BACKGROUND/OBJECTIVES:Liver fibrosis, if left untreated, can lead to cirrhosis and cancer. The current standard liver biopsy for fibrosis staging is invasive and prone to risks of complication. The objective of this study was to develop a new noninvasive method to quantify fibrosis using diamagnetic susceptibility sources generated from multi-echo gradient echo (mGRE) data with both magnitude decay R2* modeling and phase QSM modeling. METHODS:mGRE data of ex vivo liver explants was processed with fat-water separation and then susceptibility source separation. Negative susceptibility was used to measure diamagnetic fibrosis. In 20 formalin-fixed liver explant sections, negative susceptibility maps were compared with other MRI parameters against pathology for fibrosis staging. RESULTS:The correlation between the negative susceptibility sources and the fibrosis stages was evaluated with Spearman coefficients. Negative susceptibility differentiated (i) no or mild fibrosis (stages F0 to F1) from moderate-to-advanced fibrosis (stages F2 to F3; p = 0.0025), (ii) stages F2 to F3 from cirrhosis (stage F4; p = 0.021), and (iii) no-to-moderate fibrosis (stages F0 to F2) from advanced fibrosis or cirrhosis (stages F3 to F4) with a sensitivity of 90%, a specificity of 90%, and a 0.88 Receiver Operating Characteristic Area Under the Curve (AUC) (p = 0.0017). CONCLUSIONS:For staging fibrosis, negative susceptibility was superior to other MRI parameters, including R2*, QSM, and PDFF. Negative susceptibility sources were positively correlated with the fibrosis stage (r = 0.60). Negative susceptibility could be valuable for MRI staging in liver fibrosis.

Introduction:Transgenic Alzheimer's (AD) mouse models and post mortem studies have shown that tau pathology disrupts the mitochondrial electron transport chain and results in mitochondrial damage and synaptic dysfunction. We assessed whether magnetic resonance imaging (MRI)-derived measures of oxygen metabolism, oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen (CMRO2) were associated with tau deposition in vivo. Methods:We assessed tau using 18F-MK-6240 positron emission tomography and CMRO2/OEF using multi-echo gradient-recalled echo with QQ processing, as well as pseudo-continuous arterial spin-labeling MRI in cognitively normal (CN) elderly and subjects with mild cognitive impairment/AD (N = 42). Associations among imaging measures were evaluated across cortical lobes, including comparisons between regions with and without tau deposition. Results:Across all subjects, higher tau standardized uptake value ratio (SUVR) was associated with lower cerebral blood flow (CBF) and CMRO2. Tau SUVR was negatively associated with Montreal Cognitive Assessment scores, whereas OEF, CBF, and CMRO2 were positively associated. Within subjects, CMRO2 was lower in tau-positive temporal regions in both CN and MCI/AD subjects, and CBF was lower in tau-positive temporal regions in CN subjects. Discussion:MRI-derived CBF and CMRO2 were associated with regional tau deposition, particularly in the temporal lobe, which suggests they have potential as non-invasive markers of metabolic alterations accompanying tau pathology.

BACKGROUND:Tricuspid regurgitation (TR) leads to systemic venous congestion and congestive hepatopathy, but conventional TR imaging parameters incompletely capture systemic consequences. Hepatic extracellular volume fraction (ECV) on cardiac magnetic resonance T1 mapping may reflect hepatic tissue remodeling and provide prognostic information beyond conventional risk markers. METHODS:Consecutive patients with moderate or greater TR who underwent cardiac magnetic resonance with hepatic T1 mapping were studied. Hepatic ECV was calculated using pre- and postcontrast T1 values and hematocrit. Patients were stratified by hepatic ECV tertiles. The primary end point was all-cause mortality. RESULTS:Among 234 patients (mean age, 65.6±15.8 years; 46.2% men), mean hepatic ECV was 37.7±9.0%, with tertile cutoffs at 32.5% and 41.3%. Higher hepatic ECV tertiles were associated with worse biventricular function and greater TR severity. Right ventricular ejection fraction decreased across tertiles (48.2% versus 48.5% versus 40.3%, P<0.001), while right ventricular end-diastolic volume index increased (107.4 versus 105.4 versus 127.4 mL/m², P<0.001). The prevalence of severe TR (regurgitant fraction ≥50%) increased from 10.9% (mean) across tertiles 1 and 2 to 29.5% in tertile 3 (P<0.001). During a mean follow-up of 2.2 years, 43 (18.4%) deaths occurred. Mortality increased across hepatic ECV tertiles: 12.8% versus 11.5% versus 30.8% (P=0.002 for trend). Kaplan-Meier analysis showed 3-year survival rates of 88%, 89%, and 57% across tertiles 1, 2, and 3, respectively. In multivariable Cox regression adjusting for age, right ventricular dysfunction, and severe TR, hepatic ECV tertiles remained independently predictive of mortality (hazard ratio, 1.62 [95% CI, 1.06-2.48]; P=0.027). Forward stepwise analysis yielded significant incremental prognostic value beyond traditional TR risk factors, improving model discrimination from χ²=24.4 to 30.1 (P=0.02). CONCLUSIONS:Hepatic ECV is a novel prognostic marker that provides incremental risk stratification in TR and has potential to impact therapeutic decision-making in the era of expanded treatment options for TR.

Purpose: This study aims to assess the repeatability and reproducibility of qBOLD+QSM (QQ) oxygen extraction fraction (OEF) measurements across 3 and 1.5 T. Methods: The effects of field strength on signal to noise ratio (SNR) and OEF sampling time were experimentally assessed in 14 healthy subjects using repeated scans performed at 3 and 1.5 T. Whole-brain and regional OEF values were analyzed using Bland-Altman and correlation between repeated scans and across field strengths. Results: Whole-brain and regional OEF values showed strong agreement between repeated scans at the same field strength, with minimal differences (<= 0.74%) and high correlation (r> 0.92). Across field strengths, comparisons similarly showed small mean differences (<= 1.51%) and strong correlations (r> 0.95). Conclusion: QQ-OEF has good repeatability and reproducibility at both 3 and 1.5 T. Good performance at 1.5 T may arise from accurate noise modeling and longer sampling times at lower field strengths.

Purpose: To develop a deep neural network-based, AIF-free, perfusion estimation method (QTMnet) for improved performance on glioma classification. Methods: A globally defined arterial input function (AIF) is needed to recover perfusion parameters in the two-compartment exchange model (2CXM). We have developed Quantitative Transport Mapping (QTM) to create an AIF-independent estimation method. QTM estimation can be formulated using deep neural networks trained on synthetic DCE-MRI data (QTMnet). Here, we provide a fluid mechanics-based DCE-MRI simulation with exchange between the capillaries and extravascular extracellular space. We implemented tumor ROI generation to morphologically characterize tissue perfusion. We compared our QTMnet implementation with 2CXM on 30 glioma human subjects, 15 of which had low-grade gliomas, and 15 with high-grade glioblastomas. Results: QTMnet outperforms (best AUC: 0.973) traditional 2CXM (best AUC: 0.911) in a glioma grading task. Conclusion: The AIF-independent QTMnet estimation provides a quantitative delineation between low-grade and high-grade gliomas. ### Competing Interest Statement Y.W. and P.S are coinventors on QSM-related patents owned by Cornell University and have ownership shares in MedImageMetric, LLC. ### Funding Statement This work was supported in part by NIH grants R01DK116126, R01EB034755 ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board of Weill Cornell Medicine gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present work are contained in the manuscript

Objective: The traditional kinetic model (TKM) for perfusion quantification from arterial spin labeling (ASL) assumes a global arterial input function (AIF) and uniform plug flow of spin label transport. This AIF assumption causes systematic errors of overestimating the local arterial input to a voxel, mainly due to the lack of flow velocity dispersion across and along vessels, resulting in underestimation of cerebral blood flow (CBF). Recently developed quantitative transport mapping (QTM) is free of and overcoming AIF problems. We present QTM deep neural network (QTMnet) for quantifying CBF. Methods: QTMnet was trained on synthesized multi-delay ASL data from multiscale vascular fluid mechanics simulations for CBF quantification from ASL data. QTMnet was validated against in-silico truth using simulated brain ASL data and against phase-contrast (PC) measured total brain flow using in vivo brain ASL data; QTMnet was also compared to TKM for CBF quantification from ASL. Results: QTMnet reduced the CBF underestimation in TKM by approximately 3-4X: Against the in-silico ground truth, the TKM underestimation was reduced from TKM single/multiple delay biases of -12.80/-9.73 mL/100g/min to QTMnet bias of -3.96 mL/100g/min; Against average whole brain PC flow, the TKM underestimation was reduced from single/multiple delay biases of -16.0±3.1/-13.5±3.3 mL/100g/min to QTMnet bias of -3.31±2.7 mL/100g/min. Conclusion: QTMnet is a promising approach for CBF quantification from ASL. QTMnet demonstrates higher accuracy in both in-silico and in-vivo ASL data compared to TKM. Significance: Fluid-mechanics-based QTMnet improves CBF quantification from ASL data.

BACKGROUND:Iron accumulation in the substantia nigra (SN) is a hallmark of Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) including source separation can generate maps of total susceptibility χ, paramagnetic or positive susceptibility [Formula: see text] likely dominated by tissue iron, and diamagnetic or negative susceptibility [Formula: see text] reflecting myelin and other sources. PURPOSE:To compare χ, [Formula: see text], and [Formula: see text] for tracking SN longitudinal changes in PD and for correlating with dopaminergic PET measures and cognitive decline. MATERIALS AND METHODS:This longitudinal study included 32 patients with PD (mean age, 65.88 ± 8.47 years) who underwent 3T MRI with 3D multi-echo gradient-echo (mGRE) and dynamic 11C-N-(3-iodoprop-2E-enyl)-2β-carbomethoxy-3β-(4-methylphenyl) nortropane (PE2I) PET between August 2018 and April 2024. χ, [Formula: see text], and [Formula: see text] maps were reconstructed from mGRE data using the MEDI algorithm with susceptibility source separation. Dopamine transporter binding potential (BP) images were estimated from dynamic PET using a deep learning based kinetic model. Paired t tests, linear regression, and Pearson correlation analyses with Bonferroni correction were performed, with P < .05 considered significant. RESULTS:Both χ and [Formula: see text] from QSM revealed significant longitudinal susceptibility increases in the rostral and caudal SN (Bonferroni-corrected P < .05), with [Formula: see text] showing larger effect sizes (t = 9.99 vs 2.65 for the caudal SN). The left putaminal BP from PET significantly decreased at follow-up (P < .05). The longitudinal increase in [Formula: see text] within the rostral SN strongly correlated with the reduction in putaminal BP (r = - 0.60, P = .005, Bonferroni-corrected), whereas χ showed no significant association. Higher baseline [Formula: see text] values in the rostral and caudal SN predicted greater longitudinal cognitive decline (P = .01-.02, Bonferroni-corrected). Subregional analyses confirmed significant [Formula: see text] increases predominantly in the rostral-anterior SN. No significant change or correlation was observed with [Formula: see text] mapping at the SN. CONCLUSION:Positive susceptibility [Formula: see text] mapping showed larger longitudinal effect sizes for SN changes and stronger associations with dopaminergic PET decline and cognitive deterioration than to total susceptibility χ. These findings support [Formula: see text] mapping as a biologically informative MRI measure for the longitudinal assessment of SN changes in PD.

Hippocampal iron, as measured with imaging, biofluids, and histology, has been associated with Alzheimer's disease (AD), its progression, and potentially neuroinflammatory disease mechanisms. With its high sensitivity to tissue magnetic susceptibility, 7T MRI offers the potential to detect abnormal iron deposition within the hippocampus of AD and mild cognitive impairment (MCI) brains in vivo , especially when combined with dedicated methods such as quantitative susceptibility mapping (QSM). We aim to utilize ultra-high resolution 7T MRI and explore conventional and novel source-separated QSM to quantify hippocampal iron deposition in AD, providing insights into the involvement of brain iron in disease progression. We conducted 7T MRI on 19 ADRC human volunteers, including 8 healthy controls (HC), 6 individuals with MCI, and 5 with AD. MR images were acquired using a GE MR950 scanner utilizing optical prospective motion correction. Automatic Segmentation of Hippocampal Subfields generated segmentations of the subiculum and CA1 (Figure 1), which were manually edited in a diagnosis-blind manner, followed by one-pixel erosion. R2* and source-separated QSM (positive susceptibility sources QSM-χ + , negative QSM-χ - ) were computed using MEDI and averaged within the subiculum and CA1. Blinded image quality assessments were conducted. Memory composite scores were correlated with iron measurements available in 18 participants. Nonparametric tests quantified hyperintensity gradation in hippocampal QSM/R2* images and assessed the relationship between memory scores and QSM/R2*. We found a significant ordinal increase of R2* according to participant diagnoses (AD>MCI>HC) in the subiculum ( p  = 0.0445) and combined subiculum-CA1 ( p  = 0.0232) subfields (examples of negative and positive findings in Figure 2, boxplots in Figure 3-top), suggestive of increased iron. No significant differences were seen in QSM without source separation, QSM-χ + , or QSM-χ - . However, a significant negative association between memory scores and QSM-χ + was observed in CA1 ( p  = 0.0351, Figure 3-bottom). We found elevated iron in the subiculum-CA1 hippocampal subregions in vivo in MCI and AD using 7T MRI, correlating with degraded memory performance. Our noninvasive visualization of microscopic hippocampal iron deposition utilizing ultra-high resolution 7T MRI in vivo corroborates post-mortem data. This translational finding could serve as a novel neuroimaging biomarker for iron-based AD pathology and inflammation.

PURPOSE:Differential blood oxygenation between the right and left heart (ΔSO2) is an indicator of cardiovascular function currently assessed in clinical practice by invasive right heart catheterization. Cardiac MRI can non-invasively quantify ΔSO2 with quantitative susceptibility mapping (QSM) using a prospective navigator gated 3D cartesian acquisition. However, this method suffers from long acquisition time and reduced robustness. Here, a free-breathing cardiac QSM using spiral sampling and deep learning motion compensation is proposed. METHODS:A retrospective self-gated stack-of-spirals multi-echo gradient echo sequence is combined with implicit neural representation (INR) learning for image reconstruction. The self-gating signals measure superior-inferior cardiac and respiratory motion thus allowing k-space binning. Using a physics-informed signal model and the spatiotemporal coordinate input, INR infers motion fields as well as motion-corrected water, fat, and field maps. Then, QSM and ΔSO2 are accordingly computed. Data were acquired in 10 healthy subjects. For comparison, a free-breathing prospective navigator ECG-triggered Cartesian acquisition (NAV) was performed. RESULTS:INR reconstructed motion-corrected water, fat, R2* and field maps were successfully obtained in all subjects. INR-QSM showed superior image quality (p = 0.0067) and equivalent ΔSO2 measurement in the heart (r = 0.74, p < 0.001; 1.07% ± 3.52% bias/limits of agreement) compared to the reference NAV-QSM. CONCLUSION:This study demonstrated the feasibility of INR for compensation of cardiac and respiratory motion in free-breathing 3D cardiac QSM.

BACKGROUND AND PURPOSE:Quantitative susceptibility mapping is an emerging method for characterizing tissue composition and studying myelination and iron deposition. However, accurate assessment of myelin and iron content in the neonate brain using this method is challenging because these 2 susceptibility sources of opposite signs (myelin, negative; iron, positive) occupy the same voxel, with minimal and comparable content in both sources. In this study, susceptibilities were measured in the healthy neonate brain using susceptibility source separation. MATERIALS AND METHODS:Sixty-nine healthy neonates without clinical indications were prospectively recruited for MRI. All neonates underwent gradient-echo imaging for quantitative susceptibility mapping. Positive (paramagnetic) and negative (diamagnetic) susceptibility sources were separated using additional information from R2* with linear modeling performed for the neonate brain. Average susceptibility maps were generated by normalizing all susceptibility maps to an atlas space. Mean regional susceptibility measurements were obtained in the cortical GM, WM, deep GM, caudate nucleus, putamen, globus pallidus, thalamus, and the 4 brain lobes. RESULTS:A total of 65 healthy neonates (mean postmenstrual age, 42.8 [SD, 2.3] weeks; 34 females) were studied. The negative susceptibility maps visually demonstrated high signals in the thalamus, brainstem, and potentially myelinated WM regions, whereas the positive susceptibility maps depicted high signals in the GM compared with all WM regions, including both myelinated and unmyelinated WM. The WM exhibited significantly lower mean positive susceptibility and significantly higher mean negative susceptibility than cortical GM and deep GM. Within the deep GM, the thalamus showed a significantly lower mean negative susceptibility than the other nuclei, and the putamen and globus pallidus showed significant associations with neonate age in positive and/or negative susceptibility. Among the 4 brain lobes, the occipital lobe showed a significantly higher mean positive susceptibility and a significantly lower mean negative susceptibility than the frontal lobe. CONCLUSIONS:This study demonstrates regional variations and temporal changes in positive and negative susceptibilities of the neonate brain, potentially associated with myelination and iron deposition patterns in normal brain development. It suggests that quantitative susceptibility mapping with source separation may be used for early identification of delayed myelination or iron deficiency.

PURPOSE:To develop a multiparametric free-breathing three-dimensional, whole-liver quantitative maps of water T1, water T2, fat fraction (FF) and R2*. METHODS:A multi-echo 3D stack-of-spiral gradient-echo sequence with inversion recovery and T2-prep magnetization preparations was implemented for multiparametric MRI. Fingerprinting and a neural network based on implicit neural representation (FINR) were developed to simultaneously reconstruct the motion deformation fields, the static images, perform water-fat separation, and generate T1, T2, R2*, and FF maps. FINR performance was evaluated in 10 healthy subjects by comparison with quantitative maps generated using conventional breath-holding imaging. RESULTS:FINR consistently generated sharp images in all subjects free of motion artifacts. FINR showed minimal bias and narrow 95% limits of agreement for T1, T2, R2*, and FF values in the liver compared with conventional imaging. FINR training took about 3 h per subject, and FINR inference took less than 1 min to produce static images and motion deformation fields. CONCLUSIONS:FINR is a promising approach for 3D whole-liver T1, T2, R2*, and FF mapping in a single free-breathing continuous scan.

Motivation: Tau deposition is an important pathological process in aging and AD/MCI. Goal(s): Analyze oxygen metabolism and association with Tau burden. Approach: We mapped CMRO2 with ASL based CBF and mGRE based OEF in an AD cohort. We compared the spatial distribution and association with Tau burden measured with 18F-MK-6240 PET. Results: We found that a higher Tau deposition is associated with lower CMRO2 at both subject and regional levels, especially in cortical temporal and parietal lobes. Oxygen metabolism measured with MRI is a potential biomarker in aging and AD and opens opportunities for future research of tau accumulation and metabolism dysfunction. Impact: Negative association observed between tau deposition and oxygen metabolism at both subject and regional levels extend understanding of the neurotoxity of tau accumulation, potentially helps to the development of tau targeted disease modifiers.

Myelin integrity is central to healthy brains and is increasingly shown to be compromised in neurodegenerative diseases. Diffusion- and susceptibility-based MRI metrics can detect myelin changes. We show advanced diffusion and susceptibility metrics can detect degenerative myelin changes in ex vivo AD and HD mouse models. AD mice included 2 groups: 8-month-old male hAPP (Lond/Swe mutations, n=4) and wild-type (WT, n=4). HD mice included 3 groups: 12-week-old vehicle-treated controls (WT, n=4), R6/2 HD treated for 7 weeks with vehicle (HD, n=4) or LM11A-31 (HD-treated, n=4). After perfusion-fixation and brain extraction, 4-shell diffusion (b=1,2,5,10ms/μm 2 , 100 directions) and multi-echo gradient echo (MGE) MRI (10 echoes, GRE=4-40ms) were performed on a Bruker 7T scanner. We used DESIGNER and MEDI to generate diffusion- and susceptibility-based myelin-sensitive metrics, respectively (diffusion: mean/radial/axial diffusivities -MD/RD/AD, kurtoses -MK/RK/AK, axonal water fraction -AWF; susceptibility: R2*, quantitative susceptibility mapping-QSM) (Figure 1A). Datasets were registered to the Allen Atlas through linear/non-linear transformations using FSL flirt/ANTs (Figure 1B). Median values were derived for two Allen Atlas white matter regions-of-interest -ROIs (corpus callosum and fornix). For AD, scan timing effects were included in a 2-way ANOVA analysis. For HD, two-sample t-tests were performed between the 3 groups. For histological validation, a second set of R6/2 HD brains (WT, HD, HD-treated n=10-13 mice/group) were myelin basic protein (MBP)-stained, and the percent area of striatum immunostaining determined by ImageJ thresholding. AD mice showed increased RD and reduced AWF and RK compared to controls in both ROIs, suggesting a loss of myelinated axons. Susceptibility-based metrics show no clear pattern. HD mice showed an increasing trend in AWF and RK and decreases in RD in both ROIs vs WT, suggesting increased myelination. Interestingly, LM11A-31-treated HD mice showed a significant reversal in RD and AWF. Histologically, myelin immunostaining was increased in the striatum of HD mice, reversed by LM11A-31. Diffusion MRI myelin-sensitive metrics detected possibly compromised myelin in AD mouse white matter (corpus callosum and fornix). In HD mice, both diffusion MRI and histology showed a trend towards increased myelin, which was reversed by LM11A-31 treatment.

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.

BACKGROUNDBlood donation increases the risk of iron deficiency, but its effect on brain iron, myelination, and neurocognition remains unclear.METHODSThis ancillary study enrolled 67 iron-deficient blood donors, 19-73 years of age, participating in a double-blind, randomized trial. After donating blood, positive and negative susceptibility were measured using quantitative susceptibility mapping (QSM) MRI to estimate brain iron and myelin levels, respectively. Furthermore, neurocognitive function was evaluated using the NIH Toolbox, and neural network activation patterns were assessed during neurocognitive tasks using functional MRI (fMRI). Donors were randomized to i.v. iron repletion (1 g iron) or placebo, and outcome measures repeated approximately 4 months later.RESULTSIron repletion corrected systemic iron deficiency and led to trends toward increased whole brain iron (P = 0.04) and myelination (P = 0.02), with no change in the placebo group. Although overall cognitive performance did not differ significantly between groups, iron-treated participants showed improved engagement of functional neural networks (e.g., memory pattern activation during speed tasks, P < 0.001). Brain region-specific changes in iron and myelin correlated with cognitive performance: iron in the putamen correlated with working memory scores (P < 0.01), and thalamic myelination correlated with attention and inhibitory control (P < 0.01).CONCLUSIONIron repletion in iron-deficient blood donors may influence brain iron, myelination, and function, with region-specific changes in iron and myelination linked to distinct cognitive domains.REGISTRATIONClinicalTrials.gov NCT02990559FUNDINGThis work was funded by the NIH.

PURPOSE:To evaluate the accuracy of a deep learning-based quantitative transport mapping method (QTMnet) for measuring total tissue perfusion. METHODS:QTMnet obtains tissue perfusion parametric maps from dynamic contrast-enhanced MRI images by training on simulated data. This data uses synthetic arterial and venous vasculature geometries with flow based on constrained constructive optimization. Gadolinium contrast agent distribution is governed by the transport-forward problem, allowing us to generate a synthetic concentration spacetime profile for a given flow, blood volume fraction, and boundary condition. Tissue flows determined by QTMnet were compared to those obtained with traditional perfusion quantification (Kety equation with Tofts generalization), which uses a global arterial input function. Their total flow accuracies were validated on explanted porcine livers that were connected to an MR compatible flow pump with specified total flow rate for dynamic contrast-enhanced MRI experiments. RESULTS:The mean total flow error for QTMnet was -0.34% ± 16.21% with range [-24.79%, 23.96%], compared to -35.74% ± 36.30% [-77.28%, 29.87%] for the Kety method. QTMnet provides 72% lower mean absolute error than the Kety method (12.15% vs. 43.21%, a 3.6-fold reduction). CONCLUSION:The fluid mechanics-based QTMnet accurately estimates total tissue flow in liver explants.

To evaluate the potential overestimation of cerebral microbleed (CMB) burden by Quantitative Susceptibility Mapping (QSM) compared to 2D gradient recalled echo (2D GRE), as well as the impact of increased motion degradation due to longer scan times, reduced CMB detection from skull-stripping failures, and the relative visibility of CMBs between techniques. Seventy-nine adult subjects with intracranial hemorrhage underwent same-session brain MRI including 2D GRE and multi-echo GRE for QSM processing, as part of routine clinical care. Images were reviewed by a neuroradiologist and trained research assistant for CMB detection, visibility rating, and anatomical distribution. Motion artifacts and areas of non-visualized brain due to skull-stripping were assessed. Statistical analysis included Wilcoxon signed-rank tests for CMB counts, Mann-Whitney U test for motion assessment, and Fisher’s exact testing for anatomical distribution patterns. QSM showed no significant difference in median CMB counts compared to 2D GRE (1 vs 2, p = 0.175) with strong correlation (r = 0.879, p < 1.65e-26). No significant difference in motion degradation was found between techniques (p = 0.7465). Skull-stripping failures affected only 2