Quantitative susceptibility mapping of multiple system atrophy and Parkinson's disease correlates with neurotransmitter reference maps.

BACKGROUND: Multiple system atrophy (MSA) and Parkinson's disease (PD) are neurodegenerative disorders characterized by α-synuclein pathology, disrupted iron homeostasis and impaired neurochemical transmission. Considering the critical role of iron in neurotransmitter synthesis and transport, our study aims to identify distinct patterns of whole-brain iron accumulation in MSA and PD, and to elucidate the corresponding neurochemical substrates. METHODS: A total of 122 PD patients, 58 MSA patients and 78 age-, sex-matched health controls underwent multi-echo gradient echo sequences and neurological evaluations. We conducted voxel-wise and regional analyses using quantitative susceptibility mapping to explore MSA or PD-specific alterations in cortical and subcortical iron concentrations. Spatial correlation approaches were employed to examine the topographical alignment of cortical iron accumulation patterns with normative atlases of neurotransmitter receptor and transporter densities. Furthermore, we assessed the associations between the colocalization strength of neurochemical systems and disease severity. RESULTS: MSA patients exhibited increased susceptibility in the striatal, midbrain, cerebellar nuclei, as well as the frontal, temporal, occipital lobes, and anterior cingulate gyrus. In contrast, PD patients displayed elevated iron levels in the left inferior occipital gyrus, precentral gyrus, and substantia nigra. The excessive iron accumulation in MSA or PD correlated with the spatial distribution of cholinergic, noradrenaline, glutamate, serotonin, cannabinoids, and opioid neurotransmitters, and the degree of this alignment was related to motor deficits. CONCLUSIONS: Our findings provide evidence of the interaction between iron accumulation and non-dopamine neurotransmitters in the pathogenesis of MSA and PD, which inspires research on potential targets for pharmacotherapy.

The influence of accelerated brain aging on coactivation pattern dynamics in Parkinson's disease.

Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.

Assessment the Impact of IDH Mutation Status on MRI Assessments of White Matter Integrity in Glioma Patients: Insights From Peak Width of Skeletonized Mean Diffusivity and Free Water Metrics.

BACKGROUND: Gliomas are highly invasive brain tumors that evade accurate geographic assessment by conventional MRI due to microscopic invasion along white matter (WM) tracts. Advanced diffusion MRI techniques are needed to assess occult WM involvement. PURPOSE: To evaluate peak width of skeletonized mean diffusivity (PSMD) and peak width of skeletonized free water (PSFW), and axonal water fraction (AWF) for assessing glioma-induced alterations in normal-appearing WM and their relationship with isocitrate dehydrogenase 1 (IDH1) mutation. STUDY TYPE: Retrospective. POPULATION: One hundred five glioma patients (46 ± 13 years), 53 healthy controls (HCs) (46 ± 9 years). FIELD STRENGTH/SEQUENCE: 3.0 T, T1WI, T1-CE, T2WI, T2FLAIR, and DKI. ASSESSMENT: PSMD and PSFW were compared between lesion and contralateral sides in glioma patients and between patients and HCs. The associations between these metrics and clinical variables, including IDH1 mutation, was assessed. Corpus callosum (CC) injury, quantified by the AWF, was evaluated for its mediated effect of IDH1 mutation on contralesional PSMD and PSFW. STATISTICAL TESTS: Paired-t tests, ANCOVA, univariate and multivariate linear regression, and mediation analysis with significance set at P < 0.05. RESULTS: Contralateral PSMD and PSFW were significantly higher in left-sided gliomas (PSMD: 0.206 ± 0.027 vs. 0.193 ± 0.023; PSFW: 0.119 ± 0.019 vs. 0.106 ± 0.020) than in HCs, with similar increases in right-sided gliomas (PSMD: 0.219 ± 0.036 vs. 0.195 ± 0.023; PSFW: 0.129 ± 0.031 vs. 0.109 ± 0.020). IDH1 wild-type gliomas were associated with higher contralateral PSMD and PSFW (ß = -0.302 and -0.412). AWF of CC mediated the impact of IDH1 mutations on contralesional PSMD and PSFW (mediated proportion: 42.7% and 53.7%). DATA CONCLUSION: PSMD and PSFW are effective biomarkers for assessing WM integrity in gliomas, significantly associated with IDH1 mutation status. AWF of CC mediates the relationship between IDH1 mutation and contralesional PSMD and PSFW. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

MRI Radiomics Features of Adenohypophysis Determine the Activation of Hypothalamic-Pituitary-Gonadal Axis in Peri-Puberty Children.

BACKGROUND: The status of the hypothalamic-pituitary-gonadal (HPG) axis is important for assessing the onset of physiological or pathological puberty. The reference standard gonadotropin-releasing hormone (GnRH) stimulation test requires hospital admission and repeated blood samples. A simple noninvasive method would be beneficial. OBJECTIVES: To explore a noninvasive method for evaluating HPG axis activation in children using an MRI radiomics model. STUDY TYPE: Retrospective. POPULATION: Two hundred thirty-nine children (83 male; 3.6-14.6 years) with hypophysial MRI and GnRH stimulation tests, randomly divided a training set (168 children) and a test set (71 children). FIELD STRENGTH/SEQUENCE: 3.0 T, 3D isotropic fast spin echo (CUBE) T1-weighted imaging (T1WI) sequences. ASSESSMENT: Radiomics features were extracted from sagittal 3D CUBE T1WI, and imaging signatures were generated using the least absolute shrinkage and selection operator (LASSO) with 10-fold cross-validation. Diagnostic performance for differential diagnosis of HPG status was compared between a radiomics model and MRI features (adenohypophyseal height [aPH] and volume [aPV]). STATISTICAL TESTS: Receiver operating characteristic (ROC) and decision curve analysis (DCA). A P value <0.05 was considered statistically significant. RESULTS: Eight hundred fifty-one radiomics features were extracted and reduced to 10 by the LASSO method in the training cohort. The radiomics model based on CUBE T1WI showed good performance in assessment of HPG axis activation with an area under the ROC curve (AUC) of 0.81 (95% CI: 0.71, 0.91) in the test set. The AUC of the radiomics model was significantly higher than that of aPH (0.81 vs. 0.65) but there was no significant difference compared to aPV (0.81 vs. 0.78, P = 0.58). In DCA analysis, the radiomics signature showed higher net benefit over the aPV and aPH models. DATA CONCLUSIONS: The MRI radiomics model has potential to assess HPG axis activation status noninvasively, potentially providing valuable information in the diagnosis of patients with pathological puberty onset. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits.

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation.

PURPOSE: To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5). METHODS: 95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation. RESULTS: The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001). CONCLUSION: Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

The changes of oxygen extraction fraction in different types of lesions in relapsing-remitting multiple sclerosis: A cross-sectional and longitudinal study.

OBJECTIVES: To explore the oxygen metabolism level of different types of lesions in relapsing-remitting multiple sclerosis (RRMS) patients by oxygen extraction fraction (OEF) both cross-sectionally and longitudinally. METHODS: Forty-six RRMS patients and forty-one healthy controls (HC) went MRI examination. The quantitative susceptibility mapping (QSM) and OEF map were reconstructed from a 3D multi-echo gradient echo sequence. MS lesions in white matter were classified as contrast-enhancing lesions (CELs) on post-gadolinium T1-weighted sequence, paramagnetic rim lesions (PRLs), hyperintense lesions and non-hyperintense lesions on QSM, respectively. The susceptibility and OEF of different types of lesions were compared. The susceptibility and OEF values were measured and compared among different types of lesions. Among these RRMS patients, seventeen had follow-up MRI and 232 lesions, and baseline to follow-up longitudinal changes in susceptibility and OEF were measured. RESULTS: PRLs had higher susceptibility and lower OEF than CELs, hyperintense lesions, and non-hyperintense lesions. The hyperintense lesions had higher susceptibility and lower OEF than non-hyperintense lesions. In longitudinal changes, PRLs had susceptibility increased (P < 0.001) and OEF decreased (P < 0.001). The hyperintense lesions showed significant decreases in susceptibility (P = 0.020), and non-hyperintense lesions showed significant increases in OEF during follow-up (P = 0.005). Notably, hyperintense lesions may convert to PRLs or non-hyperintense lesions as time progresses, accompanied by changes of OEF and susceptibility in the lesions. CONCLUSION: This study revealed tissue damage and oxygen metabolism level in different types of MS lesions. The OEF may contribute to further understanding the evolution of MS lesions.

Dynamic effective connectivity among large-scale brain networks mediates risk of anxiety.

Anxiety is characterized by altered brain networks. Directional information flows among dynamic brain networks concerning neuropathogenesis of anxiety have not yet been investigated. The role of directional influences between networks in gene-environment effects on anxiety remains to be further elucidated. In a large community sample, this resting-state functional MRI study estimated dynamic effective connectivity among large-scale brain networks based on a sliding-window approach and Granger causality analysis, providing dynamic and directional information for signal transmission in networks. We first explored altered effective connectivity among networks related to anxiety in distinct connectivity states. Due to the potential gene-environment effects on brain and anxiety, we further performed mediation and moderated mediation analyses to investigate the role of altered effective connectivity networks in relationships between polygenic risk scores, childhood trauma, and anxiety. State and trait anxiety scores showed correlations with altered effective connectivity among extensive networks in distinct connectivity states (p < .05, uncorrected). Only in a more frequent and strongly connected state, there were significant correlations between altered effective connectivity networks and trait anxiety (PFDR <0.05). Furthermore, mediation and moderated mediation analyses showed that the effective connectivity networks played a mediating role in the effects of childhood trauma and polygenic risk on trait anxiety. State-dependent effective connectivity changes among brain networks were significantly related to trait anxiety, and mediated gene-environment effects on trait anxiety. Our work sheds novel light on the neurobiological mechanisms underlying anxiety, and provides new insights into early objective diagnosis and intervention evaluation.

Long-term SARS-CoV-2 neutralizing antibody level prediction using multimodal deep learning: A prospective cohort study on longitudinal data in Wuhan, China.

The ongoing epidemic of SARS-CoV-2 is taking a substantial financial and health toll on people worldwide. Assessing the level and duration of SARS-CoV-2 neutralizing antibody (Nab) would provide key information for government to make sound healthcare policies. Assessed at 3-, 6-, 12-, and 18-month postdischarge, we described the temporal change of IgG levels in 450 individuals with moderate to critical COVID-19 infection. Moreover, a data imputation framework combined with a novel deep learning model was implemented to predict the long-term Nab and IgG levels in these patients. Demographic characteristics, inspection reports, and CT scans during hospitalization were used in this model. Interpretability of the model was further validated with Shapely Additive exPlanation (SHAP) and Gradient-weighted Class Activation Mapping (GradCAM). IgG levels peaked at 3 months and remained stable in 12 months postdischarge, followed by a significant decline in 18 months postdischarge. However, the Nab levels declined from 6 months postdischarge. By training on the cohort of 450 patients, our long-term antibody prediction (LTAP) model could predict long-term IgG levels with relatively high area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1-score, which far exceeds the performance achievable by commonly used models. Several prognostic factors including FDP levels, the percentages of T cells, B cells and natural killer cells, older age, sex, underlying diseases, and so forth, served as important indicators for IgG prediction. Based on these top 15 prognostic factors identified in IgG prediction, a simplified LTAP model for Nab level prediction was established and achieved an AUC of 0.828, which was 8.9% higher than MLP and 6.6% higher than LSTM. The close correlation between IgG and Nab levels making it possible to predict long-term Nab levels based on the factors selected by our LTAP model. Furthermore, our model identified that coagulation disorders and excessive immune response, which indicate disease severity, are closely related to the production of IgG and Nab. This universal model can be used as routine discharge tests to identify virus-infected individuals at risk for recurrent infection and determine the optimal timing of vaccination for general populations.

Noninvasive Evaluation of the Notch Signaling Pathway via Radiomic Signatures Based on Multiparametric MRI in Association With Biological Functions of Patients With Glioma: A Multi-institutional Study.

BACKGROUND: Noninvasive determination of Notch signaling is important for prognostic evaluation and therapeutic intervention in glioma. PURPOSE: To predict Notch signaling using multiparametric (mp) MRI radiomics and correlate with biological characteristics in gliomas. STUDY TYPE: Retrospective. POPULATION: A total of 63 patients for model construction and 47 patients from two public databases for external testing. FIELD STRENGTH/SEQUENCE: A 1.5 T and 3.0 T, T1-weighted imaging (T1WI), T2WI, T2 fluid attenuated inversion recovery (FLAIR), contrast-enhanced (CE)-T1WI. ASSESSMENT: Radiomic features were extracted from CE-T1WI, T1WI, T2WI, and T2FLAIR and imaging signatures were selected using a least absolute shrinkage and selection operator. Diagnostic performance was compared between single modality and a combined mpMRI radiomics model. A radiomic-clinical nomogram was constructed incorporating the mpMRI radiomic signature and Karnofsky Performance score. The performance was validated in the test set. The radiomic signatures were correlated with immunohistochemistry (IHC) analysis of downstream Notch pathway components. STATISTICAL TESTS: Receiver operating characteristic curve, decision curve analysis (DCA), Pearson correlation, and Hosmer-Lemeshow test. A P value < 0.05 was considered statistically significant. RESULTS: The radiomic signature derived from the combination of all sequences numerically showed highest area under the curve (AUC) in both training and external test sets (AUCs of 0.857 and 0.823). The radiomics nomogram that incorporated the mpMRI radiomic signature and KPS status resulted in AUCs of 0.891 and 0.859 in the training and test sets. The calibration curves showed good agreement between prediction and observation in both sets (P= 0.279 and 0.170, respectively). DCA confirmed the clinical usefulness of the nomogram. IHC identified Notch pathway inactivation and the expression levels of Hes1 correlated with higher combined radiomic scores (r = -0.711) in Notch1 mutant tumors. DATA CONCLUSION: The mpMRI-based radiomics nomogram may reflect the intratumor heterogeneity associated with downstream biofunction that predicts Notch signaling in a noninvasive manner. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Spatiotemporal patterns of brain iron-oxygen metabolism in patients with Parkinson's disease.

OBJECTIVES: Iron deposition and mitochondrial dysfunction are closely associated with the genesis and progression of Parkinson's disease (PD). This study aims to extract susceptibility and oxygen extraction fraction (OEF) values of deep grey matter (DGM) to explore spatiotemporal progression patterns of brain iron-oxygen metabolism in PD. METHODS: Ninety-five PD patients and forty healthy controls (HCs) were included. Quantitative susceptibility mapping (QSM) and OEF maps were computed from MRI multi-echo gradient echo data. Analysis of covariance (ANCOVA) was used to compare mean susceptibility and OEF values in DGM between early-stage PD (ESP), advanced-stage PD (ASP) patients and HCs. Then Granger causality analysis on the pseudo-time-series of MRI data was applied to assess the causal effect of early altered nuclei on iron content and oxygen extraction in other DGM nuclei. RESULTS: The susceptibility values in substantia nigra (SN), red nucleus, and globus pallidus (GP) significantly increased in PD patients compared with HCs, while the iron content in GP did not elevate obviously until the late stage. The mean OEF values for the caudate nucleus, putamen, and dentate nucleus were higher in ESP patients than in ASP patients or/and HCs. We also found that iron accumulation progressively expands from the midbrain to the striatum. These alterations were correlated with clinical features and improved AUC for early PD diagnosis to 0.824. CONCLUSIONS: Abnormal cerebral iron deposition and tissue oxygen utilization in PD measured by QSM and OEF maps could reflect pathological alterations in neurodegenerative processes and provide valuable indicators for disease identification and management. CLINICAL RELEVANCE STATEMENT: Noninvasive assessment of cerebral iron-oxygen metabolism may serve as clinical evidence of pathological changes in PD and improve the validity of diagnosis and disease monitoring. KEY POINTS: • Quantitative susceptibility mapping and oxygen extraction fraction maps indicated the cerebral pathology of abnormal iron accumulation and oxygen metabolism in Parkinson's disease. • Iron deposition is mainly in the midbrain, while altered oxygen metabolism is concentrated in the striatum and cerebellum. • The susceptibility and oxygen extraction fraction values in subcortical nuclei were associated with clinical severity.

Impaired topological properties of cortical morphological brain networks correlate with motor symptoms in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is characterized by loss of selectively vulnerable neurons within the basal ganglia circuit and progressive atrophy in subcortical and cortical regions. However, the impact of neurodegenerative pathology on the topological organization of cortical morphological networks has not been explored. The aims of this study were to investigate altered network patterns of covariance in cortical thickness and complexity, and to evaluate how morphological network integrity in PD is related to motor impairment. METHODS: Individual morphological networks were constructed for 50 PD patients and 46 healthy controls (HCs) by estimating interregional similarity distributions in surface-based indices. We performed graph theoretical analysis and network-based statistics to detect PD-related alterations and further examined the correlation of network metrics with clinical scores. Furthermore, support vector regression based on topological characteristics was applied to predict the severity of motor impairment in PD. RESULTS: Compared with HCs, PD patients showed lower local efficiency (p = 0.004), normalized characteristic path length (p = 0.022), and clustering coefficient (p = 0.005) for gyrification index-based morphological brain networks. Nodal topological abnormalities were mainly in the frontal, parietal and temporal regions, and impaired morphological connectivity was involved in the sensorimotor and default mode networks. The support vector regression model using network-based features allowed prediction of motor symptom severity with a correlation coefficient of 0.606. CONCLUSIONS: This study identified a disrupted topological organization of cortical morphological networks that could substantially advance our understanding of the network degeneration mechanism of PD and might offer indicators for monitoring disease progression.

The asymmetry of glymphatic system dysfunction in patients with temporal lobe epilepsy: A DTI-ALPS study.

BACKGROUND AND PURPOSE: While the occurrence of glymphatic system dysfunction has been observed in temporal lobe epilepsy (TLE), the potential asymmetry of this system has yet to be investigated in the TLE context. We aimed to investigate the glymphatic system function in both hemispheres and to analyze asymmetric features of the glymphatic system in TLE patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) method. MATERIALS AND METHODS: 43 patients (left TLE (LTLE), n = 20; right TLE (RTLE), n = 23) and 39 healthy controls (HC) were enrolled in this study. The DTI-ALPS index was calculated for the left (left ALPS index) and right (right ALPS index) hemispheres respectively. An asymmetry index (AI) was calculated by AI = (Right - Left)/ [(Right + Left)/2] to represent the asymmetric pattern. Independent two sample t-test, two-sample paired t-test or one-way ANOVA with Bonferroni correction were conducted to compare the differences in ALPS indices and AI among the groups. RESULTS: Both left ALPS index (p = 0.040) and right ALPS index (p = 0.001) of RTLE patients were significantly decreased, while only left ALPS index of LTLE patients (p = 0.005) was reduced. Compared to contralateral ALPS index, the ipsilateral ALPS index was significantly decreased in TLE (p = 0.008) and RTLE (p = 0.009) patients. Leftward asymmetry of the glymphatic system was found in HC (p = 0.045) and RTLE (p = 0.009) patients. The LTLE patients presented reduced asymmetric traits when compared to RTLE patients (p = 0.029). CONCLUSION: The TLE patients exhibited altered ALPS indices, which could be triggered by glymphatic system dysfunction. Altered ALPS indices were more severe in ipsilateral than in the contralateral hemisphere. Moreover, LTLE and RTLE patients exhibited different change patterns of the glymphatic system. In addition, glymphatic system function presented asymmetric patterns in both normal adult brain and RTLE patients.

Twelve-Month Systemic Consequences of Coronavirus Disease 2019 (COVID-19) in Patients Discharged From Hospital: A Prospective Cohort Study in Wuhan, China.

BACKGROUND: Follow-up study of coronavirus disease 2019 (COVID-19) survivors has rarely been reported. We aimed to investigate longitudinal changes in the characteristics of COVID-19 survivors after discharge. METHODS: A total of 594 COVID-19 survivors discharged from Tongji Hospital in Wuhan from February 10 to April 30, 2020 were included and followed up until May 17, 2021. Laboratory and radiological findings, pulmonary function tests, electrocardiogram, symptoms and signs were analyzed. RESULTS: 257 (51.2%) patients had at least one symptom at 3 months post-discharge, which decreased to 169 (40.0%) and 138 (28.4%) at 6-month and 12-month visit respectively. During follow-up period, insomnia, chest tightness, and fatigue were the most prevalent symptoms. Most laboratory parameters returned to normal, whereas increased incidence of abnormal liver and renal function and cardiovascular injury was evidenced after discharge. Fibrous stripes (213; 42.4%), pleural thickening and adhesions (188; 37.5%) and enlarged lymph nodes (120; 23.9%) were the most common radiographical findings at 3 months post-discharge. The abnormalities of pulmonary function included obstructive, restrictive, and mixed, which were 5.5%, 4.0%, 0.9% at 6 months post, and 1.9%, 4.7%, 0.2% at 12 months. Electrocardiogram abnormalities occurred in 256 (51.0%) patients at 3 months post-discharge, including arrhythmia, ST-T change and conduction block, which increased to 258 (61.1%) cases at 6-month visit and were maintained at high frequency (242;49.8%) at 12-month visit. CONCLUSIONS: Physiological, laboratory, radiological, or electrocardiogram abnormalities, particularly those related to renal, cardiovascular, and liver functions are common in patients who recovered from coronavirus disease 2019 (COVID-19) up to 12 months post-discharge.

Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors.

Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.

Diffusion Tensor Imaging Reveals Altered Topological Efficiency of Structural Networks in Type-2 Diabetes Patients With and Without Mild Cognitive Impairment.

BACKGROUND: Some patients with type 2 diabetes mellitus (T2DM) progress towards mild cognitive impairment (MCI), while some patients can always maintain normal cognitive function. Network topologic alterations at global and nodal levels between T2DM individuals with and without cognitive impairment may underlie the difference. PURPOSE: To investigate the topological alterations of the whole-brain white matter (WM) structural connectome in T2DM patients with and without MCI and characterize its relationship with disease severity. STUDY TYPE: Cross-sectional and prospective study. SUBJECTS: Forty-four (63.6% females) T2DM patients, 22 with mild cognitive impairment (DM-MCI) and 22 with normal cognition (DM-NC), and 34 (58.8% females) healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3 T/diffusion tensor imaging. ASSESSMENT: Graph theoretical analysis was used to investigate the topological organization of the structural networks. The global topological properties and nodal efficiency were investigated and compared. Relationship between network metrics and clinical measurements was characterized. STATISTICAL TESTS: Student's t-test, chi-square test, ANOVA, partial correlation analyses, and multiple comparisons correction. RESULTS: The global topological organization of WM networks was significantly disrupted in T2DM patients with cognitive impairment (reduced global and local efficiency and increased shortest path length) but not in those with normal cognition, compared with controls. The DM-MCI group had significantly decreased network efficiency compared with the DM-NC group. Compared with controls, decreased nodal efficiency was detected in three regions in DM-NC group. More regions with decreased nodal efficiency were found in the DM-MCI group. Altered global network properties and nodal efficiency of some regions were correlated with diabetic duration, HbA1c levels, and cognitive assessment scores. DATA CONCLUSION: The more disrupted WM connections and weaker organized network are found in DM-MCI patients relative to DM-NC patients and controls. Network analyses provide information for the neuropathology of cognitive decline in T2DM patients. Altered nodal efficiency may act as potential markers for early detection of T2DM-related MCI. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Tractometry-Based Estimation of Corticospinal Tract Injury to Assess Initial Impairment and Predict Functional Outcomes in Ischemic Stroke Patients.

BACKGROUND: Corticospinal tract (CST) injury has been shown to exert a major influence on functional recovery after ischemic stroke. PURPOSE: To evaluate the prognostic value of CST injury estimated using a recent developed tractometry-based method. STUDY TYPE: Prospective. POPULATION: Forty-eight patients with CST damage induced by stroke lesion who underwent brain magnetic resonance imaging within 7 days from onset. SEQUENCE: Diffusion-weighted imaging (b = 1000 seconds/mm2 ) and diffusion kurtosis imaging (DKI) spin-echo echo-planar sequence with three b-values (0, 1250, and 2500 seconds/mm2 ) at 3.0 T. ASSESSMENT: A recently developed approach that combines tract segmentation and orientation mapping was used for CST-specific tractography and tractometry. CST injury was estimated using the proposed method with diffusion metrics extracted from DKI sequence and with the first principal component (PC1) of the metrics. We also calculated the weighted lesion load (wLL) for comparison. Clinical evaluation included the National Institutes of Health Stroke Score in the acute phase and the modified Rankin scale at 3 months post-stroke. The correlations between CST injury and initial motor impairment, as well as the prognostic values of CST injury for functional outcomes were evaluated. STATISTICAL TESTS: Pearson correlation and logistic regression. Area under the receiver operating characteristic curve. P < 0.05 was considered statistically significant. RESULTS: CST injury calculated with diffusion metrics except fractional anisotropy all showed significant correlations with initial motor impairment. PC1 achieved the largest correlation coefficient (R = 0.65) compared with wLL and other diffusion metrics. In addition to wLL, DKI_AK, AFD_total, and PC1 maximum all showed predictive values for functional outcomes. DATA CONCLUSION: Structural injury to CST is important for the assessment of the extent of injury and the prediction of functional outcome. The method proposed in our study could provide an imaging indicator to quantify the CST injury after ischemic stroke. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

Fractional anisotropy helps to differentiate the optic nerve impairment between neuromyelitis optica spectrum disorders and multiple sclerosis.

OBJECTIVES: To assess the characteristics of optic nerve impairment between neuromyelitis optica spectrum disorders (NMOSD) and multiple sclerosis (MS) patients by fractional anisotropy (FA). METHODS: Thirty-one NMOSD patients, 25 MS patients, and 17 heathy controls (HC) who underwent optic nerve DTI were included. The optic nerves of the NMOSD and MS patients were divided into vision-impaired (VI) subgroups and normal-appearing (NA) subgroups according to visual status, respectively. FA values were measured in the anterior, middle, and posterior segments of each intraorbital optic nerve. RESULTS: FA values in VI NMOSD were significantly decreased in the whole optic nerve, especially the posterior segment of the optic nerve (p < 0.001). FA values measured in the anterior and middle segments of the optic nerve in VI MS were significantly decreased as compared to those in the HC (p < 0.05). Between NMOSD and MS, FA values in the posterior segment of the optic nerve showed significant differences (VI NMOSD vs. VI MS, 0.458 ± 0.097 vs. 0.568 ± 0.098, p < 0.001; NA NMOSD vs. NA MS, 0.568 ± 0.098 vs. 0.600 ± 0.085, p = 0.041, respectively). The signal intensity ratio (SIR) in the posterior segment of the optic nerve was significantly increased in VI NMOSD as compared with VI MS (p = 0.002). The combination of SIR and FA for distinguishing VI NMOSD from VI MS resulted in sensitivity, specificity, and positive and negative predictive values of 86.49%, 80.00%, 88.9%, and 76.2%, respectively. CONCLUSION: FA could quantify the characteristics of NMOSD- and MS-related optic nerve impairment. DTI was a simple and effective imaging tool to differentiate between the two. KEY POINTS: • NMOSD-related optic nerve impairment is extensive, often greater than half of the optic nerve, with the most significant involvement of the posterior segment of the optic nerve. • MS-related optic nerve impairment is more limited than NMOSD, and anterior and middle optic nerve involvement is common. • Optic nerve DTI is a convenient and effective imaging tool that can help characterize NMOSD and MS.

Cross-cultural differences in adult attachment and depression: A culturally congruent approach.

This cross-cultural study investigated a conditional indirect effect model in which country membership (South Korea or United States) and the need for approval of others (AO) were hypothesized to moderate the direct and indirect effects of attachment insecurity on depression via social self-efficacy (SSE). A total of 673 Korean university students and 401 American university students completed research questionnaires. Results indicated that Korean students endorsed a significantly higher level of AO than American students. Additionally, findings revealed that the strengths of several significant direct and indirect effects varied significantly by country membership and AO. Finally, we found a significant three-way interaction (Attachment avoidance × Country membership × AO), suggesting the necessity of considering cultural differences in attachment influence. The limitations and implications of our cross-cultural findings for decolonization in Western-based psychology are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The relationship between responsibility attribution and session outcomes: Two-dimension attribution and two-person perspective.

OBJECTIVE: Blame attribution (who is to blame for problem causes) and solution attribution (who is to control problem solving) are two critical dimensions of responsibility attribution in psychotherapy. The present study aimed to (1) investigate the impacts of blame attribution and solution attribution on session outcomes from both client and therapist perspectives and (2) clarify the relationship between the therapist-client congruence of responsibility attribution and session outcomes. METHOD: A total of 69 clients were recruited at a university counselling centre. Client-rated responsibility attribution (to what extent they were responsible for the causes and solution of their current concerns), therapist-rated responsibility attribution (to what extent they thought their clients should be responsible for the causes and solution of clients' current concerns), client-rated session quality and symptom level for each session were collected across 387 sessions. Multilevel regression was used to explore the relationship between responsibility attribution and session outcomes. Truth and bias model and response surface analysis were utilized to analyse the within-client and between-client client-therapist congruence effects. RESULTS: The main results included that (1) the clients with higher solution responsibility had more symptom improvement and higher evaluation of session quality (between-client level). A client's perceived solution responsibility predicted better session quality and fewer next session symptom levels (within-client level). (2) If a therapist attributed more solution responsibility to his/her client, the session quality was higher (within-client level). (3) Neither clients' nor therapists' perspectives on blame attribution directly affected session outcomes. But the higher the client's blame for his/her problem causes, the stronger the association between solution responsibility and symptom reduction (within-client level). (4) Higher within-client client-therapist congruence on blame responsibility led to better session outcomes. CONCLUSION: The clients' solution responsibility and client-therapist congruence on blame for problem causes contribute to session outcomes in psychotherapy.