed independent from NK/T-cell ratio, change in anti-EBNA-1 IgG, and vitamin D supplementation. Transitional B-cells may predict treatment response in MS., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: Mechanical thrombectomy (MT) is not recommended for acute stroke with large vessel occlusion (LVO) and a large volume of irreversibly injured tissue ("core"). Perfusion imaging may identify a subset of patients with large core who benefit from MT., Methods: We compared two cohorts of LVO-related patients with large core (>50 ml on diffusion-weighted-imaging or CT-perfusion using RAPID), available perfusion imaging, and treated within 6 hours from onset by either MT + Best Medical Management (BMM) in one prospective study, or BMM alone in the pre-MT era from a prospective registry. Primary outcome was 90-day modified Rankin Scale ≤2. We searched for an interaction between treatment group and amount of penumbra as estimated by the mismatch ratio (MMRatio = critical hypoperfusion/core volume)., Results: Overall, 107 patients were included (56 MT + BMM and 51 BMM): Mean age was 68 ± 15 years, median core volume 99 ml (IQR: 72-131) and MMRatio 1.4 (IQR: 1.0-1.9). Baseline clinical and radiological variables were similar between the two groups, except for a higher intravenous thrombolysis rate in the BMM group. The MMRatio strongly modified the clinical outcome following MT (p interaction  < 0.001 for continuous MMRatio); MT was associated with a higher rate of good outcome in patients with, but not in those without, MMRatio>1.2 (adjusted OR [95% CI] = 6.8 [1.7-27.0] vs 0.7 [0.1-6.2], respectively). Similar findings were present for MMRatio ≥1.8 in the subgroup with core ≥70 ml. Parenchymal hemorrhage on follow-up imaging was more frequent in the MT + BMM group regardless of the MMRatio., Interpretation: Perfusion imaging may help select which patients with large core should be considered for MT. Randomized studies are warranted. ANN NEUROL 2021;90:417-427., (© 2021 American Neurological Association.)

Objective: The hippocampus is connected to 2 distinct cortical brain networks, the posterior-medial and the anterior-temporal networks, involving different medial temporal lobe (MTL) subregions. The aim of this study was to assess the functional alterations of these 2 networks, their changes over time, and links to cognition in Alzheimer's disease., Methods: We assessed MTL connectivity in 53 amyloid-β-positive patients with mild cognitive impairment and AD dementia and 68 healthy elderly controls, using resting-state functional magnetic resonance imaging, cross-sectionally and longitudinally. First, we compared the functional connectivity of the posterior-medial and anterior-temporal networks within the control group to highlight their specificities. Second, we compared the connectivity of these networks between groups, and between baseline and 18-month follow-up in patients. Third, we assessed the association in the connectivity changes between the 2 networks, and with cognitive performance., Results: We found decreased connectivity in patients specifically between the hippocampus and the posterior-medial network, together with increased connectivity between several MTL subregions and the anterior-temporal network. Moreover, changes in the posterior-medial and anterior-temporal networks were interrelated such that decreased MTL-posterior-medial connectivity was associated with increased MTL-anterior-temporal connectivity. Finally, both MTL-posterior-medial decrease and MTL-anterior-temporal increase predicted cognitive decline., Interpretation: Our findings demonstrate that longitudinal connectivity changes in the posterior-medial and anterior-temporal hippocampal networks are linked together and that they both contribute to cognitive decline in Alzheimer's disease. These results shed light on the critical role of the posterior-medial and anterior-temporal networks in Alzheimer's disease pathophysiology and clinical symptoms. ANN NEUROL 2021;90:391-406., (© 2021 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Research exploring the underlying neuroanatomical correlates of early motherhood seems to suggest that the period after giving birth is marked by tissue increases in the mother's brain. While some studies point to the amygdala as one of the areas undergoing postpartum changes, existing analyses did not discriminate between the different subregions of this functionally heterogeneous structure. Thus, to further extend this understudied field of research and to better understand the potential role of the amygdala when transitioning to motherhood, we applied an advanced region-of-interest technique that enabled us to analyze the amygdala as a whole as well as its different subareas, specifically the left and right centromedian (CM), laterobasal (LB), and superficial (SF) regions. Comparing the brains of 14 healthy women between immediate postpartum (within 1-2 days of childbirth) and late postpartum (at 4-6 weeks after childbirth), we revealed increases of the amygdala. However, effects manifested differentially across subareas, with particularly strong effects for the SF region, moderate effects for the CM region, and no effects for the LB region. These findings might reflect region-specific adaptations of the mother's brain tuning into the distinct and ever-changing needs of a newborn, either as a cause for it or as a consequence thereof., (© 2021 Wiley Periodicals LLC.)

Objective: We aimed to determine in relapsing multiple sclerosis (MS) whether intrathecal synthesis of immunoglobulin (Ig) M and IgG is associated with outcomes reflecting inflammatory activity and chronic worsening., Methods: We compared cerebrospinal fluid analysis, clinical and magnetic resonance imaging data, and serum neurofilament light chain (sNfL) levels at baseline and follow-up in 530 patients with relapsing MS. Patients were categorized by the presence of oligoclonal IgG bands (OCGB) and intrathecal synthesis of IgG and IgM (intrathecal fraction [IF]: IgG IF and IgM IF ). Relationships with the time to first relapse, sNfL concentrations, T2-weighted (T2w) lesions, MS Severity Score (MSSS), and time to initiation of high-efficacy therapy were analyzed in covariate-adjusted statistical models., Results: By categorical analysis, in patients with IgM IF the median time to first relapse was 28 months shorter and MSSS on average higher by 1.11 steps compared with patients without intrathecal immunoglobulin synthesis. Moreover, patients with IgM IF had higher sNfL concentrations, more new/enlarging T2w lesions, and higher total T2w lesion counts (all p ≤ 0.01). These associations were absent or equally smaller in patients who were positive for only OCGB or OCGB/IgG IF . Furthermore, quantitative analyses revealed that in patients with IgM IF  ≥ median, the time to first relapse and to initiation of high-efficacy therapy was shorter by 32 and by 203 months, respectively (both p < 0.01), in comparison to patients with IgM IF  < median. Dose-dependent associations were also found for IgM IF but not for IgG IF with magnetic resonance imaging-defined disease activity and sNfL., Interpretation: This large study supports the value of intrathecal IgM synthesis as an independent biomarker of disease activity and severity in relapsing MS. ANN NEUROL 2021;90:477-489., (© 2021 The Authors. Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Recent evidence indicates that both cardiovascular fitness and gross motor skill performance are related to enhanced neurocognitive functioning in children by influencing brain structure and functioning. This study investigates the role of white matter microstructure in the relationship of both cardiovascular fitness and gross motor skills with neurocognitive functioning in healthy children. In total 92 children (mean age 9.1 years, range 8.0-10.7) were included in this study. Cardiovascular fitness and gross motor skill performance were assessed using performance-based tests. Neurocognitive functioning was assessed using computerized tests (working memory, inhibition, interference control, information processing, and attention). Diffusion tensor imaging was used in combination with tract-based spatial statistics to assess white matter microstructure as defined by fractional anisotropy (FA), axial and radial diffusivity (AD, RD). The results revealed positive associations of both cardiovascular fitness and gross motor skills with neurocognitive functioning. Information processing and motor response inhibition were associated with FA in a cluster located in the corpus callosum. Within this cluster, higher cardiovascular fitness and better gross motor skills were both associated with greater FA, greater AD, and lower RD. No mediating role was found for FA in the relationship of both cardiovascular fitness and gross motor skills with neurocognitive functioning. The results indicate that cardiovascular fitness and gross motor skills are related to neurocognitive functioning as well as white matter microstructure in children. However, this study provides no evidence for a mediating role of white matter microstructure in these relationships., (© 2021 The Authors. Journal of Neuroscience Research published by Wiley Periodicals LLC.)

This review article summarizes the clinical applications of established and emerging PET tracers in the evaluation of the 5 most common gynecologic malignancies: endometrial, ovarian, cervical, vaginal, and vulvar cancers. Emphasis is given to 2-deoxy-2-[ 18 F]fluoro-d-glucose as the most widely used and studied tracer, with additional clinical tracers also explored. The common imaging protocols are discussed, including standard dose ranges and uptake times, established roles, as well as the challenges and future directions of these imaging techniques. The key points are emphasized with images from selected cases., Competing Interests: Disclosure The authors have nothing to disclose., (Copyright © 2021 Elsevier Inc. All rights reserved.)

PET/MR imaging is in routine clinical use and is at least as effective as PET/CT for oncologic and neurologic studies with advantages with certain PET radiopharmaceuticals and applications. In addition, whole body PET/MR imaging substantially reduces radiation dosages compared with PET/CT which is particularly relevant to pediatric and young adult population. For cancer imaging, assessment of hepatic, pelvic, and soft-tissue malignancies may benefit from PET/MR imaging. For neurologic imaging, volumetric brain MR imaging can detect regional volume loss relevant to cognitive impairment and epilepsy. In addition, the single-bed position acquisition enables dynamic brain PET imaging without extending the total study length which has the potential to enhance the diagnostic information from PET., Competing Interests: Disclosure F. Moradi has nothing to disclose. A. Iagaru disclosed receiving consulting and research support from GE Healthcare, Progenics, and Novartis and consulting fee from ITM. J. McConathy disclosed receiving consulting and research support from GE Healthcare, Blue Earth Diagnostics, and Eli Lilly/Avid Radiopharmaceuticals., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Neuroplasticity refers to the fact that our brain can partially modify both structure and function to adequately respond to novel environmental stimulations. Neuroplasticity mechanisms are not only operating during the acquisition of novel information (i.e., online) but also during the offline periods that take place after the end of the actual learning episode. Structural brain changes as a consequence of learning have been consistently demonstrated on the long term using non-invasive neuroimaging methods, but short-term changes remained more elusive. Fortunately, the swift development of advanced MR methods over the last decade now allows tracking fine-grained cerebral changes on short timescales beyond gross volumetric modifications stretching over several days or weeks. Besides a mere effect of time, post-learning sleep mechanisms have been shown to play an important role in memory consolidation and promote long-lasting changes in neural networks. Sleep was shown to contribute to structural modifications over weeks of prolonged training, but studies evidencing more rapid post-training sleep structural effects linked to memory consolidation are still scarce in human. On the other hand, animal studies convincingly show how sleep might modulate synaptic microstructure. We aim here at reviewing the literature establishing a link between different types of training/learning and the resulting structural changes, with an emphasis on the role of post-training sleep and time in tuning these modifications. Open questions are raised such as the role of post-learning sleep in macrostructural changes, the links between different MR structural measurement-related modifications and the underlying microstructural brain processes, and bidirectional influences between structural and functional brain changes., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Olfactory dysfunction (OD) is more common than hearing loss, partial blindness, or blindness and can have a significant impact on the quality of life. Moreover, unexplained OD is an early biomarker in neurodegenerative diseases and increases 5-year mortality risk. Structural alterations in olfactory eloquent brain regions may represent the neuroanatomical correlates of OD. Previous studies have demonstrated reduced gray matter (GM) volume in areas of presumed olfactory relevance in patients with OD. However, being cross-sectional in nature, these studies do not provide evidence of causality, for which longitudinal work is required. At present, however, longitudinal studies addressing olfactory structural plasticity are limited, both in number and methodological approach: to our knowledge, such work has not included parallel functional imaging to confirm the relevance of structural change. We therefore performed a longitudinal multimodal neuroimaging study investigating structural and functional plasticity in 24 patients undergoing surgical treatment for chronic rhinosinusitis, compared with 17 healthy controls. We demonstrated functionally significant structural plasticity within the orbitofrontal, anterior cingulate and insular cortices, and temporal poles in patients 3 months after surgery. Of interest, GM volume decreased in these regions, in association with increased psychophysical scores and BOLD signal. To our knowledge, this is the first study to demonstrate both structural and functional plasticity of the central olfactory networks, thereby confirming these areas as neuroanatomical correlates of olfactory function/dysfunction., (© 2021 The Authors. Journal of Neuroscience Research published by Wiley Periodicals LLC.)

The combination of transcranial direct current stimulation (tDCS) with functional magnetic resonance imaging (fMRI) can provide original data to investigate age-related brain changes. We examined neural activity modulations induced by two multifocal tDCS procedures based on two distinct montages fitting two N-back task-based fMRI patterns ("compensatory" and "maintenance") related to high working memory (WM) in a previous publication (Fernández-Cabello et al. Neurobiol Aging (2016);48:23-33). We included 24 participants classified as stable or decliners according to their 4-year WM trajectories following a retrospective longitudinal approach. Then, we studied longitudinal fMRI differences between groups (stable and decliners) and across multifocal tDCS montages ("compensatory" and "maintenance") applied using a single-blind sham-controlled cross-over design. Decliners evidenced over-activation of non-related WM areas after 4 years of follow-up. Focusing on tDCS effects, among the decliner group, the "compensatory"-tDCS montage reduced the activity over the posterior regions where these subjects showed longitudinal hyperactivation. These results reinforce the notion that tDCS effects are characterized by an activity reduction and might be more noticeable in compromised systems. Importantly, the data provide novel evidence that cognitive trajectories predict tDCS effects in older adults., (© 2021 Wiley Periodicals, Inc.)

Background: The combinatorial effect of multiple genetic factors calculated as a polygenic risk score (PRS) has been studied to predict disease progression to Alzheimer's disease (AD) from mild cognitive impairment (MCI). Previous studies have investigated the performance of PRS in the prediction of disease progression to AD by including and excluding single nucleotide polymorphisms within the region surrounding the APOE gene. These studies may have missed the APOE genotype-specific predictability of PRS for disease progression to AD., Methods: We analyzed 732 MCI from the Alzheimer's Disease Neuroimaging Initiative cohort, including those who progressed to AD within 5 years post-baseline (n = 270) and remained stable as MCI (n = 462). The predictability of PRS including and excluding the APOE region (PRS +APOE and PRS -APOE ) on the conversion to AD and its interaction with the APOE ε4 carrier status were assessed using Cox regression analyses., Results: PRS +APOE (hazard ratio [HR] 1.468, 95% CI 1.335-1.615) and PRS -APOE (HR 1.293, 95% CI 1.157-1.445) were both associated with a significantly increased risk of MCI progression to dementia. The interaction between PRS +APOE and APOE ε4 carrier status was significant with a P-value of 0.0378. The association of PRSs with the progression risk was stronger in APOE ε4 non-carriers (PRS +APOE : HR 1.710, 95% CI 1.244-2.351; PRS -APOE : HR 1.429, 95% CI 1.182-1.728) than in APOE ε4 carriers (PRS +APOE : HR 1.167, 95% CI 1.005-1.355; PRS -APOE : HR 1.172, 95% CI 1.020-1.346)., Conclusions: PRS could predict the conversion of MCI to dementia with a stronger association in APOE ε4 non-carriers than APOE ε4 carriers. This indicates PRS as a potential genetic predictor particularly for MCI with no APOE ε4 alleles., (© 2021. The Author(s).)

Smart theranostics are dynamic platforms that integrate multiple functions, including at least imaging, therapy, and responsiveness, in a single agent. This review showcases a variety of responsive theranostic agents developed specifically for magnetic resonance imaging (MRI), due to the privileged position this non-invasive, non-ionising imaging modality continues to hold within the clinical imaging field. Different MRI smart theranostic designs have been devised in the search for more efficient cancer therapy, and improved diagnostic efficiency, through the increase of the local concentration of therapeutic effectors and MRI signal intensity in pathological tissues. This review explores novel small-molecule and nanosized MRI theranostic agents for cancer that exhibit responsiveness to endogenous (change in pH, redox environment, or enzymes) or exogenous (temperature, ultrasound, or light) stimuli. The challenges and obstacles in the design and in vivo application of responsive theranostics are also discussed to guide future research in this interdisciplinary field towards more controllable, efficient, and diagnostically relevant smart theranostics agents., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

The central role of MRI in neuro-oncology is undisputed. The technique is used, both in clinical practice and in clinical trials, to diagnose and monitor disease activity, support treatment decision-making, guide the use of focused treatments and determine response to treatment. Despite recent substantial advances in imaging technology and image analysis techniques, clinical MRI is still primarily used for the qualitative subjective interpretation of macrostructural features, as opposed to quantitative analyses that take into consideration multiple pathophysiological features. However, the field of quantitative imaging and imaging biomarker development is maturing. The European Imaging Biomarkers Alliance (EIBALL) and Quantitative Imaging Biomarkers Alliance (QIBA) are setting standards for biomarker development, validation and implementation, as well as promoting the use of quantitative imaging and imaging biomarkers by demonstrating their clinical value. In parallel, advanced imaging techniques are reaching the clinical arena, providing quantitative, commonly physiological imaging parameters that are driving the discovery, validation and implementation of quantitative imaging and imaging biomarkers in the clinical routine. Additionally, computational analysis techniques are increasingly being used in the research setting to convert medical images into objective high-dimensional data and define radiomic signatures of disease states. Here, I review the definition and current state of MRI biomarkers in neuro-oncology, and discuss the clinical potential of quantitative image analysis techniques., (© 2021. Springer Nature Limited.)

Objective : The purpose of our study was to distinguish the changes in the microstructure of the cingulate cortex in patients with mild cognitive impairment (MCI) induced by cerebral small vessel disease (CSVD). Method: 80 patients were diagnosed with CSVD in this study, including 55 patients with MCI and 25 patients without MCI. Diffusion kurtosis imaging (DKI) and Montreal cognitive assessment (MoCA) were performed in all patients. The anterior cingulate gyrus, posterior cingulate gyrus and middle cingulate gyrus were selected as the regions of interest, and some parameters were recorded. Results: Compared with the non-MCI group, the MCI group mainly showed obviously higher mean diffusion (MD) and radial diffusion (RD) values ( P = 0.022 and P = 0.029) but lower fractional anisotropy (FA), axial kurtosis (AK), mean kurtosis (MK) and radial kurtosis (RK) values ( P = 0.047, P = 0.001, P < 0.01, and P = 0.001, respectively) in the right anterior cingulate gyrus. Meanwhile, in the right posterior cingulate gyrus, the MCI group also showed higher axial diffusion (AD) and MD ( P = 0.027 and P = 0.030) and lower AK ( P = 0.014). Additionally, negative correlations of AD, MD, and RD with MoCA scores and positive correlations of FA, AK, MK and RK with MoCA scores were observed in some regions of the cingulate gyrus. Conclusions: DKI is a good method to examine microstructural damage in the cingulate cortex, and some parameters of DKI may be used as imaging biomarkers to detect early MCI in patients with CSVD.

Objective: In vivo measures of myeloid activity are promising biomarkers in multiple sclerosis. We previously demonstrated that cerebrospinal fluid (CSF) myeloid microvesicles are markers of microglial/macrophage activity and neuroinflammation in multiple sclerosis. Here, we aimed at investigating the diagnostic and prognostic value of myeloid microvesicles in a clinical setting., Methods: Six hundred one patients discharged with a diagnosis of neuroinflammatory, neurodegenerative, or no neurological disease were enrolled. Myeloid microvesicles were measured with flow cytometry as isolectin B4-positive events in fresh CSF. Clinical, demographical, and magnetic resonance imaging (MRI) data were collected at diagnosis (all patients) and during follow-up (n = 176)., Results: CSF myeloid microvesicles were elevated in neuroinflammatory patients compared to the neurodegenerative and control groups. In multiple sclerosis, microvesicles were higher in patients with MRI disease activity and their concentration increased along with the number of enhancing lesions (p < 0.0001, Jonckheere-Terpstra test). CSF myeloid microvesicles were also higher in patients with higher disease activity in the month and year preceding diagnosis. Microvesicles excellently discriminated between the relapsing-remitting and control groups (receiver operator characteristic curve, area under the curve = 0.939, p < 0.0001) and between radiologically isolated syndrome and unspecific brain lesions (0.942, p < 0.0001). Furthermore, microvesicles were independent predictors of prognosis for both the relapsing-remitting and progressive groups. Microvesicles independently predicted future disease activity in relapsing-remitting patients (hazard ratio [HR] = 1.967, 95% confidence interval [CI] = 1.147-3.372), correcting for prognostic factors of standard clinical use. In the progressive group, microvesicles were independent predictors of disability accrual (HR = 10.767, 95% CI = 1.335-86.812)., Interpretation: Our results confirm that CSF myeloid microvesicles are a clinically meaningful biomarker of neuroinflammation and microglial/macrophage activity in vivo. These findings may support a possible use in clinical practice during diagnostic workup and prognostic assessment. ANN NEUROL 2021;90:253-265., (© 2021 American Neurological Association.)

Maternal childhood maltreatment and depression increase risks for the psychopathology of the offspring. This study employed a longitudinal dataset of mother-child dyads to investigate the developmental trajectories of brain functional networks and behaviors of children in relation with maternal childhood adverse experience and depression. Maternal childhood trauma was retrospectively assessed via childhood trauma questionnaire, whereas maternal depressive symptoms were prospectively evaluated during pregnancy and after delivery (n = 518). Child brain scans were acquired at age of 4.5, 6, and 7.5 years (n = 163) and behavioral problems were measured at 7.5 years using the Child Behavior Checklist. We found the functional connectivity of the language network with the sensorimotor, frontal, and attentional networks as a function of maternal adverse experience that interacted with sex and age. Girls exposed to mothers with depressive symptoms or childhood abuse showed the increased development of the functional connectivity of the language network with the visual networks, which was associated with social problems. Girls exposed to mothers with depressive symptoms showed the slower growth of the functional connectivity of the language network with the sensorimotor networks. Our findings, in a community sample, suggest the language network organization as neuroendophenotypes for maternal childhood trauma and depression., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Ultra-high-field functional magnetic resonance imaging (fMRI) offers a way to new insights while increasing the spatial and temporal resolution. However, a crucial concern in 7T human MRI is the increase in power deposition, supervised through the specific absorption rate (SAR). The SAR limitation can restrict the brain coverage or the minimal repetition time of fMRI experiments. In the majority of today's studies fMRI relies on the well-known gradient-echo echo-planar imaging (GRE-EPI) sequence, which offers ultrafast acquisition. Commonly, the GRE-EPI sequence comprises two pulses: fat suppression and excitation. This work provides the means for a significant reduction in the SAR by circumventing the fat-suppression pulse. Without this fat-suppression, however, lipid signal can result in artifacts due to the chemical shift between the lipid and water signals. Our approach exploits a reconstruction similar to the simultaneous-multi-slice method to separate the lipid and water images, thus avoiding undesired lipid artifacts in brain images. The lipid-water separation is based on the known spatial shift of the lipid signal, which can be detected by the multi-channel coils sensitivity profiles. Our study shows robust human imaging, offering greater flexibility to reduce the SAR, shorten the repetition time or increase the volume coverage with substantial benefit for brain functional studies., (© 2021. The Author(s).)

Objective: To assess whether ictal electric source imaging (ESI) on low-density scalp EEG can approximate the seizure onset zone (SOZ) location and predict surgical outcome in children with refractory epilepsy undergoing surgery., Methods: We examined 35 children with refractory epilepsy. We dichotomized surgical outcome into seizure- and non-seizure-free. We identified ictal onsets recorded with scalp and intracranial EEG and localized them using equivalent current dipoles and standardized low-resolution magnetic tomography (sLORETA). We estimated the localization accuracy of scalp EEG as distance of scalp dipoles from intracranial dipoles. We also calculated the distances of scalp dipoles from resection, as well as their resection percentage and compared between seizure-free and non-seizure-free patients. We built receiver operating characteristic curves to test whether resection percentage predicted outcome., Results: Resection distance was lower in seizure-free patients for both dipoles (p = 0.006) and sLORETA (p = 0.04). Resection percentage predicted outcome with a sensitivity of 57.1% (95% CI, 34-78.2%), a specificity of 85.7% (95% CI, 57.2-98.2%) and an accuracy of 68.6% (95% CI, 50.7-83.5%) (p = 0.01)., Conclusion: Ictal ESI performed on low-density scalp EEG can delineate the SOZ and predict outcome., Significance: Such an application may increase the number of children who are referred for epilepsy surgery and improve their outcome., Competing Interests: Conflict of interest None of the authors have potential conflict of interest to be disclosed. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate of high-grade glioma is poor. Magnetic resonance imaging (MRI) is essential for detecting, characterizing and monitoring brain tumors but definitive diagnosis still relies on surgical pathology. Machine learning has been applied to the analysis of MRI data in glioma research and has the potential to change clinical practice and improve patient outcomes. This systematic review synthesizes and analyzes the current state of machine learning applications to glioma MRI data and explores the use of machine learning for systematic review automation. Various datapoints were extracted from the 153 studies that met inclusion criteria and analyzed. Natural language processing (NLP) analysis involved keyword extraction, topic modeling and document classification. Machine learning has been applied to tumor grading and diagnosis, tumor segmentation, non-invasive genomic biomarker identification, detection of progression and patient survival prediction. Model performance was generally strong (AUC = 0.87 ± 0.09; sensitivity = 0.87 ± 0.10; specificity = 0.0.86 ± 0.10; precision = 0.88 ± 0.11). Convolutional neural network, support vector machine and random forest algorithms were top performers. Deep learning document classifiers yielded acceptable performance (mean 5-fold cross-validation AUC = 0.71). Machine learning tools and data resources were synthesized and summarized to facilitate future research. Machine learning has been widely applied to the processing of MRI data in glioma research and has demonstrated substantial utility. NLP and transfer learning resources enabled the successful development of a replicable method for automating the systematic review article screening process, which has potential for shortening the time from discovery to clinical application in medicine., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Isoflurane, the most commonly used preclinical anesthetic, induces brain plasticity and long-term cellular and molecular changes leading to behavioral and/or cognitive consequences. These changes are most likely associated with network-level changes in brain function. To elucidate the mechanisms underlying long-term effects of isoflurane, we investigated the influence of a single isoflurane exposure on functional connectivity, brain electrical activity, and gene expression. Male Wistar rats (n = 22) were exposed to 1.8% isoflurane for 3 h. Control rats (n = 22) spent 3 h in the same room without exposure to anesthesia. After 1 month, functional connectivity was evaluated with resting-state functional magnetic resonance imaging (fMRI; n = 6 + 6) and local field potential measurements (n = 6 + 6) in anesthetized animals. A whole genome expression analysis (n = 10+10) was also conducted with mRNA-sequencing from cortical and hippocampal tissue samples. Isoflurane treatment strengthened thalamo-cortical and hippocampal-cortical functional connectivity. Cortical low-frequency fMRI power was also significantly increased in response to the isoflurane treatment. The local field potential results indicating strengthened hippocampal-cortical alpha and beta coherence were in good agreement with the fMRI findings. Furthermore, altered expression was found in 20 cortical genes, several of which are involved in neuronal signal transmission, but no gene expression changes were noted in the hippocampus. Isoflurane induced prolonged changes in thalamo-cortical and hippocampal-cortical function and expression of genes contributing to signal transmission in the cortex. Further studies are required to investigate whether these changes are associated with the postoperative behavioral and cognitive symptoms commonly observed in patients and animals., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)

Background and Purpose: Clot fragmentation and distal embolization during endovascular thrombectomy for acute ischemic stroke may produce emboli downstream of the target occlusion or in previously uninvolved territories. Susceptibility-weighted magnetic resonance imaging can identify both emboli to distal territories (EDT) and new territories (ENT) as new susceptibility vessel signs (SVS). Diffusion-weighted imaging (DWI) can identify infarcts in new territories (INT)., Methods: We studied consecutive acute ischemic stroke patients undergoing magnetic resonance imaging before and after thrombectomy. Frequency, predictors, and outcomes of EDT and ENT detected on gradient-recalled echo imaging (EDT-SVS and ENT-SVS) and INT detected on DWI (INT-DWI) were analyzed., Results: Among 50 thrombectomy-treated acute ischemic stroke patients meeting study criteria, mean age was 70 (±16) years, 44% were women, and presenting National Institutes of Health Stroke Scale score 15 (interquartile range, 8–19). Overall, 21 of 50 (42%) patients showed periprocedural embolic events, including 10 of 50 (20%) with new EDT-SVS, 10 of 50 (20%) with INT-DWI, and 1 of 50 (2%) with both. No patient showed ENT-SVS. On multivariate analysis, model-selected predictors of EDT-SVS were lower initial diastolic blood pressure (odds ratio, 1.09 [95% CI, 1.02–1.16]), alteplase pretreatment (odds ratio, 5.54 [95% CI, 0.94–32.49]), and atrial fibrillation (odds ratio, 7.38 [95% CI, 1.02–53.32]). Classification tree analysis identified pretreatment target occlusion SVS as an additional predictor. On univariate analysis, INT-DWI was less common with internal carotid artery (5%), intermediate with middle cerebral artery (25%), and highest with vertebrobasilar (57%) target occlusions (P=0.02). EDT-SVS was not associated with imaging/functional outcomes, but INT-DWI was associated with reduced radiological hemorrhagic transformation (0% versus 54%; P<0.01)., Conclusions: Among acute ischemic stroke patients treated with thrombectomy, imaging evidence of distal emboli, including EDT-SVS beyond the target occlusion and INT-DWI in novel territories, occur in about 2 in every 5 cases. Predictors of EDT-SVS are pretreatment intravenous fibrinolysis, potentially disrupting thrombus structural integrity; atrial fibrillation, possibly reflecting larger target thrombus burden; lower diastolic blood pressure, suggestive of impaired embolic washout; and pretreatment target occlusion SVS sign, indicating erythrocyte-rich, friable target thrombus.

Deep brain stimulation (DBS), specifically thalamic DBS, has achieved promising results to reduce seizure severity and frequency in pharmacoresistant epilepsies, thereby establishing it for clinical use. The mechanisms of action are, however, still unknown. We evidenced the brain networks directly modulated by centromedian (CM) nucleus-DBS and responsible for clinical outcomes in a cohort of patients uniquely diagnosed with generalized pharmacoresistant epilepsy. Preoperative imaging and long-term (2-11 years) clinical data from ten generalized pharmacoresistant epilepsy patients (mean age at surgery = 30.8 ± 5.9 years, 4 female) were evaluated. Volume of tissue activated (VTA) was included as seeds to reconstruct the targeted network to thalamic DBS from diffusion and functional imaging data. CM-DBS clinical outcome improvement (> 50%) appeared in 80% of patients and was tightly related to VTAs interconnected with a reticular system network encompassing sensorimotor and supplementary motor cortices, together with cerebellum/brainstem. Despite methodological differences, both structural and functional connectomes revealed the same targeted network. Our results demonstrate that CM-DBS outcome in generalized pharmacoresistant epilepsy is highly dependent on the individual connectivity profile, involving the cerebello-thalamo-cortical circuits. The proposed framework could be implemented in future studies to refine stereotactic implantation or the parameters for individualized neuromodulation., (© 2021. The Author(s).)

Effective anticoagulation status may determine the recanalization and outcome of cerebral venous thrombosis (CVT). We report impact of anticoagulation status on recanalization and outcome of CVT. This is a retrospective study on 126 patients with CVT diagnosed on magnetic resonance venography (MRV). Their clinical features and risk factors were noted. The data were retrieved from a prospectively maintained registry, and international normalized ratio (INR) was noted after discharge till 3 months. All the patients were on acenocoumarol. Based on INR value, patients were categorized as Group A (effective anticoagulation INR within the therapeutic range or above) and Group B (ineffective anticoagulation INR > 50% below the therapeutic range). A repeat MRV at 3 months was done for recanalization. Outcome at 3 months was evaluated using modified Rankin Scale (mRS), and categorized as good (mRS ≤ 2) and poor (mRS 2 or more) 101(80.2%) patients were in group A and 25(19.8%) in group B. Their demographic, risk factors, magnetic resonance imaging (MRI) and MRV findings were comparable. On repeat MRV, recanalization occurred in 22/24(91.7%); 15(88%) in group A and 7(100%) in group B. Recanalization was independent of coagulation status. Seven (5.6%) patients died and 107(84.9%) had good outcome; 85(84.2%) in group A and 22(88%) in group B. Kaplan Meier analysis also did not reveal survival or good outcome benefits between the groups. In CVT, outcome and recanalization at 3 months are not dependent on coagulation status. Further prospective studies are needed regarding duration of anticoagulant and its impact on recanalization and outcome., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objectives: To investigate the aetiology of acute-onset binocular diplopia (AOBD) in neurological units and identify the key diagnostic procedures in this setting., Materials and Methods: Clinico-demographic data from patients hospitalized for AOBD from 2008 to 2019 were retrospectively reviewed. AOBD due to an underlying neurological disorder known to cause diplopia was addressed as secondary diplopia. Ophthalmoparesis plus was defined when subtle neurological signs/symptoms other than ophthalmoparesis were detected during neurological examination., Results: A total of 171 patients (mean age 57.6 years) were included in the study. A total of 89 subjects (52%) had an oculomotor disturbance consistent with sixth nerve palsy, and 42 (24.6%) showed multiple oculomotor nerve involvement. The most common cause of AOBD was presumed to be microvascular in 56 patients (32.7%), while a secondary aetiology was identified in 102 (59.6%). Ophthalmoparesis plus and multiple oculomotor nerve involvement significantly predicted a secondary aetiology in multivariable logistic regression analysis. Brain CT was never diagnostic in isolated ophthalmoparesis. A combination of neuroimaging examinations established AOBD diagnosis in 54.9% of subjects, whereas rachicentesis and neurophysiological examinations were found to be performant in the remaining cases., Conclusions: AOBD may herald insidious neurological disease, and an extensive diagnostic workup is often needed to establish a diagnosis. Neurological examination was pivotal in identifying patients at higher risk of secondary aetiology. Even in cases of apparently benign presentation, a serious underlying disease cannot be excluded. Brain MRI was found to perform well in all clinical scenarios, and it should be always considered when managing AOBD., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)