1H-Magnetic resonance spectroscopy (1H-MRS) is a noninvasive technique for quantifying brain metabolites, including glutamate, glutathione (GSH), and γ-aminobutyric acid (GABA), which are essential for brain function and implicated in various neurodevelopmental conditions. As such, 1H-MRS methods that enable reliable and accurate measurement of these metabolites are of considerable clinical value. Hadamard Encoding and Reconstruction of MEGA-Edited Spectroscopy (HERMES; echo time [TE] = 80 ms) is a spectral editing technique that allows for the simultaneous quantification of GABA and GSH, using subtraction approaches to resolve these metabolites in a difference spectrum. Additionally, glutamate plus glutamine resonances (Glx) can be resolved either from the HERMES GABA-edited difference spectrum (GABA-DIFF) or from the sum of all HERMES transients (SUM spectrum). However, the reliability of 80-ms HERMES for quantification of Glx has not been systematically assessed. Here, we evaluate the agreement between Glx obtained from HERMES GABA-DIFF and SUM spectra with Glx derived from short-TE PRESS (TE = 35 ms), which is conventionally used for Glx estimation and has demonstrated reproducibility. Data were acquired from 139 participants across two brain regions (ACC and Thalamus voxels), three scanners, two diagnostic groups (autism and neurotypical development) and two age groups (adolescent/adult and preschooler). Comparisons were made using both creatine-scaled and tissue-corrected Glx estimates. Our findings demonstrate significant systematic and proportional bias between Glx estimates from HERMES (SUM and GABA-DIFF) and short-TE PRESS, consistent across scanners, voxels, age groups and diagnostic categories. These findings indicate that Glx estimates derived from HERMES are not directly comparable to those from short-TE PRESS, and this discrepancy is consistent across a multisite study setting. This underscores the importance of sequence selection and careful methodological consideration when integrating and interpreting data from 1H-MRS across different acquisition protocols.

Background Hippocampal avoidance during prophylactic cranial irradiation (HA-PCI) is proposed to reduce neurocognitive decline, while preserving the benefits of PCI. We evaluated whether (HA-)PCI induces changes in white matter (WM) microstructure and whether sparing the hippocampus has an impact on preserving brain network topology. In addition, we evaluated associations between topological metrics with hippocampal volume and neuropsychological outcomes.Methods In this multicenter randomized phase 3 trial (NCT01780675), small-cell lung cancer (SCLC) patients underwent neuropsychological testing and diffusion tensor imaging (DTI) before, 4 months (33 PCI, 37 HA-PCI) and 1 year (19 PCI, 17 HA-PCI) after (HA-)PCI. Changes in WM microstructure were investigated using whole-brain voxel-based analysis of fractional anisotropy (FA) and mean diffusivity (MD). Both hippocampal and whole-brain graph measures were used to evaluate the topological organization of structural networks. Correlation analysis was performed to associate topological metrics with neuropsychological outcomes and hippocampal volume.Results Both HA-PCI and PCI were associated with decreased FA in major WM tracts, such as the corpus callosum, at 4 months and 1 year post-treatment. While these FA decreases did not differ significantly between treatment groups, only PCI demonstrated increased MD over time. In addition, PCI showed decreased global efficiency and increased characteristic path length over time when compared with HA-PCI. Significant correlations were found between whole-brain graph measures and neuropsychological outcomes.Conclusion While both techniques induce important changes in the WM microstructure, HA-PCI might better preserve the topological organization of brain networks than PCI. The neuroprotective role of hippocampal sparing still needs further investigation.

Arterial spin labeling (ASL) MRI allows non-invasive quantification of renal blood flow (RBF) and shows great potential for renal assessment. To our knowledge, renal ASL-MRI has not previously been performed in dogs. The aim of this pilot study was to determine parameters essential for ALS-MRI-based quantification of RBF in dogs: T1, blood (longitudinal relaxation time), λ (blood tissue partition coefficient) and TI (inversion time). A Beagle was scanned at 3T with a multi-TI ASL sequence, with TIs ranging from 250 to 2500 ms, to determine the optimal TI value. The T1 of blood for dogs was determined by scanning a blood sample with a 2D IR TSE sequence. The water content of the dog's kidney was determined by analyzing kidney samples from four dogs with a moisture analyzer and was subsequently used to calculate λ. The optimal TI and the measured values for T1,blood, and λ were 2000 ms, 1463 ms and 0.91 mL/g, respectively. These optimized parameters for dogs resulted in lower RBF values than those obtained from inline generated RBF maps. In conclusion, this study determined preliminary parameters essential for ALS-MRI-based RBF quantification in dogs. Further research is needed to confirm these values, but it may help guide future research.

In 2010, the National Institute of Neurological Disorders and Stroke (NINDS) created a set of common data elements (CDEs) to help standardize the assessment and reporting of imaging findings in traumatic brain injury (TBI). However, as opposed to other standardized radiology reporting systems, a visual overview and data to support the proposed standardized lexicon are lacking. We used over 4000 admission computed tomography (CT) scans of patients with TBI from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study to develop an extensive pictorial overview of the NINDS TBI CDEs, with visual examples and background information on individual pathoanatomical lesion types, up to the level of supplemental and emerging information (e.g., location and estimated volumes). We documented the frequency of lesion occurrence, aiming to quantify the relative importance of different CDEs for characterizing TBI, and performed a critical appraisal of our experience with the intent to inform updating of the CDEs. In addition, we investigated the co-occurrence and clustering of lesion types and the distribution of six CT classification systems. The median age of the 4087 patients in our dataset was 50 years (interquartile range, 29-66; range, 0-96), including 238 patients under 18 years old (5.8%). Traumatic subarachnoid hemorrhage (45.3%), skull fractures (37.4%), contusions (31.3%), and acute subdural hematoma (28.9%) were the most frequently occurring CT findings in acute TBI. The ranking of these lesions was the same in patients with mild TBI (baseline Glasgow Coma Scale [GCS] score 13-15) compared with those with moderate-severe TBI (baseline GCS score 3-12), but the frequency of occurrence was up to three times higher in moderate-severe TBI. In most TBI patients with CT abnormalities, there was co-occurrence and clustering of different lesion types, with significant differences between mild and moderate-severe TBI patients. More specifically, lesion patterns were more complex in moderate-severe TBI patients, with more co-existing lesions and more frequent signs of mass effect. These patients also had higher and more heterogeneous CT score distributions, associated with worse predicted outcomes. The critical appraisal of the NINDS CDEs was highly positive, but revealed that full assessment can be time consuming, that some CDEs had very low frequencies, and identified a few redundancies and ambiguity in some definitions. Whilst primarily developed for research, implementation of CDE templates for use in clinical practice is advocated, but this will require development of an abbreviated version. In conclusion, with this study, we provide an educational resource for clinicians and researchers to help assess, characterize, and report the vast and complex spectrum of imaging findings in patients with TBI. Our data provides a comprehensive overview of the contemporary landscape of TBI imaging pathology in Europe, and the findings can serve as empirical evidence for updating the current NINDS radiologic CDEs to version 3.0.

An MRI protocol tree on a clinical MRI system is a large database containing hundreds of protocols, each containing multiple sequences, and up to 900 parameters per sequence. Protocol variation between scan sessions or patients must be avoided as much as possible, as it may lead to financial loss and less than optimal outcomes for the patient. Without proper management, protocol variation and errors in MRI protocol trees are easily introduced and may remain undetected, leading to a cluttered protocol tree. This in turn reduces the efficiency of the radiological MRI workflow. We introduce a method and open-source software tools for managing MRI protocols on a sequence parameter level, which can detect deviations and variations in the protocol tree. It can be used offline, away from the scanner console, without disturbing the clinical workflow. These tools help to create a standardized protocol library across multiple MRI scanners, reducing variation and errors, enabling radiology departments to create optimal value for the patient and institution.

OBJECTIVE:Renal multiparametric magnetic resonance imaging (mpMRI) sequences, including T1-T2 mapping, Blood oxygenation level-dependent (BOLD), Renal blood flow (RBF), and Apparent Diffusion Coefficient (ADC) from diffusion-weighted imaging (DWI), provide insights into kidney function. However, consensus on selecting regions of interest (ROIs) is lacking. This study aims to describe and compare the Concentric Objects (CO) and Equiangular Objects (EO) methods for standardized ROI selection and assess their efficacy in capturing regional variations in renal MRI parameters. MATERIALS AND METHODS:Twelve healthy volunteers underwent mpMRI renal scans. ROIs were selected manually and by applying the CO and EO algorithms to each mpMRI sequence. The methods were tested across various subregion configurations. Regional differences in renal MRI parameters were evaluated. RESULTS:CO and EO methods demonstrated statistically significant differences in mpMRI parameters across renal regions. ASL-RBF, BOLD-MRI, and T2-map results indicated substantial variations from the lower to upper kidney areas. DISCUSSION:This study implemented CO and EO algorithms in renal mpMRI, showing their potential for evaluating cortico-medullary and cranio-caudal profiles. The findings validate the CO method for BOLD and ADC measurements and presented ASL-RBF and T1-T2 map profiles. The EO method's utility needs further validation with renal patients.

IntroductionDynamic contrast-enhanced (DCE) MRI and arterial spin labeling (ASL) MRI enable non-invasive measurement of renal blood flow (RBF), whereas blood oxygenation level-dependent (BOLD) MRI enables non-invasive measurement of the apparent relaxation rate (R2*), an indicator of oxygenation. This study was conducted to evaluate the potential role of these MRI modalities in assessing RBF and oxygenation in dogs. The correlation between contrast-enhanced ultrasound (CEUS) and the MRI modalities was examined and also the ability of the MRI modalities to detect pharmacologically induced changes.MethodsRBF, using CEUS, ASL- and DCE-MRI, as well as renal oxygenation, using BOLD-MRI of eight adult beagles were assessed at two time-points, 2–3 weeks apart. During each time point, the anesthetized dogs received either a control (0.9% sodium chloride) or a dopamine treatment. For each time point, measurements were carried out over 2 days. An MRI scan at 3 T was performed on day one, followed by CEUS on day two.ResultsUsing the model-free model with caudal placement of the arterial input function (AIF) region of interest (ROI) in the aorta, the DCE results showed a significant correlation with ASL measured RBF and detected significant changes in blood flow during dopamine infusion. Additionally, R2* negatively correlated with ASL measured RBF at the cortex and medulla, as well as with medullary wash-in rate (WiR) and peak intensity (PI). ASL measured RBF, in its turn, showed a positive correlation with cortical WiR, PI, area under the curve (AUC) and fall time (FT), and with medullary WiR and PI, but a negative correlation with medullary rise time (RT). During dopamine infusion, BOLD-MRI observed a significant decrease in R2* at the medulla and entire kidney, while ASL-MRI demonstrated a significant increase in RBF at the cortex, medulla and the entire kidney.ConclusionASL- and BOLD-MRI can measure pharmacologically induced changes in renal blood flow and renal oxygenation in dogs and might allow detection of changes that cannot be observed with CEUS. However, further research is needed to confirm the potential of ASL- and BOLD-MRI in dogs and to clarify which analysis method is most suitable for DCE-MRI in dogs.

BACKGROUND:Multiparametric MRI (mpMRI) provides detailed insights into renal function, but the impact of anthropometric factors on renal imaging is not fully understood. PURPOSE:To investigate regional correlations between mpMRI parameters and age, body mass index (BMI), and body surface area (BSA). STUDY TYPE:Prospective, cross-sectional observational study. POPULATION:Twenty-nine healthy volunteers (44.5 ± 18.3 years, 18 females) without a history of renal disease. FIELD STRENGTH/SEQUENCE:3-T, pseudo-continuous arterial spin labeling, multi-echo gradient-recalled echo, diffusion-weighted imaging, T1 and T2 mapping. ASSESSMENT:Bilateral kidneys were segmented into nine concentric layers (outer cortex to inner regions) and nine equiangular sections (lower to upper pole). Key parameters (renal blood flow [RBF], R 2 * , apparent diffusion coefficient [ADC], T1 and T2 maps) were correlated with age, BMI, and BSA. Differences in parameters between age and BMI groups were also evaluated. STATISTICAL TESTS:Spearman correlation, Mann-Whitney U test, and rank-biserial correlation coefficient for effect size. A P-value <0.05 was considered statistically significant. RESULTS:RBF correlated negatively with age in all regions and BMI in inner layers and lower pole. ADC negatively correlated with BMI (significance was not reached in layers 2, 7, 8; P-value = 0.06-0.12) and BSA in layers 1-7. T1 negatively correlated with age in inner regions and lower medial pole. Significant positive correlations were found between age and R 2 * (outermost layer, upper pole), age and T2 (inner and cranial-caudal regions), as well as BMI and T2 (except upper pole; P-value = 0.06). Significant differences between age groups were observed for RBF (all regions), R 2 * (outermost and second innermost layers, central lateral region), T1 (innermost layer), and T2 (upper medial pole). Between BMI groups, ADC (middle layers, upper medial pole) and T2 (outermost and inner layers, lower pole to lateral region) differed significantly. DATA CONCLUSION:Intrarenal variance of mpMRI parameters correlated with age, BMI, and BSA. EVIDENCE LEVEL:4 TECHNICAL EFFICACY: Stage 1.

Tumor fluid dynamics and drug delivery simulations in solid tumors are highly relevant topics in clinical oncology. The current study introduces a novel method combining computational fluid dynamics (CFD) modeling, quantitative magnetic resonance imaging (MRI; including dynamic contrast-enhanced (DCE) MRI and diffusion-weighted (DW) MRI), and a novel ex-vivo protocol to generate patient-specific models of solid tumors in four patients with peritoneal metastases. DCE-MRI data were analyzed using the extended Tofts model to estimate the spatial distribution of tumor capillary permeability using the Ktrans parameter. DW-MRI data analysis provided a 3D representation of drug diffusivity, and DW-MRI coupled to an ex-vivo measurement protocol informed the spatial heterogeneity of the hydraulic conductivity of tumor tissue. The patient-specific data were subsequently incorporated into a computational fluid dynamics (CFD) model to simulate individualized tumor perfusion and drug transport maps. The results on interstitial fluid flow demonstrated noticeable heterogeneity of interstitial fluid pressure and velocity within the tumor, along with heterogeneous drug penetration profiles among different tumors, even with a similar drug administration regimen.

Inadequate uptake of therapeutic agents by tumor cells is still a major barrier in clinical cancer therapy. Mathematical modeling is a powerful tool to describe and investigate the transport phenomena involved. However, current models for interstitial flow and drug delivery in solid tumors have not yet embedded the existing heterogeneity of tumor biomechanical properties. The purpose of this study is to introduce a novel and more realistic methodology for computational models of solid tumor perfusion and drug delivery accounting for these regional heterogeneities as well as lymphatic drainage effects. Several tumor geometries were studied using an advanced computational fluid dynamics (CFD) modeling approach of intratumor interstitial fluid flow and drug transport. Hereby, the following novelties were implemented: (i) the heterogeneity of tumor-specific hydraulic conductivity and capillary permeability; (ii) the effect of lymphatic drainage on interstitial fluid flow and drug penetration. Tumor size and shape both have a crucial role on the interstitial fluid flow regime as well as drug transport illustrating a direct correlation with interstitial fluid pressure (IFP) and an inverse correlation with drug penetration, except for large tumors having a diameter larger than 50 mm. The results also suggest that the interstitial fluid flow and drug penetration in small tumors depend on tumor shape. A parameter study on the necrotic core size illustrated that the core effect (i.e. fluid flow and drug penetration alteration) was only profound in small tumors. Interestingly, the impact of a necrotic core on drug penetration differs depending on the tumor shape from having no effect in ideally spherical tumors to a clear effect in elliptical tumors with a necrotic core. A realistic presence of lymphatic vessels only slightly affected tumor perfusion, having no substantial effect on drug delivery. In conclusion, our findings illustrated that our novel parametric CFD modeling strategy in combination with accurate profiling of heterogeneous tumor biophysical properties can provide a powerful tool for better insights into tumor perfusion and drug transport, enabling effective therapy planning.

reported to be a potentially safe and feasible procedure for early gastric cancer (EGC), there is currently no study demonstrating the feasibility of SIDG for advanced gastric cancer (AGC) alone.Materials and Methods: Database of patients clinically diagnosed as AGC who underwent SIDG from November 2017 to April 2022 was retrospectively analyzed.Those who had distant metastasis, and those who underwent palliative surgery were excluded.Patient demographics, operation data, and postoperative complications were reviewed.Results: A total of 117 patients were included for the final analysis.Among them, 74 (63.2%) were male, and mean age was 63.9 ± 11.9 years.Average body mass index was 24.2 ± 2.9 kg/m2.The number of patients with stage pT2, pT3, pT4a and pT4b after surgery was 34 (29.1%),47 (40.2%), 34 (29.1%) and 2 (1.7%) respectively.Mean operation time was 170.3 ± 65.0 mins.and average estimated blood loss was 30.8 ± 63.0 ml.Average number of retrieved lymph nodes was 59.3 ± 22.1.Patients started their first soft fluid diet on an average of 2.3 ± 1.0 postoperative days, and first flatus was observed after 3.1 ± 1.3 postoperative days.Overall mean hospital stay was 6.9 ± 2.9 days.Early complications (within 30 days) greater than Clavien-Dindo grade III were found in 5 patients (4.3%) and late complications (after 30 days) were found in 4 patients (3.4%).Conclusions: This study shows that SIDG is feasible in some selected patients with AGC.

AbstractBackgroundElevated tumor tissue interstitial fluid pressure (IFP) is an adverse biomechanical biomarker that predicts poor therapy response and an aggressive phenotype. Advances in functional imaging have opened the prospect of measuring IFP non‐invasively. Image‐based estimation of the IFP requires knowledge of the tissue hydraulic conductivity (K), a measure for the ease of bulk flow through the interstitium. However, data on the magnitude of K in human cancer tissue are not available.MethodsWe measured the hydraulic conductivity of tumor tissue using modified Ussing chambers in surgical resection specimens. The effect of the tumor microenvironment (TME) on K was investigated by quantifying the collagen content, cell density, and fibroblast density of the tested samples using quantitative immune histochemistry. Also, we developed a computational fluid dynamics (CFD) model to evaluate the role of K on interstitial fluid flow and drug transport in solid tumors.ResultsThe results show that the hydraulic conductivity of human tumor tissues is very limited, ranging from approximately 10−15 to 10−14 m2/Pa∙s. Moreover, K values varied significantly between tumor types and between different samples from the same tumor. A significant inverse correlation was found between collagen fiber density and hydraulic conductivity values. However, no correlation was detected between K and cancer cell or fibroblast densities. The computational model demonstrated the impact of K on the interstitial fluid flow and the drug concentration profile: higher K values led to a lower IFP and deeper drug penetration.ConclusionsHuman tumor tissue is characterized by a very limited hydraulic conductivity, representing a barrier to effective drug transport. The results of this study can inform the development of realistic computational models, facilitate non‐invasive IFP estimation, and contribute to stromal targeting anticancer therapies.

BACKGROUND:Reducing radiation dose to the hippocampus with hippocampal avoidance prophylactic cranial irradiation (HA-PCI) is proposed to prevent cognitive decline. It has, however, not been investigated whether hippocampal atrophy is actually mitigated by this approach. Here, we determined whether HA-PCI reduces hippocampal atrophy. Additionally, we evaluated neurotoxicity of (HA-)PCI to other brain regions. Finally, we evaluated associations of hippocampal atrophy and brain neurotoxicity with memory decline.METHODS:High-quality research MRI scans were acquired in the multicenter, randomized phase 3 trial NCT01780675. Hippocampal atrophy was evaluated for 4 months (57 HA-PCI patients and 46 PCI patients) and 12 months (28 HA-PCI patients and 27 PCI patients) after (HA-)PCI. We additionally studied multimodal indices of brain injury. Memory was assessed with the Hopkins Verbal Learning Test-Revised (HVLT-R).RESULTS:HA-PCI reduced hippocampal atrophy at 4 months (1.8% for HA-PCI and 3.0% for PCI) and at 12 months (3.0% for HA-PCI and 5.8% for PCI). Both HA-PCI and PCI were associated with considerable reductions in gray matter and normal-appearing white matter, increases in white matter hyperintensities, and brain aging. There were no significant associations between hippocampal atrophy and memory.CONCLUSIONS:HA-PCI reduces hippocampal atrophy at 4 and 12 months compared to regular PCI. Both types of radiotherapy are associated with considerable brain injury. We did not find evidence for excessive brain injury after HA-PCI relative to PCI. Hippocampal atrophy was not associated with memory decline in this population as measured with HVLT-R. The usefulness of HA-PCI is still subject to debate.

The physical microenvironment of cancer is characterized by elevated stiffness and tissue pressure, the main component of which is the interstitial fluid pressure (IFP). Elevated IFP is an established negative predictive and prognostic parameter, directly affecting malignant behavior and therapy response. As such, measurement of the IFP would allow to develop strategies aimed at engineering the physical microenvironment of cancer. Traditionally, IFP measurement required the use of invasive methods. Recent progress in dynamic and functional imaging methods such as dynamic contrast enhanced (DCE) magnetic resonance imaging and elastography, combined with numerical models and simulation, allows to comprehensively assess the biomechanical landscape of cancer, and may help to overcome physical barriers to drug delivery and immune cell infiltration. Here, we provide a comprehensive overview of the origin of elevated IFP, and its role in the malignant phenotype. Also, we review the methods used to measure IFP using invasive and imaging based methods, and highlight remaining obstacles and potential areas of progress in order to implement IFP measurement in clinical practice.

Thiel embalming followed by freezing in the desired position and acquiring CT + MRI scans is expected to be the ideal approach to obtain accurate, enhanced CT data for delineation guideline development. The effect of Thiel embalming and freezing on MRI image quality is not known. This study evaluates the above-described process to obtain enhanced CT datasets, focusing on the integration of MRI data obtained from frozen, Thiel-embalmed specimens. Three Thiel-embalmed specimens were frozen in prone crawl position and MRI scanning protocols were evaluated based on contrast detail and structural conformity between 3D renderings from corresponding structures, segmented on corresponding MRI and CT scans. The measurement error of the dataset registration procedure was also assessed. Scanning protocol T1 VIBE FS enabled swift differentiation of soft tissues based on contrast detail, even allowing a fully detailed segmentation of the brachial plexus. Structural conformity between the reconstructed structures on CT and MRI was excellent, with nerves and blood vessels imported into the CT scan never intersecting with the bones. The mean measurement error for the image registration procedure was consistently in the submillimeter range (range 0.77–0.94 mm). Based on the excellent MRI image quality and the submillimeter error margin, the procedure of scanning frozen Thiel-embalmed specimens in the treatment position to obtain enhanced CT scans is recommended. The procedure can be used to support the postulation of delineation guidelines, or for training deep learning algorithms, considering automated segmentations.

Resistance against drug delivery is a challenge in oncology. The elevated interstitial fluid pressure (IFP) in solid tumors has been identified as a barrier for drug transport. Also, the hydraulic conductivity (K) of tumor stroma strongly correlates with the IFP. However, values of K in human cancer tissue are not available. Here, we developed a novel in vitro setup that allows to measure K in clinical samples.

Purpose: MRI is the imaging modality of choice for soft tissue-related spine disease. However, CT is superior to MRI in providing clear visualization of bony morphology. The purpose of this study is to test equivalency of MRIbased synthetic CT to conventional CT in quantitatively assessing bony morphology of the lumbar spine. Method: A prospective study with an equivalency design was performed. Adult patients who had undergone MRI and CT of the lumbar spine were included. Synthetic CT images were generated from MRI using a deep learningbased image synthesis method. Two readers independently measured pedicle width, spinal canal width, neuroforamen length, anterior and posterior vertebral body height, superior and inferior vertebral body length, superior and inferior vertebral body width, maximal disc height, lumbar curvature and spinous process length on synthetic CT and CT. The agreement among CT and synthetic CT was evaluated using equivalency statistical testing. Results: Thirty participants were included (14 men and 16 women, range 20-60 years). The measurements performed on synthetic CT of pedicle width, spinal canal width, vertebral body height, vertebral body width, vertebral body length and spinous process length were statistically equivalent to CT measurements at the considered margins. Excellent inter- and intra-reader reliability was found for both synthetic CT and CT. Conclusions: Equivalency of MRI-based synthetic CT to CT was demonstrated on geometrical measurements in the lumbar spine. In combination with the soft tissue information of the conventional MRI, this provides new possibilities in diagnosis and surgical planning without ionizing radiation.

Background Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. Purpose To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. Study Type Retrospective. Subjects and Phantoms In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. Field Strength/Sequence Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. Assessment From HCP data with b-values = 1000, 2000, 3000 s/mm(2) (dataset A), two additional datasets with b-values = 1000, 3000 s/mm(2) (dataset B) and b-values = 1000, 2000 s/mm(2) (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). Statistical Tests DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. Results Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). Data Conclusion The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.