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The growing use of artificial neural network (ANN) tools for computed tomography angiography (CTA) data analysis underscores the necessity for elevated data protection measures. We aimed to establish an automated defacing pipeline for CTA data. In this retrospective study, CTA data from multi-institutional cohorts were utilized to annotate facemasks (n = 100) and train an ANN model, subsequently tested on an external institution's dataset (n = 50) and compared to a publicly available defacing algorithm. Face detection (MTCNN) and verification (FaceNet) networks were applied to measure the similarity between the original and defaced CTA images. Dice similarity coefficient (DSC), face detection probability, and face similarity measures were calculated to evaluate model performance. The CTA-DEFACE model effectively segmented soft face tissue in CTA data achieving a DSC of 0.94 ± 0.02 (mean ± standard deviation) on the test set. Our model was benchmarked against a publicly available defacing algorithm. After applying face detection and verification networks, our model showed substantially reduced face detection probability (p < 0.001) and similarity to the original CTA image (p < 0.001). The CTA-DEFACE model enabled robust and precise defacing of CTA data. The trained network is publicly accessible at www.github.com/neuroAI-HD/CTA-DEFACE. Relevance statement: The ANN model CTA-DEFACE, developed for automatic defacing of CT angiography images, achieves significantly lower face detection probabilities and greater dissimilarity from the original images compared to a publicly available model. The algorithm has been externally validated and is publicly accessible. Key Points: The developed ANN model (CTA-DEFACE) automatically generates facemasks for CT angiography images. CTA-DEFACE offers superior deidentification capabilities compared to a publicly available model. By means of graphics processing unit optimization, our model ensures rapid processing of medical images. Our model underwent external validation, underscoring its reliability for real-world application. [ABSTRACT FROM AUTHOR]

Objective: The piriform cortex is considered to be highly epileptogenic. Its resection during epilepsy surgery is a predictor for postoperative seizure freedom in temporal lobe epilepsy. Epilepsy is associated with a dysfunction of the blood–brain barrier. We investigated blood–brain barrier dysfunction in the piriform cortex of people with temporal lobe epilepsy using quantitative T1‐relaxometry. Methods: Gadolinium‐based contrast agent was administered ictally and interictally in 37 individuals before undergoing quantitative T1‐relaxometry. Postictal and interictal images were co‐registered, and subtraction maps were created as biomarkers for peri‐ictal (∆qT1interictal‐postictal) and interictal (∆qT1noncontrast‐interictal) blood–brain barrier dysfunction. Values were extracted for the piriform cortex, hippocampus, amygdala, and the whole cortex. Results: In temporal lobe epilepsy (n = 14), ∆qT1noncontrast‐interictal was significantly higher in the piriform cortex than in the whole cortex (p = 0.02). In extratemporal lobe epilepsy (n = 23), ∆qT1noncontrast‐interictal was higher in the hippocampus than in the whole cortex (p = 0.05). Across all individuals (n = 37), duration of epilepsy was correlated with ∆qT1noncontrast‐interictal (ß = 0.001, p < 0.001) in all regions, while the association was strongest in the piriform cortex. Impaired verbal memory was associated with ∆qT1noncontrast‐interictal only in the piriform cortex (p = 0.04). ∆qT1interictal‐postictal did not show differences in any region. Interpretation: Interictal blood–brain barrier dysfunction occurs in the piriform cortex in temporal lobe epilepsy. This dysfunction is linked to longer disease duration and worse cognitive deficits, emphasizing the central role of the piriform cortex in the epileptogenic network of temporal lobe epilepsy. [ABSTRACT FROM AUTHOR]

Background Subarachnoid hyperdensities after mechanical thrombectomy (MT) are a common finding. However, it is often regarded as clinically insignificant. Objective With this single-center investigation, to identify the prevalence of subarachnoid hyperdensities following MT, associated predictors, and the impact on the clinical outcome of the patients. Methods 383 patients from the stroke registry were analyzed for the presence of subarachnoid hyperdensities on flat detector CT (FDCT) directly after the completion of MT, and on follow-up dual-energy CT, then classified according to a visual grading scale. 178 patients were included with anterior circulation occlusions. Regression analysis was performed to identify significant predictors, and Kruskal-Wallis analysis and X² test were performed to test the variables among the different groups. The primary outcome was the modified Rankin Scale (mRS) score at 90 days and was analyzed with the Wilcoxon-Mann-Whitney rank-sum test. Results The prevalence of subarachnoid hyperdensities on FDCT was (66/178, 37.1%) with patients experiencing a significant unfavorable outcome (P=0.035). Significantly fewer patients with subarachnoid hyperdensities achieved a mRS score of ≤3 at 90 days 25/66 (37.9%) vs 60/1 12 (53.6%), P=0.043). In addition, mortality was significantly higher in the subarachnoid hyperdensities group (34.8% vs 19.6%, P=0.024). Distal occlusions and a higher number of device passes were significantly associated with subarachnoid hyperdensities (P=0.026) and (P=0.001), respectively. Patients who received intravenous tissue plasminogen activator had significantly fewer subarachnoid hyperdensities (P=0.029). Conclusions Postinterventional subarachnoid hyperdensities are a frequent finding after MT and are associated with neurological decline and worse functional outcome. They are more common with distal occlusions and multiple device passes. [ABSTRACT FROM AUTHOR]

Over the last decade, it has become evident that cerebrospinal fluid (CSF) plays a pivotal role in brain solute clearance through perivascular pathways and interactions between the brain and meningeal lymphatic vessels. Whereas most of this fundamental knowledge was gained from rodent models, human brain clearance imaging has provided important insights into the human system and highlighted the existence of important interspecies differences. Current gold standard techniques for human brain clearance imaging involve the injection of gadolinium‐based contrast agents and monitoring their distribution and clearance over a period from a few hours up to 2 days. With both intrathecal and intravenous injections being used, which each have their own specific routes of distribution and thus clearance of contrast agent, a clear understanding of the kinetics associated with both approaches, and especially the differences between them, is needed to properly interpret the results. Because it is known that intrathecally injected contrast agent reaches the blood, albeit in small concentrations, and that similarly some of the intravenously injected agent can be detected in CSF, both pathways are connected and will, in theory, reach the same compartments. However, because of clear differences in relative enhancement patterns, both injection approaches will result in varying sensitivities for assessment of different subparts of the brain clearance system. In this opinion review article, the "EU Joint Programme – Neurodegenerative Disease Research (JPND)" consortium on human brain clearance imaging provides an overview of contrast agent pharmacokinetics in vivo following intrathecal and intravenous injections and what typical concentrations and concentration–time curves should be expected. This can be the basis for optimizing and interpreting contrast‐enhanced MRI for brain clearance imaging. Furthermore, this can shed light on how molecules may exchange between blood, brain, and CSF. [ABSTRACT FROM AUTHOR]

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer's disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < −0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment. [ABSTRACT FROM AUTHOR]

A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations. Twenty-two patients were included retrospectively, consisting of eleven patients with Huntington's disease and caudate nucleus atrophy and an age- and sex-matched control group. To quantify caudate head atrophy, the frontal horn width to intercaudate distance ratio and the intercaudate distance to inner table width ratio were obtained. The software mdbrain was used for automated volumetry. Manually measured ratios and automatically measured volumes of the groups were compared using two-sample t-tests. Pearson correlation analyses were performed. The relative difference between automatically and manually determined volumes of the caudate nuclei was calculated. Both ratios were significantly different between the groups. The automatically and manually determined volumes of the caudate nuclei showed a high level of agreement with a mean relative discrepancy of − 2.3 ± 5.5%. The Huntington's disease group showed significantly lower volumes in a variety of supratentorial brain structures. The highest degree of atrophy was shown for the caudate nucleus, putamen, and pallidum (all p <.0001). The caudate nucleus volume and the ratios were found to be strongly correlated in both groups. In conclusion, in patients with progressed Huntington's disease, it was shown that the automatically determined caudate nucleus volume correlates strongly with measured ratios commonly used in clinical practice. Both methods allowed clear differentiation between groups in this collective. The software additionally allows radiologists to more objectively assess the involvement of a variety of brain structures that are less accessible to standard semiquantitative methods. [ABSTRACT FROM AUTHOR]

Introduction: Physical activity influences psychological well-being. This study aimed to determine the impact of exercise intensity on psychological well-being and alterations in emotion-related brain functional connectivity (FC). Methods: Twenty young, healthy, trained athletes performed a low- and highintensity interval exercise (LIIE and HIIE) as well as a control condition in a within-subject crossover design. Before and after each condition, Positive And Negative Affect Scale (PANAS) was assessed as well as resting-state functional MRI (rs-fMRI). Voxel-wise FC was examined for bilateral amygdala seed region to whole-brain and emotion-related anatomical regions (e.g., insula, temporal pole, precuneus). Data analyses were performed using linear mixed-effect models with fixed factors condition and time. Results: The PANAS Positive Affect scale showed a significant increase after LIIE and HIIE and a significant reduction in Negative Affect after the control condition. In rs-fMRI, no significant condition-by-time interactions were observed between the amygdala and whole brain. Amygdala-precuneus FC analysis showed an interaction effect, suggesting reduced post-exercise anticorrelation after the control condition, but stable, or even slightly enhanced anticorrelation for the exercise conditions, especially HIIE. Discussion: In conclusion, both LIIE and HIIE had positive effects on mood and concomitant effects on amygdala-precuneus FC, particularly after HIIE. Although no significant correlations were found between amygdala-precuneus FC and PANAS, results should be discussed in the context of affective disorders in whom abnormal amygdala-precuneus FC has been observed. [ABSTRACT FROM AUTHOR]

Temporal discounting, the tendency to devalue future rewards as a function of delay until receipt, is influenced by time framing. Specifically, discount rates are shallower when the time at which the reward is received is presented as a date (date condition; e.g., June 8, 2023) rather than in delay units (delay condition; e.g., 30 days), which is commonly referred to as the date/delay effect. However, the cognitive and neural mechanisms of this effect are not well understood. Here, we examined the date/delay effect by analysing combined fMRI and eye‐tracking data of N = 31 participants completing a temporal discounting task in both a delay and a date condition. The results confirmed the date/delay effect and revealed that the date condition led to higher fixation durations on time attributes and to higher activity in precuneus/PCC and angular gyrus, that is, areas previously associated with episodic thinking. Additionally, participants made more comparative eye movements in the date compared to the delay condition. A lower date/delay effect was associated with higher prefrontal activity in the date > delay contrast, suggesting that higher control or arithmetic operations may reduce the date/delay effect. Our findings are in line with hypotheses positing that the date condition is associated with differential time estimation and the use of more comparative as opposed to integrative choice strategies. Specifically, higher activity in memory‐related brain areas suggests that the date condition leads to higher perceived proximity of delayed rewards, while higher frontal activity (middle/superior frontal gyrus, posterior medial frontal cortex, cingulate) in participants with a lower date/delay effect suggests that the effect is particularly pronounced in participants avoiding complex arithmetic operations in the date condition. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance High‐field magnetic resonance imaging (MRI) is a standard in the diagnosis of epilepsy. However, high costs and technical barriers have limited adoption in low‐ and middle‐income countries. Even in high‐income nations, many individuals with epilepsy face delays in undergoing MRI. Recent advancements in ultra‐low‐field (ULF) MRI technology, particularly the development of portable scanners, offer a promising solution to the limited accessibility of MRI. In this study, we present and evaluate the imaging capability of ULF MRI in detecting structural abnormalities typically associated with epilepsy and compare it to high‐field MRI at 3 T.Data collection was conducted within 3 consecutive weeks at the University Hospital Bonn. Inclusion criteria were a minimum age of 18 years, diagnosed epilepsy, and clinical high‐field MRI with abnormalities. We used a .064 T Swoop portable MR Imaging System. Both high‐field MRI and ULF MRI scans were evaluated independently by two experienced neuroradiologists as part of their clinical routine, comparing pathology detection and diagnosis completeness.Twenty‐three individuals with epilepsy were recruited. One subject presented with a dual pathology. Across the entire cohort, in 17 of 24 (71%) pathologies, an anomaly colocalizing with the actual lesion was observed on ULF MRI. For 11 of 24 (46%) pathologies, the full diagnosis could be made based on ULF MRI. Tumors and posttraumatic lesions could be diagnosed best on ULF MRI, whereas cortical dysplasia and other focal pathologies were the least well diagnosed.This single‐center series of individuals with epilepsy demonstrates the feasibility and utility of ULF MRI for the field of epileptology. Its integration into epilepsy care offers transformative potential, particularly in resource‐limited settings. Further research is needed to position ULF MRI within imaging modalities in the diagnosis of epilepsy. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation To assess whether arterial spin labeling perfusion images of healthy controls can enhance ictal single‐photon emission computed tomography analysis and whether the acquisition of the interictal image can be omitted.We developed 2 pipelines: The first uses ictal and interictal images and compares these to single‐photon emission computed tomography and arterial spin labeling of healthy controls. The second pipeline uses only the ictal image and the analogous healthy controls. Both pipelines were compared to the gold standard analysis and evaluated on data of individuals with epilepsy who underwent ictal single‐photon emission computed tomography imaging during presurgical evaluation between 2010 and 2022. Fifty healthy controls prospectively underwent arterial spin labeling imaging. The correspondence between the detected hyperperfusion and the postoperative resection cavity or the presumably affected lobe was assessed using Dice score and mean Euclidean distance. Additionally, the outcomes of the pipelines were automatically assigned to 1 of 5 concordance categories.Inclusion criteria were met by 43 individuals who underwent epilepsy surgery and by 73 non‐surgical individuals with epilepsy. Compared to the gold standard analysis, both pipelines resulted in significantly higher Dice scores and lower mean distances (p < 0.05). The combination of both provided localizing results in 85/116 cases, compared to 54/116 generated by the current gold standard analysis and the ictal image alone produced localizing results in 60/116 (52%) cases.We propose a new ictal single‐photon emission computed tomography protocol; it finds relevantly more ictal hyperperfusion, and halves the radiation dose in about half of the individuals. ANN NEUROL 2024 [ABSTRACT FROM AUTHOR]

The epileptogenic network in temporal lobe epilepsy (TLE) contains structures of the primary and secondary olfactory cortex such as the piriform and entorhinal cortex, the amygdala, and the hippocampus. Olfactory auras and olfactory dysfunction are relevant symptoms of TLE. This study aims to characterize olfactory function in TLE using olfactory testing and olfactory functional magnetic resonance imaging (fMRI). We prospectively enrolled 20 individuals with unilateral TLE (age 45 ± 20 years [mean ± SD], 65% female, 90% right-handed) and 20 healthy individuals (age 33 ± 15 years [mean ± SD], 35% female, 90% right-handed). In the TLE group, the presumed seizure onset zone was left-sided in 75%; in 45% of the individuals with TLE limbic encephalitis was the presumed etiology; and 15% of the individuals with TLE reported olfactory auras. Olfactory function was assessed with a Screening Sniffin' Sticks Test (Burkhart, Wedel, Germany) during a pre-assessment. During a pre-testing, all individuals were asked to rate the intensity, valence, familiarity, and associated memory of five different odors (eugenol, vanillin, phenethyl alcohol, decanoic acid, valeric acid) and a control solution. During the fMRI experiment, all individuals repeatedly smelled eugenol (positively valenced odor), valeric acid (negatively valenced odor), and the control solution and were asked to rate odor intensity on a five-point Likert scale. We acquired functional EPI sequences and structural images (T1, T2, FLAIR). Compared to healthy individuals, individuals with TLE rated the presented odors as more neutral (two-sided Mann-Whitney U tests, FDR-p < 0.05) and less familiar (two-sided Mann-Whitney U tests, FDR-p < 0.05). fMRI data analysis revealed a reduced response contrast in secondary olfactory areas (e.g., hippocampus) connected to the limbic system when comparing eugenol and valeric acid in individuals with TLE when compared with healthy individuals. However, no lateralization effect was obtained when calculating a lateralization index by the number of activated voxels in the olfactory system (two-sided Mann-Whitney U test; U = 176.0; p = 0.525). TLE is characterized by olfactory dysfunction and associated with hypoactivation of secondary olfactory structures connected to the limbic system. These findings contribute to our understanding of the pathophysiology of TLE. This study was preregistered on OSF Registries (www.osf.io)., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Objectives: Artificial intelligence (AI) is thought to improve lesion detection. However, a lack of knowledge about human performance prevents a comparative evaluation of AI and an accurate assessment of its impact on clinical decision-making. The objective of this work is to quantitatively evaluate the ability of humans to detect focal cortical dysplasia (FCD), compare it to state-of-the-art AI, and determine how it may aid diagnostics., Materials and Methods: We prospectively recorded the performance of readers in detecting FCDs using single points and 3-dimensional bounding boxes. We acquired predictions of 3 AI models for the same dataset and compared these to readers. Finally, we analyzed pairwise combinations of readers and models., Results: Twenty-eight readers, including 20 nonexpert and 5 expert physicians, reviewed 180 cases: 146 subjects with FCD (median age: 25, interquartile range: 18) and 34 healthy control subjects (median age: 43, interquartile range: 19). Nonexpert readers detected 47% (95% confidence interval [CI]: 46, 49) of FCDs, whereas experts detected 68% (95% CI: 65, 71). The 3 AI models detected 32%, 51%, and 72% of FCDs, respectively. The latter, however, also predicted more than 13 false-positive clusters per subject on average. Human performance was improved in the presence of a transmantle sign (P < 0.001) and cortical thickening (P < 0.001). In contrast, AI models were sensitive to abnormal gyration (P < 0.01) or gray-white matter blurring (P < 0.01). Compared with single experts, expert-expert pairs detected 13% (95% CI: 9, 18) more FCDs (P < 0.001). All AI models increased expert detection rates by up to 19% (95% CI: 15, 24) (P < 0.001). Nonexpert+AI pairs could still outperform single experts by up to 13% (95% CI: 10, 17)., Conclusions: This study pioneers the comparative evaluation of humans and AI for FCD lesion detection. It shows that AI and human predictions differ, especially for certain MRI features of FCD, and, thus, how AI may complement the diagnostic workup., Competing Interests: Conflicts of interest and sources of funding: A.R. has received fees as a speaker from UCB Pharma and travel support from the Elisabeth und Helmut Uhl Stiftung. U.A. has received fees as a speaker for Siemens Healthineers and as clinical consultant for Bayer. A.R. lectures for Guerbet and Bayer, and is part of the Advisory Board for GE, Bracco, and Guerbet. R.S. has received personal fees as speaker or for serving on advisory boards from Angelini, Arvelle, Bial, Desitin, Eisai, Jazz Pharmaceuticals Germany GmbH, Janssen-Cilag GmbH, LivaNova, LivAssured B.V., Novartis, Precisis GmbH, Rapport Therapeutics, Tabuk Pharmaceuticals, UCB Pharma, UNEEG, and Zogenix. T.R. has received fees as a speaker from Eisai. None of the previously mentioned activities were related to the content of this manuscript. The remaining authors have nothing to declare. No external funding was received for this work., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence . This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Artificial intelligence (AI) models often face performance drops after deployment to external datasets. This study evaluated the potential of a novel data augmentation framework based on generative adversarial networks (GAN) that creates synthetic patient image data during model training to improve model generalizability. Model development and external testing were performed for a given classification task, namely the detection of new fluid-attenuated inversion recovery (FLAIR) lesions on MRI during longitudinal follow-up of patients with multiple sclerosis (MS). An internal dataset of 669 patients with MS ( n = 3083 examinations) was used to develop an attention-based network, trained both with and without the inclusion of the GAN-based synthetic data augmentation framework. External testing was performed on 134 patients with MS from a different institution, with MR images acquired using different scanners and protocols than images used during training. Models trained using synthetic data augmentation showed a significant performance improvement when applied on external data (AUC 83.6% without synthetic data versus AUC 93.3% with synthetic data augmentation, P = .03), achieving comparable results to the internal test set (AUC 95.5%, P = .53), whereas models without synthetic data augmentation demonstrated a performance drop upon external testing (AUC 93.8% on internal dataset versus AUC 83.6% on external data, P = .03). Data augmentation with synthetic patient data substantially improved performance of AI models on unseen MRI data and may be extended to other clinical conditions or tasks to mitigate domain shift, limit class imbalance, and enhance the robustness of AI applications in medical imaging. ©RSNA, 2024.

Background: Maximum tumor resection improves overall survival (OS) in patients with glioblastoma. The extent of resection (EOR) is historically dichotomized. The RANO resect group recently proposed criteria for volumetry-based EOR assessment in patients that were treated according to Stupp´s protocol. The purpose of this study was (1) to investigate the prognostic value of EOR in patients receiving combined chemotherapy with lomustine (CCNU)/temozolomide (TMZ), and (2) to analyse the prognostic performance of binary EOR assessment compared to volumetric assessment., Methods: 78 patients with newly diagnosed MGMT-methylated GBM undergoing tumor resection followed by radiochemotherapy with CCNU/TMZ were included in this study. Residual contrast-enhancing (CE) tumor volume after the first resection was measured and its influence on OS and PFS was analysed using uni- and multivariable Cox regression analysis as well as two-sided log rank test. Patients were divided into RTV ≤1 cm³, >1 cm³ - ≤5 cm³ and >5 cm³ following the proposed criteria of the RANO resect group., Results: Prolonged OS was associated with age <60 years, low RTV, and gross total resection (GTR). Residual tumor volume (RTV) had a superior prognostic value compared to binary EOR assessment. Patients with total or near total resection of CE tumor (≤1 cm³ RTV) showed prolonged OS (median 54.4 months, 95% CI 46.94-not reached), with a 5-year survival rate of 49%., Conclusion: Low RTV is associated with increased survival in glioblastoma patients undergoing radiochemotherapy with CCNU/TMZ. This study demonstrates the applicability of the recently proposed RANO resect criteria in this subgroup of patients., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Objectives: Reducing gadolinium-based contrast agents to lower costs, the environmental impact of gadolinium-containing wastewater, and patient exposure is still an unresolved issue. Published methods have never been compared. The purpose of this study was to compare the performance of 2 reimplemented state-of-the-art deep learning methods (settings A and B) and a proposed method for contrast signal extraction (setting C) to synthesize artificial T1-weighted full-dose images from corresponding noncontrast and low-dose images., Materials and Methods: In this prospective study, 213 participants received magnetic resonance imaging of the brain between August and October 2021 including low-dose (0.02 mmol/kg) and full-dose images (0.1 mmol/kg). Fifty participants were randomly set aside as test set before training (mean age ± SD, 52.6 ± 15.3 years; 30 men). Artificial and true full-dose images were compared using a reader-based study. Two readers noted all false-positive lesions and scored the overall interchangeability in regard to the clinical conclusion. Using a 5-point Likert scale (0 being the worst), they scored the contrast enhancement of each lesion and its conformity to the respective reference in the true image., Results: The average counts of false-positives per participant were 0.33 ± 0.93, 0.07 ± 0.33, and 0.05 ± 0.22 for settings A-C, respectively. Setting C showed a significantly higher proportion of scans scored as fully or mostly interchangeable (70/100) than settings A (40/100, P < 0.001) and B (57/100, P < 0.001), and generated the smallest mean enhancement reduction of scored lesions (-0.50 ± 0.55) compared with the true images (setting A: -1.10 ± 0.98; setting B: -0.91 ± 0.67, both P < 0.001). The average scores of conformity of the lesion were 1.75 ± 1.07, 2.19 ± 1.04, and 2.48 ± 0.91 for settings A-C, respectively, with significant differences among all settings (all P < 0.001)., Conclusions: The proposed method for contrast signal extraction showed significant improvements in synthesizing postcontrast images. A relevant proportion of images showing inadequate interchangeability with the reference remains at this dosage., Competing Interests: Conflicts of interest and sources of funding: R.H., T.P., E.K., D.P., A.E., A.R., and K.D. are cofounders and stakeholders of relios.vision GmbH; Z.B. and C.G. have no conflicts to declare. R.H. is funded by a research grant (BONFOR; O-194.0002.1 and O-194.0003.1) of the Medical Faculty of the University of Bonn. A.E. and T.P. are funded by the German Research Foundation under Germany's Excellence Strategy (EXC-2047/1, 390685813 and EXC-2151, 390873048)., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Dopaminergic, opiod and endocannabinoid neurotransmission are thought to play an important role in the neurobiology of acute exercise and, in particular, in mediating positive affective responses and reward processes. Recent evidence indicates that changes in fractional amplitude of low-frequency fluctuations (zfALFF) in resting-state functional MRI (rs-fMRI) may reflect changes in specific neurotransmitter systems as tested by means of spatial correlation analyses., Methods: Here, we investigated this relationship at different exercise intensities in twenty young healthy trained athletes performing low-intensity (LIIE), high-intensity (HIIE) interval exercises, and a control condition on three separate days. Positive And Negative Affect Schedule (PANAS) scores and rs-fMRI were acquired before and after each of the three experimental conditions. Respective zfALFF changes were analyzed using repeated measures ANOVAs. We examined the spatial correspondence of changes in zfALFF before and after training with the available neurotransmitter maps across all voxels and additionally, hypothesis-driven, for neurotransmitter maps implicated in the neurobiology of exercise (dopaminergic, opiodic and endocannabinoid) in specific brain networks associated with "reward" and "emotion.", Results: Elevated PANAS Positive Affect was observed after LIIE and HIIE but not after the control condition. HIIE compared to the control condition resulted in differential zfALFF decreases in precuneus, temporo-occipital, midcingulate and frontal regions, thalamus, and cerebellum, whereas differential zfALFF increases were identified in hypothalamus, pituitary, and periaqueductal gray. The spatial alteration patterns in zfALFF during HIIE were positively associated with dopaminergic and μ-opioidergic receptor distributions within the 'reward' network., Discussion: These findings provide new insight into the neurobiology of exercise supporting the importance of reward-related neurotransmission at least during high-intensity physical activity., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Boecker, Daamen, Maurer, Bodensohn, Werkhausen, Lohaus, Manunzio, Manunzio, Radbruch, Attenberger, Dukart and Upadhyay.)