Rapid simultaneous estimation of relaxation rates using multi-echo, multi-contrast MRI.

PURPOSE: Multi-echo, multi-contrast methods are increasingly used in dynamic imaging studies to simultaneously quantify R2* and R2. To overcome the computational challenges associated with nonlinear least squares (NLSQ) fitting, we propose a generalized linear least squares (LLSQ) solution to rapidly fit R2* and R2. METHODS: Spin- and gradient-echo (SAGE) data were simulated across T2⁎ and T2 values at high (200) and low (20) SNR. Full (four-parameter) and reduced (three-parameter) parameter fits were implemented and compared with both LLSQ and NLSQ fitting. Fit data were compared to ground truth using concordance correlation coefficient (CCC) and coefficient of variation (CV). In vivo SAGE perfusion data were acquired in 20 subjects with relapsing-remitting multiple sclerosis. LLSQ R2* and R2, as well as cerebral blood volume (CBV), were compared with the standard NLSQ approach. RESULTS: Across all fitting methods, T2⁎ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.87, CV ≤ 0.08) SNR. Except for short T2⁎ values (5-15 ms), T2 was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.99, CV ≤ 0.03) SNR. In vivo, LLSQ R2⁎ and R2 estimates were similar to NLSQ, and there were no differences in R2⁎ across fitting methods at high SNR. However, there were some differences at low SNR and for R2 at high and low SNR. In vivo NLSQ and LLSQ three parameter fits performed similarly, as did NLSQ and LLSQ four-parameter fits. LLSQ CBV nearly matched the standard NLSQ method for R2*- (0.97 ratio) and R2-CBV (0.98 ratio). Voxel-wise whole-brain fitting was faster for LLSQ (3-4 min) than NLSQ (16-18 h). CONCLUSIONS: LLSQ reliably fit for R2* and R2 in simulated and in vivo data. Use of LLSQ methods reduced the computational demand, enabling rapid estimation of R2⁎ and R2.

Identification of a single-dose, low flip angle based CBV threshold for fractional tumor burden (FTB) mapping in recurrent glioblastoma.

BACKGROUND AND PURPOSE: DSC-MRI can be used to generate fractional tumor burden (FTB) maps, via application of relative CBV thresholds, to spatially differentiate glioblastoma recurrence from post treatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MRI protocol using preload, a moderate flip angle (MFA, 60°) and post-processing leakage correction. Recently, a DSC-MRI protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected RCBV equivalent to the reference protocol. This study aims to identify the RCBV thresholds for the LFA protocol that generate the most accurate FTB maps, concordant with those obtained from the reference MFA protocol. MATERIALS AND METHODS: Fifty-two patients with grade IV GBM who had prior surgical resection and received chemotherapy and radiotherapy were included in the study. Two sets of DSC-MRI data were collected sequentially first using LFA protocol with no preload, which served as the preload for the subsequent MFA protocol. Standardized relative CBV maps (sRCBV) were obtained for each patient and co-registered with the anatomical post-contrast T1-weighted images. The reference MFA-based FTB maps were computed using previously published sRCBV thresholds (1.0 and 1.56). An ROC analysis was conducted to identify the optimal, voxelwise LFA sRCBV thresholds, and the sensitivity, specificity, and accuracy of the LFA-based FTB maps were computed with respect to the MFA-based reference. RESULTS: The mean sRCBV values of tumors across patients exhibited strong agreement (CCC = 0.99) between the two protocols. Using the ROC analysis, the optimal lower LFA threshold that accurately distinguishes PTRE from tumor recurrence was found to be 1.0 (sensitivity: 87.77%; specificity: 90.22%), equivalent to the ground truth. To identify aggressive tumor regions, the ROC analysis identified an upper LFA threshold of 1.37 (sensitivity: 90.87%; specificity: 91.10%) for the reference MFA threshold of 1.56. CONCLUSION: For LFA-based FTB maps, a sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumor. FTB maps aids in surgical planning, guiding pathological diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MRI. ABBREVIATIONS: LFA = low flip angle; MFA = moderate flip angle; sRCBV = standardized relative cerebral blood volume; FTB = fractional tumor burden; PTRE = post treatment radiation effects; ROC = receiver operating characteristics; CCC = concordance correlation coefficient.

Altered resting-state functional connectivity and dynamic network properties in cognitive impairment: an independent component and dominant-coactivation pattern analyses study.

Introduction: Cognitive impairment (CI) due to Alzheimer's disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual's quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia. Methods: In this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined. Results: Results showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions. Discussion: The findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

A 3D dual-echo spiral sequence for simultaneous dynamic susceptibility contrast and dynamic contrast-enhanced MRI with single bolus injection.

PURPOSE: Perfusion MRI reveals important tumor physiological and pathophysiologic information, making it a critical component in managing brain tumor patients. This study aimed to develop a dual-echo 3D spiral technique with a single-bolus scheme to simultaneously acquire both dynamic susceptibility contrast (DSC) and dynamic contrast-enhanced (DCE) data and overcome the limitations of current EPI-based techniques. METHODS: A 3D spiral-based technique with dual-echo acquisition was implemented and optimized on a 3T MRI scanner with a spiral staircase trajectory and through-plane SENSE acceleration for improved speed and image quality, in-plane variable-density undersampling combined with a sliding-window acquisition and reconstruction approach for increased speed, and an advanced iterative deblurring algorithm. Four volunteers were scanned and compared with the standard of care (SOC) single-echo EPI and a dual-echo EPI technique. Two patients were scanned with the spiral technique during a preload bolus and compared with the SOC single-echo EPI collected during the second bolus injection. RESULTS: Volunteer data demonstrated that the spiral technique achieved high image quality, reduced geometric artifacts, and high temporal SNR compared with both single-echo and dual-echo EPI. Patient perfusion data showed that the spiral acquisition achieved accurate DSC quantification comparable to SOC single-echo dual-dose EPI, with the additional DCE information. CONCLUSION: A 3D dual-echo spiral technique was developed to simultaneously acquire both DSC and DCE data in a single-bolus injection with reduced contrast use. Preliminary volunteer and patient data demonstrated increased temporal SNR, reduced geometric artifacts, and accurate perfusion quantification, suggesting a competitive alternative to SOC-EPI techniques for brain perfusion MRI.

White Matter Microstructure Analysis in Subjective Memory Complaints and Cognitive Impairment: Insights from Diffusion Kurtosis Imaging and Free-Water DTI.

Background: Dementia is characterized by a cognitive decline in memory and other domains that lead to functional impairments. As people age, subjective memory complaints (SMC) become common, where individuals perceive cognitive decline without objective deficits on assessments. SMC can be an early sign and may precede amnestic mild cognitive impairment (MCI), which frequently advances to Alzheimer's disease (AD). Objective: This study aims to investigate white matter microstructure in individuals with SMC, in cognitively impaired (CI) cohorts, and in cognitively normal individuals using diffusion kurtosis imaging (DKI) and free water imaging (FWI). The study also explores voxel-based correlations between DKI/FWI metrics and cognitive scores to understand the relationship between brain microstructure and cognitive function. Methods: Twelve healthy controls (HCs), ten individuals with SMC, and eleven CI individuals (MCI or AD) were enrolled in this study. All participants underwent MRI 3T scan and the BNI Screen (BNIS) for Higher Cerebral Functions. Results: The mean kurtosis tensor and anisotropy of the kurtosis tensor showed significant differences across the three groups, indicating altered white matter microstructure in CI and SMC individuals. The free water volume fraction (f) also revealed group differences, suggesting changes in extracellular water content. Notably, these metrics effectively discriminated between the CI and HC/SMC groups. Additionally, correlations between imaging metrics and BNIS scores were found for CI and SMC groups. Conclusions: These imaging metrics hold promise in discriminating between individuals with CI and SMC. The observed differences indicate their potential as sensitive and specific biomarkers for early detection and differentiation of cognitive decline.

The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI-Dynamic Contrast-Enhanced challenge.

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology.

White Matter Microstructural Differences between Essential Tremor and Parkinson Disease, Evaluated Using Advanced Diffusion MRI Biomarkers.

BACKGROUND: Essential tremor (ET) is a common slowly-progressive neurologic disorder. It is predominantly characterized by kinetic tremors involving bilateral upper limbs. Although ET shares motor similarities with Parkinson disease (PD), there is no known relationship between ET and PD. METHODS: We studied white matter differences between 17 ET and 68 PD patients using standard diffusion tensor imaging and fixel-based analysis (FBA). Diffusion magnetic resonance imaging data were acquired from two scanners (General Electric (GE) and Philips) with different numbers of diffusion directions. Fractional anisotropy maps were generated by the Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL), and FBA was performed using MRtrix3 to obtain fiber density, fiber bundle, and fiber density bundle cross-section. RESULTS: Compared with PD, significantly lower values of fiber density, fiber bundle, and fiber density bundle cross-section were found in the corpus callosum and left tapetum of the ET group. Additionally, significantly lower functional anisotropy values were found in the ET compared to the PD group, principally in the corpus callosum, corona radiata, and cingulum. In conclusion, differences in white matter integrity between ET and PD were observed by both FBA-based metrics and diffusion tensor imaging. CONCLUSIONS: Advanced diffusion-based metrics may provide a better understanding of the white matter microstructural characteristics in disparate motor-associated diseases with different underlying phenotypes, such as ET and PD.

Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study.

Introduction: Parkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD. Objective: In this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months. Result: Compared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes. Conclusion: In conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.

Assessment of complementary white matter microstructural changes and grey matter atrophy in a preclinical model of Alzheimer's disease.

Alzheimer's disease (AD) has been associated with amyloid and tau pathology, as well as neurodegeneration. Beyond these hallmark features, white matter microstructural abnormalities have been observed using MRI. The objective of this study was to assess grey matter atrophy and white matter microstructural changes in a preclinical mouse model of AD (3xTg-AD) using voxel-based morphometry (VBM) and free-water (FW) diffusion tensor imaging (FW-DTI). Compared to controls, lower grey matter density was observed in the 3xTg-AD model, corresponding to the small clusters in the caudate-putamen, hypothalamus, and cortex. DTI-based fractional anisotropy (FA) was decreased in the 3xTg model, while the FW index was increased. Notably, the largest clusters for both FW-FA and FW index were in the fimbria, with other regions including the anterior commissure, corpus callosum, forebrain septum, and internal capsule. Additionally, the presence of amyloid and tau in the 3xTg model was confirmed with histopathology, with significantly higher levels observed across many regions of the brain. Taken together, these results are consistent with subtle neurodegenerative and white matter microstructural changes in the 3xTg-AD model that manifest as increased FW, decreased FW-FA, and decreased grey matter density.

Identification of single-dose, dual-echo based CBV threshold for fractional tumor burden mapping in recurrent glioblastoma.

Background: Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is widely used to distinguish high grade glioma recurrence from post treatment radiation effects (PTRE). Application of rCBV thresholds yield maps to distinguish between regional tumor burden and PTRE, a biomarker termed the fractional tumor burden (FTB). FTB is generally measured using conventional double-dose, single-echo DSC-MRI protocols; recently, a single-dose, dual-echo DSC-MRI protocol was clinically validated by direct comparison to the conventional double-dose, single-echo protocol. As the single-dose, dual-echo acquisition enables reduction in the contrast agent dose and provides greater pulse sequence parameter flexibility, there is a compelling need to establish dual-echo DSC-MRI based FTB mapping. In this study, we determine the optimum standardized rCBV threshold for the single-dose, dual-echo protocol to generate FTB maps that best match those derived from the reference standard, double-dose, single-echo protocol. Methods: The study consisted of 23 high grade glioma patients undergoing perfusion scans to confirm suspected tumor recurrence. We sequentially acquired single dose, dual-echo and double dose, single-echo DSC-MRI data. For both protocols, we generated leakage-corrected standardized rCBV maps. Standardized rCBV (sRCBV) thresholds of 1.0 and 1.75 were used to compute single-echo FTB maps as the reference for delineating PTRE (sRCBV < 1.0), tumor with moderate angiogenesis (1.0 < sRCBV < 1.75), and tumor with high angiogenesis (sRCBV > 1.75) regions. To assess the sRCBV agreement between acquisition protocols, the concordance correlation coefficient (CCC) was computed between the mean tumor sRCBV values across the patients. A receiver operating characteristics (ROC) analysis was performed to determine the optimum dual-echo sRCBV threshold. The sensitivity, specificity, and accuracy were compared between the obtained optimized threshold (1.64) and the standard reference threshold (1.75) for the dual-echo sRCBV threshold. Results: The mean tumor sRCBV values across the patients showed a strong correlation (CCC = 0.96) between the two protocols. The ROC analysis showed maximum accuracy at thresholds of 1.0 (delineate PTRE from tumor) and 1.64 (differentiate aggressive tumors). The reference threshold (1.75) and the obtained optimized threshold (1.64) yielded similar accuracy, with slight differences in sensitivity and specificity which were not statistically significant (1.75 threshold: Sensitivity = 81.94%; Specificity: 87.23%; Accuracy: 84.58% and 1.64 threshold: Sensitivity = 84.48%; Specificity: 84.97%; Accuracy: 84.73%). Conclusions: The optimal sRCBV threshold for single-dose, dual-echo protocol was found to be 1.0 and 1.64 for distinguishing tumor recurrence from PTRE; however, minimal differences were observed when using the standard threshold (1.75) as the upper threshold, suggesting that the standard threshold could be used for both protocols. While the prior study validated the agreement of the mean sRCBV values between the protocols, this study confirmed that their voxel-wise agreement is suitable for reliable FTB mapping. Dual-echo DSC-MRI acquisitions enable robust single-dose sRCBV and FTB mapping, provide pulse sequence parameter flexibility and should improve reproducibility by mitigating variations in preload dose and incubation time.

Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models.

BACKGROUND: It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting. METHODS: Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow). RESULTS: For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions. CONCLUSION: A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.

Rapid parameter estimation for selective inversion recovery myelin imaging using an open-source Julia toolkit.

Background: Magnetic resonance imaging (MRI) is used extensively to quantify myelin content, however computational bottlenecks remain challenging for advanced imaging techniques in clinical settings. We present a fast, open-source toolkit for processing quantitative magnetization transfer derived from selective inversion recovery (SIR) acquisitions that allows parameter map estimation, including the myelin-sensitive macromolecular pool size ratio (PSR). Significant progress has been made in reducing SIR acquisition times to improve clinically feasibility. However, parameter map estimation from the resulting data remains computationally expensive. To overcome this computational limitation, we developed a computationally efficient, open-source toolkit implemented in the Julia language. Methods: To test the accuracy of this toolkit, we simulated SIR images with varying PSR and spin-lattice relaxation time of the free water pool (R 1f) over a physiologically meaningful scale from 5% to 20% and 0.5 to 1.5 s-1, respectively. Rician noise was then added, and the parameter maps were estimated using our Julia toolkit. Probability density histogram plots and Lin's concordance correlation coefficients (LCCC) were used to assess accuracy and precision of the fits to our known simulation data. To further mimic biological tissue, we generated five cross-linked bovine serum albumin (BSA) phantoms with concentrations that ranged from 1.25% to 20%. The phantoms were imaged at 3T using SIR, and data were fit to estimate PSR and R 1f. Similarly, a healthy volunteer was imaged at 3T, and SIR parameter maps were estimated to demonstrate the reduced computational time for a real-world clinical example. Results: Estimated SIR parameter maps from our Julia toolkit agreed with simulated values (LCCC > 0.98). This toolkit was further validated using BSA phantoms and a whole brain scan at 3T. In both cases, SIR parameter estimates were consistent with published values using MATLAB. However, compared to earlier work using MATLAB, our Julia toolkit provided an approximate 20-fold reduction in computational time. Conclusions: Presented here, we developed a fast, open-source, toolkit for rapid and accurate SIR MRI using Julia. The reduction in computational cost should allow SIR parameters to be accessible in clinical settings.

Longitudinal Assessment of Intravoxel Incoherent Motion Diffusion-Weighted MRI Metrics in Cognitive Decline.

BACKGROUND: Advanced diffusion-based MRI biomarkers may provide insight into microstructural and perfusion changes associated with neurodegeneration and cognitive decline. PURPOSE: To assess longitudinal microstructural and perfusion changes using apparent diffusion coefficient (ADC) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in cognitively impaired (CI) and healthy control (HC) groups. STUDY TYPE: Prospective/longitudinal. POPULATION: Twelve CI patients (75% female) and 13 HC subjects (69% female). FIELD STRENGTH/SEQUENCE: 3 T; Spin-Echo-IVIM-DWI. ASSESSMENT: Two MRI scans were performed with a 12-month interval. ADC and IVIM-DWI metrics (diffusion coefficient [D] and perfusion fraction [f]) were generated from monoexponential and biexponential fits, respectively. Additionally, voxel-based correlations were evaluated between change in Montreal Cognitive Assessment (ΔMoCA) and baseline imaging parameters. STATISTICAL TESTS: Analysis of covariance with sex and age as covariates was performed for main effects of group and time (false discovery rate [FDR] corrected) with post hoc comparisons using Bonferroni correction. Partial-η2 and Hedges' g were used for effect-size analysis. Spearman's correlations (FDR corrected) were used for the relationship between ΔMoCA score and imaging. P < 0.05 was considered statistically significant. RESULTS: Significant differences were found for the main effects of group (HC vs. CI) and time. For group effects, higher ADC, IVIM-D, and IVIM-f were observed in the CI group compared to HC (ADC: 1.23 ± 0.08. 10-3 vs. 1.09 ± 0.07. 10-3  mm2 /sec; IVIM-D: 0.82 ± 0.01. 10-3 vs. 0.73 ± 0.01. 10-3  mm2 /sec; and IVIM-f: 0.317 ± 0.008 vs. 0.253 ± 0.009). Significantly higher ADC, IVIM-D, and IVIM-f values were observed in the CI group after 12 months (ADC: 1.45 ± 0.05. 10-3 vs. 1.50 ± 0.07. 10-3  mm2 /sec; IVIM-D: 0.87 ± 0.01. 10-3 vs. 0.94 ± 0.02. 10-3  mm2 /sec; and IVIM-f: 0.303 ± 0.007 vs. 0.332 ± 0.008), but not in the HC group at large effect size. ADC, IVIM-D, and IVIM-f negatively correlated with ΔMoCA score (ρ = -0.49, -0.51, and -0.50, respectively). DATA CONCLUSION: These findings demonstrate that longitudinal differences between CI and HC cohorts can be measured using IVIM-based metrics. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment.

White matter integrity and structural connectivity may be altered in mild cognitive impairment (MCI), and these changes may closely reflect decline in specific cognitive domains. Multi-shell diffusion data in healthy control (HC, n = 31) and mild cognitive impairment (MCI, n = 19) cohorts were downloaded from the ADNI3 database. The data were analyzed using an advanced approach to assess both white matter microstructural integrity and structural connectivity. Compared with HC, lower intracellular compartment (IC) and higher isotropic (ISO) values were found in MCI. Additionally, significant correlations were found between IC and Montreal Cognitive Assessment (MoCA) scores in the MCI cohort. Network analysis detected structural connectivity differences between the two groups, with lower connectivity in MCI. Additionally, significant differences between HC and MCI were observed for global network efficiency. Our results demonstrate the potential of advanced diffusion MRI biomarkers for understanding brain changes in MCI.

Longitudinal evaluation of myofiber microstructural changes in a preclinical ALS model using the transverse relaxivity at tracer equilibrium (TRATE): A preliminary study.

T2⁎ relaxivity contrast imaging may serve as a potential imaging biomarker for amyotrophic lateral sclerosis (ALS) by noninvasively quantifying the tissue microstructure. In this preliminary longitudinal study, we investigated the Transverse Relaxivity at Tracer Equilibrium (TRATE) in three muscle groups between SOD1-G93A (ALS model) rat and a control population at two different timepoints. The control group was time matched to the ALS group such that the second timepoint was the onset of disease. We observed a statistically significant decrease in TRATE over time in the gastrocnemius, tibialis, and digital flexor muscles in the SOD1-G93A model (p-value = 0.003, 0.008, 0.005; respectively), whereas TRATE did not change over time in the control group (p-value = 0.4777, 0.6837, 0.9682; respectively). Immunofluorescent staining revealed a decrease in minimum fiber area and cell density in the SOD1-G93A model when compared to the control group (p-value = 6.043E-10 and 2.265E-10, respectively). These microstructural changes observed from histology align with the theorized biophysical properties of TRATE. We demonstrate that TRATE can longitudinally differentiate disease associated atrophy from healthy muscle and has potential to serve as a biomarker for disease progression and ultimately therapy response in patients with ALS.

Sex Differences in Alzheimer's Disease Revealed by Free-Water Diffusion Tensor Imaging and Voxel-Based Morphometry.

BACKGROUND: Imaging biomarkers are increasingly used in Alzheimer's disease (AD), and the identification of sex differences using neuroimaging may provide insight into disease heterogeneity, progression, and therapeutic targets. OBJECTIVE: The purpose of this study was to investigate differences in grey matter (GM) volume and white matter (WM) microstructural disorganization between males and females with AD using voxel-based morphometry (VBM) and free-water-corrected diffusion tensor imaging (FW-DTI). METHODS: Data were downloaded from the OASIS-3 database, including 158 healthy control (HC; 86 females) and 46 mild AD subjects (24 females). VBM and FW-DTI metrics (fractional anisotropy (FA), axial and radial diffusivities (AxD and RD, respectively), and FW index) were compared using effect size for the main effects of group, sex, and their interaction. RESULTS: Significant group and sex differences were observed, with no significant interaction. Post-hoc comparisons showed that AD is associated with reduced GM volume, reduced FW-FA, and higher FW-RD/FW-index, consistent with neurodegeneration. Females in both groups exhibited higher GM volume than males, while FW-DTI metrics showed sex differences only in the AD group. Lower FW, lower FW-FA and higher FW-RD were observed in females relative to males in the AD group. CONCLUSION: The combination of VBM and DTI may reveal complementary sex-specific changes in GM and WM associated with AD and aging. Sex differences in GM volume were observed for both groups, while FW-DTI metrics only showed significant sex differences in the AD group, suggesting that WM tract disorganization may play a differential role in AD pathophysiology between females and males.

Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients.

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.

Investigating the relationship between multi-scale perfusion and white matter microstructural integrity in patients with relapsing-remitting MS.

BACKGROUND: Multiple sclerosis is characterized by the formation of central nervous system demyelinating lesions with microvasculature inflammation. OBJECTIVE: Evaluate how lesion cerebral perfusion relates to white matter microstructural integrity in patients with RRMS using perfusion MRI and myelin-related T1-weighted to T2-weighted (T1w/T2w) ratios. METHODS: Forty-eight patients with RRMS were imaged with dynamic susceptibility contrast imaging using SAGE (spin- and gradient-echo) to calculate global and capillary-sized perfusion parameters, including cerebral blood flow (CBF), volume (CBV), and mean transit time (MTT). T1w/T2w ratios were used to indirectly assess white matter microstructural integrity. RESULTS: For global perfusion metrics, CBF was reduced 28.4% in lesion regions of interest (ROIs) compared to normal appearing white matter (NAWM), CBV was reduced 25.9% in lesion ROIs compared to NAWM, and MTT increased 12.9%. For capillary perfusion metrics (via spin-echo (SE)), CBF-SE was reduced 35.7% in lesion ROIs compared to NAWM, CBV-SE was reduced 35.2% in lesion ROIs compared to NAWM, and MTT-SE increased 9.1%. Capillary-level CBF was correlated (ρ = 0.34, p = 0.024) with white matter microstructural integrity in lesion ROIs. CONCLUSION: This study demonstrates that lesion perfusion is reduced at both the global and capillary level and capillary-associated hypoperfusion is associated with reduced white matter microstructural integrity in RRMS.

Development of a spiral spin- and gradient-echo (spiral-SAGE) approach for improved multi-parametric dynamic contrast neuroimaging.

PURPOSE: The purpose of this study was to develop a spiral-based combined spin- and gradient-echo (spiral-SAGE) method for simultaneous dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI). METHODS: Using this sequence, we obtained gradient-echo TEs of 1.69 and 26 ms, a SE TE of 87.72 ms, with a TR of 1663 ms. Using an iterative SENSE reconstruction followed by deblurring, spiral-induced image artifacts were minimized. Healthy volunteer images are shown to demonstrate image quality using the optimized reconstruction, as well as for comparison with EPI-based SAGE. A bioreactor phantom was used to compare dynamic-contrast time courses with both spiral-SAGE and EPI-SAGE. A proof-of-concept cohort of patients with brain tumors shows the range of hemodynamic maps available using spiral-SAGE. RESULTS: Comparison of spiral-SAGE images with conventional EPI-SAGE images illustrates substantial reductions of image distortion and artifactual image intensity variations. Bioreactor phantom data show similar dynamic contrast time courses between standard EPI-SAGE and spiral-SAGE for the second and third echoes, whereas first-echo data show improvements in quantifying T1 changes with shorter echo times. In a cohort of patients with brain tumors, spiral-SAGE-based perfusion and permeability maps are shown with comparison with the standard single-echo EPI perfusion map. CONCLUSION: Spiral-SAGE provides a substantial improvement for the assessment of perfusion and permeability by mitigating artifacts typically encountered with EPI and by providing a shorter echo time for improved characterization of permeability. Spiral-SAGE enables quantification of perfusion, permeability, and vessel architectural parameters, as demonstrated in brain tumors.

Evaluation of Amyotrophic Lateral Sclerosis-Induced Muscle Degeneration Using Magnetic Resonance-Based Relaxivity Contrast Imaging (RCI).

(1) Background: This work characterizes the sensitivity of magnetic resonance-based Relaxivity Contrast Imaging (RCI) to Amyotrophic Lateral Sclerosis (ALS)-induced changes in myofiber microstructure. Transverse Relaxivity at Tracer Equilibrium (TRATE), an RCI-based parameter, was evaluated in the lower extremities of ALS patients and healthy subjects. (2) Methods: In this IRB-approved study, 23 subjects (12 ALS patients and 11 healthy controls) were scanned at 3T (Philips, The Netherlands). RCI data were obtained during injection of a gadolinium-based contrast agent. TRATE, fat fraction and T2 measures, were compared in five muscle groups of the calf muscle, between ALS and control populations. TRATE was also evaluated longitudinally (baseline and 6 months) and was compared to clinical measures, namely ALS Functional Rating Scale (ALSFRS-R) and Hand-Held Dynamometry (HHD), in a subset of the ALS population. (3) Results: TRATE was significantly lower (p < 0.001) in ALS-affected muscle than in healthy muscle in all muscle groups. Fat fraction differences between ALS and healthy muscle were statistically significant for the tibialis anterior (p = 0.01), tibialis posterior (p = 0.004), and peroneus longus (p = 0.02) muscle groups but were not statistically significant for the medial (p = 0.07) and lateral gastrocnemius (p = 0.06) muscles. T2 differences between ALS and healthy muscle were statistically significant for the tibialis anterior (p = 0.004), peroneus longus (p = 0.004) and lateral gastrocnemius (p = 0.03) muscle groups but were not statistically significant for the tibialis posterior (p = 0.06) and medial gastrocnemius (p = 0.07) muscles. Longitudinally, TRATE, averaged over all patients, decreased by 28 ± 16% in the tibialis anterior, 47 ± 18% in the peroneus longus, 25 ± 19% in the tibialis posterior, 29 ± 14% in the medial gastrocnemius and 35 ± 18% in the lateral gastrocnemius muscles between two timepoints. ALSFRS-R scores were stable in two of four ALS patients. HHD scores decreased in three of four ALS patients. (4) Conclusion: RCI-based TRATE was shown to consistently differentiate ALS-affected muscle from healthy muscle and also provide a quantitative measure of longitudinal muscle degeneration.