Quantitative susceptibility mapping (QSM) is a post-processing magnetic resonance imaging technique that quantifies the magnetic susceptibility of biological tissue and provides insights into factors such as iron deposition, hemorrhage, calcification, myelin content, and oxygen extraction fraction. A variety of analytical approaches have been developed to interpret QSM data from different perspectives, including region-of-interest-based, depth-wise, surface-based, network-based, and voxel-wise methods. Among these, voxel-wise analysis has gained increasing prominence due to its ability to perform a detailed examination of the entire brain without anatomically predefined regions. This approach is especially valuable for investigating neurological pathologies and aging-related changes, including neurodegenerative and neuropsychiatric disorders. This article aims to comprehensively summarize voxel-wise analysis in QSM by outlining key methodological considerations and clinical applications. Moreover, it offers practical data processing recommendations to advance the reproducibility and transparency of voxel-wise QSM research.

PURPOSE:To develop and validate a framework for rapid, accurate, and repeatable whole-brain, multi-pool chemical exchange saturation transfer (CEST) imaging at 3 T, addressing challenges of long acquisition times and confounding factors. METHODS:A single-shot 3D true fast imaging with steady-state precession (True FISP) sequence was optimized for whole-brain multi-pool CEST. Rapid B0, B1, and T1 mapping was performed using a dual-echo modified four-angle method. A feed-forward neural network was developed for rapid B1 correction, trained against the conventional multi-power method. The apparent exchange-dependent relaxation (AREX) metric was used to correct for T1 and magnetization transfer (MT) effects. The framework was validated in phantoms and 50 healthy subjects, including a different-day test-retest repeatability assessment. RESULTS:The True FISP sequence yielded high-quality, whole-brain images with minimal artifacts and distortion in a clinically feasible scan time (∼9 min). Phantom studies confirmed the effectiveness of B1 correction (coefficient of variation [CV] for the magnetization transfer ratio based on Lorentzian difference (MTRLD) of the MT pool decreased from 22.49% to 4.61%) and AREX-based confounder correction (CV for APT_AREX reduced from 33.6% to 6.9%). The neural network B1 correction showed excellent agreement with the conventional multi-power method in vivo (ICC > 0.95). High different-day test-retest repeatability was demonstrated across 96 brain regions, with the average CV for APT_AREX under 10% for 95 of 96 analyzed regions. CONCLUSION:A rapid and robust framework for whole-brain quantitative multi-pool CEST imaging was successfully developed and validated. By integrating an efficient acquisition sequence with a streamlined correction pipeline, this approach overcomes key barriers to clinical translation, enabling reliable metabolic imaging for widespread brain pathologies.

This study investigated time-dependent group-level changes in chemical exchange saturation transfer (CEST) signals in a mouse model and explored utility in identifying stroke onset time. Multiparametric magnetic resonance imaging (diffusion weighted imaging, arterial spin labeling, and CEST) was conducted on 12 normal and 26 ischemic mice. Imaging findings were validated by immunohistochemical analysis. CEST parameters in infarct and penumbra were compared between strokes within 4.5 h and over 4.5 h. Correlations, regression, and receiver operating characteristic curves evaluated performance. Infarct guanidine, magnetization transfer (MT), nuclear Overhauser enhancement (NOE) (-3.5 ppm), and NOE (-1.6 ppm) significantly differed between groups and associated with onset time (P < .01). MT, NOE (-3.5 ppm), NOE (-1.6 ppm) showed significant associations with onset time in univariate logistic regression (P < .05). The NOE (-3.5 ppm) achieved an area under the curve of 0.848 (95% CI: 0.655-1.000), outperforming apparent diffusion coefficient (z = -2.397, P = .017) and cerebral blood flow (z = -2.271, P = .0271). NOE (-3.5 ppm) signals and lipid peroxidation both declined progressively with ischemic duration. These findings indicate that NOE (-3.5 ppm) signal attenuation parallels lipid peroxidation and may indicate progressive membrane lipid loss in ischemia.

Accumulating evidence implicates cholinergic dysfunction in freezing of gait (FOG) in Parkinson’s disease (PD). Given the basal forebrain (BF) provides the primary cholinergic input to the cortex, elucidating BF-cortical connectivity and its dynamic reconfiguration during motor challenges in PD-FOG is important. This study included 44 PD-FOG, 45 without FOG (PD-NFOG), and 27 healthy controls (HC). All underwent diffusion and resting-state functional MRI. A subgroup (27 PD-FOG, 20 PD-NFOG, 27 HC) also underwent gait-related task-based fMRI. Multimodal gradients of BF connectivity were compared across the three groups and between task and rest. BF free-water was elevated in both PD groups versus HC. Connectivity gradient analysis further revealed reduced structure-function coupling along the anteromedial-to-posterolateral BF axis, with weakest coupling in posterolateral subregions. Cortically, coupling progressively reduced from unimodal sensory to transmodal association cortex. While this topographic architecture was qualitatively preserved in both PD groups, during turning imagery, PD-FOG patients exhibited impaired adaptive decoupling in the somatomotor network, localized to an insular hub with attenuated task-evoked nodal responsivity. BF free-water elevation and hub dysfunction independently predicted clinical status along the continuum from healthy to PD-NFOG to PD-FOG. Our findings reveal a state-dependent reconfiguration failure in PD-FOG, suggesting a circuit-level, neurodynamic mechanism for FOG.

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging technique that quantifies tissue magnetic susceptibility by deconvolving the measured signal phase data. Accurate background field removal is essential for QSM, especially in surface regions of the brain, such as the cerebral cortex, where the background field interference is substantial. Existing methods have errors in estimating background field near the boundary of an organ, such as those of the brain, due to assumptions or loss of low-frequency information. A novel Green’s function total field inversion (gTFI) method is proposed here to model the background field using integral equations composed of Green’s function and boundary conditions, thereby eliminating the need for traditional filtering, assumption or regularization. The gTFI method simultaneously determines the background field at the boundary and the tissue susceptibility from the measured phase data. Numerical simulations and in vivo experiments demonstrate that the gTFI effectively separates the background field and reconstructs whole-brain QSM images without boundary erosion, offering superior performance over existing methods, particularly in cortical regions.

Multi-Pool Chemical Exchange Saturation Transfer (CEST) MRI provides valuable metabolic information but is clinically limited by long acquisition times. Although sparse sampling reduces scanning time, reconstructing high-resolution Z-spectra from limited data remains an ill-posed inverse problem. Conventional interpolation and generic Implicit Neural Rep-resentations (INRs) often lack physical constraints, leading to spectral artifacts and physically invalid signals. To address this, we propose Lorentz Encoding (LE), a physics-informed framework that formulates CEST reconstruction as a self-supervised reconstruction task via implicit continuous coordinate learning. Unlike generic positional encodings, LE regularizes the continuous spectral mapping by projecting sparse coordinates into a physically constrained space governed by a combination of parametric Lorentzian profiles with learnable basis functions. This mechanism effectively reduces noise and enforces consistency with physical models. Experiments on in vivo human brain data demonstrate that LE significantly outperforms state-of-the-art methods. Specifically, under a 39-point sampling strategy, LE achieves a PSNR of 57.58 dB and an SSIM of 0.9994. Furthermore, the learned physics-informed encodings form a continuous, geometrically ordered trajectory in the latent space, ensuring accurate quantitative metabo-lite mapping (APT, NOE, MT).

BACKGROUND:Mounting evidence highlights the critical role of the brain's glymphatic system in cerebral waste clearance, yet its alterations in Wilson's disease (WD) remain unclear. This study aimed to systematically evaluate structural and functional alterations of the glymphatic system across WD clinical phenotypes and their associations with neurological impairment. METHODS:Nineteen patients with neurological WD (neuro-WD), 13 with hepatic WD (hep-WD), and 25 healthy controls (HCs) were enrolled. Quantitative MRI metrics included choroid plexus (ChP) volume and diffusion parameters, basal ganglia perivascular space (PVSBG) volume, and free water-eliminated diffusion tensor imaging analysis along the perivascular space (FWE-DTI-ALPS) index. Group differences were analyzed using ANCOVA, post hoc t-tests, and receiver operating characteristic analyses. Partial correlation analyses were performed to examine associations between MRI and clinical parameters. RESULTS:ChP and PVSBG volumes increased progressively across HC, hep-WD, and neuro-WD groups, whereas the FWE-DTI-ALPS index decreased (all p < 0.01), accompanied by elevated free water content and altered diffusion properties in the ChP. The combination of ChP and PVS markers distinguished WD from HC (AUC = 0.939), while ChP volume alone effectively differentiated neuro-WD from hep-WD (AUC = 0.799). ChP volume correlated negatively with the FWE-DTI-ALPS index (r = -0.619), and PVSBG volume was inversely associated with FWE-DTI-ALPS (r = -0.320). Clinically, ChP enlargement correlated with higher urinary copper levels, whereas fractional anisotropy values, both before and after free water correction, were negatively correlated with serum iron. CONCLUSIONS:These findings provide preliminary imaging evidence of alterations in glymphatic-related MRI markers in WD and suggest that these markers may help differentiate neurological from hepatic phenotypes in research settings. In addition, we emphasize that the observed ALPS changes should be interpreted cautiously, and future longitudinal and multi-shell studies are required before clinical translation can be considered.

Quantitative assessment of extraocular muscles (EOMs) is crucial for the clinical management of thyroid-associated ophthalmopathy, and other orbital disorders. The multi-dynamic multi-echo (MDME) sequence is a synthetic MRI technique acquiring 2D multi-echo images via turbo spin echo or a combination of gradient echo and spin echo methods. The aim of this study was to evaluate the scan-rescan reproducibility and interobserver reliability of T1 and T2 quantification in the EOMs using MDME sequence. In this prospective study, twenty-two healthy volunteers underwent two MDME scans (interval, 7–14 days) on a 3T MRI system with a 20-channel head-neck coil. Quantitative T1 and T2 maps were generated using post-processing software. Two observers independently outlined regions-of-interest within the EOMs to extract T1 and T2 relaxation times. Intraclass correlation coefficient (ICC), coefficient of variation (CV), and Bland-Altman analyses were employed to assess reproducibility and agreement. Nineteen subjects (mean age 40.3 ± 10.5 years) were finally analyzed. The median scan-rescan interval was 9 days [interquartile range (IQR), 7–14]. Scan-rescan reproducibility was good for T1 value (first scan: 933.4 [892.5–1102.5] ms, second scan: 956.4 [856.7–1069.9] ms, ICC = 0.694, bias = 28.1 ms, CV = 8.47

Background:Brain structural alterations have been implicated in the pathophysiology of minimal hepatic encephalopathy (MHE). This study aimed to investigate cortical microstructural abnormalities and their correlation with cognitive impairment in MHE using neurite orientation dispersion and density imaging (NODDI) and voxel-wise gray matter-based spatial statistics (GBSS). Methods:The NODDI model was fit to multi-shell diffusion-weighted magnetic resonance imaging (dMRI) acquisitions obtained from 35 healthy controls (HC), 41 cirrhotic patients without MHE (NHE), and 21 cirrhotic patients with MHE. The metrics of NODDI, including neurite density index (NDI) and orientation dispersion index (ODI), were compared among groups using GBSS. The relationships between NODDI-derived parameters and neurocognitive performance, measured by the Psychometric Hepatic Encephalopathy Score (PHES), were assessed in the cirrhotic patients. Results:The MHE group showed decreased NDI in several cortical regions, primarily including the default mode network (DMN)-related regions, left insula, left middle frontal gyrus, bilateral lateral temporal cortex, and the sensorimotor, visual, and auditory cortices [family-wise error (FWE)-corrected P<0.05]. The regions with decreased NDI in the MHE group were more extensive than those in the NHE group. There was no significant difference in ODI across the three groups (FWE-corrected P>0.05). Reduced NDI in the right parahippocampal gyrus and lingual gyrus correlated with PHES in the cirrhotic patients (FWE-corrected P<0.05). Conclusions:This study provides evidence for the microstructural modulation of cortical neurites in MHE and contributes to our understanding of the latent biological basis of MHE-related cognitive impairments.

BACKGROUND:Neonatal hypoxic-ischemic encephalopathy (HIE) diagnosis is confounded by heterogeneous neural injury and metabolic dysfunction. Multi-pool chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) uniquely quantifies amide proton transfer, nuclear Overhauser enhancement, and magnetization transfer signals, providing multi-parametric assessment of HIE pathophysiology. OBJECTIVE:To investigate whether multi-pool CEST MRI can serve as a molecular-specific biomarker for histopathological alterations in HIE and assess its efficacy in grading disease severity. MATERIALS AND METHODS:This prospective study included 20 neonates with HIE and 42 age-matched controls undergoing 3.0-T CEST MRI. Imaging data were spatially normalized to a neonatal atlas for region-specific analysis (caudate, putamen, thalamus, pallidum, amygdala, hippocampus). Group differences in CEST signals (amide proton transfer, nuclear Overhauser enhancement, magnetization transfer) were analyzed via Wilcoxon tests, with diagnostic performance evaluated through receiver operating characteristic analysis. RESULTS:Compared to controls, HIE neonates showed significant reductions in amide proton transfer (bilateral putamen, right hippocampus/pallidum/amygdala, left thalamus/caudate), nuclear Overhauser enhancement (left thalamus/caudate/putamen), and magnetization transfer signals (bilateral thalamus/pallidum/putamen, left caudate; all P<0.05). Subgroup analysis revealed progressive metabolic decline: moderate-to-severe HIE exhibited further amide proton transfer reduction in the right thalamus, nuclear Overhauser enhancement decreases in bilateral hippocampus, and magnetization transfer decreases in left hippocampus/thalamus compared to mild cases (all P<0.05). Notably, conventional amide proton transfer-weighted imaging showed no significant changes, as the reduction in amide proton transfer signal was offset by a concurrent decrease in the nuclear Overhauser enhancement, highlighting the superiority of multi-pool analysis. Left hippocampal nuclear Overhauser enhancement demonstrated exceptional severity discrimination (area under curve (AUC)=0.96), while a multi-region integrated model achieved perfect staging accuracy (AUC=1.00). CONCLUSION:Multi-pool CEST MRI effectively captures histopathological changes in neonatal HIE, with left hippocampal nuclear Overhauser enhancement emerging as a precise biomarker for severity stratification. The combined dynamics of amide proton transfer, nuclear Overhauser enhancement, and magnetization transfer signals provide noninvasive insights into metabolic-pathological correlations, highlighting its transformative potential for early diagnosis and targeted therapeutic monitoring.

Purpose: This study aimed to develop a reliable whole-brain multi-parameter CEST imaging sequence at 3T. By overcoming the limitations of existing imaging techniques, such as low SNR, image distortion, and magnetic susceptibility artifacts, this research intended to facilitate clinical research on brain diseases. Methods: A whole-brain single-shot CEST sequence with True FISP readout,also called bSSFP was designed. The sequence included a pre-saturation module followed by a fast True FISP readout. The four-angle method was used to acquire B0, rB1, and T1 maps for CEST data correction. MRI experiments were carried out on five healthy volunteers using a 3T whole-body MRI system. Data processing involved motion correction, deep-learning denoising, B0 correction, neural network B1 correction, and four-pool Lorentz fitting. One participant underwent three scans over three days to calculate the coefficient of variation of CEST metrics in different brain regions and nuclei. Results: The CEST contrast of MTRLD and AREX with B1 correction, incorporating APT, NOE, and MT effects, was obtained within 9 minutes. Neural network B1 correction not only reduced the relative error of CEST images but also eliminated the inhomogeneous spatial distribution related to the B1 field. The coefficient of variation of CEST metrics in most brain regions was below 10%. Notably, no banding artifacts or magnetic susceptibility artifacts were observed, and the SAR value was within an acceptable range. Conclusion: Homogeneous, unbiased, multi-parameter whole-brain CEST imaging can be achieved within 9 minutes at 3T using a single-shot True FISP readout. This sequence enables rapid acquisition of high-SNR CEST images free from banding artifacts and magnetic susceptibility artifacts, making it suitable for clinical multi-parameter CEST imaging applications.

To simultaneously fit multiple-pool effects, spectrally selective 3D CEST imaging typically requires single-shot readouts to save time. However, to date, FLASH and EPI have been the primary pulse sequences used for this purpose. They suffer from low SNR or image distortion related to B0 field inhomogeneity. In this work, we developed a 3D single-shot CEST sequence using true fast imaging with steady-state precession (True FISP) readout, also known as bSSFP, and optimized the scanning parameters through simulations. The performance of the CEST sequence was validated using an egg white phantom, ten healthy volunteers, and a patient with a brain tumor on a 3T human scanner. Subsequently, the proposed CEST sequence using True FISP was compared with the commonly used FLASH-based CEST sequence, focusing on SNR and image contrast, while maintaining identical pre-saturation modes, repetition time, echo time and scan time. In the simulation experiments, the maximum CEST signal obtained from the True FISP was significantly greater than that obtained from the FLASH sequence. In the egg white phantom, the SNRs of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effect images obtained from the True FISP were 68.3

Chronic kidney disease (CKD) is an increasing global health problem, resulting in gradual loss of renal function and irreversible renal injury. The noninvasive detection, monitoring, and timely intervention of CKD might benefit the patients' prognosis. This study aims to assess renal functional injury in CKD patients by using magnetic resonance imaging (MRI) of quantitative susceptibility mapping (QSM). One hundred thirty-four consecutive CKD patients with stage (S) 1-5 and 28 healthy volunteers (HVs) underwent MRI to obtain renal susceptibility values and renal volumes. Clinical information and serum biomarkers were collected. Differences in susceptibility values and renal volumes were compared among HVs and CKD patients. Correlations between susceptibility values, renal volumes, and clinical indicators were analyzed. The performance of QSM in discriminating HVs, S1-2, and S3-5 CKD patients was evaluated using areas under the curve (AUCs). Susceptibility values were significantly lower in CKD S3-5 patients than in both HVs and CKD S1-2 patients, and lower in CKD S1-2 patients than in HVs (all p < 0.05). No significant difference in renal volumes was found among HVs, CKD S1-2, and S3-5 patients (p = 0.117). Significant correlations were observed between estimated glomerular filtration rate (eGFR) and renal volumes (r = 0.296, p < 0.001), and between eGFR and susceptibility values (r = 0.579, p < 0.001). Susceptibility values were significant for discriminating patients with CKD S1-2 from HVs (AUC = 0.698, p < 0.001), S3-5 from HVs (AUC = 0.896, p < 0.001), and S3-5 from S1-2 (AUC = 0.701, p < 0.001). Therefore, QSM was feasible for assessing renal functional injury in CKD patients. The QSM parameter exhibits potential values in differentiating HVs, CKD S1-2, and S3-5 patients.

To simultaneously fit multiple-pool effects, spectrally selective 3D chemical exchange saturation transfer (CEST) imaging typically requires single-shot readouts to save time. However, to date, fast low angle shot (FLASH) and echo planar imaging (EPI) have been the primary pulse sequences used for this purpose. They suffer from low signal-to-noise ratio (SNR) or image distortion related to B0 field inhomogeneity. In this work, we developed a 3D single-shot CEST sequence using true fast imaging with steady-state precession (True FISP) readout, also known as balanced steady state free precession (bSSFP), and optimized the scanning parameters through simulations. The performance of the CEST sequence was validated using an egg white phantom, 10 healthy volunteers, and two patients with brain tumors on a 3T human scanner. Subsequently, the proposed CEST sequence using True FISP was compared with the commonly used FLASH-based CEST sequence, focusing on SNR and image contrast, while maintaining identical pre-saturation modes, repetition time, echo time, and scan time. In the simulation experiments, the maximum CEST signal obtained from the True FISP was significantly greater than that obtained from the FLASH sequence. In the egg white phantom, the SNRs of amide proton transfer-weighted (APTw) and nuclear Overhauser enhancement (NOE) effect images obtained from the True FISP were 68.3% and 57.0% higher than those obtained from the FLASH sequence, respectively. In healthy volunteers, saturated images collected with the True FISP sequence at 3.5 ppm showed an approximately 84% increase in mean temporal SNR compared to those collected with the FLASH sequence. Compared to the FLASH sequence, the CEST images obtained from the True FISP sequence could display more detailed brain tissue structures of both normal individuals and patients with brain tumors. Therefore, due to the high SNR inherent in the sequence, True FISP has the potential to be used for fast and high-quality 3D image readout of CEST contrasts in clinical applications.

BACKGROUND AND OBJECTIVES:Parkinson disease (PD) patients with motor complications are often considered for deep brain stimulation (DBS) surgery. Predicting symptom improvement to separate DBS responders and nonresponders remains an unmet need. Currently, DBS candidacy is evaluated using the levodopa challenge test (LCT) to confirm dopamine responsiveness and diagnosis. However, prediction of DBS success by measuring presurgical symptom improvement associated with levodopa dosage changes is highly problematic. Quantitative susceptibility mapping (QSM) is a recently developed MRI method that depicts brain iron distribution. As the substantia nigra and subthalamic nuclei are well visualized, QSM has been used in presurgical planning of DBS. Spatial features resulting from iron distribution in these nuclei have been previously linked with disease progression and motor symptom severity. Given its clear target depiction and prior findings regarding susceptibility and PD, this study demonstrates the technical feasibility of predicting DBS outcomes from presurgical QSM. METHODS:A novel presurgical QSM radiomics approach using a regression model is presented to predict DBS outcome according to spatial features in QSM deep gray nuclei. To overcome limited and noisy training data, data augmentation using label noise injection or "compensation" was used to improve outcome prediction of the regression model. The QSM radiomics model was evaluated on 67 patients with PD who underwent DBS at 2 medical centers. RESULTS:The QSM radiomics model predicted DBS improvement in the Unified Parkinson Disease Rating Scale at Center 1 and Center 2 with Pearson correlation , ( ) and , ( ), respectively. LCT failed to predict DBS improvement at Center 1 and Center 2 with Pearson correlation ( ) and ( ), respectively. CONCLUSION:QSM radiomics has potential to accurately predict DBS outcome in treating patients with PD, offering a valuable alternative to the time-consuming and low-accuracy LCT.

BACKGROUND AND PURPOSE:This study aims to comprehensively assess microstructural abnormalities in both gray matter (GM) and white matter (WM) in patients with moyamoya disease (MMD) using neurite orientation dispersion and density imaging (NODDI). The analysis integrates GM-based and tract-based spatial statistics (GBSS and TBSS, respectively). METHODS:Diffusion-weighted imaging was performed on 26 healthy controls and 15 patients with MMD. NODDI metrics-including the neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)-as well as diffusion tensor imaging (DTI) parameters-fractional anisotropy and mean diffusivity (MD)-were estimated and compared using GBSS and TBSS approaches. RESULTS:The analysis revealed significant microstructural alterations in both GM and WM among patients with MMD. In GM, reduced ODI was observed in multiple regions, including areas associated with the default mode network, executive control network, visual cortex, auditory cortex, sensorimotor cortex, and insula. In WM, decreased NDI and increased ISOVF were identified, predominantly in the corpus callosum, corona radiata, and bilateral frontal and parietal lobes. Although both DTI and NODDI metrics showed similar spatial distribution patterns of WM changes, the alterations detected by NODDI were more widespread. This suggests that NODDI may provide superior sensitivity for identifying microstructural changes associated with MMD. CONCLUSION:The integration of NODDI with GBSS and TBSS enhances the detection of cerebral microstructural alterations in MMD. These findings highlight the potential of NODDI-based metrics as valuable imaging biomarkers for improving diagnostic accuracy in MMD.

Cerebral iron deposition is a pathological hallmark of Parkinson's disease. Notably, Parkinson's disease patients exhibit the characteristic neuroimaging features of enlarged choroid plexus volume (CPV) and diminished glymphatic function. While previous research has focused on potential iron influx dysregulation in Parkinson's disease, the critical question of whether impaired iron clearance stemming from choroid plexus and glymphatic system dysfunction constitutes a key mechanism underlying pathological iron accumulation remains unexplored. Therefore, the aim of this study was to investigate the relationship between cerebral iron deposition and glymphatic dysfunction in Parkinson's disease, and explored its clinical relevance. We hypothesized that impaired glymphatic clearance contributes to pathological iron accumulation in Parkinson's disease. This cross-sectional study enrolled 65 patients with mild-to-moderate Parkinson's disease and 38 age- and sex-matched healthy controls. Multimodal MRI was used to assess the CPV, diffusion tensor imaging analysis along the perivascular space (ALPS) index (indirectly reflecting glymphatic function) and quantitative susceptibility mapping-derived iron levels. The clinical evaluations included motor, cognitive and psychiatric assessments. Statistical analyses compared group differences, correlations, mediation effects and diagnostic performance via receiver operating characteristic analysis. Compared to healthy controls, Parkinson's disease patients exhibited bilateral CPV enlargement (P < 0.01), reduced ALPS indices (P < 0.05) and elevated iron deposition in the substantia nigra, red nucleus and putamen (P < 0.05). CPV negatively correlated with ALPS index (left hemisphere: r = -0.305, P = 0.014; right hemisphere: r = -0.357, P = 0.004). Notably, the degree of glymphatic dysfunction, manifested by either choroid plexus enlargement or a reduced ALPS index, was significantly correlated with regional iron deposition patterns, especially between the CPV and substantia nigra iron deposition (left hemisphere: r = 0.236, P = 0.029; right hemisphere: r = 0.233, P = 0.031). Mediation analysis revealed that ALPS and putamen iron deposition-mediated CPV affected daily living impairments and psychiatric symptoms. A comprehensive diagnostic model integrating neuroimaging, cognitive and psychiatric variables achieved near-perfect discrimination for mild-to-moderate Parkinson's disease (area under the receiver operating characteristic curve = 0.972, sensitivity = 100%, specificity = 97.4%). In conclusion, our results suggest that CPV enlargement and reduced ALPS index are closely linked to pathological iron deposition in Parkinson's disease. These biomarkers correlate with motor deficits, cognitive decline and psychiatric symptoms, highlighting their roles in disease progression. The integrated diagnostic model demonstrated exceptional accuracy, advocating multimodal approaches for Parkinson's disease management. These findings suggest that glymphatic modulation and iron chelation are potential therapeutic targets that warrant further longitudinal validation.

BACKGROUND AND HYPOTHESIS:Social anhedonia is a core feature of schizotypy and correlates significantly with social functioning and range adaptation. Range adaptation refers to representing a stimulus value based on its relative position in the range of pre-experienced values. This study aimed to examine the resting-state neural correlates of range adaptation and its associations with social anhedonia and social functioning. STUDY DESIGN:In study 1, 60 participants completed resting-state magnetic resonance spectroscopy and fMRI scans. Range adaptation was assessed by a valid effort-based decision-making paradigm. Self-reported questionnaires was used to measure social anhedonia and social functioning. Study 2 utilized 26 pairs of participants with high (HSoA) and low levels of social anhedonia (LSoA) to examine the group difference in range adaptation's neural correlates and its relationship with social anhedonia and social functioning. An independent sample of 40 pairs of HSoA and LSoA was used to verify the findings. STUDY RESULTS:Study 1 showed that range adaptation correlated with excitation-inhibition balance (EIB) and ventral prefrontal cortex (vPFC) functional connectivity, which in turn correlating positively with social functioning. Range adaptation was specifically determined by the EIB via mediation of ventral-medial prefrontal cortex functional connectivities. Study 2 found HSoA and LSoA participants exhibiting comparable EIB and vPFC connectivities. However, EIB and vPFC connectivities were negatively correlated with social anhedonia and social functioning in HSoA participants. CONCLUSIONS:EIB and vPFC functional connectivity is putative neural correlates for range adaptation. Such neural correlates are associated with social anhedonia and social functioning.

Purpose: To develop and validate a framework for rapid, accurate, and reproducible whole-brain, multi-pool chemical exchange saturation transfer (CEST) imaging at 3T, addressing challenges of long acquisition times and confounding factors. Methods: A single-shot 3D true fast imaging with steady-state precession (True FISP) sequence was optimized for whole-brain multi-pool CEST. Rapid B0, B1, and T1 mapping was performed using a dual-echo modified four-angle method. A feed-forward neural network was developed for rapid B1 correction, trained against the conventional multi-power method. The apparent exchange-dependent relaxation (AREX) metric was used to correct for T1 and magnetization transfer (MT) effects. The framework was validated in phantoms and healthy human subjects (N=8), including a test-retest reproducibility assessment. Results: The True FISP sequence yielded high-quality, whole-brain images with minimal artifacts and distortion in a clinically feasible scan time ( 9 minutes). Phantom studies confirmed the effectiveness of B1 correction (coefficient of variation [CV] for MT_MTRLD decreased from 22.49