Quantitative susceptibility mapping (QSM): Decoding MRI data for a tissue magnetic biomarker

Multicenter, multivendor validation of liver quantitative susceptibility mapping in patients with iron overload at 1.5 T and 3 T

PURPOSE

To evaluate the repeatability and reproducibility of QSM of the liver via single breath-hold chemical shift-encoded MRI at both 1.5 T and 3 T in a multicenter, multivendor study in subjects with iron overload.

METHODS

This prospective study included four academic medical centers with three different MRI vendors at 1.5 T and 3 T. Subjects with known or suspected liver iron overload underwent multi-echo spoiled gradient-recalled-echo scans at each field strength. A subset received repeatability testing at either 1.5 T or 3 T. Susceptibility andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps were reconstructed from the multi-echo images and analyzed at a single center. QSM-measured susceptibility was compared withR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and a commercial R2-based liver iron concentration method across centers and field strengths using linear regression and F-tests on the intercept and slope. Field-strength reproducibility and test/retest repeatability were evaluated using Bland-Altman analysis.

RESULTS

A total of 155/80 data sets (test/retest) were available at 1.5 T, and 159/70 data sets (test/retest) were available at 3 T. Calibrations across sites were reproducible, with some variability (e.g., susceptibility slope with liver iron concentration ranged from 0.102 to 0.123 g/[mg· $$ \cdotp $$ ppm] across centers at 1.5 T). Field strength reproducibility was good (concordance correlation coefficient = 0.862), and test/retest repeatability was excellent (intraclass correlation coefficient = 0.951).

CONCLUSION

QSM as an imaging biomarker of liver iron overload is feasible and repeatable across centers and MR vendors. It may be complementary withR 2 * $$ {\mathrm{R}}_2^{\ast } $$ as they are obtained from the same acquisition. Although good reproducibility was observed, liver QSM may benefit from standardization of acquisition parameters. Overall, QSM is a promising method for liver iron quantification.

XSIM: A structural similarity index measure optimized for MRI QSM

PURPOSE

The structural similarity index measure (SSIM) has become a popular quality metric to evaluate QSM in a way that is closer to human perception than RMS error (RMSE). However, SSIM may overpenalize errors in diamagnetic tissues and underpenalize them in paramagnetic tissues, resulting in biasing. In addition, extreme artifacts may compress the dynamic range, resulting in unrealistically high SSIM scores (hacking). To overcome biasing and hacking, we propose XSIM: SSIM implemented in the native QSM range, and with internal parameters optimized for QSM.

METHODS

We used forward simulations from a COSMOS ground-truth brain susceptibility map included in the 2016 QSM Reconstruction Challenge to investigate the effect of QSM reconstruction errors on the SSIM, XSIM, and RMSE metrics. We also used these metrics to optimize QSM reconstructions of the in vivo challenge data set. We repeated this experiment with the QSM abdominal phantom. To validate the use of XSIM instead of SSIM for QSM quality assessment across a range of different reconstruction techniques/algorithms, we analyzed the reconstructions submitted to the 2019 QSM Reconstruction Challenge 2.0.

RESULTS

Our experiments confirmed the biasing and hacking effects on the SSIM metric applied to QSM. The XSIM metric was robust to those effects, penalizing the presence of streaking artifacts and reconstruction errors. Using XSIM to optimize QSM reconstruction regularization weights returned less overregularization than SSIM and RMSE.

CONCLUSION

XSIM is recommended over traditional SSIM to evaluate QSM reconstructions against a known ground truth, as it avoids biasing and hacking effects and provides a larger dynamic range of scores.

Multiband accelerated 2D EPI for multi-echo brain QSM at 3 T

PURPOSE

Data for QSM are typically acquired using multi-echo 3D gradient echo (GRE), but EPI can be used to accelerate QSM and provide shorter acquisition times. So far, EPI-QSM has been limited to single-echo acquisitions, which, for 3D GRE, are known to be less accurate than multi-echo sequences. Therefore, we compared single-echo and multi-echo EPI-QSM reconstructions across a range of parallel imaging and multiband acceleration factors.

METHODS

Using 2D single-shot EPI in the brain, we compared QSM from single-echo and multi-echo acquisitions across combined parallel-imaging and multiband acceleration factors ranging from 2 to 16, with volume pulse TRs from 21.7 to 3.2 s, respectively. For single-echo versus multi-echo reconstructions, we investigated the effect of acceleration factors on regional susceptibility values, temporal noise, and image quality. We introduce a novel masking method based on thresholding the magnitude of the local field gradients to improve brain masking in challenging regions.

RESULTS

At 1.6-mm isotropic resolution, high-quality QSM was achieved using multi-echo 2D EPI with a combined acceleration factor of 16 and a TR of 3.2 s, which enables functional applications. With these high acceleration factors, single-echo reconstructions are inaccurate and artefacted, rendering them unusable. Multi-echo acquisitions greatly improve QSM quality, particularly at higher acceleration factors, provide more consistent regional susceptibility values across acceleration factors, and decrease temporal noise compared with single-echo QSM reconstructions.

CONCLUSION

Multi-echo acquisition is more robust for EPI-QSM across parallel imaging and multiband acceleration factors than single-echo acquisition. Multi-echo EPI can be used for highly accelerated acquisition while preserving QSM accuracy and quality relative to gold-standard 3D-GRE QSM.

Motion and temporal B0-shift corrections for QSM and R 2 * mapping using dual-echo spiral navigators and conjugate-phase reconstruction

PURPOSE

To develop an efficient navigator-based motion and temporal B0-shift correction technique for 3D multi-echo gradient-echo (ME-GRE) MRI for quantitative susceptibility mapping (QSM) andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping.

THEORY AND METHODS

A dual-echo 3D stack-of-spiral navigator was designed to interleave with the Cartesian multi-echo gradient-echo acquisitions, allowing the acquisition of both low-echo and high-echo time signals. We additionally designed a novel conjugate phase-based reconstruction method for the joint correction of motion and temporal B0 shifts. We performed numerical simulation, phantom scans, and in vivo human scans to assess the performance of the methods.

RESULTS

Numerical simulation and human brain scans demonstrated that the proposed technique successfully corrected artifacts induced by both head motions and temporal B0 changes. Efficient B0-change correction with conjugate-phase reconstruction can be performed on fewer than 10 clustered k-space segments. In vivo scans showed that combining temporal B0 correction with motion correction further reduced artifacts and improved image quality in bothR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM images.

CONCLUSION

Our proposed approach of using 3D spiral navigators and a novel conjugate-phase reconstruction method can improve susceptibility-related measurements using MR.

High correlation of quantitative susceptibility mapping and echo intensity measurements of nigral iron overload in Parkinson's disease

Quantitative susceptibility mapping (QSM) and transcranial sonography (TCS) offer proximal evaluations of iron load in the substantia nigra. Our prospective study aimed to investigate the relationship between QSM and TCS measurements of nigral iron content in patients with Parkinson's disease (PD). In secondary analyses, we wanted to explore the correlation of substantia nigra imaging data with clinical and laboratory findings. Eighteen magnetic resonance imaging and TCS examinations were performed in 15 PD patients at various disease stages. Susceptibility measures of substantia nigra were calculated from referenced QSM maps. Echogenicity of substantia nigra on TCS was measured planimetrically (echogenic area) and by digitized analysis (echo-intensity). Iron-related blood serum parameters were measured. Clinical assessments included the Unified PD Rating Scale and non-motor symptom scales. Substantia nigra susceptibility correlated with echogenic area (Pearson correlation, r = 0.53, p = 0.001) and echo-intensity (r = 0.78, p < 0.001). Individual asymmetry indices correlated between susceptibility and echogenic area measurements (r = 0.50, p = 0.042) and, more clearly, between susceptibility and echo-intensity measurements (r = 0.85, p < 0.001). Substantia nigra susceptibility (individual mean of bilateral measurements) correlated with serum transferrin saturation (Spearman test, r = 0.78, p < 0.001) and, by trend, with serum iron (r = 0.69, p = 0.004). Nigral echogenicity was not clearly related to serum values associated with iron metabolism. Susceptibility and echogenicity measurements were unrelated to PD duration, motor subtype, and severity of motor and non-motor symptoms. The present results support the assumption that iron accumulation is involved in the increase of nigral echogenicity in PD. Nigral echo-intensity probably reflects ferritin-bound iron, e.g. stored in microglia.

Automatic segmentation and diameter measurement of deep medullary veins

PURPOSE

As one of the pathogenic factors of cerebral small vessel disease, venous collagenosis may result in the occlusion or stenosis of deep medullary veins (DMVs). Although numerous DMVs can be observed in susceptibility-weighted MRI images, their diameters are usually smaller than the MRI resolution, making it difficult to segment them and quantify their sizes. We aim to automatically segment DMVs and measure their diameters from gradient-echo images.

METHODS

A neural network model was trained for DMV segmentation based on the gradient-echo magnitude and phase images of 20 subjects at 7 T. The diameters of DMVs were obtained by fitting measured complex images with model images that accounted for the DMV-induced magnetic field and point spread function. A phantom study with graphite rods of different diameters was conducted to validate the proposed method. Simulation was carried out to evaluate the voxel-size dependence of measurement accuracy for a typical DMV size.

RESULTS

The automatically segmented DMV masks had Dice similarity coefficients of 0.68 ± 0.03 (voxel level) and 0.83 ± 0.04 (cluster level). The fitted graphite-rod diameters closely matched their true values. In simulation, the fitted diameters closely matched the true value when voxel size was ≤ 0.45 mm, and 92.2% of DMVs had diameters between 90 μm and 200 μm with a peak at about 120 μm, which agreed well with an earlier ex vivo report.

CONCLUSION

The proposed methods enabled efficient and quantitative study of DMVs, which may help illuminate the role of DMVs in the etiopathogenesis of cerebral small vessel disease.

Comparison study of quantitative susceptibility mapping with GRAPPA and wave-CAIPI: reproducibility, consistency, and microbleeds detection

PURPOSE

We compared quantitative susceptibility mapping (QSM) with wave-CAIPI 9 × (QSM_WC9 ×) with reference standard QSM with GRAPPA 2 × (QSM_G2 ×) in two MR scanners. We also compared detectability of microbleeds in both QSMs to demonstrate clinical feasibility of both QSMs.

MATERIALS AND METHODS

This prospective study was approved by the institutional review board and written informed consent was obtained from each subject. Healthy subjects were recruited to evaluate intra-scanner reproducibility, inter-scanner consistency, and inter-sequence consistency of QSM_G2 × and QSM_WC9 × at 2 MR scanners. Susceptibility values measured with volume of interests (VOIs) were evaluated. Patients who were requested for susceptibility weighted imaging were also recruited in this study to measure microbleeds on QSM_G2 × and QSM_WC9 × . The number of microbleeds was compared between two QSMs.

RESULTS

Total 55 healthy subjects (male 34, female 21, 38.3 years [23-79]) were included in this study. We investigated reproducibility and consistency of QSM_WC9 × by comparing reference standard QSM_G2 × in two MR scanners in this study, and high correlation (ρ, 0.93-0.97) and high intraclass correlation coefficient (ICC) (0.97-0.99) were obtained. Sixty patients (male 30, female 30; age, 55.4 years [21-85]) were finally enrolled in this prospective study. The ICC of the detected number of microbleeds between QSM_G2 × and QSM_WC9 × was 0.99 (0.98-0.99).

CONCLUSION

QSM_WC9 × and reference standard QSM_G2 × in two MR scanners showed good reproducibility and consistency in estimating magnetic susceptibilities. QSM_WC9 × and QSM_G2 × were also comparable in terms of microbleeds detection with good agreement of raters and high ICC.

Trajectories and sex differences of brain structure, oxygenation and perfusion functions in normal aging

BACKGROUND

Brain structure, oxygenation and perfusion are important factors in aging. Coupling between regional cerebral oxygen consumption and perfusion also reflects functions of neurovascular unit (NVU). Their trajectories and sex differences during normal aging important for clinical interpretation are still not well defined. In this study, we aim to investigate the relationship between brain structure, functions and age, and exam the sex disparities.

METHOD

A total of 137 healthy subjects between 20∼69 years old were enrolled with conventional MRI, structural three-dimensional T1-weighted imaging (3D-T1WI), 3D multi-echo gradient echo sequence (3D-mGRE), and 3D pseudo-continuous arterial spin labeling (3D-pCASL). Oxygen extraction fraction (OEF) and cerebral blood flow (CBF) were respectively reconstructed from 3D-mGRE and 3D-pCASL images. Cerebral metabolic rate of oxygen (CMRO2) were calculated as follows: CMRO2=CBF·OEF·[H]a, [H]a=7.377 μmol/mL. Brains were segmented into global gray matter (GM), global white matter (WM), and 148 cortical subregions. OEF, CBF, CMRO2, and volumes of GM/WM relative to intracranial volumes (rel_GM/rel_WM) were compared between males and females. Generalized additive models were used to evaluate the aging trajectories of brain structure and functions. The coupling between OEF and CBF was analyzed by correlation analysis. P or PFDR < 0.05 was considered statistically significant.

RESULTS

Females had larger rel_GM, higher CMRO2 and CBF of GM/WM than males (P < 0.05). With control of sex, CBF of GM significantly declined between 20 and 32 years, CMRO2 of GM declined subsequently from 33 to 41 years and rel_GM decreased significantly at all ages (R2 = 0.27, P < 0.001; R2 = 0.17, P < 0.001; R2 = 0.52, P < 0.001). In subregion analysis, CBF declined dispersedly while CMRO2 declined widely across most subregions of the cortex during aging. Robust negative coupling between OEF and CBF was found in most of the subregions (r range = -0.12∼-0.48, PFDR < 0.05).

CONCLUSION

The sex disparities, age trajectories of brain structure and functions as well as the coupling of NVU in healthy individuals provide insights into normal aging which are potential targets for study of pathological conditions.

Exploring the links among brain iron accumulation, cognitive performance, and dietary intake in older adults: A longitudinal MRI study

This study evaluated longitudinal brain iron accumulation in older adults, its association with cognition, and the role of specific nutrients in mitigating iron accumulation. MRI-based, quantitative susceptibility mapping estimates of brain iron concentration were acquired from seventy-two healthy older adults (47 women, ages 60-86) at a baseline timepoint (TP1) and a follow-up timepoint (TP2) 2.5-3.0 years later. Dietary intake was evaluated at baseline using a validated questionnaire. Cognitive performance was assessed at TP2 using the uniform data set (Version 3) neuropsychological tests of episodic memory (MEM) and executive function (EF). Voxel-wise, linear mixed-effects models, adjusted for longitudinal gray matter volume alterations, age, and several non-dietary lifestyle factors revealed brain iron accumulation in multiple subcortical and cortical brain regions, which was negatively associated with both MEM and EF performance at T2. However, consumption of specific dietary nutrients at TP1 was associated with reduced brain iron accumulation. Our study provides a map of brain regions showing iron accumulation in older adults over a short 2.5-year follow-up and indicates that certain dietary nutrients may slow brain iron accumulation.

Biophysical contrast sources for magnetic susceptibility and R2* mapping: A combined 7 Tesla, mass spectrometry and electron paramagnetic resonance study

Iron is the most abundant trace metal in the human brain and consistently shown elevated in prevalent neurological disorders. Because of its paramagnetism, brain iron can be assessed in vivo by quantitative MRI techniques such as R2* mapping and Quantitative Susceptibility Mapping (QSM). While Inductively Coupled Plasma Mass Spectrometry (ICP-MS) has demonstrated good correlations of the total iron content to MRI parameters in gray matter, the relationship to ferritin levels as assessed by Electron Paramagnetic Resonance (EPR) has not been systematically analyzed. Therefore, we included 15 postmortem subjects (age: 26-91 years) which underwent quantitative in-situ MRI at 7 Tesla within a post-mortem interval of 24 h after death. ICP-MS and EPR were used to measure the total iron and ferritin content in 8 selected gray matter (GM) structures and the correlations to R2* and QSM were calculated. We found that R2* and QSM in the iron rich basal ganglia and the red nucleus were highly correlated with iron (R² > 0.7) and ferritin (R² > 0.6), whereas those correlations were lost in cortical regions and the hippocampus. The neuromelanin-rich substantia nigra showed a different behavior with a correlation with total iron only (R² > 0.5) but not with ferritin. Although qualitative results were similar for both qMRI techniques the observed correlation was always stronger for QSM than R2*. This study demonstrated the quantitative correlations between R2*, QSM, total iron and ferritin levels in an in-situ MRI setup and therefore aids to understand how molecular forms of iron are responsible for MRI contrast generation.

Bilateral orthogonality generative acquisitions method for homogeneous T 2 * images using parallel transmission at 7 T

PURPOSE

The novel bilateral orthogonality generative acquisitions method has been developed for homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ images without the effects of transmit field inhomogeneity using a parallel-transmission (pTx) system at 7 T.

THEORY AND METHODS

A new method has been introduced using four low-angle gradient-echo (GRE) acquisitions to obtain homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast by removing the effects of transmit field inhomogeneity in the pTx system. First, two input images are obtained in circularly polarized mode and another mode in which the first transmit channel or channel group have an additional transmit phase of π. The last two acquisitions are single-channel acquisitions for a dual-channel system or single-channel group acquisitions for more than two channels. The introduced method is demonstrated in dual-channel and eight-channel pTx systems using phantom and whole-brain in vivo experiments. Noise performance of the proposed method is also tested against the ratio of two GRE acquisitions and the TIAMO (time-interleaved acquisitions of modes) method.

RESULTS

Th new method results in more homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ contrast in the final images than the compared methods, particularly in the low-intensity regions of circularly polarized-mode images for the images obtained via ratio of the two GRE acquisitions.

CONCLUSION

The introduced method is easy to implement, robust, and provides homogeneousT 2 * $$ {\mathrm{T}}_2^{\ast } $$ images of the whole brain using pTx systems with any number of channels, compared with the ratio of the two GRE images and the TIAMO method.

Iron accumulation/overload and Alzheimer's disease risk factors in the precuneus region: A comprehensive narrative review

Alzheimer's disease (AD) is a neurodegenerative disease that is characterized by amyloid plaques, neurofibrillary tangles, and neuronal loss. Early cerebral and body iron dysregulation and accumulation interact with AD pathology, particularly in the precuneus, a crucial functional hub in cognitive functions. Quantitative susceptibility mapping (QSM), a novel post-processing approach, provides insights into tissue iron levels and cerebral oxygen metabolism and reveals abnormal iron accumulation early in AD. Increased iron deposition in the precuneus can lead to oxidative stress, neuroinflammation, and accelerated neurodegeneration. Metabolic disorders (diabetes, non-alcoholic fatty liver disease (NAFLD), and obesity), genetic factors, and small vessel pathology contribute to abnormal iron accumulation in the precuneus. Therefore, in line with the growing body of literature in the precuneus region of patients with AD, QSM as a neuroimaging method could serve as a non-invasive biomarker to track disease progression, complement other imaging modalities, and aid in early AD diagnosis and monitoring.

QSM-detected iron accumulation in the cerebellar gray matter is selectively associated with executive dysfunction in non-demented ALS patients

Background

This study aimed to assess whether quantitative susceptibility imaging (QSM)-based measures of iron accumulation in the cerebellum predict cognitive and behavioral features in non-demented amyotrophic lateral sclerosis (ALS) patients.

Methods

A total of ALS patients underwent 3-T MRI and a clinical assessment using the ALS Functional Rating Scale-Revised (ALSFRS-R) and the Edinburgh Cognitive and Behavioural ALS Screen (ECAS). Regression models were applied to each subscale of the cognitive section of the ECAS and the ECAS-Carer Interview to examine the effect of QSM-based measures in white and gray matter (WM; GM) of the cerebellum, separately for right, left, and bilateral cerebellar regions of interest (ROIs). These effects were compared to those of cerebellar volumetrics in WM/GM, right and left hemispheres while controlling for demographics, disease status, and total intracranial volume.

Results

Higher QSM measures of the cerebellar GM on the left, right, and bilateral sides significantly predicted (ps ≤ 0.003) a greater number of errors on the executive functioning (EF) subscale of the ECAS (ECAS-EF). Moreover, higher GM-related, QSM measures of the cerebellum were associated with an increased probability of a below-cut-off performance on the ECAS-EF (ps ≤ 0.024). No significant effects were observed for QSM measures of the cerebellar WM or for volumetric measures on the ECAS-EF. Other ECAS measures showed no significant effects. Bilateral QSM measures of the cerebellar GM also selectively predicted performance on backward digit span and social cognition tasks.

Discussion

Iron accumulation within the cerebellar GM, particularly in the cerebellar cortices, may be associated with executive functioning deficits in non-demented ALS patients. Therefore, QSM-based measures could be useful for identifying the neural correlates of extra-motor cognitive deficits in ALS patients.

Unveiling metabolic patterns in dementia: Insights from high-resolution quantitative blood-oxygenation-level-dependent MRI

BACKGROUND

Oxygen extraction fraction (OEF) and deoxyhemoglobin (DoHb) levels reflect variations in cerebral oxygen metabolism in demented patients.

PURPOSE

Delineating the metabolic profiles evident throughout different phases of dementia necessitates an integrated analysis of OEF and DoHb levels. This is enabled by leveraging high-resolution quantitative blood oxygenation level dependent (qBOLD) analysis of magnitude images obtained from a multi-echo gradient-echo MRI (mGRE) scan performed on a 3.0 Tesla scanner.

METHODS

Achieving superior spatial resolution in qBOLD necessitates the utilization of an mGRE scan with only four echoes, which in turn limits the number of measurements compared to the parameters within the qBOLD model. Consequently, it becomes imperative to discard non-essential parameters to facilitate further analysis. This process entails transforming the qBOLD model into a format suitable for fitting the log-magnitude difference (L-MDif) profiles of the four echo magnitudes present in each brain voxel. In order to bolster spatial specificity, the log-difference qBOLD model undergoes refinement into a representative form, termed as r-qBOLD, particularly when applied to class-averaged L-MDif signals derived through k-means clustering of L-MDif signals from all brain voxels into a predetermined number of clusters. The agreement between parameters estimated using r-qBOLD for different cluster sizes is validated using Bland-Altman analysis, and the model's goodness-of-fit is evaluated using aχ 2 ${\chi ^2}$ -test. Retrospective MRI data of Alzheimer's disease (AD), mild cognitive impairment (MCI), and non-demented patients without neuropathological disorders, pacemakers, other implants, or psychiatric disorders, who completed a minimum of three visits prior to MRI enrolment, are utilized for the study.

RESULTS

Utilizing a cohort comprising 30 demented patients aged 65-83 years in stages 4-6 representing mild, moderate, and severe stages according to the clinical dementia rating (CDR), matched with an age-matched non-demented control group of 18 individuals, we conducted joint observations of OEF and DoHb levels estimated using r-qBOLD. The observations elucidate metabolic signatures in dementia based on OEF and DoHb levels in each voxel. Our principal findings highlight the significance of spatial patterns of metabolic profiles (metabolic patterns) within two distinct regimes: OEF levels exceeding the normal range (S1-regime), and OEF levels below the normal range (S2-regime). The S1-regime, accompanied by low DoHb levels, predominantly manifests in fronto-parietal and perivascular regions with increase in dementia severity. Conversely, the S2-regime, accompanied by low DoHb levels, is observed in medial temporal (MTL) regions. Other regions with abnormal metabolic patterns included the orbitofrontal cortex (OFC), medial-orbital prefrontal cortex (MOPFC), hypothalamus, ventro-medial prefrontal cortex (VMPFC), and retrosplenial cortex (RSP). Dysfunction in the OFC and MOPFC indicated cognitive and emotional impairment, while hypothalamic involvement potentially indicated preclinical dementia. Reduced metabolic activity in the RSP suggested early-stage AD related functional abnormalities.

CONCLUSIONS

Integrated analysis of OEF and DoHb levels using r-qBOLD reveals distinct metabolic signatures across dementia phases, highlighting regions susceptible to neuronal loss, vascular involvement, and preclinical indicators.

DF-QSM: Data Fidelity based Hybrid Approach for Improved Quantitative Susceptibility Mapping of the Brain

Quantitative Susceptibility Mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique to quantify the magnetic susceptibility of the tissue under investigation. Deep learning methods have shown promising results in deconvolving the susceptibility distribution from the measured local field obtained from the MR phase. Although existing deep learning based QSM methods can produce high-quality reconstruction, they are highly biased toward training data distribution with less scope for generalizability. This work proposes a hybrid two-step reconstruction approach to improve deep learning based QSM reconstruction. The susceptibility map prediction obtained from the deep learning methods has been refined in the framework developed in this work to ensure consistency with the measured local field. The developed method was validated on existing deep learning and model-based deep learning methods for susceptibility mapping of the brain. The developed method resulted in improved reconstruction for MRI volumes obtained with different acquisition settings, including deep learning models trained on constrained (limited) data settings.

Comparative analysis of quantitative susceptibility mapping in preclinical dementia detection

PURPOSE

This review aims to explore the role of Quantitative Susceptibility Mapping (QSM) in the early detection of neurodegenerative diseases, particularly Alzheimer's disease (AD) and Lewy body dementia (LBD). By examining QSM's ability to map brain iron deposition, we seek to highlight its potential as a diagnostic tool for preclinical dementia.

METHODOLOGY

QSM techniques involve the advanced processing of MRI phase images to reconstruct tissue susceptibility, employing methods such as spherical mean value filtering and Tikhonov regularization for accurate background field removal. This review discusses how these methodologies enable the precise quantification of iron and other elements within the brain.

RESULTS

QSM has demonstrated effectiveness in identifying early pathological changes in key brain regions, including the hippocampus, basal ganglia, and substantia nigra. These regions are significantly impacted in the early stages of AD and LBD. Studies reviewed indicate that QSM can detect subtle neurodegenerative changes, providing valuable insights into disease progression. However, challenges remain in standardizing QSM processing algorithms to ensure consistent results across different studies.

CONCLUSION

QSM emerges as a promising tool for early dementia detection, offering precise measurements of brain iron deposition and other critical biomarkers. The review underscores the importance of refining QSM methodologies and integrating them with other imaging modalities to improve early diagnosis and management of neurodegenerative diseases. Future research should focus on standardizing QSM techniques and exploring their synergistic use with other neuroimaging methods to enhance its clinical utility.

Exploring cognitive related microstructural alterations in normal appearing white matter and deep grey matter for small vessel disease: A quantitative susceptibility mapping study

Brain microstructural alterations possibly occur in the normal-appearing white matter (NAWM) and grey matter of small vessel disease (SVD) patients, and may contribute to cognitive impairment. The aim of this study was to explore cognitive related microstructural alterations in white matter and deep grey matter nuclei in SVD patients using magnetic resonance (MR) quantitative susceptibility mapping (QSM). 170 SVD patients, including 103 vascular mild cognitive impairment (VaMCI) and 67 no cognitive impairment (NCI), and 21 healthy control (HC) subjects were included, all underwent a whole-brain QSM scanning. Using a white matter and a deep grey matter atlas, subregion-based QSM analysis was conducted to identify and characterize microstructural alterations occurring within white matter and subcortical nuclei. Significantly different susceptibility values were revealed in NAWM and in several specific white matter tracts including anterior limb of internal capsule, corticospinal tract, medial lemniscus, middle frontal blade, superior corona radiata and tapetum among VaMCI, NCI and HC groups. However, no difference was found in white matter hyperintensities between VaMCI and NCI. A trend toward higher susceptibility in the caudate nucleus and globus pallidus of VaMCI patients compared to HC, indicating elevated iron deposition in these areas. Interestingly, some of these QSM parameters were closely correlated with both global and specific cognitive function scores, controlling age, gender and education level. Our study suggested that QSM may serve as a useful imaging tool for monitoring cognitive related microstructural alterations in brain. This is especially meaningful for white matter which previously lacks of attention.

Design and validation of the ADNI MR protocol

Phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI4) magnetic resonance imaging (MRI) protocols aim to maintain longitudinal consistency across two decades of data acquisition, while adopting new technologies. Here we describe and justify the study's design and targeted biomarkers. The ADNI4 MRI protocol includes nine MRI sequences. Some sequences require the latest hardware and software system upgrades and are continuously rolled out as they become available at each site. The main sequence additions/changes in ADNI4 are: (1) compressed sensing (CS) T1-weighting, (2) pseudo-continuous arterial spin labeling (ASL) on all three vendors (GE, Siemens, Philips), (3) multiple-post-labeling-delay ASL, (4) 1 mm3 isotropic 3D fluid-attenuated inversion recovery, and (5) CS 3D T2-weighted. ADNI4 aims to help the neuroimaging community extract valuable imaging biomarkers and provide a database to test the impact of advanced imaging strategies on diagnostic accuracy and disease sensitivity among individuals lying on the cognitively normal to impaired spectrum. HIGHLIGHTS: A summary of MRI protocols for phase four of the Alzheimer's Disease Neuroimaging Initiative (ADNI 4). The design and justification for the ADNI 4 MRI protocols. Compressed sensing and multi-band advances have been applied to improve scan time. ADNI4 protocols aim to streamline safety screening and therapy monitoring. The ADNI4 database will be a valuable test bed for academic research.

Assessing brain iron and its relationship to cognition and comorbidity in children with ADHD with quantitative susceptibility mapping (QSM)

BACKGROUND

Quantitative susceptibility mapping (QSM) is a neuroimaging technique that detects local changes in magnetic susceptibility induced by brain iron. Brain iron and the dopaminergic system are linked since iron is an important cofactor for dopamine synthesis. ADHD is associated with dysregulation of dopaminergic transmission. Therefore, we applied QSM on subcortical structures, to study potential alterations in brain iron and its impact on cognition and mental health in children with ADHD.

METHODS

3 Tesla QSM-data of 111 participants (nADHD= 58, mean age: 13.2 (0.63); nControls=53, mean age: 13.2 (0.51)) were analyzed. Subcortical regional brain iron values were extracted. ANOVAs examined group differences for each region of interest. For dimensional approaches, Pearson correlation analysis was performed across the cohort examining the association with symptoms, mental health, and cognition.

RESULTS

No significant differences were found in iron susceptibility between ADHD and control, between persistent and remitted ADHD, or between medication use. An unexpected finding was that children with internalising disorder had significantly higher iron susceptibility, but the result did not survive multiple comparison corrections. Higher brain iron was associated with sustained attention, but not on inhibition, IQ, and working memory.

CONCLUSION

This is the first study addressing brain iron susceptibility and its association with comorbidities and cognition in ADHD. Alterations in brain iron may not account for the full diagnosis of ADHD but may be an indicator of internalising problems in children. Alterations in brain iron content in children were linked to detrimental sustained attention and may represent developmental variation in cognition.

On the equivalence of demagnetization tensors as discrete cell size approaches zero in three-dimensional space

The calculation of the demagnetization field is crucial in various disciplines, including magnetic resonance imaging and micromagnetics. A standard method involves discretizing the spatial domain into finite difference cells and using demagnetization tensors to compute the field. Different demagnetization tensors can result in contributions from adjacent cells that do not approach zero, nor do their differences, even as the cell size decreases. This work demonstrates that in three-dimensional space, a specific set of magnetization tensors produces the same total demagnetization field as the Cauchy principal value when the cell size approaches zero. Additionally, we provide a lower bound for the convergence speed, validated through numerical experiments.

Measuring the Magnetic Anisotropy of Metal-Metal Multiple Bonds: The Importance of Correcting for Ligand Effects

We describe the synthesis and characterization of the quadruply-bonded dimer Mo2(CH2NMe2BH3)4 in which each molybdenum(II) center is bound to two chelating boranatodimethylaminomethyl (BDAM) ligands. The BDAM anions bind to the metal at one end by a metal-carbon σ bond and at the other by a three-center M-H-B interaction. Each BDAM ligand chelates to a single Mo atom so that the metal-metal bond is unbridged; the Mo-Mo distance is 2.114(2) Å. Structural and solution NMR data, analyzed via McConnell's equation and supported by DFT calculations, show that the magnetic anisotropies associated with highly polarizable and π-bonding ligands (such as chloride groups and aryl rings) can greatly affect the NMR chemical shifts of reporter groups, so that ignoring their contributions leads to significant overestimates of the anisotropy due just to the metal-metal bond. We propose a method to quantify and correct for the magnetic anisotropy effects arising from the ligands. Application of this method to Mo2(BDAM)4 indicates that the magnetic anisotropy of the Mo-Mo quadruple bond in this molecule is about -800 × 10-36 m3 molecule-1. Anisotropies significantly higher than this value (as sometimes reported in the prior literature) are most likely incorrect.

Whole brain multiparametric mapping in two minutes using a dual-flip-angle stack-of-stars blipped multi-gradient-echo acquisition

A new MRI technique is presented for three-dimensional fast simultaneous whole brain mapping of myelin water fraction (MWF), T1, proton density (PD), R2*, magnetic susceptibility (QSM), and B1 transmit field (B1+). Phantom and human (N = 9) datasets were acquired using a dual-flip-angle blipped multi-gradient-echo (DFA-mGRE) sequence with a stack-of-stars (SOS) trajectory. Images were reconstructed using a subspace-based algorithm with a locally low-rank constraint. A novel joint-sparsity-constrained multicomponent T2*-T1 spectrum estimation (JMSE) algorithm is proposed to correct for the T1 saturation effect and B1+/B1- inhomogeneities in the quantification of MWF. A tissue-prior-based B1+ estimation algorithm was adapted for B1 correction in the mapping of T1 and PD. In the phantom study, measurements obtained at an acceleration factor (R) of 12 using prospectively under-sampled SOS showed good consistency (R2 > 0.997) with Cartesian reference for R2*/T1app/M0app. In the in vivo study, results of retrospectively under-sampled SOS with R = 6, 12, 18, showed good quality (structure similarity index measure > 0.95) compared with those of fully-sampled SOS. Besides, results of prospectively under-sampled SOS with R = 12 showed good consistency (intraclass correlation coefficient > 0.91) with Cartesian reference for T1/PD/B1+/MWF/QSM/R2*, and good reproducibility (coefficient of variation < 7.0 %) in the test-retest analysis for T1/PD/B1+/MWF/R2*. This study has demonstrated the feasibility of simultaneous whole brain multiparametric mapping with a two-minute scan using the DFA-mGRE SOS sequence, which may overcome a major obstacle for neurological applications of multiparametric MRI.

SIPAS: A comprehensive susceptibility imaging process and analysis studio

Quantitative susceptibility mapping (QSM) is a rising MRI-based technology and quite a few QSM-related algorithms have been proposed to reconstruct maps of tissue susceptibility distribution from phase images. In this paper, we develop a comprehensive susceptibility imaging process and analysis studio (SIPAS) that can accomplish reliable QSM processing and offer a standardized evaluation system. Specifically, SIPAS integrates multiple methods for each step, enabling users to select algorithm combinations according to data conditions, and QSM maps could be evaluated by two aspects, including image quality indicators within all voxels and region-of-interest (ROI) analysis. Through a sophisticated design of user-friendly interfaces, the results of each procedure are able to be exhibited in axial, coronal, and sagittal views in real-time, meanwhile ROIs can be displayed in 3D rendering visualization. The accuracy and compatibility of SIPAS are demonstrated by experiments on multiple in vivo human brain datasets acquired from 3T, 5T, and 7T MRI scanners of different manufacturers. We also validate the QSM maps obtained by various algorithm combinations in SIPAS, among which the combination of iRSHARP and SFCR achieves the best results on its evaluation system. SIPAS is a comprehensive, sophisticated, and reliable toolkit that may prompt the QSM application in scientific research and clinical practice.

Reduced oxygen extraction fraction in deep cerebral veins associated with cognitive impairment in multiple sclerosis

Studying the relationship between cerebral oxygen utilization and cognitive impairment is essential to understanding neuronal functional changes in the disease progression of multiple sclerosis (MS). This study explores the potential of using venous susceptibility in internal cerebral veins (ICVs) as an imaging biomarker for cognitive impairment in relapsing-remitting MS (RRMS) patients. Quantitative susceptibility mapping derived from fully flow-compensated MRI phase data was employed to directly measure venous blood oxygen saturation levels (SvO2) in the ICVs. Results revealed a significant reduction in the susceptibility of ICVs (212.4 ± 30.8 ppb vs 239.4 ± 25.9 ppb) and a significant increase of SvO2 (74.5 ± 1.89% vs 72.4 ± 2.23%) in patients with RRMS compared with age- and sex-matched healthy controls. Both the susceptibility of ICVs (r = 0.508, p = 0.031) and the SvO2 (r = -0.498, p = 0.036) exhibited a moderate correlation with cognitive decline in these patients assessed by the Paced Auditory Serial Addition Test, while no significant correlation was observed with clinical disability measured by the Expanded Disability Status Scale. The findings suggest that venous susceptibility in ICVs has the potential to serve as a specific indicator of oxygen metabolism and cognitive function in RRMS. .

Quantifying cerebral microbleeds using quantitative susceptibility mapping from magnetization-prepared rapid gradient-echo

T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) is commonly included in brain studies for structural imaging using magnitude images; however, its phase images can provide an opportunity to assess microbleed burden using quantitative susceptibility mapping (QSM). This potential application for MPRAGE-based QSM was evaluated using in vivo and simulated measurements. Possible factors affecting image quality were also explored. Detection sensitivity was evaluated against standard multiecho gradient echo (MEGE) QSM using 3-T in vivo data of 15 subjects with a combined total of 108 confirmed microbleeds. The two methods were compared based on the microbleed size and susceptibility measurements. In addition, simulations explored the detection sensitivity of MPRAGE-QSM at different representative magnetic field strengths and echo times using microbleeds of different size, susceptibility, and location. Results showed that in vivo microbleeds appeared to be smaller (× 0.54) and of higher mean susceptibility (× 1.9) on MPRAGE-QSM than on MEGE-QSM, but total susceptibility estimates were in closer agreement (slope: 0.97, r2: 0.94), and detection sensitivity was comparable. In simulations, QSM at 1.5 T had a low contrast-to-noise ratio that obscured the detection of many microbleeds. Signal-to-noise ratio (SNR) levels at 3 T and above resulted in better contrast and increased detection. The detection rates for microbleeds of minimum one-voxel diameter and 0.4-ppm susceptibility were 0.55, 0.80, and 0.88 at SNR levels of 1.5, 3, and 7 T, respectively. Size and total susceptibility estimates were more consistent than mean susceptibility estimates, which showed size-dependent underestimation. MPRAGE-QSM provides an opportunity to detect and quantify the size and susceptibility of microbleeds of at least one-voxel diameter at B0 of 3 T or higher with no additional time cost, when standard T2*-weighted images are not available or have inadequate spatial resolution. The total susceptibility measure is more robust against sequence variations and might allow combining data from different protocols.

From impact to recovery: tracking mild traumatic brain injury with MRI-a pilot study and case series

Background

Diagnosis and recovery tracking of mild traumatic brain injury (mTBI) is often challenging due to the lack of clear findings on routine imaging techniques. This also complicates defining safe points for returning to activities.

Hypothesis/purpose

Quantitative susceptibility mapping (QSM) can provide information about cerebral venous oxygen saturation (CSvO2) in the context of brain injury. We tested the prediction that these imaging modalities would enable the detection of changes and recovery patterns in the brains of patients with mTBI.

Study design

In a case-control study, we recruited a cohort of 24 contact sport athletes for baseline QSM and resting-state functional MRI (rs-fMRI) scanning. Two of those who subsequently experienced head impact with significant post-injury symptoms underwent scans at 3, 7, 14 and 28 days post-injury; one had a boxing match without classical mTBI symptoms were also followed-up on.

Results

The cohort baseline QSM measurements of the straight sinus were established. The two injured athletes with post-impact symptoms consistent with mTBI had susceptibility results at days 3 and 7 post-impact that fell below the 25th percentile of the baseline values. The per cent amplitude fluctuation quantified from rs-fMRI agreed with the susceptibility trends in the straight sinus.

Conclusion

QSM holds promise as a diagnostic tool for tracking mTBI progression or recovery in contact sport head injury.

Atrophy-Independent and Dependent Iron and Myelin Changes in Deep Gray Matter of Multiple Sclerosis: A Longitudinal Study Using χ-Separation Imaging

RATIONALE AND OBJECTIVES

To investigate iron and myelin changes in deep gray matter (DGM) of relapsing-remitting multiple sclerosis (RRMS) patients and their relationship to atrophy by χ-separation imaging.

MATERIALS AND METHODS

33 RRMS patients and 34 healthy controls (HC) were included in this study. The χ-separation map reconstructed from a 3D multi-echo gradient echo scan was used to measure the positive susceptibility (χpos) and negative susceptibility (χneg) of DGM. To take into account the effect of atrophy, susceptibility mass of DGM was calculated by multiplying volume by the mean bulk susceptibility. Differences in MRI metrics between baseline patients, follow-up patients, and HC were compared respectively.

RESULTS

Compared to HC, χpos of basal ganglia were significantly increased in follow-up patients (P < 0.05). The χpos of pallidum was significantly higher in follow-up patients than that in baseline patients (P = 0.006). The χneg of caudate, pallidum and hippocampus in baseline and follow-up patients was significantly higher than that in HC (P < 0.05). When taking into account the effect of atrophy, there was a significant decrease in χpos mass and a significant increase in χneg mass of thalamus, accumbens and amygdala in follow-up patients compared to HC (P < 0.05). The χpos mass of the thalamus was further decreased in follow-up patients compared to baseline patients (P = 0.006).

CONCLUSION

χ-separation imaging could generate independent information on iron and myelin changes in RRMS patients, showing atrophy-dependent iron increase in basal ganglia and atrophy-independent iron and myelin decrease in thalamus.

A modified Tseng algorithm approach to restoring thoracic diseases' computerized tomography images

It is well-known that the Tseng algorithm and its modifications have been successfully employed in approximating zeros of the sum of monotone operators. In this study, we restored various thoracic diseases' computerized tomography (CT) images, which were degraded with a known blur function and additive noise, using a modified Tseng algorithm. The test images used in the study depict calcification of the Aorta, Subcutaneous Emphysema, Tortuous Aorta, Pneumomediastinum, and Pneumoperitoneum. Additionally, we employed well-known image restoration tools to enhance image quality and compared the quality of restored images with the originals. Finally, the study demonstrates the potential to advance monotone inclusion problem-solving, particularly in the field of medical image recovery.

Brain Magnetic Resonance Imaging in Wilson's Disease-Significance and Practical Aspects-A Narrative Review

Wilson's disease (WD) is a genetic disorder of copper metabolism with pathological copper accumulation in many organs, resulting in clinical symptoms, mostly hepatic and neuropsychiatric. As copper accumulates in the brain during WD, and almost 50% of WD patients at diagnosis present with neurological symptoms, neuroimaging studies (especially brain magnetic resonance imaging (MRI)) are part of WD diagnosis. The classical sequences (T1, T2, and fluid-attenuated inversion recovery) were used to describe brain MRI; however, with the development of neuroradiology, several papers proposed the use of new MRI sequences and techniques like susceptibility-weighted images, T2*, diffusion MRI, tractography, volumetric assessment and post-processing brain MRI analysis of paramagnetic accumulation-quantitative susceptibility mapping. Based on these neuroradiological data in WD, currently, brain MRI semiquantitative scale and the pathognomonic neuroradiological brain MRI signs in WD were proposed. Further, the volumetric studies and brain iron accumulation MRI analysis suggested brain atrophy and iron accumulation as biomarkers of neurological WD disease severity. All these results highlight the significance of brain MRI examinations in WD. Due to the extreme progress of these studies, based on the available literature, the authors present the current state of knowledge about the significance, practical aspects, and future directions of brain MRI in WD.

Combined MR quantitative susceptibility mapping and multi-shell diffusion in Parkinson's disease

BACKGROUND AND PURPOSE

Quantitative susceptibility mapping (QSM), neurite orientation dispersion and density imaging (NODDI), and the g-ratio have separately shown differences between Parkinson's disease (PD) and healthy controls. The g-ratio has, however, not been studied in PD in the substantia nigra (SN) and the putamen. A combination of these methods could also potentially be a complementary imaging biomarker for PD. This study aimed to assess the diagnostic performance of QSM, NODDI, the g-ratio, and a combined QSM-NODDI imaging marker in the SN and putamen of PD patients.

METHODS

In this prospective study, the diagnostic performance of median region of interest values was compared in a cohort of 15 participants with PD and 14 healthy controls after manual segmentation. The diagnostic performance was assessed using the area under curve (AUC) for the receiving operator characteristic.

RESULTS

Median QSM in the contralateral SN identified PD with AUC 0.77, and median isotropic volume fraction identified PD in the ipsilateral SN with AUC 0.68. A combined NODDI-QSM marker improved diagnostic performance (AUC 0.80). No significant differences were found in the g-ratio.

CONCLUSION

A combination of median QSM and median isotropic volume fraction improves the differentiation of PD from healthy controls and is a potential biomarker in the diagnostics of PD. This confirms previously reported results indicating that combining QSM and NODDI modestly improves differentiation of PD.

Quantitative susceptibility mapping for detection of kidney stones, hemorrhage differentiation, and cyst classification in ADPKD

BACKGROUND AND PURPOSE

The objective is to demonstrate feasibility of quantitative susceptibility mapping (QSM) in autosomal dominant polycystic kidney disease (ADPKD) patients and to compare imaging findings with traditional T1/T2w magnetic resonance imaging (MRI).

METHODS

Thirty-three consecutive patients (11 male, 22 female) diagnosed with ADPKD were initially selected. QSM images were reconstructed from the multiecho gradient echo data and compared to co-registered T2w, T1w, and CT images. Complex cysts were identified and classified into distinct subclasses based on their imaging features. Prevalence of each subclass was estimated.

RESULTS

QSM visualized two renal calcifications measuring 9 and 10 mm and three pelvic phleboliths measuring 2 mm but missed 24 calcifications measuring 1 mm or less and 1 larger calcification at the edge of the field of view. A total of 121 complex T1 hyperintense/T2 hypointense renal cysts were detected. 52 (43%) Cysts appeared hyperintense on QSM consistent with hemorrhage; 60 (49%) cysts were isointense with respect to simple cysts and normal kidney parenchyma, while the remaining 9 (7%) were hypointense. The presentation of the latter two complex cyst subtypes is likely indicative of proteinaceous composition without hemorrhage.

CONCLUSION

Our results indicate that QSM of ADPKD kidneys is possible and uniquely suited to detect large renal calculi without ionizing radiation and able to identify properties of complex cysts unattainable with traditional approaches.

A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation

Quantitative susceptibility mapping (QSM) is an MRI-based technique that estimates the underlying tissue magnetic susceptibility based on phase signal. Deep learning (DL)-based methods have shown promise in handling the challenging ill-posed inverse problem for QSM reconstruction. However, they require extensive paired training data that are typically unavailable and suffer from generalization problems. Recent model-incorporated DL approaches also overlook the non-local effect of the tissue phase in applying the source-to-field forward model due to patch-based training constraint, resulting in a discrepancy between the prediction and measurement and subsequently suboptimal QSM reconstruction. This study proposes an unsupervised and subject-specific DL method for QSM reconstruction based on implicit neural representation (INR), referred to as INR-QSM. INR has emerged as a powerful framework for learning a high-quality continuous representation of the signal (image) by exploiting its internal information without training labels. In INR-QSM, the desired susceptibility map is represented as a continuous function of the spatial coordinates, parameterized by a fully-connected neural network. The weights are learned by minimizing a loss function that includes a data fidelity term incorporated by the physical model and regularization terms. Additionally, a novel phase compensation strategy is proposed for the first time to account for the non-local effect of tissue phase in data consistency calculation to make the physical model more accurate. Our experiments show that INR-QSM outperforms traditional established QSM reconstruction methods and the compared unsupervised DL method both qualitatively and quantitatively, and is competitive against supervised DL methods under data perturbations.

So You Want to Image Myelin Using MRI: Magnetic Susceptibility Source Separation for Myelin Imaging

In MRI, researchers have long endeavored to effectively visualize myelin distribution in the brain, a pursuit with significant implications for both scientific research and clinical applications. Over time, various methods such as myelin water imaging, magnetization transfer imaging, and relaxometric imaging have been developed, each carrying distinct advantages and limitations. Recently, an innovative technique named as magnetic susceptibility source separation has emerged, introducing a novel surrogate biomarker for myelin in the form of a diamagnetic susceptibility map. This paper comprehensively reviews this cutting-edge method, providing the fundamental concepts of magnetic susceptibility, susceptibility imaging, and the validation of the diamagnetic susceptibility map as a myelin biomarker that indirectly measures myelin content. Additionally, the paper explores essential aspects of data acquisition and processing, offering practical insights for readers. A comparison with established myelin imaging methods is also presented, and both current and prospective clinical and scientific applications are discussed to provide a holistic understanding of the technique. This work aims to serve as a foundational resource for newcomers entering this dynamic and rapidly expanding field.

Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications

Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.

Quantitative susceptibility mapping in the brain reflects spatial expression of genes involved in iron homeostasis and myelination

Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p < .05, corrected) between expression of ferritin and the QSM signal in deep grey nuclei regions. We repeated the analysis for other genes that encode proteins thought to be involved in the transport and storage of iron in the brain, as well as myelination. In addition to ferritin, our findings demonstrate a positive correlation (p < .05, corrected) between the expression of ferroportin, transferrin, divalent metal transporter 1, several gene markers of myelinating oligodendrocytes, and the QSM signal in deep grey nuclei regions. Our results suggest that the QSM signal reflects both the storage and active transport of iron in the deep grey nuclei regions of the brain.

Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis

Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.

Improved test-retest reliability of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and susceptibility quantification using multishot multi-echo 3D EPI

PURPOSE

This study aimed to evaluate the potential of 3D EPI for improving the reliability ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted data and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ decay rate and susceptibility (χ) compared with conventional gradient-echo (GRE)-based acquisition.

METHODS

Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ were quantified, and their interscan differences were used to evaluate the test-retest reliability. Interprotocol differences ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ between GRE and EPI were also measured voxel by voxel and in selected regions of interest to test the consistency between the two acquisition methods.

RESULTS

The quantifications ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE.

CONCLUSION

The result suggests that multishot multi-echo 3D EPI can be a useful alternative acquisition method forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ with reduced scan time, improved test-retest reliability, and similar accuracy compared with commonly used 3D GRE.

Phase-sensitive deep reconstruction method for rapid multiparametric MR fingerprinting and quantitative susceptibility mapping in the brain

INTRODUCTION

This study explores the potential of Magnetic Resonance Fingerprinting (MRF) with a novel Phase-Sensitivity Deep Reconstruction Network (PS-DRONE) for simultaneous quantification of T1, T2, Proton Density, B1+, phase and quantitative susceptibility mapping (QSM).

METHODS

Data were acquired at 3 T in vitro and in vivo using an optimized EPI-based MRF sequence. Phantom experiments were conducted using a standardized phantom for T1 and T2 maps and a custom-made agar-based gadolinium phantom for B1 and QSM maps. In vivo experiments included five healthy volunteers and one patient diagnosed with brain metastasis. PSDRONE maps were compared to reference maps obtained through standard imaging sequences.

RESULTS

Total scan time was 2 min for 32 slices and a resolution of [1 mm, 1 mm, 4.5 mm]. The reconstruction of T1, T2, Proton Density, B1+ and phase maps were reconstructed within 1 s. In the phantoms, PS-DRONE analysis presented accurate and strongly correlated T1 and T2 maps (r = 0.99) compared to the reference maps. B1 maps from PS-DRONE showed slightly higher values, though still correlated (r = 0.6) with the reference. QSM values showed a small bias but were strongly correlated (r = 0.99) with reference data. In the in vivo analysis, PS-DRONE-derived T1 and T2 values for gray and white matter matched reference values in healthy volunteers. PS-DRONE B1 and QSM maps showed strong correlations with reference values.

CONCLUSION

The PS-DRONE network enables concurrent acquisition of T1, T2, PD, B1+, phase and QSM maps, within 2 min of acquisition time and 1 s of reconstruction time.

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a simulated-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms. The PnP OA-LFE module's versatility was further demonstrated by its successful application to xQSM, a distinct DL-QSM network for dipole inversion. In conclusion, this work introduces a new DL paradigm, allowing researchers to develop innovative QSM methods without requiring a complete overhaul of their existing architectures.

Quantitative susceptibility mapping through model-based deep image prior (MoDIP)

The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects. To address this generalization issue in supervised QSM methods, we propose a novel training-free model-based unsupervised method called MoDIP (Model-based Deep Image Prior). MoDIP comprises a small, untrained network and a Data Fidelity Optimization (DFO) module. The network converges to an interim state, acting as an implicit prior for image regularization, while the optimization process enforces the physical model of QSM dipole inversion. Experimental results demonstrate MoDIP's excellent generalizability in solving QSM dipole inversion across different scan parameters. It exhibits robustness against pathological brain QSM, achieving over 32 % accuracy improvement than supervised deep learning methods. It is also 33 % more computationally efficient and runs 4 times faster than conventional DIP-based approaches, enabling 3D high-resolution image reconstruction in under 4.5 min.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Distinguishing microgliosis and tau deposition in the mouse brain using paramagnetic and diamagnetic susceptibility source separation

Tauopathies, including Alzheimer's disease (AD), are neurodegenerative disorders characterized by hyperphosphorylated tau protein aggregates in the brain. In addition to protein aggregates, microglia-mediated inflammation and iron dyshomeostasis are other pathological features observed in AD and other tauopathies. It is known that these alterations at the subcellular level occur much before the onset of macroscopic tissue atrophy or cognitive deficits. The ability to detect these microstructural changes with MRI therefore has substantive importance for improved characterization of disease pathogenesis. In this study, we demonstrate that quantitative susceptibility mapping (QSM) with paramagnetic and diamagnetic susceptibility source separation has the potential to distinguish neuropathological alterations in a transgenic mouse model of tauopathy. 3D multi-echo gradient echo data were acquired from fixed brains of PS19 (Tau) transgenic mice and age-matched wild-type (WT) mice (n = 5 each) at 11.7 T. The multi-echo data were fit to a 3-pool complex signal model to derive maps of paramagnetic component susceptibility (PCS) and diamagnetic component susceptibility (DCS). Group-averaged signal fraction and composite susceptibility maps showed significant region-specific differences between the WT and Tau mouse brains. Significant bilateral increases in PCS and |DCS| were observed in specific hippocampal and cortical sub-regions of the Tau mice relative to WT controls. Comparison with immunohistological staining for microglia (Iba1) and phosphorylated-tau (AT8) further indicated that the PCS and DCS differences corresponded to regional microgliosis and tau deposition in the PS19 mouse brains, respectively. The results demonstrate that quantitative susceptibility source separation may provide sensitive imaging markers to detect distinct pathological alterations in tauopathies.

Evaluation of brain iron deposition in different cerebral arteries of acute ischaemic stroke patients using quantitative susceptibility mapping

AIM

To investigate differences in iron deposition between infarct and normal cerebral arterial regions in acute ischaemic stroke (AIS) patients using quantitative susceptibility mapping (QSM).

MATERIALS AND METHODS

Forty healthy controls and 40 AIS patients were recruited, and their QSM images were obtained. There were seven regions of interest (ROIs) in AIS patients, including the infarct regions of responsible arteries (R1), the non-infarct regions of responsible arteries (R2), the contralateral symmetrical sites of lesions (R3), and the non-responsible cerebral arterial regions (R4, R5, R6, R7). For the healthy controls, the cerebral arterial regions corresponding to the AIS patient group were selected as ROIs. The differences in corresponding ROI susceptibilities between AIS patients and healthy controls and the differences in susceptibilities between infarcted and non-infarct regions in AIS patients were compared.

RESULTS

The susceptibilities of infarct regions in AIS patients were significantly higher than those in healthy controls (p<0.0001). There was no significant difference in non-infarct regions between the two groups (p>0.05). The susceptibility of the infarct regions in AIS patients was significantly higher than those of the non-infarct region of responsible artery and non-responsible cerebral arterial regions (p<0.01).

CONCLUSIONS

Abnormal iron deposition detected by QSM in the infarct regions of AIS patients may not affect iron levels in the non-infarct regions of responsible arteries and normal cerebral arteries, which may open the door for potential new diagnostic and treatment strategies.

Maximum spherical mean value filtering for whole-brain QSM

PURPOSE

To develop a tissue field-filtering algorithm, called maximum spherical mean value (mSMV), for reducing shadow artifacts in QSM of the brain without requiring brain-tissue erosion.

THEORY AND METHODS

Residual background field is a major source of shadow artifacts in QSM. The mSMV algorithm filters large field-magnitude values near the border, where the maximum value of the harmonic background field is located. The effectiveness of mSMV for artifact removal was evaluated by comparing existing QSM algorithms in numerical brain simulation as well as using in vivo human data acquired from 11 healthy volunteers and 93 patients.

RESULTS

Numerical simulation showed that mSMV reduces shadow artifacts and improves QSM accuracy. Better shadow reduction, as demonstrated by lower QSM variation in the gray matter and higher QSM image quality score, was also observed in healthy subjects and in patients with hemorrhages, stroke, and multiple sclerosis.

CONCLUSION

The mSMV algorithm allows QSM maps that are substantially equivalent to those obtained using SMV-filtered dipole inversion without eroding the volume of interest.

Simultaneous time-of-flight MR angiography and quantitative susceptibility mapping with key time-of-flight features

A technique for combined time-of-flight (TOF) MR angiography (MRA) and quantitative susceptibility mapping (QSM) was developed with key features of standard three-dimensional (3D) TOF acquisitions, including multiple overlapping thin slab acquisition (MOTSA), ramped RF excitation, and venous saturation. The developed triple-echo 3D TOF-QSM sequence enabled TOF-MRA, susceptibility-weighted imaging (SWI), QSM, and R2* mapping. The effects of ramped RF, resolution, flip angle, venous saturation, and MOTSA were studied on QSM. Six volunteers were scanned at 3 T with the developed sequence, conventional TOF-MRA, and conventional SWI. Quantitative comparison of susceptibility values on QSM and normalized arterial and venous vessel-to-background contrasts on TOF and SWI were performed. The ramped RF excitation created an inherent phase variation in the raw phase. A generic correction factor was computed to remove the phase variation to obtain QSM without artifacts from the TOF-QSM sequence. No statistically significant difference was observed between the developed and standard QSM sequence for susceptibility values. However, maintaining standard TOF features led to compromises in signal-to-noise ratio for QSM and SWI, arising from the use of MOTSA rather than one large 3D slab, higher TOF spatial resolution, increased TOF background suppression due to larger flip angles, and reduced venous signal from venous saturation. In terms of vessel contrast, veins showed higher normalized contrast on SWI derived from TOF-QSM than the standard SWI sequence. While fast flowing arteries had reduced contrast compared with standard TOF-MRA, no statistical difference was observed for slow flowing arteries. Arterial contrast differences largely arise from the longer TR used in TOF-QSM over standard TOF-MRA to accommodate additional later echoes for SWI. In conclusion, although the sequence has a longer TR and slightly lower arterial contrast, provided an adequate correction is made for ramped RF excitation effects on phase, QSM may be performed from a multiecho sequence that includes all key TOF features, thus enabling simultaneous TOF-MRA, SWI, QSM, and R2* map computation.

Exploiting gradient-echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility-induced frequency for quantitative susceptibility mapping

PURPOSE

This work is to investigate the microstructure-induced frequency shift in white matter (WM) with crossing fibers and to separate the microstructure-related frequency shift from the bulk susceptibility-induced frequency shift by model fitting the gradient-echo (GRE) frequency evolution for potentially more accurate quantitative susceptibility mapping (QSM).

METHODS

A hollow-cylinder fiber model (HCFM) with two fiber populations was developed to investigate GRE frequency evolutions in WM voxels with microstructural orientation dispersion. The simulated and experimentally measured TE-dependent local frequency shift was then fitted to a simplified frequency evolution model to obtain a microstructure-related frequency difference parameter (∆ f $$ \Delta f $$ ) and a TE-independent bulk susceptibility-induced frequency shift (C f $$ {C}_f $$ ). The obtainedC f $$ {C}_f $$ was then used for QSM reconstruction. Reconstruction performances were evaluated using a numerical head phantom and in vivo data and then compared to other multi-echo combination methods.

RESULTS

GRE frequency evolutions and∆ f $$ \Delta f $$ -based tissue parameters in both parallel and crossing fibers determined from our simulations were comparable to those observed in vivo. The TE-dependent frequency fitting method outperformed other multi-echo combination methods in estimatingC f $$ {C}_f $$ in simulations. The fitted∆ f $$ \Delta f $$ ,C f $$ {C}_f $$ , and QSM could be improved further by navigator-based B0 fluctuation correction.

CONCLUSION

A HCFM with two fiber populations can be used to characterize microstructure-induced frequency shifts in WM regions with crossing fibers. HCFM-based TE-dependent frequency fitting provides tissue contrast related to microstructure (∆ f $$ \Delta f $$ ) and in addition may help improve the quantification accuracy ofC f $$ {C}_f $$ and the corresponding QSM.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

Assessment for Carotid Atherosclerotic Plaque Using Vessel Wall Magnetic Resonance Imaging: A Multireader ROC Study to Determine Optimal Sequence for Detecting Vessel Wall Calcification

INTRODUCTION

We aimed to compare conventional vessel wall MR imaging techniques and quantitative susceptibility mapping (QSM) to determine the optimal sequence for detecting carotid artery calcification.

METHODS

Twenty-two patients who underwent carotid vessel wall MR imaging and neck CT were enrolled. Four slices of 6-mm sections from the bilateral internal carotid bifurcation were subdivided into 4 segments according to clock position (0-3, 3-6, 6-9, and 9-12) and assessed for calcification. Two blinded radiologists independently reviewed a total of 704 segments and scored the likelihood of calcification using a 5-point scale on spin-echo imaging, FLASH, and QSM. The observer performance for detecting calcification was evaluated by a multireader, multiple-case receiver operating characteristic study. Weighted κ statistics were calculated to assess interobserver agreement.

RESULTS

QSM had a mean area under the receiver operating characteristic curve of 0.85, which was significantly higher than that of any other sequence (p < 0.01) and showed substantial interreader agreement (κ = 0.68). A segment with a score of 3-5 was defined as positive, and a segment with a score of 1-2 was defined as negative; the sensitivity and specificity of QSM were 0.75 and 0.87, respectively.

CONCLUSION

QSM was the most reliable MR sequence for the detection of plaque calcification.

Quantitative susceptibility mapping in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

Quantitative susceptibility mapping (QSM) is a quantitative measure based on magnetic resonance imaging sensitive to iron and myelin content. This makes QSM a promising non-invasive tool for multiple sclerosis (MS) in research and clinical practice.

OBJECTIVE

We performed a systematic review and meta-analysis on the use of QSM in MS.

METHODS

Our review was prospectively registered on PROSPERO (CRD42022309563). We searched five databases for studies published between inception and 30th April 2023. We identified 83 English peer-reviewed studies that applied QSM images on MS cohorts. Fifty-five included studies had at least one of the following outcome measures: deep grey matter QSM values in MS, either compared to healthy controls (HC) (k = 13) or correlated with the score on the Expanded Disability Status Scale (EDSS) (k = 7), QSM lesion characteristics (k = 22) and their clinical correlates (k = 17), longitudinal correlates (k = 11), histological correlates (k = 7), or correlates with other imaging techniques (k = 12). Two meta-analyses on deep grey matter (DGM) susceptibility data were performed, while the remaining findings could only be analyzed descriptively.

RESULTS

After outlier removal, meta-analyses demonstrated a significant increase in the basal ganglia susceptibility (QSM values) in MS compared to HC, caudate (k = 9, standardized mean difference (SDM) = 0.54, 95 % CI = 0.39-0.70, I2 = 46 %), putamen (k = 9, SDM = 0.38, 95 % CI = 0.19-0.57, I2 = 59 %), and globus pallidus (k = 9, SDM = 0.48, 95 % CI = 0.28-0.67, I2 = 60 %), whereas thalamic QSM values exhibited a significant reduction (k = 12, SDM = -0.39, 95 % CI = -0.66--0.12, I2 = 84 %); these susceptibility differences in MS were independent of age. Further, putamen QSM values positively correlated with EDSS (k = 4, r = 0.36, 95 % CI = 0.16-0.53, I2 = 0 %). Regarding rim lesions, four out of seven studies, representing 73 % of all patients, reported rim lesions to be associated with more severe disability. Moreover, lesion development from initial detection to the inactive stage is paralleled by increasing, plateauing (after about two years), and gradually decreasing QSM values, respectively. Only one longitudinal study provided clinical outcome measures and found no association. Histological data suggest iron content to be the primary source of QSM values in DGM and at the edges of rim lesions; further, when also considering data from myelin water imaging, the decrease of myelin is likely to drive the increase of QSM values within WM lesions.

CONCLUSIONS

We could provide meta-analytic evidence for DGM susceptibility changes in MS compared to HC; basal ganglia susceptibility is increased and, in the putamen, associated with disability, while thalamic susceptibility is decreased. Beyond these findings, further investigations are necessary to establish the role of QSM in MS for research or even clinical routine.