Morphology Enabled Dipole Inversion Research Articles

Development of the MIITRA QSM template: a high‐resolution magnetic susceptibility template of the older adult brain in the MIITRA atlas space

AbstractBackgroundA QSM template of the older‐adult brain is not yet available. This study constructed a high resolution QSM template of the older‐adult brain for the MITRA atlas using data from a large, diverse, community cohort of non‐demented older‐adults.MethodMagnetic susceptibility maps were generated for the 400 older‐adult paricipants used in the construction of MIITRA using the Morphology Enabled Dipole Inversion(MEDI) on the 3D 5‐echo GRE data(0.7×0.7×1.3mm3) and upsampled to 0.7×0.7×0.65mm3 using nonlocal upsampling. The first GRE echo of each participant were N4 bias field corrected, then upsampled to 0.7×0.7×0.65mm3 using non‐local upsampling and converted to synthetic T1w images using mri_synthsr. The original 3D T1w MPRAGE(1×1×1mm3) data were upsampled to 0.5×0.5×0.5mm3. The synthetic T1w images were linearly registered to the upsampled T1w data and the resulting transformations were used to forward‐map magnetic susceptibility values from the native space of each participant to exact physical locations in MIITRA space. A sparse representation based data‐fusion approach was used on the transformed signals to generate the final 0.5×0.5×0.5mm3 resolution template, denoted as MIITRA_QSM(Fig.1). Since no other magnetic susceptibility template of the older‐adult brain is currently available, we compared MIITRA_QSM to a young adult template named MuSus‐100(1×1×1mm3,100 participants,mean age 24 years) in terms of image quality and magnetic susceptibility properties.ResultVisual showed that MIITRA_QSM template includes fine details, has the expected QSM contrast, highest values in subcortical, brainstem, and cerebellar structures known for their high magnetic susceptibility(especially in older adults), lower values in the white compared to gray matter, and higher values in white matter of the frontal lobe compared to parietal and occipital lobes. When compared to MuSus‐100, MIITRA_QSM showed better delineation of cortical structures and higher image sharpness(Fig.2), as well as higher magnetic susceptibility values in most subcortical brain structures(Fig.3A), Cortical structures from the two templates exhibited more similar magnetic susceptibility values(Fig.3B).ConclusionMagnetic susceptibility values in specific subcortical, brainstem and cerebellar structures are higher in the MIITRA_QSM template compared to a young adult template, probably due to increased metal deposition in these structures with aging. The new template is expected to greatly enhance the accuracy of voxel‐wise and atlas‐based QSM studies on older‐adults.

Development of the MIITRA QSM template: a high‐resolution magnetic susceptibility template of the older adult brain in the MIITRA atlas space

AbstractBackgroundA QSM template of the older‐adult brain is not yet available. This study constructed a high resolution QSM template of the older‐adult brain for the MITRA atlas using data from a large, diverse, community cohort of non‐demented older‐adults.MethodMagnetic susceptibility maps were generated for the 400 older‐adult paricipants used in the construction of MIITRA using the Morphology Enabled Dipole Inversion(MEDI) on the 3D 5‐echo GRE data(0.7×0.7×1.3mm3) and upsampled to 0.7×0.7×0.65mm3 using nonlocal upsampling. The first GRE echo of each participant were N4 bias field corrected, then upsampled to 0.7×0.7×0.65mm3 using non‐local upsampling and converted to synthetic T1w images using mri_synthsr. The original 3D T1w MPRAGE(1×1×1mm3) data were upsampled to 0.5×0.5×0.5mm3. The synthetic T1w images were linearly registered to the upsampled T1w data and the resulting transformations were used to forward‐map magnetic susceptibility values from the native space of each participant to exact physical locations in MIITRA space. A sparse representation based data‐fusion approach was used on the transformed signals to generate the final 0.5×0.5×0.5mm3 resolution template, denoted as MIITRA_QSM(Fig.1). Since no other magnetic susceptibility template of the older‐adult brain is currently available, we compared MIITRA_QSM to a young adult template named MuSus‐100(1×1×1mm3,100 participants,mean age 24 years) in terms of image quality and magnetic susceptibility properties.ResultVisual showed that MIITRA_QSM template includes fine details, has the expected QSM contrast, highest values in subcortical, brainstem, and cerebellar structures known for their high magnetic susceptibility(especially in older adults), lower values in the white compared to gray matter, and higher values in white matter of the frontal lobe compared to parietal and occipital lobes. When compared to MuSus‐100, MIITRA_QSM showed better delineation of cortical structures and higher image sharpness(Fig.2), as well as higher magnetic susceptibility values in most subcortical brain structures(Fig.3A), Cortical structures from the two templates exhibited more similar magnetic susceptibility values(Fig.3B).ConclusionMagnetic susceptibility values in specific subcortical, brainstem and cerebellar structures are higher in the MIITRA_QSM template compared to a young adult template, probably due to increased metal deposition in these structures with aging. The new template is expected to greatly enhance the accuracy of voxel‐wise and atlas‐based QSM studies on older‐adults.

Cerebral Oxygen Metabolism Improves Following Hematopoietic Cell Transplantation in Children with Sickle Cell Disease

Introduction: Allogeneic hematopoietic cell transplantation (HCT) is potentially curative for patients with sickle cell disease (SCD). It is often recommended for patients with severe SCD, including those at risk of, or with a history of stroke. There has been limited investigation into the direct impact of HCT on cerebral hemodynamics. Quantitative biomarkers of cerebral hemodynamics, including oxygen extraction fraction (OEF) and cerebral blood flow (CBF), can provide an objective assessment of therapeutic efficacy of HCT as well as other emerging therapies. We have previously shown that CBF improves after HCT in patients with SCD (Sharma A, et al. Suppl 1, Blood 2021). Here, we performed a prospective evaluation using magnetic resonance imaging (MRI) to measure the OEF of the whole brain and the superior sagittal sinus (SSS), to compare cerebral oxygen metabolism in SCD patients before and after HCT. Methods: We performed anatomical and hemodynamic MRI of the brain prior to, and at 6 months after HCT in children with SCD undergoing a reduced intensity conditioning based HCT on a clinical trial (NCT04362293). Patients were receiving either hydroxyurea (HU) or chronic transfusion therapy (CTT) before HCT. MRI brain scanning was performed for all patients in a 3 Tesla MRI imaging system (Siemens MAGNETOM Prisma, Erlangen, Germany) with a 16-channel phased-array coil. Quantitative susceptibility map (QSM) imaging was performed through a 3D multi-echo gradient echo sequence with flow compensation and reconstructed with the morphology-enabled dipole inversion (MEDI) method (Liu T, et al. MRM 2013). The oxygen extraction fraction was calculated utilizing the established formula incorporating clinically measured hematocrit, tissue susceptibility, and hemoglobin susceptibility values quantified through quantitative susceptibility mapping (QSM), as previously delineated (Fan A, et al. JCBFM 2020) for the segmented vessels from the whole brain and the SSS. Results: The median age at HCT was 15.6 years (N=11). Hematocrit as well as global and regional (SSS) OEF of the patients were quantified and compared between baseline and at 6 months after HCT (Fig 1). All patients experienced a decrease in OEF after HCT. We then stratified the patients into those who were receiving HU or CTT prior to HCT. In patients receiving HU prior to HCT (n=7), there was a small decrease in OEF for the whole brain (42.4% vs. 39.9%, P = 0.40) and SSS (33.1% vs. 31.3%, P =0.12) at 6 months after HCT compared to baseline. However, in patients receiving CTT prior to HCT (n=4) both the global OEF (50.0% vs. 34.4 %, P < 0.01) and regional OEF (31.8% vs. 26.7 %, P < 0.05) decreased significantly at 6 months after HCT. All patients exhibited an increased hematocrit following HCT (Fig 2). Specifically, the HU cohort improved from a mean of 27.4% to 37.5% ( P<0.01), while the CTT cohort increased from 26.2% to 39.6% ( P<0.01) after HCT. Conclusions: Our results demonstrate the feasibility of global and regional OEF quantification using MRI in patients undergoing HCT for SCD. We observed that the OEF of the whole brain and SSS exhibited a similar downward trend after HCT in patients receiving either HU or CTT. This indicates an overall improvement in oxygen delivery after HCT. OEF decrease was marked after HCT in the CTT group, suggesting that HCT provided better cerebral hemodynamic outcomes than at baseline for this group. In contrast, the cohort of patients receiving HU showed a subtle decrease in OEF after HCT, perhaps implying that these patients had milder cerebral hemodynamic compromise than the CTT group. Both pretreatment groups demonstrated significantly higher hemoglobin concentrations after HCT compared to before treatment which may have contributed to the improvement in OEF. Our study presents objective physiologic comparisons of different clinical therapies on cerebral hemodynamics, providing early data on the effects of cerebral oxygen delivery in pediatric patients with SCD. Further studies with larger patient numbers are warranted to confirm the trends observed in oxygen metabolism and understand the mechanisms underlying differential responses to HCT and other disease-modifying therapies. These imaging biomarkers may also help assess different genetic therapies currently in development.

Evaluation of gadolinium deposition in cortical bone using three-dimensional ultrashort echo time quantitative susceptibility mapping: A preliminary study.

The aim of the current study was to investigate the feasibility of three-dimensional ultrashort echo time quantitative susceptibility mapping (3D UTE-QSM) for the assessment of gadolinium (Gd) deposition in cortical bone. To this end, 40 tibial bovine cortical bone specimens were divided into five groups then soaked in phosphate-buffered saline (PBS) solutions with five different Gd concentrations of 0, 0.4, 0.8, 1.2, and 1.6 mmol/L for 48 h. Additionally, eight rabbits were randomly allocated into three groups, consisting of a normal-dose macrocyclic gadolinium-based contrast agent (GBCA) group (n = 3), a high-dose macrocyclic GBCA group (n = 3), and a control group (n = 2). All bovine and rabbit tibial bone samples underwent magnetic resonance imaging (MRI) on a 3-T clinical MR system. A 3D UTE-Cones sequence was utilized to acquire images with five different echo times (i.e., 0.032, 0.2, 0.4, 0.8, and 1.2 ms). The UTE images were subsequently processed with the morphology-enabled dipole inversion algorithm to yield a susceptibility map. The average susceptibility was calculated in three regions of interest in the middle of each specimen, and the Pearson's correlation between the estimated susceptibility and Gd concentration was calculated. The bone samples soaked in PBS with higher Gd concentrations exhibited elevated susceptibility values. A mean susceptibility value of -2.47 ± 0.23 ppm was observed for bovine bone soaked in regular PBS, while the mean QSM value increased to -1.75 ± 0.24 ppm for bone soaked in PBS with the highest Gd concentration of 1.6 mmol/L. A strong positive correlation was observed between Gd concentrations and QSM values. The mean susceptibility values of rabbit tibial specimens in the control group, normal-dose GBCA group, and high-dose GBCA group were -4.11 ± 1.52, -3.85 ± 1.33, and -3.39 ± 1.35 ppm, respectively. In conclusion, a significant linear correlation between Gd in cortical bone and QSM values was observed. The preliminary results suggest that 3D UTE-QSM may provide sensitive noninvasive assessment of Gd deposition in cortical bone.

Quantitative susceptibility mapping using multi-channel convolutional neural networks with dipole-adaptive multi-frequency inputs.

Quantitative susceptibility mapping (QSM) quantifies the distribution of magnetic susceptibility and shows great potential in assessing tissue contents such as iron, myelin, and calcium in numerous brain diseases. The accuracy of QSM reconstruction was challenged by an ill-posed field-to-susceptibility inversion problem, which is related to the impaired information near the zero-frequency response of the dipole kernel. Recently, deep learning methods demonstrated great capability in improving the accuracy and efficiency of QSM reconstruction. However, the construction of neural networks in most deep learning-based QSM methods did not take the intrinsic nature of the dipole kernel into account. In this study, we propose a dipole kernel-adaptive multi-channel convolutional neural network (DIAM-CNN) method for the dipole inversion problem in QSM. DIAM-CNN first divided the original tissue field into high-fidelity and low-fidelity components by thresholding the dipole kernel in the frequency domain, and it then inputs the two components as additional channels into a multichannel 3D Unet. QSM maps from the calculation of susceptibility through multiple orientation sampling (COSMOS) were used as training labels and evaluation reference. DIAM-CNN was compared with two conventional model-based methods [morphology enabled dipole inversion (MEDI) and improved sparse linear equation and least squares (iLSQR) and one deep learning method (QSMnet)]. High-frequency error norm (HFEN), peak signal-to-noise-ratio (PSNR), normalized root mean squared error (NRMSE), and the structural similarity index (SSIM) were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the DIAM-CNN results had superior image quality to those of the MEDI, iLSQR, or QSMnet results. Experiments on data with simulated hemorrhagic lesions demonstrated that DIAM-CNN produced fewer shadow artifacts around the bleeding lesion than the compared methods. This study demonstrates that the incorporation of dipole-related knowledge into the network construction has a potential to improve deep learning-based QSM reconstruction.

Simulated and experimental phantom data for multi-center quality assurance of quantitative susceptibility maps at 3 T, 7 T and 9.4 T

PurposeTo develop methods for quality assurance of quantitative susceptibility mapping (QSM) using MRI at different magnetic field strengths, and scanners, using different MR-sequence protocols, and post-processing pipelines. MethodsWe built a custom phantom based on iron in two forms: homogeneous susceptibility (‘free iron’) and with fine-scaled variations in susceptibility (‘clustered iron’) at different iron concentrations. The phantom was measured at 3.0 T (two scanners), 7.0 T and 9.4 T using multi-echo, gradient echo acquisition sequences. A digital phantom analogue to the iron-phantom, tailored to obtain similar results as in experimentation was developed, with similar geometry and susceptibility values. Morphology enabled dipole inversion was applied to the phase images to obtain QSM for experimental and simulated data using the MEDI + 0 approach for background regularization. ResultsAcross all scanners, QSM-values showed a linear increase with iron concentrations. The QSM-relaxivity was 0.231 ± 0.047 ppm/mM for free and 0.054 ± 0.013 ppm/mM for clustered iron, with adjusted determination coefficients (DoC) ≥ 0.87. Similarly, the simulations yielded linear increases (DoC ≥ 0.99). In both the experimental and digital phantoms, the estimated molar susceptibility was lower with clustered iron, because clustering led to highly localized field effects. ConclusionOur iron phantom can be used to evaluate the capability of QSM to detect local variations in susceptibility across different field strengths, when using different MR-sequence protocols. The devised simulation method captures the effect of iron clustering in QSM as seen experimentally and could be used in the future to optimize QSM processing pipelines and achieve higher accuracy for local field effects, as also seen in Alzheimer’s beta-amyloid plaques.

Abstract WP106: Hemispheric Comparison Of Magnetic Susceptibility 24-72 Hours After Reperfusion

Introduction: Magnetic susceptibility is a radiological contrast mechanism that may provide a measure of oxygenation and contribute to an understanding the pathophysiology of stroke. Currently, there are few studies that have explored magnetic susceptibility in ischemic tissue as a marker of tissue injury. Our study assesses day one ischemic tissue post-reperfusion for changes in magnetic susceptibility and evaluates its relationship with radiological markers of ischemic injury - apparent diffusion coefficient (ADC). Methods: In a prospective observational study, thirty-five ischemic stroke patients who underwent endovascular thrombectomy were scanned with MRI (24 – 72 hours after reperfusion) to obtain multi-echo Gradient Echo and DWI images. An experienced neuroradiologist manually delineated ischemic tissue ROIs (region of interest) on DWI images. Contralateral ROIs were obtained using an automated method. The cerebrospinal fluid and regions of haemorrhagic transformation were excluded from the ROIs. A Morphology Enabled Dipole Inversion (MEDI) pipeline was employed to generate Quantitative Susceptibility Mapping (QSM) images, and these were used to quantify magnetic susceptibility. Mean magnetic susceptibility and mean ADC values were measured in these ROIs, and these values were then correlated. Results: Mean magnetic susceptibility of the ischemic ROI was significantly higher than that of the contralateral ROI (0.71±11.72 ppb, -5.59±7.30 ppb; p = 0.003). Mean ADC values of the ROI in the ischemic hemisphere were significantly lower than those in the contralateral hemisphere (0.65±0.09 х 10 -3 mm 2 /s, 0.81±0.05 х 10 -3 mm 2 /s; p = 1.31 х 10 -11 ). No significant correlation between susceptibility and ADC was found (ρ = -0.278, p = 0.106). Conclusion: Magnetic susceptibility in the ischemic tissue is measurable and is elevated when compared to the normal tissue. This may be attributed to the increased oxygen extraction fraction in the ischemic tissue. Further voxel wise analysis and larger longitudinal multi-parametric analysis correlating magnetic susceptibility with other imaging measures of tissue injury over time will help characterise the significance of lesional magnetic susceptibility changes in ischemic tissue.

Association between iron accumulation in the dorsal striatum and compulsive drinking in alcohol use disorder

RationaleBrain iron accumulation has been observed in neuropsychiatric disorders and shown to be related to neurodegeneration.ObjectivesIn this study, we used quantitative susceptibility mapping (QSM), an emerging MRI technique developed for quantifying tissue magnetic susceptibility, to examine brain iron accumulation in individuals with alcohol use disorder (AUD) and its relation to compulsive drinking.MethodsBased on our previous projects, QSM was performed as a secondary analysis with gradient echo sequence images, in 186 individuals with AUD and 274 healthy participants. Whole-brain susceptibility values were calculated with morphology-enabled dipole inversion and referenced to the cerebrospinal fluid. Then, the susceptibility maps were compared between AUD individuals and healthy participants. The relationship between drinking patterns and susceptibility was explored.ResultsWhole-brain analyses showed that the susceptibility in the dorsal striatum (putamen and caudate) among AUD individuals was higher than healthy participants and was positively related to the Obsessive Compulsive Drinking Scale (OCDS) scores and the amount of drinking in the past three months.ConclusionsIncreased susceptibility suggests higher iron accumulation in the dorsal striatum in AUD. This surrogate for the brain iron level was linearly associated with the compulsive drinking pattern and the recent amount of drinking, which provides us a new clinical perspective in relation to brain iron accumulation, and also might indicate an association of AUD with neuroinflammation as a consequence of brain iron accumulation. The iron accumulation in the striatum is further relevant for functional imaging studies in AUD by potentially producing signal dropout and artefacts in fMRI images.

A multi-channel input convolutional neural network for artifact reduction in quantitative susceptibility mapping

To develop a deep learning-based QSM reconstruction method for reducing artifacts to improve the accuracy of magnetic susceptibility results. To eliminate artifacts caused by susceptibility interfaces with gigantic differences, we propose a multi-channel input convolutional neural network for artifact reduction (MAR-CNN) for solving the dipole inversion problem in QSM. In this neural network, the original tissue field was first separated into two components, which were subsequently imported as additional channels into a multi-channel 3D U-Net. MAR-CNN was compared with 3 conventional model-based methods, namely truncated k-space deconvolution (TKD), morphology enabled dipole inversion (MEDI), and improved sparse linear equation and least squares method (iLSQR), and with a deep learning method (QSMnet). High-frequency error norm, peak signal-to-noise ratio, normalized root mean squared error, and structure similarity index were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the results obtained using MAR-CNN had superior peak signal-to-noise ratio (43.12±1.19) and normalized root mean squared error (51.98± 3.65) to those of TKD, MEDI, iLSQR and QSMnet. MAR-CNN outperformed QSMnet reconstruction on all the 4 quantitative metrics with significant differences (P < 0.05). Experiment on data of simulated hemorrhagic lesion demonstrated that MAR-CNN produced less shadow artifacts around the bleeding lesion than the other 4 methods. The proposed MAR-CNN for artifact reduction is capable of improving the accuracy of deep learning- based QSM reconstruction to effectively reduce artifacts.

Test-retest analysis of cerebral oxygen extraction estimates in healthy volunteers: comparison of methods based on quantitative susceptibility mapping and dynamic susceptibility contrast magnetic resonance imaging

BackgroundEstimation of the oxygen extraction fraction (OEF) by quantitative susceptibility mapping (QSM) magnetic resonance imaging (MRI) is promising but requires systematic evaluation. Extraction of OEF-related information from the tissue residue function in dynamic susceptibility contrast MRI (DSC-MRI) has also been proposed. In this study, whole-brain OEF repeatability was investigated, as well as the relationships between QSM-based OEF and DSC-MRI-based parameters, i.e., mean transit time (MTT) and an oxygen extraction index, referred to as apparent OEF (AOEF). MethodTest-retest data were obtained from 20 healthy volunteers at 3 T. QSM maps were reconstructed from 3D gradient-echo MRI phase data, using morphology-enabled dipole inversion. DSC-MRI was accomplished using gradient-echo MRI at a temporal resolution of 1.24 s. ResultsThe whole-brain QSM-based OEF was (40.4±4.8) % and, in combination with a previously published cerebral blood flow (CBF) estimate, this corresponds to a cerebral metabolic rate of oxygen level of CMRO2 = 3.36 ml O2/min/100 g. The intra-class correlation coefficient [ICC(2,1)] for OEF test-retest data was 0.73. The MTT-versus-OEF and AOEF-versus-OEF relationships showed correlation coefficients of 0.61 (p = 0.004) and 0.52 (p = 0.019), respectively. DiscussionQSM-based OEF showed a convincing absolute level and good test-retest results in terms of the ICC. Moderate to good correlations between QSM-based OEF and DSC-MRI-based parameters were observed. The present results constitute an indicator of the level of robustness that can be achieved without applying extraordinary resources in terms of MRI equipment, imaging protocol, QSM reconstruction, and OEF analysis.

Feasibility of ultrashort echo time quantitative susceptibility mapping with a 3D cones trajectory in the human brain.

Quantitative susceptibility mapping (QSM) has surfaced as a promising non-invasive quantitative biomarker that provides information about tissue composition and microenvironment. Recently, ultrashort echo time quantitative susceptibility mapping (UTE-QSM) has been investigated to achieve QSM of short T2 tissues. As the feasibility of UTE-QSM has not been demonstrated in the brain, the goal of this study was to develop a UTE-QSM with an efficient 3D cones trajectory and validate it in the human brain. An ultrashort echo time (UTE) cones sequence was implemented in a 3T clinical MRI scanner. Six images were acquired within a single acquisition, including UTE and gradient recalled echo (GRE) images. To achieve QSM, a morphology-enabled dipole inversion (MEDI) algorithm was incorporated, which utilizes both magnitude and phase images. Three fresh cadaveric human brains were scanned using the 3D cones trajectory with eight stretching factors (SFs) ranging from 1.0 to 1.7. In addition, five healthy volunteers were recruited and underwent UTE-QSM to demonstrate the feasibility in vivo. The acquired data were processed with the MEDI-QSM pipeline. The susceptibility maps estimated by UTE-QSM showed reliable tissue contrast. In the ex vivo experiment, high correlations were found between the baseline (SF of 1.0) and SFs from 1.1 to 1.7 with Pearson's correlations of 0.9983, 0.9968, 0.9959, 0.9960, 0.9954, 0.9943, and 0.9879, respectively (all p-values < 0.05). In the in vivo experiment, the measured QSM values in cortical gray matter, juxtacortical white matter, corpus callosum, caudate, and putamen were 25.4 ± 4.0, -21.8 ± 3.2, -22.6 ± 10.0, 77.5 ± 18.8, and 53.8 ± 7.1 ppb, consistent with the values reported in the literature. Ultrashort echo time quantitative susceptibility mapping enables direct estimation of the magnetic susceptibility in the brain with a dramatically reduced total scan time by use of a stretched 3D cones trajectory. This technique provides a new biomarker for susceptibility mapping in the in vivo brain.

Quantitative susceptibility mapping improves cerebral microbleed detection relative to susceptibility-weighted images.

Cerebral microbleed (CMB) detection impacts disease diagnosis and management. Susceptibility-weighted imaging (SWI) MRI depictions of CMBs are used with phase images (SWIP) to distinguish blood from calcification, via qualitative intensity evaluation (bright/dark). However, the intensities depicted for a single lesion can vary within and across consecutive SWIP image planes, impairing the classification of findings as a CMB. We hypothesize that quantitative susceptibility mapping (QSM) MRI, which maps tissue susceptibility, demonstrates less in- and through-plane intensity variation, improving the clinician's ability to categorize a finding as a CMB. Forty-eight patients with acute intracranial hemorrhage who received multi-echo gradient echo MRI used to generate both SWI/SWIP and morphology-enabled dipole inversion QSM images were enrolled. Five hundred and sixty lesions were visually classified as having homogeneous or heterogeneous in-plane and through-plane intensity by a neuroradiologist and two diagnostic radiology residents using published rating criteria. When available, brain CT scans were analyzed for calcification or acute hemorrhage. Relative risk (RR) ratios and confidence intervals (CIs) were calculated using a generalized linear model with log link and binary error. QSM showed unambiguous lesion signal intensity three times more frequently than SWIP (RR = 0.3235, 95% CI 0.2386-0.4386, p<.0001). The probability of QSM depicting homogeneous lesion intensity was three times greater than SWIP for small (RR = 0.3172, 95% CI 0.2382-0.4225, p<.0001), large (RR = 0.3431, 95% CI 0.2045-0.5758, p<.0001), lobar (RR = 0.3215, 95% CI 0.2151-0.4805, p<.0001), cerebellar (RR = 0.3215, 95% CI 0.2151-0.4805, p<.0001), brainstem (RR = 0.3100, 95% CI 0.1192-0.8061, p = .0163), and basal ganglia (RR = 0.3380, 95% CI 0.1980-0.5769, p<.0001) lesions. QSM more consistently demonstrates interpretable lesion intensity compared to SWIP as used for distinguishing CMBs from calcification.

Early differentiation of neurodegenerative diseases using the novel QSM technique: what is the biomarker of each disorder?

During neurodegenerative diseases, the brain undergoes morphological and pathological changes; Iron deposits are one of the causes of pathological changes in the brain. The Quantitative susceptibility mapping (QSM) technique, a type of magnetic resonance (MR) image reconstruction, is one of the newest diagnostic methods for iron deposits to detect changes in magnetic susceptibility. Numerous research projects have been conducted in this field. The purpose of writing this review article is to identify the first deep brain nuclei that undergo magnetic susceptibility changes during neurodegenerative diseases such as Alzheimer's or Parkinson's disease. The purpose of this article is to identify the brain nuclei that are prone to iron deposition in any specific disorder. In addition to the mentioned purpose, this paper proposes the optimal scan parameters and appropriate algorithms of each QSM reconstruction step by reviewing the results of different articles. As a result, The QSM technique can identify nuclei exposed to iron deposition in various neurodegenerative diseases. Also, the selection of scan parameters is different based on the sequence and purpose; an example of the parameters is placed in the tables. The BET toolbox in FSL, Laplacian-based phase-unwrapping process, the V_SHARP algorithm, and morphology-enabled dipole inversion (MEDI) method are the most widely used algorithms in various stages of QSM reconstruction.

Cerebral Microbleeds Are Associated With Increased Brain Iron and Cognitive Impairment in Patients With Cerebral Small Vessel Disease: A Quantitative Susceptibility Mapping Study.

Cerebral microbleeds (CMBs) have been recognized to play an important role in cognitive impairment of cerebral small vessel disease (CSVD) patients. However, the mechanism of this effect is still unclear. Comparing the susceptibility values in the selected subcortical gray matter structures of CSVD patients without CMBs (CSVD-N) and with CMBs (CSVD-C) as well as healthy controls (HCs). Prospective. Sixty-nine CSVD patients and 28 HCs were included; 24 CSVD patients (34.78%) had CMBs and 45 CSVD patients (65.22%) had no CMBs. All subjects were imaged on a 3.0 T MR scanner. The protocol consisted of a three-dimensional (3D) T1-weighted sequence and a 3D multi-echo gradient echo (mGRE) sequence. Brain QSM maps were computed from mGRE data using the morphology-enabled dipole inversion with automatic uniform cerebrospinal fluid zero reference algorithm (MEDI+0). The mean susceptibility value within each region of interest was recorded. All participants underwent the cognitive assessment. Brain iron deposition burden of CMB lesions of every CSVD-C patient was computed. One-way analysis of variance test followed by Tukey's honest significance test and Kruskal-Wallis test were used with significance level of 0.05. Stepwise multivariate linear analysis was used to explore the factors influencing cognitive scores. Montreal cognitive assessment (MoCA), trail-making test (TMT)-A and TMT-B scores in the three groups were significantly different (all P < 0.05). Stepwise multivariate linear regression analysis revealed that the factors influenced MoCA scores were having CMBs (P < 0.05), white matter hyperintensities (P < 0.05), lacunes (P < 0.05) in brain, and the brain iron deposition burden of CMB lesions (P < 0.05) and for TMT scores (TMT-A + TMT-B), the influencing factors were age (P < 0.05), education years (P < 0.05), and the brain iron deposition burden of CMB lesions (P < 0.05). The higher iron deposition burden of CMB lesions in brain may be an imaging quantitative marker of cognitive decline in patients with CSVD-C. 1 TECHNICAL EFFICACY: Stage 2.

NIMG-12. MR SUSCEPTIBILITY IMAGING FOR DETECTION OF TUMOR-ASSOCIATED MACROPHAGES IN GLIOBLASTOMA

Abstract BACKGROUND Tumor-associated macrophages (TAMs) are a key component of glioblastoma (GBM) tumor microenvironment. Considering the differential role of different TAM phenotypes in iron metabolism with the M1 phenotype storing intracellular iron, and M2 phenotype releasing iron in the tumor microenvironment, here we investigated non-invasive quantitative susceptibility mapping (QSM) and T2* MRI relaxometry to quantify iron as imaging biomarkers for TAMs in adult patients with GBM. METHODS In this prospective study, 21 adult patients with GBM were enrolled between 2016 to 2019. Patients underwent a 3D single echo gradient echo sequence in addition to standard anatomical sequences on a 3 Tesla MRI. QSM images were reconstructed using the morphology-enabled dipole inversion (MEDI) algorithm. In 3 subjects, ex vivo imaging of surgical specimens was performed on a Bruker 9.4 Tesla 8.9 cm vertical bore MR using 3D multi-echo GRE scans, and R2* (1/T2*) maps were generated by a pixel-wise monoexponential fitting. Each specimen was stained with hematoxylin and eosin, as well as with CD68, CD86, CD206, and L-Ferritin. RESULTS Significant positive correlation was observed between mean susceptibility for the tumor enhancing zone and the L-ferritin positivity percent (r =0.56, p=0.018) and the combination of tumor’s enhancing zone and necrotic core and the L-Ferritin positivity percent (r=0.72; p=0.001). Moreover, the mean susceptibility significantly correlated with positivity percent for CD68 (ρ=0.52, p=0.034) and CD86 (r=0.7 p=0.001), but not for CD206 (ρ=0.09; p=0.7). There was a positive correlation between mean R2* values and CD68 positive cell counts (r =0.6, p=0.016). Similarly, mean R2* values significantly correlated with CD86 (r=0.54, p=0.03) but not with CD206 (r=0.15, p=0.5). High mean susceptibility in the necrotic core was associated with inferior PFS (hazard ratio,4.5, p=0.016). CONCLUSION MR Susceptibility Imaging can quantify the iron content of GBM and provide a non-invasive method for TAM quantification and phenotyping.

Magnetic susceptibility and R2* of myocardial reperfusion injury at 3T and 7T.

Magnetic susceptibility (Δχ) alterations have shown association with myocardial infarction (MI) iron deposition, yet there remains limited understanding of the relationship between relaxation rates and susceptibility or the effect of magnetic field strength. Hence, Δχ and in MI were compared at 3T and 7T. Subacute MI was induced by coronary artery ligation in male Yorkshire swine. 3D multiecho gradient echo imaging was performed at 1-week postinfarction at 3T and 7T. Quantitative susceptibility mapping images were reconstructed using a morphology-enabled dipole inversion. maps and quantitative susceptibility mapping were generated to assess the relationship between , Δχ, and field strength. Infarct histopathology was investigated. Magnetic susceptibility was not significantly different across field strengths (7T: 126.8 ± 41.7 ppb; 3T: 110.2 ± 21.0 ppb, P = NS), unlike (7T: 247.0 ± 14.8 Hz; 3T: 106.1 ± 6.5 Hz, P < .001). Additionally, infarct Δχ and were significantly higher than remote myocardium. Magnetic susceptibility at 7T versus 3T had a significant association (β = 1.02, R2 = 0.82, P < .001), as did (β = 2.35, R2 = 0.98, P < .001). Infarct pathophysiology and iron deposition were detected through histology and compared with imaging findings. showed dependence and Δχ showed independence of field strength. Histology validated the presence of iron and supported imaging findings.

Quantitative Susceptibility Mapping for Staging Acute Cerebral Hemorrhages: Comparing the Conventional and Multiecho Complex Total Field Inversion magnetic resonance imaging MR Methods.

The perceived acuity of intracerebral hemorrhage (ICH) impacts the management of patients, both within emergent and outpatient/urgent settings. Morphology enabled dipole inversion (MEDI) quantitative susceptibility imaging (QSM) has improved characterization of ICH acuity, despite outstanding limitations in distinguishing blood products. Using improved susceptibility quantification, novel postprocessing QSM method from multiecho complex total field inversion (mcTFI) may better discriminate between acute and subacute ICH, compared to MEDI. Retrospective cohort study. A total of 121 subjects enrolled following positive computerized tomography (CT) findings for ICH. Subjects were grouped based on time between admission and MR imaging: hyperacute (<24 hours), acute (1-3 days), early subacute (3-7 days), and late subacute (7-18 days). A multiecho gradient echo sequence at 3.0 T was paired with clinical noncontrast CT imaging. A quantitative index (CTindex ) was derived based on relative intensities of blood on noncontrast CT. All images were co-registered, from which QSM parameters within the ICH area were assessed across groups, as well as the correlation with CTindex . Group differences were assessed using ANOVAs. Linear regressions between the CTindex , MEDI, and mcTFI measurements were used to assess their relationships. Statistical significance was set at P < 0.05. A total of 21 hyperacute, 72 acute, 21 early subacute, and 7 late-subacute patients were included in this analysis. Significant changes in blood susceptibility were found over time for the MEDI and mcTFI, although mcTFI better differentiated the hyperacute/acute from subacute stages. CTindex values within the ICH were more strongly correlated with mcTFI QSM (r=0.727) than MEDI (r=0.412) QSM. McTFI susceptibility estimation demonstrated better correlation with ICH acuity as suggested by CT, providing an improved method to assess acuity of intracranial blood products in clinical settings to identify cases that may require acute intervention. 4 TECHNICAL EFFICACY STAGE: 2.

Multi-echo gradient-recalled-echo phase unwrapping using a Nyquist sampled virtual echo train in the presence of high-field gradients.

To develop a spatio-temporal approach to accurately unwrap multi-echo gradient-recalled echo phase in the presence of high-field gradients. Using the virtual echo-based Nyquist sampled (VENyS) algorithm, the temporal unwrapping procedure is modified by introduction of one or more virtual echoes between the first lower and the immediate higher echo, so as to reinstate the Nyquist condition at locations with high-field gradients. An iterative extension of the VENyS algorithm maintains spatial continuity by adjusting the phase rotations to make the neighborhood phase differences less than π. The algorithm is evaluated using simulated data, Gadolinium contrast-doped phantom, and in vivo brain, abdomen, and chest data sets acquired at 3 T and 9.4 T. The unwrapping performance is compared with the standard temporal unwrapping algorithm used in the morphology-enabled dipole inversion-QSM pipeline as a benchmark for validation. Quantitative evaluation using numerical phantom showed significant reduction in unwrapping errors in regions of large field gradients, and the unwrapped phase revealed an exact match with the linear concentration profile of vials in a gadolinium contrast-doped phantom data acquired at 9.4 T. Without the need for additional spatial unwrapping, the iterative VENyS algorithm was able to generate spatially continuous phase images. Application to in vivo data resulted in better unwrapping performance, especially in regions with large susceptibility changes such as the air/tissue interface. The iterative VENyS algorithm serves as a robust unwrapping method for multi-echo gradient-recalled echo phase in the presence of high-field gradients.

Multi-Echo Quantitative Susceptibility Mapping for Strategically Acquired Gradient Echo (STAGE) Imaging.

PurposeTo develop a method to reconstruct quantitative susceptibility mapping (QSM) from multi-echo, multi-flip angle data collected using strategically acquired gradient echo (STAGE) imaging.MethodsThe proposed QSM reconstruction algorithm, referred to as “structurally constrained Susceptibility Weighted Imaging and Mapping” scSWIM, performs an ℓ1 and ℓ2 regularization-based reconstruction in a single step. The unique contrast of the T1 weighted enhanced (T1WE) image derived from STAGE imaging was used to extract reliable geometry constraints to protect the basal ganglia from over-smoothing. The multi-echo multi-flip angle data were used for improving the contrast-to-noise ratio in QSM through a weighted averaging scheme. The measured susceptibility values from scSWIM for both simulated and in vivo data were compared to the: original susceptibility model (for simulated data only), the multi orientation COSMOS (for in vivo data only), truncated k-space division (TKD), iterative susceptibility weighted imaging and mapping (iSWIM), and morphology enabled dipole inversion (MEDI) algorithms. Goodness of fit was quantified by measuring the root mean squared error (RMSE) and structural similarity index (SSIM). Additionally, scSWIM was assessed in ten healthy subjects.ResultsThe unique contrast and tissue boundaries from T1WE and iSWIM enable the accurate definition of edges of high susceptibility regions. For the simulated brain model without the addition of microbleeds and calcium, the RMSE was best at 5.21ppb for scSWIM and 8.74ppb for MEDI thanks to the reduced streaking artifacts. However, by adding the microbleeds and calcium, MEDI’s performance dropped to 47.53ppb while scSWIM performance remained the same. The SSIM was highest for scSWIM (0.90) and then MEDI (0.80). The deviation from the expected susceptibility in deep gray matter structures for simulated data relative to the model (and for the in vivo data relative to COSMOS) as measured by the slope was lowest for scSWIM + 1%(−1%); MEDI + 2%(−11%) and then iSWIM −5%(−10%). Finally, scSWIM measurements in the basal ganglia of healthy subjects were in agreement with literature.ConclusionThis study shows that using a data fidelity term and structural constraints results in reduced noise and streaking artifacts while preserving structural details. Furthermore, the use of STAGE imaging with multi-echo and multi-flip data helps to improve the signal-to-noise ratio in QSM data and yields less artifacts.

Increased Brain Iron Deposition in the Putamen in Patients with Type 2 Diabetes Mellitus Detected by Quantitative Susceptibility Mapping.

Background The underlying brain structural changes in type 2 diabetes mellitus (T2DM) patients have attracted increasing attention. The insulin-resistant state causes iron overload in neurons and leads to lesions in the central nervous system. Quantitative susceptibility mapping (QSM) can provide a noninvasive quantitative analysis of brain iron deposition. We aimed to compare the difference of brain iron deposition in the gray matter nucleus between T2DM patients and healthy elderly individuals using QSM. Methods Thirty-two T2DM patients and thirty-two age- and gender-matched healthy controls (HCs) were enrolled in this research. Twenty-three patients and twenty-six HCs underwent cognitive assessments. Brain QSM maps were computed from multiecho GRE data using morphology-enabled dipole inversion with automatic uniform cerebrospinal fluid zero reference algorithm (MEDI+0). ITK-SNAP was used to measure the susceptibility values reflecting the content of iron in the regions of interest (ROIs). Results The study included thirty-two T2DM patients (20 males and 12 females; mean age of 61.09 ± 9.99 years) and 32 HCs (14 males and 18 females; mean age of 59.09 ± 9.77 years). These participants had no significant difference in age or gender (P > 0.05). Twenty-three patients with T2DM (11 males and 12 females; mean age, 64.65 ± 8.44 years) and twenty-six HCs (14 males and 12 females; mean age, 62.30 ± 6.13 years) received an assessment of cognitive function. T2DM patients exhibited an obviously (t = 3.237, P = 0.003) lower Montreal Cognitive Assessment (MoCA) score (26.78 ± 2.35; HCs, 28.42 ± 0.64; normal standard ≥26) and a higher Stroop color-word test (SCWT)-C score [87(65,110); HC, 63(60,76.75), Z = −2.232, P = 0.003] than HCs. The mean susceptibility values in the putamen appeared obviously higher in T2DM patients than in HCs (t = −3.994, P < 0.001). The susceptibility values and cognitive assessment scores showed no obvious association (P > 0.05). However, an obvious correlation was observed between the changes in the susceptibility values in the putamen and the thalamus/dentate nucleus (r = 0.404, P < 0.001; r = 0.423, P < 0.001). Conclusion T2DM patients showed increased susceptibility values in the putamen and had declines in executive functions, but the linear association between them was not statistically significant. Changes in susceptibility values in the putamen indicated increased iron deposition and might be used as a quantitative imaging marker of central nervous system injury in T2DM patients. QSM might be able to help probe micro neuronal damage in gray matter and provide information on diabetic encephalopathy.