Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity

Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MT_sat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.

Localizing Epileptic Foci Before Surgery in Patients With MRI-Negative Refractory Epilepsy Using Statistical Parameter Mapping and Three-Dimensional Stereotactic Surface Projection Based on 18F-FDG PET

Patients with refractory epilepsy are not only free of seizures after resecting epileptic foci, but also experience significantly improved quality of life. Fluorine-18-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) is a promising avenue for detecting epileptic foci in patients with magnetic resonance imaging (MRI)-negative refractory epilepsy. However, the detection of epileptic foci by visual assessment based on 18F-FDG PET is often complicated by a variety of factors in clinical practice. Easy imaging methods based on 18F-FDG PET images, such as statistical parameter mapping (SPM) and three-dimensional stereotactic surface projection (3D-SSP), can objectively detect epileptic foci. In this study, the regions of surgical resection of patients with over 1 year follow-up and no seizures were defined as standard epileptic foci. We retrospectively analyzed the sensitivity of visual assessment, SPM and 3D-SSP based on 18F-FDG PET to detect epileptic foci in MRI-negative refractory epilepsy patients and obtained the sensitivities of visual assessment, SPM and 3D-SSP are 57, 70 and 60% respectively. Visual assessment combined with SPM or 3D-SSP can improve the sensitivity of detecting epileptic foci. The sensitivity was highest when the three methods were combined, but decreased consistency, in localizing epileptic foci. We conclude that SPM and 3D-SSP can be used as objective methods to detect epileptic foci before surgery in patients with MRI-negative refractory epilepsy. Visual assessment is the preferred method for PET image analysis in MRI-negative refractory epilepsy. When the visual assessment is inconsistent with the patient’s electroclinical information, SPM or 3D-SSP was further selected to assess the epileptic foci. If the combination of the two methods still fails to accurately locate the epileptic foci, comprehensive evaluation can be performed by combining the three methods.

Limits to Ionization-parameter Mapping as a Diagnostic of Hii Region Optical Depth

We employ ionization-parameter mapping (IPM) to infer the optical depth of H ii regions in the northern half of M33. We construct [O iii]λ5007/[O ii]λ3727 and [O iii]λ5007/[S ii]λ6724 ratio maps from narrowband images continuum-subtracted in this way, from which we classify the H ii regions by optical depth to ionizing radiation, based on their ionization structure. This method works relatively well in the low-metallicity regime, 12 + log ( O / H ) ≤ 8.4 , where [O iii]λ λ4959, 5007 is strong. However, at higher metallicities, the method breaks down due to the strong dependence of the [O iii]λ λ4959, 5007 emission lines on the nebular temperature. Thus, although O++ may be present in metal-rich H ii regions, these commonly used emission lines do not serve as a useful indicator of its presence, and hence the O ionization state. In addition, IPM as a diagnostic of optical depth is limited by spatial resolution. We also report a region of highly excited [O iii] extending over an area ∼1 kpc across and [O iii]λ5007 luminosity of 4.9 ± 1.5 × 1038 erg s−1, which is several times higher than the ionizing budget of any potential sources in this portion of the galaxy. Finally, this work introduces a new method for continuum subtraction of narrowband images based on the dispersion of pixels around the mode of the diffuse-light flux distribution. In addition to M33, we demonstrate the method on C iii]λ1909 imaging of Haro 11, ESO 338-IG004, and Mrk 71.

Combining Navigator and Optical Prospective Motion Correction for High-Quality 500 μm Resolution Quantitative Multi-Parameter Mapping at 7T

PURPOSEHigh-resolution quantitative multi-parameter mapping shows promise for non-invasively characterizing human brain microstructure but is limited by physiological artifacts. We implemented corrections for rigid head movement and respiration-related B0-fluctuations and evaluated them in healthy volunteers and dementia patients.METHODSCamera-based optical prospective motion correction (PMC) and free-induction decay (FID) navigator correction were implemented in a gradient and RF-spoiled multi-echo 3D gradient echo sequence for mapping proton density (PD), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*). We studied their effectiveness separately and in concert in young volunteers and then evaluated the navigator correction (NAVcor) with PMC in a group of elderly volunteers and dementia patients. We used spatial homogeneity within white matter (WM) and gray matter (GM) and scan-rescan measures as quality metrics.RESULTSNAVcor and PMC reduced artifacts and improved the homogeneity and reproducibility of parameter maps. In elderly participants, NAVcor improved scan-rescan reproducibility of parameter maps (coefficient of variation decreased by 14.7% and 11.9% within WM and GM respectively). Spurious inhomogeneities within WM were reduced more in the elderly than in the young cohort (by 9% vs 2%). PMC increased regional GM/WM contrast and was especially important in the elderly cohort, which moved twice as much as the young cohort. We did not find a significant interaction between the two corrections.CONCLUSIONNavigator correction and PMC significantly improved the quality of PD, R1 and R2* maps, particularly in less compliant elderly volunteers and dementia patients.

Quantitative Parameter Mapping of Contrast Agent Concentration and Relaxivity and Brain Tumor Extracellular pH

In clinical magnetic resonance imaging (MRI), gadolinium-based contrast agents are most commonly used for evaluating brain tumors. However, contrast-enhanced MRI can only provide relative signal changes such as mixed information with longitudinal relaxivity (r1) and contrast agent concentration. Herein, we present a new method to evaluate r1 and contrast agent concentration separately in contrast-enhanced lesions using quantitative parameter mapping. We demonstrated that it is possible to evaluate pathophysiological tumor changes owing to therapeutic efficacy. Furthermore, the r1 value can be used as an extracellular pH tumor marker. We believe that our method has an easy clinical application and demonstrates how acidic environments affect the T1 relaxation time of contrast agents. In conclusion, these indices can be useful for brain tumor management.