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Abstract Quantifying tetrodotoxin (TTX) has been a challenge in both ecological and medical research due to the cost, time and training required of most quantification techniques. Here we present a modified Competitive Inhibition Enzymatic Immunoassay for the quantification of TTX, and to aid researchers in the optimization of this technique for widespread use with a high degree of accuracy and repeatability.

Background and Purpose: DSC-MR imaging can be used to generate fractional tumor burden (FTB) maps via application of relative CBV thresholds to spatially differentiate glioblastoma recurrence from posttreatment radiation effects (PTRE). Image-localized histopathology was previously used to validate FTB maps derived from a reference DSC-MR imaging protocol by using preload, a moderate flip angle (MFA, 60°), and postprocessing leakage correction. Recently, a DSC-MR imaging protocol with a low flip angle (LFA, 30°) with no preload was shown to provide leakage-corrected relative CBV (rCBV) equivalent to the reference protocol. This study aimed 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 glioblastoma who had prior surgical resection and received chemotherapy and radiation therapy were included in the study. Two sets of DSC-MR imaging data were collected sequentially first by 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 coregistered with the anatomic postcontrast T1-weighted images. The reference MFA-based FTB maps were computed by using previously published sRCBV thresholds (1.0 and 1.56). A receiver operating characteristics (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 (concordance correlation coefficient = 0.99) between the 2 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., Conclusions: For LFA-based FTB maps, an sRCBV threshold of 1.0 and 1.37 can differentiate PTRE from recurrent tumors. FTB maps aid in surgical planning, guiding pathologic diagnosis and treatment strategies in the recurrent setting. This study further confirms the reliability of single-dose LFA-based DSC-MR imaging., (© 2024 by American Journal of Neuroradiology.)

Purpose: Multi-echo, multi-contrast methods are increasingly used in dynamic imaging studies to simultaneously quantify R 2 ∗ and R 2 . To overcome the computational challenges associated with nonlinear least squares (NLSQ) fitting, we propose a generalized linear least squares (LLSQ) solution to rapidly fit R 2 ∗ and R 2 ., Methods: Spin- and gradient-echo (SAGE) data were simulated across T 2 ∗ and T 2 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 R 2 ∗ and R 2 , as well as cerebral blood volume (CBV), were compared with the standard NLSQ approach., Results: Across all fitting methods, T 2 ∗ was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.87, CV ≤ 0.08) SNR. Except for short T 2 ∗ values (5-15 ms), T 2 was well-fit at high (CCC = 1, CV = 0) and low (CCC ≥ 0.99, CV ≤ 0.03) SNR. In vivo, LLSQ R 2 ∗ and R 2 estimates were similar to NLSQ, and there were no differences in R 2 ∗ across fitting methods at high SNR. However, there were some differences at low SNR and for R 2 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 R 2 ∗ - (0.97 ratio) and R 2 -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 R 2 ∗ and R 2 in simulated and in vivo data. Use of LLSQ methods reduced the computational demand, enabling rapid estimation of R 2 ∗ and R 2 ., Competing Interests: Declaration of competing interest None., (Copyright © 2024. Published by Elsevier Inc.)

Background: Mild Cognitive Impairment (MCI) is a transitional stage from normal aging to dementia, characterized by noticeable changes in cognitive function that do not significantly impact daily life. Diffusion MRI (dMRI) plays a crucial role in understanding MCI by assessing white matter integrity and revealing early signs of axonal degeneration and myelin breakdown before cognitive symptoms appear., Methods: This study utilized the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to compare white matter microstructure in individuals with MCI to cognitively normal (CN) individuals, employing advanced dMRI techniques such as diffusion kurtosis imaging (DKI), mean signal diffusion kurtosis imaging (MSDKI), and free water imaging (FWI)., Results: Analyzing data from 55 CN subjects and 46 individuals with MCI, this study found significant differences in white matter integrity, particularly in free water levels and kurtosis values, suggesting neuroinflammatory responses and microstructural integrity disruption in MCI. Moreover, negative correlations between Mini-Mental State Examination (MMSE) scores and free water levels in the brain within the MCI group point to the potential of these measures as early biomarkers for cognitive impairment., Conclusion: In conclusion, this study demonstrates how a multimodal advanced diffusion imaging approach can uncover early microstructural changes in MCI, offering insights into the neurobiological mechanisms behind cognitive decline., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Nelson, Keeling, Stokes and Bergamino.)

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., (© 2024 International Society for Magnetic Resonance in Medicine.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Bergamino, Burke, Sabbagh, Caselli, Baxter and Stokes.)

Purpose: Extension of adjuvant endocrine therapy beyond five years confers only modest survival benefit in breast cancer patients and carries risk of toxicities. This systematic review investigates the role of biomarker tests in predicting the clinical response to an extension of endocrine therapy., Methods: We searched Ovid MEDLINE, Ovid Embase, Global Index Medicus, and the Cochrane Central Register of Controlled Trials using an iterative approach to identify full-text articles related to breast cancer, endocrine therapy, and biomarkers., Results: Of the 1,217 unique reports identified, five studies were deemed eligible. Four investigated the Breast Cancer Index (BCI) assay in three distinct study populations. These studies consistently showed that BCI score was predictive of response to extended endocrine therapy among 1,946 combined patients, who were predominately non-Hispanic white and postmenopausal., Conclusions: Evidence in the setting of predictive tests for extended endocrine therapy is sparse. Most relevant studies investigated the use of BCI, but these study populations were largely restricted to a single age, race, and ethnicity group. Future studies should evaluate a variety of biomarkers in diverse populations. Without sufficient evidence, physicians and patients face a difficult decision in balancing the benefits and risks of endocrine therapy extension., (© 2023. The Author(s).)

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.

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., (Copyright © 2023 Elsevier Inc. All rights reserved.)

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., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author(s). Published by IMR Press.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Bergamino, Keeling, Ray, Macerollo, Silverdale and Stokes.)

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., Competing Interests: LB is employed by Genentech Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Anil, Stokes, Chao, Hu, Alhilali, Karis, Bell and Quarles.)

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-η 2 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  mm 2 /sec; IVIM-D: 0.82 ± 0.01 . 10 -3 vs. 0.73 ± 0.01 . 10 -3  mm 2 /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  mm 2 /sec; IVIM-D: 0.87 ± 0.01 . 10 -3 vs. 0.94 ± 0.02 . 10 -3  mm 2 /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., (© 2022 International Society for Magnetic Resonance in Medicine.)

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., T 2 (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., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Cyberattacks on healthcare organizations increased dramatically in 2020 and 2021. The University of Vermont Medical Center suffered an attack in October 2020, during the second wave of the COVID-19 pandemic. The disruption to hospital computer systems had wide-ranging impacts, including loss of online access to the medical library for nearly three months. Library staff worked to reduce impacts and increase access for hospital employees until full access was restored. This case study offers lessons learned and resources for health sciences libraries planning for a potential cyberattack.

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., Competing Interests: The authors declare that they have no competing interests., (© 2022 Sisco et al.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bergamino, Schiavi, Daducci, Walsh and Stokes.)

T 2 ⁎ 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., (Copyright © 2021 Elsevier Inc. All rights reserved.)

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.

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.

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 T 1 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., (© 2021 International Society for Magnetic Resonance in Medicine.)

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 T 1 -weighted to T 2 -weighted (T 1 w/T 2 w) 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). T 1 w/T 2 w 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., (© The Author(s) 2021.)

(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 T 2 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. T 2 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.

Magnetic resonance imaging (MRI) based diffusion tensor imaging (DTI) can assess white matter (WM) integrity through several metrics, such as fractional anisotropy (FA), axial/radial diffusivities (AxD/RD), and mode of anisotropy (MA). Standard DTI is susceptible to the effects of extracellular free water (FW), which can be removed using an advanced free-water DTI (FW-DTI) model. The purpose of this study was to compare standard and FW-DTI metrics in the context of Alzheimer's disease (AD). Data were obtained from the Open Access Series of Imaging Studies (OASIS-3) database and included both healthy controls (HC) and mild-to-moderate AD. With both standard and FW-DTI, decreased FA was found in AD, mainly in the corpus callosum and fornix, consistent with neurodegenerative mechanisms. Widespread higher AxD and RD were observed with standard DTI; however, the FW index, indicative of AD-associated neurodegeneration, was significantly elevated in these regions in AD, highlighting the potential impact of free water contributions on standard DTI in neurodegenerative pathologies. Using FW-DTI, improved consistency was observed in FA, AxD, and RD, and the complementary FW index was higher in the AD group as expected. With both standard and FW-DTI, higher values of MA coupled with higher values of FA in AD were found in the anterior thalamic radiation and cortico-spinal tract, most likely arising from a loss of crossing fibers. In conclusion, FW-DTI better reflects the underlying pathology of AD and improves the accuracy of DTI metrics related to WM integrity in Alzheimer's disease.

Radiogenomics uses machine-learning (ML) to directly connect the morphologic and physiological appearance of tumors on clinical imaging with underlying genomic features. Despite extensive growth in the area of radiogenomics across many cancers, and its potential role in advancing clinical decision making, no published studies have directly addressed uncertainty in these model predictions. We developed a radiogenomics ML model to quantify uncertainty using transductive Gaussian Processes (GP) and a unique dataset of 95 image-localized biopsies with spatially matched MRI from 25 untreated Glioblastoma (GBM) patients. The model generated predictions for regional EGFR amplification status (a common and important target in GBM) to resolve the intratumoral genetic heterogeneity across each individual tumor-a key factor for future personalized therapeutic paradigms. The model used probability distributions for each sample prediction to quantify uncertainty, and used transductive learning to reduce the overall uncertainty. We compared predictive accuracy and uncertainty of the transductive learning GP model against a standard GP model using leave-one-patient-out cross validation. Additionally, we used a separate dataset containing 24 image-localized biopsies from 7 high-grade glioma patients to validate the model. Predictive uncertainty informed the likelihood of achieving an accurate sample prediction. When stratifying predictions based on uncertainty, we observed substantially higher performance in the group cohort (75% accuracy, n = 95) and amongst sample predictions with the lowest uncertainty (83% accuracy, n = 72) compared to predictions with higher uncertainty (48% accuracy, n = 23), due largely to data interpolation (rather than extrapolation). On the separate validation set, our model achieved 78% accuracy amongst the sample predictions with lowest uncertainty. We present a novel approach to quantify radiogenomics uncertainty to enhance model performance and clinical interpretability. This should help integrate more reliable radiogenomics models for improved medical decision-making.

White matter microstructural changes in Alzheimer's disease (AD) are often assessed using fractional anisotropy (FA) obtained from diffusion tensor imaging (DTI). FA depends on the acquisition and analysis methods, including the fitting algorithm. In this study, we compared FA maps from different acquisitions and fitting algorithms in AD, mild cognitive impairment (MCI), and healthy controls (HCs) using the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Three acquisitions from two vendors were compared (Siemens 30, GE 48, and Siemens 54 directions). DTI data were fit using nine fitting algorithms (four linear least squares (LLS), two weighted LLS (WLLS), and three non-linear LLS (NLLS) from four software tools (FSL, DSI-Studio, CAMINO, and AFNI). Different cluster volumes and effect-sizes were observed across acquisitions and fits, but higher consistency was observed as the number of diffusion directions increased. Significant differences were observed between HC and AD groups for all acquisitions, while significant differences between HC and MCI groups were only observed for GE48 and SI54. Using the intraclass correlation coefficient, AFNI-LLS and CAMINO-RESTORE were the least consistent with the other algorithms. By combining data across all three acquisitions and nine fits, differences between AD and HC/MCI groups were observed in the fornix and corpus callosum, indicating FA differences in these regions may be robust DTI-based biomarkers. This study demonstrates that comparisons of FA across aging populations could be confounded by variability in acquisitions and fit methodologies and that identifying the most robust DTI methodology is critical to provide more reliable DTI-based neuroimaging biomarkers for assessing microstructural changes in AD., Competing Interests: Conflicts of InterestThe authors declare no conflict of interest., (© 2021 by the authors.)

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease that affects aging populations. Current MRI techniques are often limited in their sensitivity to underlying neuropathological changes., Purpose: To characterize differences in voxel-based morphometry (VBM), apparent diffusion coefficient (ADC), and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) metrics in aging populations. Additionally, to investigate the connection between cognitive assessments and neuroimaging metrics., Study Type: Prospective/cross-sectional., Population: In all, 49 subjects, including 13 with AD dementia, 12 with mild cognitive impairment (MCI), and 24 healthy controls (HC)., Field Strength/sequence: 3T/magnetization-prepared rapid acquisition gradient echo (MP-RAGE) and IVIM-DWI ASSESSMENT: All participants completed a cognitive screening battery prior to MRI. IVIM-DWI maps (pure diffusion coefficient [D], pseudodiffusion coefficient [D*], and perfusion fraction [f]) were generated from a biexponential fit of diffusion MRI data. VBM was performed on the standard T 1 -weighted MP-RAGE structural images. Group-wise templates were used to compare across groups., Statistical Tests: Analysis of covariance (ANCOVA) with gender and age as covariates (familywise error [FWE] corrected, post-hoc comparisons using Bonferroni correction) for group comparisons. Partial-η 2 and Hedges' g were used for effect-size analysis. Spearman's correlations (false discovery rate [FDR]-corrected) for the relationship between cognitive scores and imaging., Results: Clusters of significant group-wise differences were found mainly in the temporal lobe, hippocampus, and amygdala using all VBM and IVIM methods (P < 0.05 FWE). While VBM showed significant changes between MCI and AD groups and between HC and AD groups, no significant clusters were observed between HC and MCI using VBM. ADC and IVIM-D demonstrated significant changes, at P < 0.05 FWE, between HC and MCI, notably in the amygdala and hippocampus. Several voxel-based correlations were observed between neuroimaging metrics and cognitive tests within the cognitively impaired groups (P < 0.05 FDR)., Data Conclusion: These findings suggest that IVIM-DWI metrics may be earlier biomarkers for AD-related changes than VBM. The use of these techniques may provide novel insight into subvoxel neurodegenerative processes., Level of Evidence: 2 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1811-1826., (© 2020 International Society for Magnetic Resonance in Medicine.)

Introduction: The Western Desert Kidney Health Project (WDKHP) aimed to determine the prevalence of type 2 diabetes (T2DM), kidney disease and associated risk factors in Aboriginal and non-Aboriginal people in a remote area of Western Australia., Methods: The project, featuring whole-of-community cross-sectional surveys and health assessments using point-of-care testing, was conducted in five small towns and six remote Aboriginal communities in the Goldfields of Western Australia between 2010 and 2014. Initial health assessments were completed by 597 adults (424 Aboriginal) and 502 children (393 Aboriginal). This included almost 80% of the Aboriginal population. All non-Aboriginal people residing in the six remote Aboriginal communities participated., Results: Risk factors for renal disease and T2DM were present in participants of all ages, including children as young as 2 years. There was no significant difference between Aboriginal and non-Aboriginal children. Aboriginal and non-Aboriginal adult participants had twice the burden of T2DM than the standard Australian population. More than 12% of all children had elevated albumin-creatinine ratio (ACR). Adults had markers of kidney disease at higher rates than expected: 51% of Aboriginal adults and 27% of non-Aboriginal adults had at least one marker of kidney disease (haematuria, proteinuria or elevated ACR). Aboriginal women were the highest risk group (32% T2DM, 40% elevated ACR). Haematuria and low urine pH were common findings, 21% of people had haematuria (greater than trace) and 71% had urine pH of 6 or less; there was no difference in this finding between Aboriginal and non-Aboriginal people., Conclusion: The WDKHP found higher than expected rates of risk factors for T2DM and renal disease compared with Australian Bureau of Statistics rates for Australian Aboriginal and non-Aboriginal adults and children, with Aboriginal women the highest risk group. The rates for non-Aboriginal participants were higher than expected, suggesting exposures in common might be more important than ethnicity.The high prevalence of aciduria and haematuria found in both Aboriginal and non-Aboriginal participants in this study suggests that factors contributing to a chronic metabolic acidosis and inflammation or irritation of the urinary tract need to be explored. Drinking water quality in this remote area is known to be poor and may be an important contributing factor. Many of the contributing factors are potentially modifiable - such as water quality, food supply, exercise opportunities and living conditions - offering scope for interventions to reduce the risk and burden of these diseases.

Background and Purpose: Perfusion MR imaging measures of relative CBV can distinguish recurrent tumor from posttreatment radiation effects in high-grade gliomas. Currently, relative CBV measurement requires normalization based on user-defined reference tissues. A recently proposed method of relative CBV standardization eliminates the need for user input. This study compares the predictive performance of relative CBV standardization against relative CBV normalization for quantifying recurrent tumor burden in high-grade gliomas relative to posttreatment radiation effects., Materials and Methods: We recruited 38 previously treated patients with high-grade gliomas (World Health Organization grades III or IV) undergoing surgical re-resection for new contrast-enhancing lesions concerning for recurrent tumor versus posttreatment radiation effects. We recovered 112 image-localized biopsies and quantified the percentage of histologic tumor content versus posttreatment radiation effects for each sample. We measured spatially matched normalized and standardized relative CBV metrics (mean, median) and fractional tumor burden for each biopsy. We compared relative CBV performance to predict tumor content, including the Pearson correlation ( r ), against histologic tumor content (0%-100%) and the receiver operating characteristic area under the curve for predicting high-versus-low tumor content using binary histologic cutoffs (≥50%; ≥80% tumor)., Results: Across relative CBV metrics, fractional tumor burden showed the highest correlations with tumor content (0%-100%) for normalized ( r  = 0.63, P  < .001) and standardized ( r = 0.66, P  < .001) values. With binary cutoffs (ie, ≥50%; ≥80% tumor), predictive accuracies were similar for both standardized and normalized metrics and across relative CBV metrics. Median relative CBV achieved the highest area under the curve (normalized = 0.87, standardized = 0.86) for predicting ≥50% tumor, while fractional tumor burden achieved the highest area under the curve (normalized = 0.77, standardized = 0.80) for predicting ≥80% tumor., Conclusions: Standardization of relative CBV achieves similar performance compared with normalized relative CBV and offers an important step toward workflow optimization and consensus methodology., (© 2020 by American Journal of Neuroradiology.)

Background: Dynamic susceptibility contrast (DSC)-MRI analysis pipelines differ across studies and sites, potentially confounding the clinical value and use of the derived biomarkers., Purpose/hypothesis: To investigate how postprocessing steps for computation of cerebral blood volume (CBV) and residue function dependent parameters (cerebral blood flow [CBF], mean transit time [MTT], capillary transit heterogeneity [CTH]) impact glioma grading., Study Type: Retrospective study from The Cancer Imaging Archive (TCIA)., Population: Forty-nine subjects with low- and high-grade gliomas., Field Strength/sequence: 1.5 and 3.0T clinical systems using a single-echo echo planar imaging (EPI) acquisition., Assessment: Manual regions of interest (ROIs) were provided by TCIA and automatically segmented ROIs were generated by k-means clustering. CBV was calculated based on conventional equations. Residue function dependent biomarkers (CBF, MTT, CTH) were found by two deconvolution methods: circular discretization followed by a signal-to-noise ratio (SNR)-adapted eigenvalue thresholding (Method 1) and Volterra discretization with L-curve-based Tikhonov regularization (Method 2)., Statistical Tests: Analysis of variance, receiver operating characteristics (ROC), and logistic regression tests., Results: MTT alone was unable to statistically differentiate glioma grade (P > 0.139). When normalized, tumor CBF, CTH, and CBV did not differ across field strengths (P > 0.141). Biomarkers normalized to automatically segmented regions performed equally (rCTH AUROC is 0.73 compared with 0.74) or better (rCBF AUROC increases from 0.74-0.84; rCBV AUROC increases 0.78-0.86) than manually drawn ROIs. By updating the current deconvolution steps (Method 2), rCTH can act as a classifier for glioma grade (P < 0.007), but not if processed by current conventional DSC methods (Method 1) (P > 0.577). Lastly, higher-order biomarkers (eg, rCBF and rCTH) along with rCBV increases AUROC to 0.92 for differentiating tumor grade as compared with 0.78 and 0.86 (manual and automatic reference regions, respectively) for rCBV alone., Data Conclusion: With optimized analysis pipelines, higher-order perfusion biomarkers (rCBF and rCTH) improve glioma grading as compared with CBV alone. Additionally, postprocessing steps impact thresholds needed for glioma grading., Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:547-553., (© 2019 International Society for Magnetic Resonance in Medicine.)

Purpose: Brain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T 1 and T 2 ∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T 1 leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol., Methods: Using a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols., Results: Multi-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV., Conclusions: Multi-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T 2 ∗ leakage effects remains compulsory for high rCBV accuracy., (© 2019 International Society for Magnetic Resonance in Medicine.)

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T 1 , T 2 and T 2 ∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T 1 , T 2 and T 2 ∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background and Purpose: The accuracy of DSC-MR imaging CBV maps in glioblastoma depends on acquisition and analysis protocols. Multisite protocol heterogeneity has challenged standardization initiatives due to the difficulties of in vivo validation. This study sought to compare the accuracy of routinely used protocols using a digital reference object., Materials and Methods: The digital reference object consisted of approximately 10,000 simulated voxels recapitulating typical signal heterogeneity encountered in vivo. The influence of acquisition and postprocessing methods on CBV reliability was evaluated across 6912 parameter combinations, including contrast agent dosing schemes, pulse sequence parameters, field strengths, and postprocessing methods. Accuracy and precision were assessed using the concordance correlation coefficient and coefficient of variation., Results: Across all parameter space, the optimal protocol included full-dose contrast agent preload and bolus, intermediate (60°) flip angle, 30-ms TE, and postprocessing with a leakage-correction algorithm (concordance correlation coefficient = 0.97, coefficient of variation = 6.6%). Protocols with no preload or fractional dose preload and bolus using these acquisition parameters were generally less robust. However, a protocol with no preload, full-dose bolus, and low (30°) flip angle performed very well (concordance correlation coefficient = 0.93, coefficient of variation = 8.7% at 1.5T and concordance correlation coefficient = 0.92, coefficient of variation = 8.2% at 3T)., Conclusions: Schemes with full-dose preload and bolus maximize CBV accuracy and reduce variability, which could enable smaller sample sizes and more reliable detection of CBV changes in clinical trials. When a lower total contrast agent dose is desired, use of a low flip angle, no preload, and full-dose bolus protocol may provide an attractive alternative., (© 2018 by American Journal of Neuroradiology.)

Background and Purpose: The optimal TE must be calculated to minimize the variance in CBV measurements made with DSC MR imaging. Simulations can be used to determine the influence of the TE on CBV, but they may not adequately recapitulate the in vivo heterogeneity of precontrast T2*, contrast agent kinetics, and the biophysical basis of contrast agent-induced T2* changes. The purpose of this study was to combine quantitative multiecho DSC MRI T2* time curves with error analysis in order to compute the optimal TE for a traditional single-echo acquisition., Materials and Methods: Eleven subjects with high-grade gliomas were scanned at 3T with a dual-echo DSC MR imaging sequence to quantify contrast agent-induced T2* changes in this retrospective study. Optimized TEs were calculated with propagation of error analysis for high-grade glial tumors, normal-appearing white matter, and arterial input function estimation., Results: The optimal TE is a weighted average of the T2* values that occur as a contrast agent bolus transverses a voxel. The mean optimal TEs were 30.0 ± 7.4 ms for high-grade glial tumors, 36.3 ± 4.6 ms for normal-appearing white matter, and 11.8 ± 1.4 ms for arterial input function estimation (repeated-measures ANOVA, P < .001)., Conclusions: Greater heterogeneity was observed in the optimal TE values for high-grade gliomas, and mean values of all 3 ROIs were statistically significant. The optimal TE for the arterial input function estimation is much shorter; this finding implies that quantitative DSC MR imaging acquisitions would benefit from multiecho acquisitions. In the case of a single-echo acquisition, the optimal TE prescribed should be 30-35 ms (without a preload) and 20-30 ms (with a standard full-dose preload)., (© 2017 by American Journal of Neuroradiology.)

With DSC-MRI, contrast agent leakage effects in brain tumors can either be leveraged for percent signal recovery (PSR) measurements or be adequately resolved for accurate relative cerebral blood volume (rCBV) measurements. Leakage effects can be dimished by administration of a preload dose before imaging and/or specific postprocessing steps. This study compares the consistency of both PSR and rCBV measurements as a function of varying preload doses in a retrospective analysis of 14 subjects with high-grade gliomas. The scans consisted of 6 DSC-MRI scans during 6 sequential bolus injections (0.05 mmol/kg). Mean PSR was calculated for tumor and normal-appearing white matter regions of interest. DSC-MRI data were corrected for leakage effects before computing mean tumor rCBV. Statistical differences were seen across varying preloads for tumor PSR ( P value = 4.57E-24). Tumor rCBV values did not exhibit statistically significant differences across preloads ( P value = .14) and were found to be highly consistent for clinically relevant preloads (intraclass correlation coefficient = 0.93). For a 0.05 mmol/kg injection bolus and pulse sequence parameters used, the highest PSR contrast between normal-appearing white matter and tumor occurs when no preload is used. This suggests that studies using PSR as a biomarker should acquire DSC-MRI data without preload. The finding that leakage-corrected rCBV values do not depend on the presence or dose of preload contradicts that of previous studies with dissimilar acquisition protocols. This further confirms the sensitivity of rCBV to preload dosing schemes and pulse sequence parameters and highlights the importance of standardization efforts for achieving multisite rCBV consistency., Competing Interests: Conflict of Interest: None reported.

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T 1 and changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials., Competing Interests: Conflict of Interest: None reported.

The goal of this study was to validate a simplified spin- and gradient-echo (sSAGE) approach to obtain T 1 -corrected dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) data in a clinical brain tumor population. A five-echo SAGE sequence was used to acquire DSC-MRI data (n=8 patients, 3 primary glioma, and 5 brain metastases). The ΔR 2 ⁎ and ΔR 2 time series obtained from a nonlinear fit of all echoes (SAGE) were compared to ΔR 2 ⁎ and ΔR 2 time series obtained analytically (sSAGE) using three echoes (two GEs and one SE). Through the use of multiple echoes, both methods removed T 1 leakage effects from the ΔR 2 ⁎ and ΔR 2 time series, and the sSAGE ΔR 2 ⁎ and ΔR 2 time series were highly correlated with those from SAGE, with average correlations of 0.9. The resulting hemodynamic parameters included GE and SE cerebral blood volume (CBV), cerebral blood flow (CBF), mean vessel diameter (mVD), volume transfer constant (K trans ), and volume fraction of the extravascular extracellular space (v e ). For each metric, there was good correlation (>0.86) between sSAGE and SAGE, with no significant differences. The sSAGE method provides T 1 -corrected GE and SE DSC-MRI parameters in an efficient and clinically feasible manner., (Copyright © 2016 Elsevier Inc. All rights reserved.)

High-grade gliomas are often characterized by hypoxia, which is associated with both poor long-term prognosis and therapy resistance. The adverse role hypoxia plays in treatment resistance and disease progression has led to the development of hypoxia imaging methods and hypoxia-targeted treatments. Here, we determined the tumor hypoxia and vascular perfusion characteristics of 2 rat orthotopic glioma models using 18-fluoromisonidozole positron emission tomography. In addition, we determined tumor response to the hypoxia-activated prodrug evofosfamide (TH-302) in these rat glioma models. C6 tumors exhibited more hypoxia and were less perfused than 9L tumors. On the basis of these differences in their tumor hypoxic burden, treatment with evofosfamide resulted in 4- and 2-fold decreases in tumor growth rates of C6 and 9L tumors, respectively. This work shows that imaging methods sensitive to tumor hypoxia and perfusion are able to predict response to hypoxia-targeted agents. This has implications for improved patient selection, particularly in clinical trials, for treatment with hypoxia-activated cytotoxic prodrugs, such as evofosfamide., Competing Interests: None to report.

Purpose: The goal of this study was to investigate the influence of water compartmentation and heterogeneous relaxation properties on quantitative magnetization transfer (qMT) imaging in tissues, and in particular whether a two-pool model is sufficient to describe qMT data in brain tumors., Methods: Computer simulations and in vivo experiments with a series of qMT measurements before and after injection of Gd-DTPA were performed. Both off-resonance pulsed saturation (pulsed) and on-resonance selective inversion recovery (SIR) qMT methods were used, and all data were fit with a two-pool model only., Results: Simulations indicated that a two-pool fitting of four-pool data yielded accurate measures of pool size ratio (PSR) of macromolecular versus free water protons when there were fast transcytolemmal exchange and slow R1 recovery. The fitted in vivo PSR of both pulsed and SIR qMT methods showed no dependence on R1 variations caused by different concentrations of Gd-DTPA during wash-out, whereas the fitted kex (magnetization transfer exchange rate) changed significantly with R1 ., Conclusion: A two-pool model provides reproducible estimates of PSR in brain tumors independent of relaxation properties in the presence of relatively fast transcytolemmal exchange, whereas estimates of kex are biased by relaxation variations. In addition, estimates of PSR in brain tumors using the pulsed and SIR qMT methods agree well with one another. Magn Reson Med 76:635-644, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

Purpose: A combined biophysical- and pharmacokinetic-based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual-echo dynamic susceptibility contrast (DSC) acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA)., Theory and Methods: Dual-echo DSC-MRI data were acquired in two rodent glioma models. The T1 leakage effects were removed and also quantified to subsequently correct for the remaining T2* leakage effects. Pharmacokinetic, biophysical, and combined biophysical and pharmacokinetic models were used to obtain corrected cerebral blood volume (CBV) and cerebral blood flow (CBF), and these were compared with CBV and CBF from an intravascular CA., Results: T1 -corrected CBV was significantly overestimated compared with MION CBV, while T1 + T2*-correction yielded CBV values closer to the reference values. The pharmacokinetic and simplified biophysical methods showed similar results and underestimated CBV in tumors exhibiting strong T2* leakage effects. The combined method was effective for correcting T1 and T2* leakage effects across tumor types., Conclusion: Correcting for both T1 and T2* leakage effects yielded more accurate measures of CBV. The combined correction method yields more reliable CBV measures than either correction method alone, but for certain brain tumor types (e.g., gliomas), the simplified biophysical method may provide a robust and computationally efficient alternative. Magn Reson Med 76:613-625, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

Background and Purpose: Clinical measurements of cerebral perfusion have been increasingly performed with multiecho dynamic susceptibility contrast-MR imaging techniques due to their ability to remove confounding T1 effects of contrast agent extravasation from perfusion quantification. However, to this point, the extra information provided by multiecho techniques has not been used to improve the process of estimating the arterial input function, which is critical to accurate perfusion quantification. The purpose of this study is to investigate methods by which multiecho DSC-MRI data can be used to automatically avoid voxels whose signal decreases to the level of noise when calculating the arterial input function., Materials and Methods: Here we compare postprocessing strategies for clinical multiecho DSC-MR imaging data to test whether arterial input function measures could be improved by automatically identifying and removing voxels exhibiting signal attenuation (truncation) artifacts., Results: In a clinical pediatric population, we found that the Pearson correlation coefficient between ΔR2* time-series calculated from each TE individually was a valuable criterion for automated estimation of the arterial input function, resulting in higher peak arterial input function values while maintaining smooth and reliable arterial input function shapes., Conclusions: This work is the first to demonstrate that multiecho information may be useful in clinically important automatic arterial input function estimation because it can be used to improve automatic selection of voxels from which the arterial input function should be measured., (© 2016 by American Journal of Neuroradiology.)

The authors discuss eight areas of quantitative MR imaging that are currently used (RECIST, DCE-MR imaging, DSC-MR imaging, diffusion MR imaging) in clinical trials or emerging (CEST, elastography, hyperpolarized MR imaging, multiparameter MR imaging) as promising techniques in diagnosing cancer and assessing or predicting response of cancer to therapy. Illustrative applications of the techniques in the clinical setting are summarized before describing the current limitations of the methods., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: In this study, we propose a simplified acquisition and analysis approach for spin and gradient echo (SAGE)-based dynamic susceptibility-contrast MRI (DSC-MRI) data that is free of contrast agent T1 leakage effects., Methods: A five-echo SAGE sequence was used to acquire DSC-MRI data in rat C6 tumors (n = 7). Nonlinear fitting of all echoes was performed to obtain T1-insensitive ΔR2* and ΔR2 time series. The simplified approach, which includes two gradient echoes and one spin echo, was also used to analytically compute T1-insensitive ΔR2* using the two gradient echoes and ΔR2 using all three echoes. The blood flow, blood volume, and vessel size values derived from each method were compared., Results: In all cases, the five-echo and simplified SAGE ΔR2* and ΔR2 were in excellent agreement and demonstrated significant T1 leakage correction compared with the uncorrected single-echo data. The derived hemodynamic parameters for blood volume, blood flow, and vessel size were not significantly different between the two methods., Conclusions: The proposed simplified SAGE technique enables the acquisition of gradient and spin echo DSC-MRI data corrected for T1 leakage effects yields parameters that are in agreement with the five-echo SAGE approach and does not require nonlinear fitting to extract ΔR2* and ΔR2 time series., (© 2015 Wiley Periodicals, Inc.)

The goal of this study was to optimize and validate a combined spin- and gradient-echo (SAGE) sequence for dynamic susceptibility-contrast magnetic resonance imaging to obtain hemodynamic parameters in a preclinical setting. The SAGE EPI sequence was applied in phantoms and in vivo rat brain (normal, tumor, and stroke tissue). Partial and full Fourier encoding schemes were implemented and characterized. Maps of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), vessel size index (VSI), volume transfer constant (K(trans)), and volume fraction of the extravascular extracellular space (ve) were obtained. Partial Fourier encoding provided shortened echo times with acceptable signal-to-noise ratio and temporal stability, thus enabling reliable characterization of T2, T2(*) and T1 in both phantoms and rat brain. The hemodynamic parameters CBV, CBF, and MTT for gradient-echo and spin-echo contrast were determined in tumor and stroke; VSI, K(trans), and ve were also computed in tumor tissue. The SAGE EPI sequence allows the acquisition of multiple gradient- and spin-echoes, from which measures of perfusion, permeability, and vessel size can be obtained in a preclinical setting. Partial Fourier encoding can be used to minimize SAGE echo times and reliably quantify dynamic T2 and T2(*) changes. This acquisition provides a more comprehensive assessment of hemodynamic status in brain tissue with vascular and perfusion abnormalities., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Nitrite undergoes reconversion to nitric oxide under conditions characteristic of the tumor microenvironment, such as hypoxia and low pH. This selective conversion of nitrite into nitric oxide in tumor tissue has led to the possibility of using nitrite to enhance drug delivery and the radiation response. In this work, we propose to serially characterize the vascular response of brain tumor-bearing rats to nitrite using contrast-enhanced R2 * mapping. Imaging is performed using a multi-echo gradient echo sequence at baseline, post iron oxide nanoparticle injection and post-nitrite injection, whilst the animal is breathing air. The results indicate that nitrite sufficiently increases the vascular permeability in C6 gliomas, such that the iron oxide nanoparticles accumulate within the tumor tissue. When animals breathed 100% oxygen, the contrast agent remained within the vasculature, indicating that the conversion of nitrite to nitric oxide occurs in the presence of hypoxia within the tumor. The hypoxia-dependent, nitrite-induced extravasation of iron oxide nanoparticles observed herein has implications for the enhancement of conventional and nanotherapeutic drug delivery., (Copyright © 2014 John Wiley & Sons, Ltd.)

Endogenous magnetic resonance contrast based on the localized composition of fat in vivo can provide functional information. We found that the unequal pulse timings of the Uhrig's dynamical decoupling multipulse echo sequences significantly alter the signal intensity compared to conventional, equal-spaced Carr-Purcell-Meiboom-Gill sequences. The signal increases and decreases depending on the tissue and sequence parameters, as well as on the interpulse spacings; particularly strong differences were observed in fatty tissues, which have a highly structured morphology and a wide range of chemical shifts and J-couplings. We found that the predominant mechanism for fat refocusing under multipulse echo sequences is the chemical structure, with stimulated echoes playing a pivotal role. As a result, specialized pulse sequences can be designed to optimize refocusing of the fat chemical shifts and J-couplings, where the degree of refocusing can be tailored to specific types of fats. To determine the optimal time delays, we simulated various Uhrig dynamical decoupling and Carr-Purcell-Meiboom-Gill pulse sequence timings, and these results are compared to experimental results obtained on excised and in vivo fatty tissue. Applications to intermolecular multiple quantum coherence imaging, where the improved echo refocusing translates directly into signal enhancements, are presented as well., (Copyright © 2012 Wiley Periodicals, Inc.)

Methadone is an effective analgesic opioid that may have a place for the treatment of pain in horses. However, its absorption seems to be impaired by the presence of a transmembrane protein, P-glycoprotein, present in different tissues including the small intestine in other species. This study aims to determine the effect of the P-glycoprotein on methadone flux in the equine intestinal mucosa, as an indicator of in vivo drug absorption. Jejunum tissues from five horses were placed into the Ussing chambers and exposed to methadone solution in the presence or absence of Rhodamine 123 or verapamil. Electrical measurements demonstrated tissue viability for 120 min, and the flux of methadone across the jejunal membrane (mucosal to submucosal direction) was calculated based on the relative drug concentration measured by ELISA. The flux of methadone was significantly higher only in the presence of verapamil. P-glycoprotein was immunolocalized in the apical membrane of the jejunal epithelial cells (enterocytes), mainly located in the tip of the villi compared to cells of the crypts. P-glycoprotein is present in the equine jejunum and may possibly mediate the intestinal transport of methadone. This study suggests that P-glycoprotein may play a role in the poor intestinal absorption of methadone in vivo., (© 2012 Blackwell Publishing Ltd.)

We report a series of investigations of the pH-sensitive magnetic resonance (MR) responses of various surface-functionalized SPIONs (superparamagnetic iron oxide nanoparticles). First, functionalization of ~12 nm highly monocrystalline SPION cores with three different generations of melamine-dendrons was optimized to give agents with high molar relaxivities (e.g. R 2 m ~300 mM -1 ·s -1 at 7 T and R 1 m ~20-30 mM -1 ·s -1 at 0.5 T) and excellent aqueous stabilities. Molar relaxivities were found to exhibit great sensitivity to pH at physiologically-relevant ionic strengths, with sharp inflections observed at pH values near the p K a of the melamine monomer. The strength of the effect was observed to grow with increasing dendron generation (with concomitant shift in the position of the main pH inflection). Opposing behavior in R 2 m and R 2 m * trends may be exploited to provide a ratiometric MR response to pH. Combined with TEM and corresponding MR measurements from solutions of varying ionic strengths, these results are consistent with the pH-sensitive behavior originating from transient, reversible SPION clustering modulated by an interplay between SPION surface charge density and solution ionic strength. Studies of SPION cellular uptake and MR response in HeLa cell cultures are also presented. Finally, comparisons with the MR responses of SPIONs with alternative functionalities-derivatives of nitrilotriacetic acid or poly(1-vinylimidazole)-indicate that these types of pH-sensitive MR responses can be highly dependent upon the chemical composition of the surface species (and thus amenable to modulation through rational design).

Improved understanding of the entrapment, transport, and release of drugs and small molecules within vesicles is important for drug delivery. Most methods rely on contrast agents or probe molecules; here, we propose a new MRI method to detect signal from water spins with restricted diffusion. This method is based on intermolecular double quantum coherences (iDQCs), which can probe the restricted diffusion characteristics at well-defined and tunable microscopic distance scales. By using an exceedingly short (and previously inaccessible) distance, the iDQC signal arises only from restricted diffusion spins and thereby provides a mechanism to directly image vesicle entrapment, transport, and release. Using uni- and multi-lamellar liposomes and polymersomes, we show how the composition, lamellar structure, vesicle size, and concentration affects the iDQC signal between coupled water spins at very short separation distances. The iDQC signal correlates well with conventional diffusion MRI and a proposed biexponential (multicompartmental) diffusion model. Finally, the iDQC signal was used to monitor dynamic changes in the lamellar structure as temperature-sensitive liposomes released their contents. These short distance iDQCs can probe the amount and diffusion of water entrapped in vesicles, which may be useful to further understand vesicle properties in materials science and drug delivery applications., (Copyright © 2012 Elsevier Inc. All rights reserved.)