Keywords: Susceptibility/QSM, Quantitative Susceptibility mapping, Breast

Motivation: Quantitative susceptibility mapping (QSM) has recently been used to detect breast microcalcifications (MCs) which could be the precursor lesions to breast-carcinoma. However, acquiring high-resolution (HR) QSM maps reduces the signal-to-noise ratio (SNR), making detection of MCs challenging.

Goal(s): Improve the SNR in HR-QSM for better MCs visualization using deep-learning-based denoising.

Approach: A complex-valued bias-free CNN (CV-BFCNN), adapted from real-valued BFCNN, was trained on complex-valued MR data with Gaussian noise to denoise multi-echo gradient-echo images used for QSM processing.

Results: CV-BFCNN improves SNR in HR-QSM and processes complex-valued MR data directly when compared to real-valued BFCNN, and allows enhanced visualisation and detection of MCs.

Impact: The application of complex-valued deep-learning-based denoising in high-resolution QSM has substantially improved SNR and detection of micro-calcifications, a precursor to breast cancer. This helps QSM, an ionizing radiation-free alternative in detection and visualization of microcalcifications in the breast.

Keywords: Susceptibility/QSM, Data Analysis

Motivation: Magnetic susceptibility in MRI offers non-invasive insights into brain substances like iron and myelin, affecting brain function and disease. The χ-separation method promises to enhance these insights by better estimating substance concentrations.

Goal(s): To assess the test-retest reproducibility of χ-separation methods to ensure their reliability for wider use in both research and clinical settings.

Approach: Reproducibility was tested by repeating scans using 3T MRI. Statistical analysis by Bland-Altman, regression, and ICC were used for evaluation.

Results: χ-separation demonstrated high reproducibility for both positive and negative susceptibility map analyses compared to previous study regarding QSM 

Impact: This study affirms the robustness of χ-separation in MRI, enhancing the detection of iron and myelin concentrations and paving the way for more accurate brain pathology studies, potentially revolutionizing both clinical diagnostics and research into neurodegenerative diseases.

Keywords: Susceptibility/QSM, Susceptibility, Susceptibility Tensor Imaging

Motivation: When solving the Susceptibility Tensor Imaging problem, fast algorithms based on Least Squares require an elevated number of acquisitions, while more robust solvers that use DTI information may produce over-smoothed solutions. 

Goal(s): To create a deep neural network based reconstruction algorithm to produce high SNR STI images with a reduced number of MRI acquisitions.

Approach: Use a physics-informed deep neural network approach, trained with various geometrical objects, capable of accurately reconstructing susceptibility tensors.

Results: We obtained susceptibility tensors with the expected anisotropy, better alignment with DTI eigenvectors and high SNR. 

Impact: Our STI-net algorithm is capable of reconstructing accurate STI images with higher SNR, compared with traditional algorithms.

Keywords: Susceptibility/QSM, Quantitative Susceptibility mapping, functional Quantitative Susceptibility Mapping

Motivation: fQSM quantitative and spatially-specific information on brain activity may be valuable in studying cortical substructures. However, fQSM response to varying stimulus intensity is unknown, and, as for QSM, reduced z-coverage may affect quantification.

Goal(s): We aimed to assess fQSM linearity to stimulus intensity and its dependence on z-coverage.

Approach: We employed visual stimuli with different contrasts and acquired whole-brain fQSM datasets that were truncated to simulate partial coverage.

Results: We reported fQSM response linearity to different contrasts and, while extremely small coverage led to brain activity underestimation, whole-brain acquisitions were not necessary to obtain accurate results.

Impact: Linearity and feasibility at reduced z-coverage, together with high spatial specificity, suggest that fQSM may provide added value to the functional study of cortical substructures.

Keywords: Susceptibility/QSM, Quantitative Susceptibility mapping

Motivation: While GRE and SWI are the primary methods for identifying iron deposition in cerebral cavernous malformation (CCM), improved preclinical lesion characterization can be achieved by using Quantitative Susceptibility Mapping (QSM).

Goal(s): Our goal was to introduce the use of QSM in a preclinical CCM model and evaluate the impact of the different QSM methods available.

Approach: 8 healthy mice and 13 CCM mice were scanned using a multi-gradient echo and images were processed through each QSM method then compared using RMSE. 

Results: Each QSM method displayed large susceptibilities in areas suspected of CCM lesions.  

Impact: The addition of QSM for preclinical CCM may benefit longitudinal analysis. By establishing the use of QSM and further development in QSM calibration with ex vivo studies, QSM can be used for tracking CCM lesion progression noninvasively. 

Keywords: Susceptibility/QSM, Head & Neck/ENT

Motivation: Identifying hypoxia in head and neck squamous cell carcinoma (HNSCC) could improve treatment. Quantitative susceptibility mapping (QSM) offers a potential method for measuring tissue composition and oxygenation.

Goal(s): To develop a robust, repeatable pipeline for QSM in the head and neck region.

Approach: We tested various QSM reconstruction pipelines and compared their intra- and inter-session repeatability, before applying an optimized pipeline to a HNSCC patient dataset.

Results: A pipeline using ROMEO phase unwrapping, V-SHARP background field removal, and iterative Tikhonov susceptibility calculation was found to be more repeatable than the previously reported best pipeline and showed nodal susceptibility differences in a HNSCC patient.

Impact: This new optimized pipeline provides repeatable susceptibility values in key ROIs through the head and neck region and detected nodal susceptibility differences in a HNSCC patient. Therefore, it is applicable for clinical studies of tissue susceptibility and oxygenation in HNSCC.

Keywords: Susceptibility/QSM, Artifacts, chi-separation

Motivation: In QSM and χ-separation (chi-separation), artifacts from various sources may be introduced. The oversight of these artifacts could lead researchers to analyse inaccurate maps, resulting in potentially erroneous conclusions. 

Goal(s): The primary objective of this research is to investigate the characteristics, origins, and solutions related to artifacts encountered in QSM and χ-separation.

Approach: We processed QSM and χ-separation in 364 subjects from Parkinson’s disease, Alzheimer’s disease, hypertension, and alcohol-exposed adolescents development studies, reporting various types of artifacts. They are categorized and explored for origins and potential solutions.

Results: This study identified and provided solutions for 11 artifact types.

Impact: While processing QSM and χ-separation in diverse subjects and vendors, various artifacts emerged. This study categorized these artifacts, investigated origins, mitigation strategies, and discernible effects on QSM and χ-separation results, aiding researchers and practitioners in artifact identification, correction, and exclusion.

Keywords: Susceptibility/QSM, Susceptibility, Dynamic Susceptibility Contrast MRI, Cellular Structures, Tissue Structures, Simulation

Motivation: Dynamic susceptibility contrast (DSC) MRI is a robust method for imaging brain tumors, and there is potential to glean more clinically useful data than is obtained with standard-of-care DSC-MRI.

Goal(s): We aimed to systematically investigate the effect of varied cellular features on the difference in DSC-MRI-derived ΔR₂* time curves to evaluate the feasibility of recovering these features in real tissue.

Approach: We generated 3D tissue structures of ellipsoids (determined by specified parameters and randomly distributed) and applied the finite difference finite perturber method to compute ΔR₂*.

Results: In general, ΔR₂* increased then plateaued as cell volume fraction, aspect ratio, and size increased.

Impact: We simulated T₂*-weighted DSC-MRI signal for 3D tissue structures with varied cellular features to evaluate the feasibility of recovering these features in real tissue. Results suggested that cell volume fraction, aspect ratio, and size may be identifiable biomarkers.

Keywords: Susceptibility/QSM, Quantitative Imaging, Hypoxia, High-Field MRI

Motivation: Investigating R₂* and QSM for deoxyhemoglobin detection is vital for diagnosing and understanding diseases where tissue oxygenation is frequently compromised.

Goal(s): To evaluate R₂* against QSM for their ability to detect deoxyhemoglobin changes in a controlled hypoxic environment using a mouse model.

Approach: Employ a graded hypoxia protocol in naïve, female C57Bl/6 mice, capturing 3D MGE images at various oxygen levels (30%, 15% and 10%) to measure R₂* and QSM responses.

Results: R₂* demonstrated significant sensitivity to hypoxia in brain regions, particularly the hippocampus, unlike QSM, suggesting its potential as a superior hypoxia biomarker.

Impact: This study reveals R₂* relaxometry's superior sensitivity to the detection of changes in deoxyhemoglobin over QSM, potentially improving early detection and monitoring of hypoxia-related diseases, such as Multiple Sclerosis, and informing future clinical imaging protocols.

Keywords: Electromagnetic Tissue Properties, Ex-Vivo Applications, Genetic Diseases, Neurodegeneration, Iron

Motivation: Ex-vivo histology is the most common method to assess iron accumulation in frontotemporal lobar degeneration, but in vivo assessment is crucial to unravel disease mechanisms.

Goal(s): This study aims to assess the distribution and severity of iron accumulation post-mortem using susceptibility MRI and compare this to histological data.

Approach: We analyzed postmortem tissue of 5 MAPT-FTLD and 2 C9orf72-FTLD cases using a histological iron staining, T2*-weighted MRI, and QSM maps.

Results: We found that histology, susceptibility MRI, and QSM show good correspondence of iron distribution in FTLD brain tissue. However, sharp details are better seen on T2*-weighted MRI, and U-fibers on QSM maps.

Impact: Our study showed that susceptibility-based imaging can be used to visualize iron accumulation in FTLD; with T2*-weighted MRI and QSM showing complementary spatial information. Therefore, these two methods should be used parallel and not independent of each other.

Keywords: Susceptibility/QSM, Susceptibility, Clinical,Statistics,Referencing

Motivation: In QSM, there is no well-established susceptibility baseline . This can be determined a-posteriori by referencing to a specific tissue but this may impact statistics in clinical studies.

Goal(s): To derive an expression for a t-test under referencing, and to investigate the effect of commonly used reference regions on a temporal lobe epilepsy study.

Approach: Reference regions were compared: three anatomical structures and three derived from global thresholds. Changes in covariances, t-test results, and regional susceptibility distributions are presented.

Results: Referencing to small regions has a bigger impact on statistical analyses than large references. Reference regions should have a low variance across groups.

Impact: Referencing QSM susceptibility values is essential, but highly contested in practice, particularly in clinical applications. We clarify the statistical theory, and investigate the impact of referencing susceptibility measurements to different regions to facilitate practical implementation and clinical applications.

Keywords: Susceptibility/QSM, Genetic Diseases, Haematology

Motivation: Sickle cell disease (SCD) can lead to cognitive difficulties, but transfusion treatment presents a risk of iron overload which may lead to neurodegeneration. Better understanding of the impact of SCD and transfusions is needed.

Goal(s): To use quantitative susceptibility mapping (QSM) to assess iron deposition in the brain in SCD with and without transfusions.

Approach: Brain susceptibility was quantified in 28 SCD patients and 16 healthy controls using QSM and related to fine motor function by a general linear model.

Results: Susceptibilities in deep brain structures were not correlated with transfusions, SCD status (except in substantia nigra), or motor function (except in pulvinar).

Impact: Using an up-to-date QSM reconstruction pipeline reduced noise and artefacts and revealed correlations of susceptibility with age which were not found previously in these data, confirming the importance of correct coil combination for QSM studies.

Keywords: Susceptibility/QSM, Microstructure, Modelling, chi-separation method

Motivation: χ-separation method relies on assuming a certain relaxometric constant (Dr) calculated as the mean of a group of healthy subjects. Recently, we demonstrated that it is subject-specific.

Goal(s): The goal of this study was to evaluate the correlation between Dr and microstructural metrics obtained from diffusion tensor and diffusion kurtosis imaging (DTI and DKI).

Approach: We regressed between Dr against DTI and DKI diffusion metrics in a cohort of healthy controls.

Results: Results showed a positive correlation with fractional anisotropy and axial diffusivity, and a negative correlation with mean and radial kurtosis.

Impact: Understanding how the relaxometric constant of the χ-separation method (Dr) depends on microstructural diffusion metrics will define its personalization. This, in turn, will impact on how we assess the presence of different magnetic susceptibility sources in the brain.

Keywords: Susceptibility/QSM, Quantitative Susceptibility mapping, Susceptibility separation, Repeatability, Reproducibility, 3T, scan-rescan

Motivation: Susceptibility separation methods aim to separate co-existing myelin and iron contributions. However, their repeatability has not been investigated.

Goal(s): Evaluating repeatability of existing separation methods in brain and comparing their performance.

Approach: Three methods (χ-Sep, χ-SepNet, and APART) were applied to 3T scan-rescan data of 21 healthy subjects, and the resultant dia- and paramagnetic maps were evaluated in white and deep gray matter regions.

Results: Reliability varied by method and region, with many regions showing moderate to good reliability. Average repeatability coefficients were 4 ppb and 8 ppb in white matter and iron-rich deep gray regions, respectively. 

Impact: Susceptibility separation methods showed moderate to good reliability in most brain regions, and sub-voxel changes around 5 ppb might be error. Comparing values reported using different methods might not be straightforward, as the difference between measurements could exceed 15 ppb.

Keywords: Susceptibility/QSM, Quantitative Susceptibility mapping, LoopNet, Bidirectional U-net, QSM dipole inversion

Motivation: Most current deep learning (DL) QSM methods were developed based on U-net, whose performances might not be sufficiently good.  

Goal(s): To proposed a new network baseline for deep learning QSM methods development. 

Approach: We developed a LoopNet, by applying the proposed bidirectional loop and a self-tailored GHPA attention module into a Unet backbone, making better use of the latent information in deep networks.

Results: Simulated and in vivo experiments showed that the propoed LoopNet led to improved results than U-net. 

Impact: This work introduces a novel deep neural network backbone, allowing researchers to develop innovative QSM methods easily by upgrading their original U-net to LoopNet, thanks to the plug-and-play design.

Keywords: Susceptibility/QSM, Susceptibility

Motivation: Important physical parameter, relaxometric constant$$$\;{D_r}$$$, linking magnetic susceptibility to induced transverse relaxation acceleration (i.e.,$$$\;{R2'}$$$) has not yet been fully understood in brain.

Goal(s): To investigate underlying mechanisms affecting relaxometric constant in brain using temperature-dependent relaxometry and susceptibility and explore a better field-strength correction for ultra-high-field MRI.  

Approach: 3T and 7T R2*/R2'/quantitative-susceptibility maps were acquired from a post-mortem brain at different temperatures and analyzed based on the physical model.

Results: In human brain, effects of temperature-dependent water susceptibility, water diffusion, and field strength on D_r were observed, and a field-strength correction coefficient was calculated, generating consistent chi-separation maps at both 3T and 7T.

Impact: A better understanding of relaxometric constant in brain can provide better insight on effects of susceptibility sources (e.g., iron and myelin), on MR relaxometry, improving quantification accuracy of those biological substances using MRI.