Repeat it without me: Crowdsourcing the T1 mapping common ground via the ISMRM reproducibility challenge

PURPOSE: T1 mapping is a widely used quantitative MRI technique, but its tissue-specific values remain inconsistent across protocols, sites, and vendors. The ISMRM Reproducible Research and Quantitative MR study groups jointly launched a challenge to assess the reproducibility of a well-established inversion-recovery T1 mapping technique, using acquisition details from a seminal T1 mapping paper on a standardized phantom and in human brains. METHODS: The challenge used the acquisition protocol from Barral et al. (2010). Researchers collected T1 mapping data on the ISMRM/NIST phantom and/or in human brains. Data submission, pipeline development, and analysis were conducted using open-source platforms. Intersubmission and intrasubmission comparisons were performed. RESULTS: Eighteen submissions (39 phantom and 56 human datasets) on scanners by three MRI vendors were collected at 3 T (except one, at 0.35 T). The mean coefficient of variation was 6.1% for intersubmission phantom measurements, and 2.9% for intrasubmission measurements. For humans, the intersubmission/intrasubmission coefficient of variation was 5.9/3.2% in the genu and 16/6.9% in the cortex. An interactive dashboard for data visualization was also developed: https://rrsg2020.dashboards.neurolibre.org. CONCLUSION: The T1 intersubmission variability was twice as high as the intrasubmission variability in both phantoms and human brains, indicating that the acquisition details in the original paper were insufficient to reproduce a quantitative MRI protocol. This study reports the inherent uncertainty in T1 measures across independent research groups, bringing us one step closer to a practical clinical baseline of T1 variations in vivo

Cubic topology in surfactant and lipid mixtures

Ternary systems of palmitoyl-oleoyl-phosphatidylcholine (POPC) and the non-ionic surfactant C12EO2 (di-ethylene-oxide-mono-dodecyl-ether) in water have been studied with optical microscopy, NMR, DSC and X-rays from ambient temperatures to 45 °C. Below 29 °C the system is in the lamellar liquid crystalline state. Between 30 and 32 °C it transforms into a cubic Ia3d structure which converts into the cubic Pn3m phase at 39 °C. The transitions are fully reversible. An epitaxial relationship between all three phases was found, which is an elegant and convenient way to rearrange molecules from lamellar bilayers to a network of curved surfaces. The la3d (Q230) to Pn3m (Q224) transition occurs without measurable enthalpy change. This, together with the metric relation of 1.60 between the cubic lattice constants is strong evidence for a Bonnet transformation, where the structural changes occur without change in curvature. The potential significance of the cubic phases as intermediate structures for biological processes, e. g. transport across a bilayer or fusion of membranes, are discussed

Myelination of major white matter tracts continues beyond childhood - combining tractography and myelin water imaging

In this project, we combine diffusion tensor imaging tractography with myelin water imaging to track myelination in the developing brain in vivo. Internal project name: TRACUL

Myelin development in visual scene-network tracts beyond late childhood: A multimethod neuroimaging study

Internal project name: SCENEPRO_strucon

dGEMRIC and metal artifact at 3T

Objective. To evaluate the effect of metal artifact reduction techniques on dGEMRIC T₁ calculation with surgical hardware present. Materials and Methods. We examined the effect of stainless steel and titanium hardware on dGEMRIC T₁ maps. We tested two strategies to reduce metal artifact in dGEMRIC: 1) saturation recovery (SR) instead of inversion recovery (IR) and 2) applying the Metal Artifact Reduction Sequence (MARS), in a gadolinium-doped agarose gel phantom and in vivo with titanium hardware. T₁ maps were obtained using custom curve-fitting software and phantom ROIs were defined to compare conditions (metal, MARS, IR, SR). Results. A large area of artifact appeared in phantom IR images with metal when TI≤700ms. IR maps with metal had additional artifact both in vivo and in the phantom (shifted null points, increased mean T₁ (+151% IR ROIartifact) and decreased mean inversion efficiency (f; 0.45 ROIartifact, versus 2 for perfect inversion)) compared to the SR maps (ROIartifact: +13% T1 SR, 0.95 versus 1 for perfect excitation), however SR produced noisier T₁ maps than IR (phantom SNR: 118 SR, 212 IR). MARS subtly reduced the extent of artifact in the phantom (IR and SR). Conclusion. dGEMRIC measurement in the presence of surgical hardware at 3T is possible with appropriately applied strategies. Measurements may work best in the presence of titanium and are severely limited with stainless steel. For regions near hardware where IR produces large artifacts making dGEMRIC analysis impossible, SRMARS may allow dGEMRIC measurements. The position and size of the IR artifact is variable, and must be assessed for each implant/imaging set-up.Applied Science, Faculty ofMedicine, Faculty ofScience, Faculty ofOther UBCNon UBCMechanical Engineering, Department ofOrthopaedic Surgery, Department ofPhysics and Astronomy, Department ofReviewedFacultyGraduat

Myelin water imaging from multi-echo T₂ MR relaxometry data using a joint sparsity constraint

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary. A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint. The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity. The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm (0.0266). In conclusion, the proposed method for MWF estimation is less computationally expensive and less susceptible to noise compared to state of the art methods. These improvements might be an important step towards clinical translation of MWF measurements.</p

Myelin water imaging from multi-echo T₂ MR relaxometry data using a joint sparsity constraint

Demyelination is the key pathological process in multiple sclerosis (MS). The extent of demyelination can be quantified with magnetic resonance imaging by assessing the myelin water fraction (MWF). However, long computation times and high noise sensitivity hinder the translation of MWF imaging to clinical practice. In this work, we introduce a more efficient and noise robust method to determine the MWF using a joint sparsity constraint and a pre-computed B1+-T2 dictionary. A single component analysis with this dictionary is used in an initial step to obtain a B1+ map. The T2 distribution is then determined from a reduced dictionary corresponding to the estimated B1+ map using a combination of a non-negativity and a joint sparsity constraint. The non-negativity constraint ensures that a feasible solution with non-negative contribution of each T2 component is obtained. The joint sparsity constraint restricts the T2 distribution to a small set of T2 relaxation times shared between all voxels and reduces the noise sensitivity. The applied Sparsity Promoting Iterative Joint NNLS (SPIJN) algorithm can be implemented efficiently, reducing the computation time by a factor of 50 compared to the commonly used regularized non-negative least squares algorithm. The proposed method was validated in simulations and in 8 healthy subjects with a 3D multi-echo gradient- and spin echo scan at 3 ​T. In simulations, the absolute error in the MWF decreased from 0.031 to 0.013 compared to the regularized NNLS algorithm for SNR ​= ​250. The in vivo results were consistent with values reported in literature and improved MWF-quantification was obtained especially in the frontal white matter. The maximum standard deviation in mean MWF in different regions of interest between subjects was smaller for the proposed method (0.0193) compared to the regularized NNLS algorithm (0.0266). In conclusion, the proposed method for MWF estimation is less computationally expensive and less susceptible to noise compared to state of the art methods. These improvements might be an important step towards clinical translation of MWF measurements.ImPhys/Medical ImagingImPhys/Computational Imagin

A pilot study of magnetic resonance fingerprinting in Parkinson's disease

Parkinson's disease (PD) affects more than six million people, but reliable MRI biomarkers with which to diagnose patients have not been established. Magnetic resonance fingerprinting (MRF) is a recent quantitative technique that can provide relaxometric maps from a single sequence. The purpose of this study is to assess the potential of MRF to identify PD in patients and their disease severity, as well as to evaluate comfort during MRF. Twenty-five PD patients and 25 matching controls underwent 3 T MRI, including an axial 2D spoiled gradient echo MRF sequence. T1 and T2 maps were generated by voxel-wise matching the measured MRF signal to a precomputed dictionary. All participants also received standard inversion recovery T1 and multi-echo T2 mapping. An ROI-based analysis of relaxation times was performed. Differences between patients and controls as well as techniques were determined by logistic regression, Spearman correlation and t-test. Patients were asked to estimate the subjective comfort of the MRF sequence. Both MRF-based T1 and T2 mapping discriminated patients from controls: T1 relaxation times differed most in cortical grey matter (PD 1337 ± 38 vs. control 1386 ± 37 ms; mean ± SD; P =.0001) and, in combination with normal-appearing white matter, enabled correct discrimination in 85.7% of cases (sensitivity 83.3%; specificity 88.0%; receiver-operating characteristic [ROC]) area under the curve [AUC] 0.87), while for T2 mapping the left putamen was the strongest classifier (40.54 ± 6.28 vs. 34.17 ± 4.96 ms; P =.0001), enabling differentiation of groups in 84.0% of all cases (sensitivity 80.0%; specificity 88.0%; ROC AUC 0.87). Relaxation time differences were not associated with disease severity. Standard mapping techniques generated significantly different relaxation time values and identified other structures as different between groups other than MRF. Twenty-three out of 25 PD patients preferred the MRF examination instead of a standard MRI. MRF-based mapping can identify PD patients with good comfort but needs further assessment regarding disease severity identification and its potential for comparability with standard mapping technique results

Tractography-assisted deep brain stimulation of the superolateral branch of the medial forebrain bundle (slMFB DBS) in major depression

Background: Deep brain stimulation (DBS) of the superolateral branch of the medial forebrain bundle (slMFB) emerges as a - yet experimental - treatment for major depressive disorder (MDD) and other treatment refractory psychiatric diseases. First experiences have been reported from two open label pilot trials in major depression (MDD) and long-term effectiveness for MDD (50 months) has been reported. Objective: To give a detailed description of the surgical technique for DBS of the superolateral branch of the medial forebrain bundle (slMFB) in MDD. Methods: Surgical experience from bilateral implantation procedures in n = 24 patients with MDD is reported. The detailed procedure of tractography-assisted targeting together with detailed electrophysiology in 144 trajectories in the target region (recording and stimulation) is described. Achieved electrode positions were evaluated based on postoperative helical CT and fused to preoperative high resolution anatomical magnetic resonance imaging (MRI; Philips Medical Systems, Best, Netherlands), including the pre-operative diffusion tensor imaging (DTI) tractographic information (StealthViz DTI, Medtronic, USA; Framelink 5.0, Medtronic, USA). Midcommissural point (MCP) coordinates of effective contact (EC) location, together with angles of entry into the target region were evaluated. To investigate incidental stimulation of surrounding nuclei (subthalamic nucleus, STN; substantia nigra, SNr; and red nucleus, RN) as a possible mechanism, a therapeutic triangle (TT) was defined, located between these structures (based on MRI criteria in T2) and evaluated with respect to EC locations. Results: Bilateral slMFB DBS was performed in all patients. We identified an electrophysiological environment (defined by autonomic reaction, passive microelectrode recording, acute effects and oculomotor effects) that helps to identify the proper target site on the operation table. Postoperative MCP-evaluation of effective contacts (EC) shows a significant variability with respect to localization. Evaluation of the TT shows that responders will typically have their active contacts inside the triangle and that surrounding nuclei (STN, SNr, RN) are not directly hit by EC, indicating a predominant white matter stimulation. The individual EC position within the triangle cannot be predicted and is based on individual slMFB (tractography) geometry. There was one intracranial bleeding (FORESEE I study) during a first implantation attempt in a patient who later received full bilateral implantation. Typical oculomotor side effects are idiosyncratic for the target region and at inferior contacts. Conclusion: The detailed surgical procedure of slMFB DBS implantation has not been described before. The slMFB emerges as an interesting region for the treatment of major depression (and other psychiatric diseases) with DBS. So far it has only been successfully researched in open label clinical case series and in 15 patients published. Stimulation probably achieves its effect through direct white-matter modulation of slMFB fibers. The surgical implantation comprises a standardized protocol combining tractographic imaging based on DTI, targeting and electrophysiological evaluation of the target region. To this end, slMFB DBS surgery is in technical aspects comparable to typical movement disorder surgery. In our view, slMFB DBS should only be performed under tractographic assistance. Keywords: Deep brain stimulation, Depression, Diffusion tensor imaging, Fiber tracking, Medial forebrain bundle, OCD, slMFB, Stereotactic surgery, Tractograph