Rapid Gradient Research Articles

Improving B1+$$ {B}_1^{+} $$‐inhomogeneity tolerance by resolving non‐bijection in MP2RAGE R1 mapping: A 2D look‐up table approach demonstrated at 3 T

AbstractPurposeRegarding in vivo, robust longitudinal relaxation rate (R1) mapping, the goal of the present paper is two‐fold. First, to verify that non‐bijective mapping in magnetization‐prepared 2 rapid gradient echo (MP2RAGE) imaging can be resolved through a two‐dimensional look‐up table approach. Second, that the expanded parameter space from this can be used to improve ‐inhomogeneity tolerance without other prerequisites.TheoryBy deriving a second contrast from the magnitude images of the MP2RAGE acquisition, ambiguities in the original MP2RAGE image resulting from non‐bijective transfer curves can be resolved. Such ambiguities may occur when protocols are optimized, such as for higher ‐inhomogeneity tolerance. A 2D look‐up table approach combines the available information to resolve these ambiguities during mapping.MethodsAt 3 T, we acquired MP2RAGE images with standard acquisition parameters and (non‐bijective) parameters optimized for ‐inhomogeneity tolerance. From 3 subjects across multiple sessions, we assessed the ‐inhomogeneity tolerance through excitation‐pulse amplitude scalings.ResultsThe R1 maps resulting from the ‐optimized protocols showed greatly reduced effects across images but without additional scanner time. Meanwhile, these maps could only successfully be derived by a 2D look‐up table approach.ConclusionWe show that it is possible to optimize for ‐inhomogeneity tolerance in MP2RAGE through sequence‐parameter settings, while still successfully estimating the R1 map with a two‐dimensional look‐up table approach. This without the need for an additional map. The increased parameter space enabled by the two‐dimensional look‐up table approach may further be used to adjust MP2RAGE acquisitions for improved scan times, signal‐to‐noise ratio, and/or contrast‐to‐noise ratio.

NIMG-40. RADIOMICS-BASED DIFFERENTIATION OF GLIOBLASTOMA AND METASTATIC DISEASE: DOES DIFFERENCE IN TYPE OF T1-CONTRAST ENHANCED SEQUENCE MATTER?

Abstract BACKGROUND To evaluate the radiomics-based model performance for differentiation between glioblastoma (GB) and intracranial metastatic disease (IMD) using magnetization prepared rapid gradient echo (MPRAGE) and volumetric interpolated breath-hold examination (VIBE) T1-contrast enhanced sequences. MATERIALS AND METHODS T1-CE MPRAGE and VIBE sequences acquired in 108 patients (31 GBs and 77 IMD) during the same MRI session were retrospectively evaluated. Post standardized image pre-processing and segmentation, radiomics features were extracted from necrotic and enhancing tumor components. A total of 90 machine learning (ML) pipelines were evaluated using a five-fold cross-validation. Performance was measured by mean AUC, Log-loss, and Brier scores. Pearson correlation analysis of radiomics features from tumor subcomponents was also performed. RESULTS The mean AUC across the top-ten pipelines varied between 0.890-0.851 with T1-CE MPRAGE and 0.907-0.869 with T1-CE VIBE sequence. Top performing models for the MPRAGE sequence commonly used support vector machines, while those for VIBE sequence used either support vector machines or random forest. Common feature reduction methods for top-performing models included linear combination filter and least absolute shrinkage and selection operator (LASSO) for both sequences. Only three of the top ten models used the same combination of feature reduction-ML algorithm pipeline. A feature-wise comparison showed that the radiomic features between sequences were strongly correlated, with the highest correlation for shape-based features. CONCLUSION Radiomics features derived from T1-CE MPRAGE and VIBE sequences may have similar overall classification performance for differentiating GB from IMD, albeit often using different feature selection-ML algorithm pipelines.

Paper Spray Ionization Mass Spectrometry Coupled with Paper-Based Three-Dimensional Tumor Model for Rapid Metabolic Gradient Profiling.

The tumor microenvironment (TME), especially with its complicated metabolic characteristics, will dynamically affect the proliferation, migration, and drug response of tumor cells. Rapid metabolic analysis brings out a deeper understanding of the TME, while the susceptibility and environmental dependence of metabolites extremely hinder real-time metabolic profiling since the TME is easily disrupted. Here, we directly integrated paper spray ionization mass spectrometry with a paper-based three-dimensional (3D) tumor model, realizing the rapid capture of metabolic gradients. The entire procedure, from sample preparation to mass spectrometry detection, took less than 4 min, which was able to provide metabolic results close to real time and contributed to understanding the real metabolic processes. At present, our method successfully detected 160 metabolites; notably, over 40 significantly gradient metabolites were revealed across the six layers of the paper-based 3D tumor model. At least 22 gradient metabolites were reported to be associated with cell viability. This strategy was powerful enough to rapidly profile metabolic gradients of a paper-based 3D tumor model for revealing cell viability changes from a metabolomics perspective.

Oxygen extraction fraction mapping based combining quantitative susceptibility mapping and quantitative blood oxygenation level-dependent imaging model using multi-delay PCASL

Background and purposeThe oxygen extraction fraction is an essential biomarker for the assessment of brain metabolism. A recently proposed method combined with quantitative susceptibility mapping and quantitative blood oxygen level-dependent magnitude enables noninvasive mapping of the oxygen extraction fraction. Our study investigated the oxygen extraction fraction mapping variations of single-delay and multi-delay arterial spin-labeling. Materials and methodsA total of twenty healthy participants were enrolled. The multi-echo spoiled gradient-echo, multi-delay arterial spin-labeling, and magnetization-prepared rapid gradient echo sequences were acquired at 3.0 T. The mean oxygen extraction fraction was generated under a single delay time of 1780 ms, multi-delay arterial spin-labeling of transit-corrected cerebral blood flow, and multi-delay arterial spin-labeling of arterial cerebral blood volume. The results were compared via paired t tests and the Wilcoxon test. Linear regression analyses were used to investigate the relationships among the oxygen extraction fraction, cerebral blood flow, and venous cerebral blood volume. ResultsThe oxygen extraction fraction estimate with multi-delay arterial spin-labeling yielded a significantly lower value than that with single-delay arterial spin-labeling. The average values for the whole brain under single-delay arterial spin-labeling, multi-delay arterial spin-labeling of transit-corrected cerebral blood flow, and multi-delay arterial spin-labeling of arterial cerebral blood volume were 41.5 ± 1.7 % (P < 0.05), 41.3 ± 1.9 % (P < 0.001), and 40.9 ± 1.9 % (N = 20), respectively. The oxygen extraction fraction also showed a significant inverse correlation with the venous cerebral blood volume under steady-state conditions when multi-delay arterial spin-labeling was used (r = 0.5834, p = 0.0069). ConclusionThese findings suggest that the oxygen extraction fraction is significantly impacted by the arterial spin-labeling methods used in the quantitative susceptibility mapping plus the quantitative blood oxygen level-dependent model, indicating that the differences should be accounted for when employing oxygen extraction fraction mapping based on this model in diseases.

Quantitative evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) MPRAGE for morphometric analysis of brain tissue in patients undergoing evaluation for memory loss

BackgroundThree-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings. MethodsWe evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia. In part (1), we used a set of 108 MPRAGE reconstructed images derived from 12 healthy volunteers to systematically assess the effectiveness of SAMER in correcting varying degrees of motion corruption, ranging from mild to severe. In part (2), 29 patients who were scheduled for brain MRI with memory loss protocol and had motion corruption on their clinical MPRAGE scans were prospectively enrolled. ResultsIn part (1), SAMER resulted in effective correction of motion-induced cortical volume and thickness reductions. We observed systematic increases in the estimated cortical volume and thickness across all neuroanatomical regions and a relative reduction in percent error values compared to reference standard scans of up to 66 % for the cerebral white matter volume. In part (2), SAMER resulted in statistically significant volume increases across anatomical regions, with the most pronounced increases seen in the parietal and temporal lobes, and general reductions in percent error relative to reference standard clinical scans. ConclusionSAMER improves the accuracy of morphometry through systematic increases and recovery of the estimated cortical volume and cortical thickness following motion correction, which may affect the evaluation of regional cortical atrophy in patients undergoing evaluation for dementia.

Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions.

Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals. This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models. Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = -5.111 × 10-5), lower disability (p = 0.04, b = -2.352 × 10-5), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = -6.686 × 10-4). χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

Different Glymphatic Kinetics in Spontaneous Intracranial Hypotension.

The glymphatic (glia-lymphatic) system is a paravascular pathway for the clearance of waste metabolites including amyloid β from the brain. Serial T1 relaxation time measurements after the intrathecal injection of gadolinium-based contrast agents facilitate the analysis of the temporal dynamics that may be different in patients with spontaneous intracranial hypotension (SIH) and those without SIH. 3D T1-weighted magnetization-prepared 2 rapid gradient echo sequences were acquired in 4 patients with SIH with proved CSF leaks and 12 patients without SIH before, 2-4, 6-8, and 24-48 hours after intrathecal gadobutrol injection. MR scans were warped to the Montreal Neurological Institute space and serial scans were coregistered. T1 relaxation times were measured in predefined ROIs including the subarachnoid space, cortex, white matter, and cervical lymph nodes. In the subarachnoid space and cortex, T1 relaxation times decreased after 2-4 and 6-8 hours before they increased again. In contrast, in the white matter of the temporal lobe T1 relaxation time still decreased after 24-48 hours. There was a striking difference in patients with SIH who did not show a clear contrast distribution within the brain parenchyma. T1 relaxation time curves are compatible with a convective flow driven by arterial pulsations via paravascular spaces surrounding penetrating arteries into the brain's interstitial fluid in the deep white matter. Different curves in patients with SIH and those without SIH indicate that the CSF pressure also impacts the temporal kinetics of the glymphatic system.

Cortical and subcortical structural changes in pediatric patients with infratentorial tumors.

This study aimed to detect supratentorial cortical and subcortical morphological changes in pediatric patients with infratentorial tumors. The study included 24 patients aged 4-18 years who were diagnosed with primary infratentorial tumors and 41 age- and gender-matched healthy controls. Synthetic magnetization-prepared rapid gradient echo images of brain magnetic resonance imaging were generated using deep learning algorithms applied to T2-axial images. The cortical thickness, surface area, volume, and local gyrification index (LGI), as well as subcortical gray matter volumes, were automatically calculated. Surface-based morphometry parameters for the patient and control groups were compared using the general linear model, and volumes between subcortical structures were compared using the t-test and Mann-Whitney U test. In the patient group, cortical thinning was observed in the left supramarginal, and cortical thickening was observed in the left caudal middle frontal (CMF), left fusiform, left lateral orbitofrontal, left lingual gyrus, right CMF, right posterior cingulate, and right superior frontal (P < 0.050). The patient group showed a volume reduction in the pars triangularis, paracentral, precentral, and supramarginal gyri of the left hemisphere (P < 0.05). A decreased surface area was observed in the bilateral superior frontal and cingulate gyri (P < 0.05). The patient group exhibited a decreased LGI in the right precentral and superior temporal gyri, left supramarginal, and posterior cingulate gyri and showed an increased volume in the bilateral caudate nucleus and hippocampus, while a volume reduction was observed in the bilateral putamen, pallidum, and amygdala (P < 0.05). The ventricular volume and tumor volume showed a positive correlation with the cortical thickness in the bilateral CMF while demonstrating a negative correlation with areas exhibiting a decreased LGI (P < 0.05). Posterior fossa tumors lead to widespread morphological changes in cortical structures, with the most prominent pattern being hypogyria. This study illuminates the neurological impacts of infratentorial tumors in children, providing a foundation for future therapeutic strategies aimed at mitigating these adverse cortical and subcortical changes and improving patient outcomes.

A singular plasmonic-thermoelectric hollow nanostructure inducing apoptosis and cuproptosis for catalytic cancer therapy

Thermoelectric technology has recently emerged as a distinct therapeutic modality. However, its therapeutic effectiveness is significantly limited by the restricted temperature gradient within living organisms. In this study, we introduce a high-performance plasmonic-thermoelectric catalytic therapy utilizing urchin-like Cu2−xSe hollow nanospheres (HNSs) with a cascade of plasmonic photothermal and thermoelectric conversion processes. Under irradiation by a 1064 nm laser, the plasmonic absorption of Cu2−xSe HNSs, featuring rich copper vacancies (VCu), leads to a rapid localized temperature gradient due to their exceptionally high photothermal conversion efficiency (67.0%). This temperature gradient activates thermoelectric catalysis, generating toxic reactive oxygen species (ROS) targeted at cancer cells. Density functional theory calculations reveal that this vacancy-enhanced thermoelectric catalytic effect arises from a much more carrier concentration and higher electrical conductivity. Furthermore, the exceptional photothermal performance of Cu2−xSe HNSs enhances their peroxidase-like and catalase-like activities, resulting in increased ROS production and apoptosis induction in cancer cells. Here we show that the accumulation of copper ions within cancer cells triggers cuproptosis through toxic mitochondrial protein aggregation, creating a synergistic therapeutic effect. Tumor-bearing female BALB/c mice are used to evaluate the high anti-cancer efficiency. This innovative approach represents the promising instance of plasmonic-thermoelectric catalytic therapy, employing dual pathways (membrane potential reduction and thioctylated protein aggregation) of mitochondrial dysfunction, all achieved within a singular nanostructure. These findings hold significant promise for inspiring the development of energy-converting nanomedicines.

Radiomics Based Differentiation of Glioblastoma and Metastatic Disease: Impact of Different T1-Contrast Enhanced Sequences on Radiomic Features and Model Performance.

To evaluate the radiomics-based model performance for differentiation between glioblastoma (GB) and brain metastases (BM) using magnetization prepared rapid gradient echo (MPRAGE) and volumetric interpolated breath-hold examination (VIBE) T1-contrast enhanced sequences. T1-CE MPRAGE and VIBE sequences acquired in 108 patients (31 GBs and 77 BM) during the same MRI session were retrospectively evaluated. Post standardized image pre-processing and segmentation, radiomics features were extracted from necrotic and enhancing tumor components. Pearson correlation analysis of radiomics features from tumor subcomponents was also performed. A total of 90 machine learning (ML) pipelines were evaluated using a five-fold cross validation. Performance was measured by mean AUC-ROC, Log-loss and Brier scores. A feature-wise comparison showed that the radiomic features between sequences were strongly correlated, with the highest correlation for shape-based features. The mean AUC across the top-ten pipelines ranged between 0.851-0.890 with T1-CE MPRAGE and between 0.869-0.907 with T1-CE VIBE sequence. Top performing models for the MPRAGE sequence commonly used support vector machines, while those for VIBE sequence used either support vector machines or random forest. Common feature reduction methods for top-performing models included linear combination filter and least absolute shrinkage and selection operator (LASSO) for both sequences. For the same ML-feature reduction pipeline, model performances were comparable (AUC-ROC difference range: [-0.078, 0.046]). Radiomic features derived from T1-CE MPRAGE and VIBE sequences are strongly correlated and may have similar overall classification performance for differentiating GB from BM. BM: Brain metastases, GB: glioblastoma, T1-CE: T1 contrast enhanced sequence, MPRAGE: magnetization prepared rapid gradient echo, ML: machine learning, RF: random forest, VIBE: volumetric interpolated breath-hold examination.

Optimization and validation of low-field MP2RAGE T1 mapping on 0.35T MR-Linac: Toward adaptive dose painting with hypoxia biomarkers.

Stereotactic MR-guided Adaptive Radiation Therapy (SMART) dose painting for hypoxia has potential to improve treatment outcomes, but clinical implementation on low-field MR-Linac faces substantial challenges due to dramatically lower signal-to-noise ratio (SNR) characteristics. While quantitative MRI and T1 mapping of hypoxia biomarkers show promise, T1-to-noise ratio (T1NR) optimization at low fields is paramount, particularly for the clinical implementation of oxygen-enhanced (OE)-MRI. The 3D Magnetization Prepared (2) Rapid Gradient Echo (MP2RAGE) sequence stands out for its ability to acquire homogeneous T1-weighted contrast images with simultaneous T1 mapping. To optimize MP2RAGE for low-field T1 mapping; conduct experimental validation in a ground-truth phantom; establish feasibility and reproducibility of low-field MP2RAGE acquisition and T1 mapping in healthy volunteers. The MP2RAGE optimization was performed to maximize the contrast-to-noise ratio (CNR) of T1 values in white matter (WM) and gray matter (GM) brain tissues at 0.35T. Low-field MP2RAGE images were acquired on a 0.35T MR-Linac (ViewRay MRIdian) using a multi-channel head coil. Validation of T1 mapping was performed with a ground-truth Eurospin phantom, containing inserts of known T1 values (400-850ms), with one and two average (1A and 2A) MP2RAGE scans across four acquisition sessions, resulting in eight T1 maps. Mean (±SD) T1 relative error, T1NR, and intersession coefficient of variation (CV) were determined. Whole-brain MP2RAGE scans were acquired in 5 healthy volunteers across two sessions (A and B) and T1 maps were generated. Mean (±SD) T1 values for WM and GM were determined. Whole-brain T1 histogram analysis was performed, and reproducibility was determined with the CV between sessions. Voxel-by-voxel T1 difference maps were generated to evaluate 3D spatial variation. Low-field MP2RAGE optimization resulted in parameters: MP2RAGETR of 3250ms, inversion times (TI1/TI2) of 500/1200ms, and flip angles (α1/α2) of 7/5°. Eurospin T1 maps exhibited a mean (±SD) relative error of 3.45%±1.30%, T1NR of 20.13±5.31, and CV of 2.22%±0.67% across all inserts. Whole-brain MP2RAGE images showed high anatomical quality with clear tissue differentiation, resulting in mean (±SD) T1 values: 435.36±10.01ms for WM and 623.29±14.64ms for GM across subjects, showing excellent concordance with literature. Whole-brain T1 histograms showed high intrapatient and intersession reproducibility with characteristic intensity peaks consistent with voxel-level WM and GM T1 values. Reproducibility analysis revealed a CV of 0.46%±0.31% and 0.35%±0.18% for WM and GM, respectively. Voxel-by-voxel T1 difference maps show a normal 3D spatial distribution of noise in WM and GM. Low-field MP2RAGE proved effective in generating accurate, reliable, and reproducible T1 maps with high T1NR in phantom studies and in vivo feasibility established in healthy volunteers. While current work is focused on refining the MP2RAGE protocol to enable clinically efficient OE-MRI, this study establishes a foundation for TOLD T1 mapping for hypoxia biomarkers. This advancement holds the potential to facilitate a paradigm shift toward MR-guided biological adaptation and dose painting by leveraging 3D hypoxic spatial distributions and improving outcomes in conventionally challenging-to-treat cancers.

High b-Value and Ultra-High b-Value Diffusion Weighted MRI in Stroke.

To explore the application value of high-b-value and ultra-high b-value DWI in noninvasive evaluation of ischemic infarctions. Prospective. Sixty-four patients with clinically diagnosed ischemic lesions based on symptoms and DWI. 3.0 T/T2-weighted fast spin-echo, fluid-attenuated inversion recovery, pre-contrast T1-weighted magnetization prepared rapid gradient echo sequence, multi-b-value trace DWI and q-space sampling sequences. Lesions were segmented on standard b-value DWI (SB-DWI, 1000 s/mm2), high b-value DWI (HB-DWI, 4000 s/mm2) and ultra-high b-value DWI (UB-DWI, 10,000 s/mm2), and cumulative segmented areas were the final abnormality volumes. Normal white matter (WM) areas were obtained after binarization of segmented brain. In 47 patients, fractional anisotropy (FA) and apparent diffusion coefficients (ADCs) at b values of 1000, 4000, and 10,000 s/mm2 were extracted from symmetrical WM masks and lesion masks of contralateral WM (CWM) and lesion-side WM (LWM). Wilcoxon matched-pairs signed-rank test and Pearson correlation analysis. Two-tailed P-values <0.05 were considered statistically significant. Various signals of HB-/UB-DWI (hypo-, iso- or hyper-intensity) were observed in strokes compared with SB-DWI, and some areas with iso-intensity of SB-DWI manifested with hyper-intensity on HB-/UB-DWI. Abnormality volumes from SB-DWI were significantly smaller than those from HB-DWI and UB-DWI (10.32 ± 16.45 cm3, vs. 12.25 ± 19.71 cm3 and 11.83 ± 19.41 cm3), while no significant difference exist in volume between HB-DWI and UB-DWI (P = 0.32). In CWM, FA significantly correlated with ADC4000 and ADC10,000 (maximum r = -0.51 and -0.64), but did not significantly correlate with ADC1000 (maximum r = -0.20, P = 0.17). ADC1000 or ADC4000 of LWM not significant correlated with FA of CWM (maximum r = -0.28, P = 0.06), while ADC10,000 of LWM significantly correlated with FA of CWM (maximum r = -0.46). HB- and UB-DWI have potential to be supplementary tools for the noninvasive evaluation of stroke lesions in clinics. 2 TECHNICAL EFFICACY: Stage 2.

Central vein sign and trigeminal lesions of multiple sclerosis visualised by 7T MRI

BackgroundAlthough trigeminal nerve involvement is a characteristic of multiple sclerosis (MS), its prevalence across studies varies greatly due to MRI resolution and cohort selection bias. The mechanism behind the site...

Hippocampal Glutamate Levels and Their Correlation With Subregion Volume in School-Aged Children With MRI-Negative Epilepsy: A Preliminary Study.

Abnormal levels of glutamate constitute a key pathophysiologic mechanism in epilepsy. The use of glutamate chemical exchange saturation transfer (GluCEST) imaging to measure glutamate levels in pediatric epilepsy is rarely reported in research. To investigate hippocampal glutamate level variations in pediatric epilepsy and the correlation between glutamate and hippocampal subregional volumes. Cross-sectional, prospective. A total of 38 school-aged pediatric epilepsy patients with structurally normal MRI as determined by at least two independent radiologists (60% males; 8.7 ± 2.5 years; including 20 cases of focal pediatric epilepsy [FE] and 18 cases of generalized pediatric epilepsy [GE]) and 17 healthy controls (HC) (41% males; 9.0 ± 2.5 years). 3.0 T; 3D magnetization prepared rapid gradient echo (MPRAGE) and 2D turbo spin echo GluCEST sequences. The relative concentration of glutamate was calculated through pixel-wise magnetization transfer ratio asymmetry (MTRasym) analysis of the GluCEST data. Hippocampal subfield volumes were computed from MPRAGE data using FreeSurfer. This study used t tests, one-way analysis of variance, Kruskal-Wallis tests, and Pearson correlation analysis. P < 0.05 was considered statistically significant. The MTRasym values of both the left and right hippocampi were significantly elevated in GE (left: 2.51 ± 0.23 [GE] vs. 2.31 ± 0.12 [HCs], right: 2.50 ± 0.22 [GE] vs. 2.27 ± 0.22 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly elevated in FE (2.49 ± 0.28 [ipsilateral] vs. 2.29 ± 0.16 [HCs]). The MTRasym values of the ipsilateral hippocampus were significantly increased compared to the contralateral hippocampus in FE (2.49 ± 0.28 [ipsilateral] vs. 2.35 ± 0.34 [contralateral]). No significant differences in hippocampal volume were found between different groups (left hippocampus, P = 0.87; right hippocampus, P = 0.87). GluCEST imaging have potential for the noninvasive measurement of glutamate levels in the brains of children with epilepsy. 2 TECHNICAL EFFICACY: Stage 1.

Brain and Ventricle Volume Alterations in Idiopathic Normal Pressure Hydrocephalus Determined by Artificial Intelligence-Based MRI Volumetry.

The aim of this study was to employ artificial intelligence (AI)-based magnetic resonance imaging (MRI) brain volumetry to potentially distinguish between idiopathic normal pressure hydrocephalus (iNPH), Alzheimer's disease (AD), and age- and sex-matched healthy controls (CG) by evaluating cortical, subcortical, and ventricular volumes. Additionally, correlations between the measured brain and ventricle volumes and two established semi-quantitative radiologic markers for iNPH were examined. An IRB-approved retrospective analysis was conducted on 123 age- and sex-matched subjects (41 iNPH, 41 AD, and 41 controls), with all of the iNPH patients undergoing routine clinical brain MRI prior to ventriculoperitoneal shunt implantation. Automated AI-based determination of different cortical and subcortical brain and ventricular volumes in mL, as well as calculation of population-based normalized percentiles according to an embedded database, was performed; the CE-certified software mdbrain v4.4.1 or above was used with a standardized T1-weighted 3D magnetization-prepared rapid gradient echo (MPRAGE) sequence. Measured brain volumes and percentiles were analyzed for between-group differences and correlated with semi-quantitative measurements of the Evans' index and corpus callosal angle: iNPH patients exhibited ventricular enlargement and changes in gray and white matter compared to AD patients and controls, with the most significant differences observed in total ventricular volume (+67%) and the lateral (+68%), third (+38%), and fourth (+31%) ventricles compared to controls. Global ventriculomegaly and marked white matter reduction with concomitant preservation of gray matter compared to AD and CG were characteristic of iNPH, whereas global and frontoparietally accentuated gray matter reductions were characteristic of AD. Evans' index and corpus callosal angle differed significantly between the three groups and moderately correlated with the lateral ventricular volumes in iNPH patients [Evans' index (r > 0.83, p ≤ 0.001), corpus callosal angle (r < -0.74, p ≤ 0.001)]. AI-based MRI volumetry in iNPH patients revealed global ventricular enlargement and focal brain atrophy, which, in contrast to healthy controls and AD patients, primarily involved the supratentorial white matter and was marked temporomesially and in the midbrain, while largely preserving gray matter. Integrating AI volumetry in conjunction with traditional radiologic measures could enhance iNPH identification and differentiation, potentially improving patient management and therapy response assessment.

Central Vein Sign, Cortical Lesions, and Paramagnetic Rim Lesions for the Diagnostic and Prognostic Workup of Multiple Sclerosis.

The diagnosis of multiple sclerosis (MS) can be challenging in clinical practice because MS presentation can be atypical and mimicked by other diseases. We evaluated the diagnostic performance, alone or in combination, of the central vein sign (CVS), paramagnetic rim lesion (PRL), and cortical lesion (CL), as well as their association with clinical outcomes. In this multicenter observational study, we first conducted a cross-sectional analysis of the CVS (proportion of CVS-positive lesions or simplified determination of CVS in 3/6 lesions-Select3*/Select6*), PRL, and CL in MS and non-MS cases on 3T-MRI brain images, including 3D T2-FLAIR, T2*-echo-planar imaging magnitude and phase, double inversion recovery, and magnetization prepared rapid gradient echo image sequences. Then, we longitudinally analyzed the progression independent of relapse and MRI activity (PIRA) in MS cases over the 2 years after study entry. Receiver operating characteristic curves were used to test diagnostic performance and regression models to predict diagnosis and clinical outcomes. The presence of ≥41% CVS-positive lesions/≥1 CL/≥1 PRL (optimal cutoffs) had 96%/90%/93% specificity, 97%/84%/60% sensitivity, and 0.99/0.90/0.77 area under the curve (AUC), respectively, to distinguish MS (n = 185) from non-MS (n = 100) cases. The Select3*/Select6* algorithms showed 93%/95% specificity, 97%/89% sensitivity, and 0.95/0.92 AUC. The combination of CVS, CL, and PRL improved the diagnostic performance, especially when Select3*/Select6* were used (93%/94% specificity, 98%/96% sensitivity, 0.99/0.98 AUC; p = 0.002/p < 0.001). In MS cases (n = 185), both CL and PRL were associated with higher MS disability and severity. Longitudinal analysis (n = 61) showed that MS cases with >4 PRL at baseline were more likely to experience PIRA at 2-year follow-up (odds ratio 17.0, 95% confidence interval: 2.1-138.5; p = 0.008), whereas no association was observed between other baseline MRI measures and PIRA, including the number of CL. The combination of CVS, CL, and PRL can improve MS differential diagnosis. CL and PRL also correlated with clinical measures of poor prognosis, with PRL being a predictor of disability accrual independent of clinical/MRI activity.

Sexual Dimorphism of Radiomic Features in the Brain: An Exploratory Study Using 700 μm MP2RAGE MRI at 7 T.

The aim of this study was to determine whether MRI radiomic features of key cerebral structures differ between women and men, and whether detection of such differences depends on the image resolution. Ultrahigh resolution (UHR) 3D MP2RAGE (magnetization-prepared 2 rapid acquisition gradient echo) T1-weighted MR images (voxel size, 0.7 × 0.7 × 0.7 mm3) of the brain of 30 subjects (18 women and 12 men; mean age, 39.0 ± 14.8 years) without abnormal findings on MRI were retrospectively included. MRI was performed on a whole-body 7 T MR system. A convolutional neural network was used to segment the following structures: frontal cortex, frontal white matter, thalamus, putamen, globus pallidus, caudate nucleus, and corpus callosum. Eighty-seven radiomic features were extracted respectively: gray-level histogram (n = 18), co-occurrence matrix (n = 24), run-length matrix (n = 16), size-zone matrix (n = 16), and dependence matrix (n = 13). Feature extraction was performed at UHR and, additionally, also after resampling to 1.4 × 1.4 × 1.4 mm3 voxel size (standard clinical resolution). Principal components (PCs) of radiomic features were calculated, and independent samples t tests with Cohen d as effect size measure were used to assess differences in PCs between women and men for the different cerebral structures. At UHR, at least a single PC differed significantly between women and men in 6/7 cerebral structures: frontal cortex (d = -0.79, P = 0.042 and d = -1.01, P = 0.010), frontal white matter (d = -0.81, P = 0.039), thalamus (d = 1.43, P < 0.001), globus pallidus (d = 0.92, P = 0.020), caudate nucleus (d = -0.83, P = 0.039), and corpus callosum (d = -0.97, P = 0.039). At standard clinical resolution, only a single PC extracted from the corpus callosum differed between sexes (d = 1.05, P = 0.009). Nonnegligible differences in radiomic features of several key structures of the brain exist between women and men, and need to be accounted for. Very high spatial resolution may be required to uncover and further investigate the sexual dimorphism of brain structures on MRI.

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults.

Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia. Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics. A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT. Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7Tesla (T) MRI. The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n=15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38vs. 1.53, p<.001) and qMT (2.47vs. 2.97, p<.001) but not in NODDI measures (p>.27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p=.03). SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition

Abstract This work presents a physics-informed fusion methodology for deformation detection using multi-sensor thermal data. A challenge with additive manufacturing (AM) is that abnormalities commonly occur due to rapid changes in the thermal gradient. Different non-destructive in-situ thermal sensors capture parts of the thermal history but are limited by the visible temperature spectrum and sensor field of view of the fabrication process. Various sensors mitigate problems with the loss of thermal history information; however, it brings forth challenges with integrating different data streams and the need to interpolate the internal thermal history. This study develops a thermal data-informed heat flux methodology that fills the gap in fusing numerical temperature approximation with data-driven knowledge of the surface of additive manufactured components. First, this study fuses infrared (IR) thermal data complexities during the AM process with the Goldak double ellipsoidal heat flux to model the energy input into the component. Second, a thermal physics-informed model input (PIMI) is created with thermal data-informed heat flux to capture internal thermal history. Lastly, a regression convolutional neural network (CNN) captures the relationship between the three-dimensional thermal gradient and the resulting surface deformation. The rapid thermal gradient formation and identification of deformation is a key step toward using thermal history data and machine learning to improve quality control in AM. The proposed surface deformation detection model achieved an mean squared error of 1.14 mm and an R2 of 0.89 in the case study when fabricating thin-walled structures.