Keywords: IVIM, Spinal Cord

Motivation: High precision of intravoxel incoherent motion (IVIM) MRI parameters in the cervical cord can facilitate studies targeting perfusion impairment and substantiate clinical findings.

Goal(s): To determine the test-retest repeatability of IVIM in the cervical cord using four different common model fitting approaches.

Approach: Test-retest cardiac-gated IVIM acquisitions, sensitive to perfusion, were performed at 3T in 10 healthy subjects at C1-C3 levels. Reliability was assessed using relative test-retest differences, within-subject coefficients of variation and intraclass correlation coefficients.

Results: IVIM parameters in the cervical cord showed high repeatability at the group level in the white and grey matter.

Impact: The high test-retest repeatability of IVIM parameters in the cervical cord will help the interpretation of future clinical findings and support its relevance for applications in various neurological diseases affecting the spinal cord. 

Keywords: Diffusion Analysis & Visualization, Diffusion/other diffusion imaging techniques, 0.55T MR system

Motivation: Comparing the image quality, distortion, and stability of quantitative parameters of MRI in parotid gland images across 0.55T, 1.5T, and 3T.

Goal(s): To compare the clinical performance of 0.55T magnetic resonance imaging (MRI) systems in parotid glands with 1.5T and 3T.

Approach: Evaluating image quality, distortion in DWI, and the stability and differences of quantitative parameters derived from IVIM across different field strengths.

Results: 0.55T MRI significantly reduces image distortion and maintains stable ADC values in DWI while providing comparable morphologic image quality to 1.5T. Additionally, the diffusion parameters in 0.55T showed significant differences compared to those of 1.5T and 3T.

Impact: 0.55T MRI may offer a valuable alternative with the significant altered IVIM-DKI parameters for  parotid gland imagings in patients with limited conditions, maintaining image quality and stable ADC values, potentially improving the diagnostic process for certain individuals.

Keywords: Diffusion Modeling, Modelling, Quantitative Imaging, Diffusion

Motivation: Estimating IVIM diffusion MRI (dMRI) parameters through non-linear fitting is challenging due to the inherent ill-posed mathematical problem, causing large uncertainty and poor reproducibility.

Goal(s): Understand IVIM-dMRI model properties and derive a more reliable metric than individual IVIM parameters.

Approach: Given a dMRI protocol, we investigated diffusion decay signal distributions for various IVIM parameters via numerical simulations. Employing dimension reduction, we defined a new parameter that captured the largest decay signal variation and is hence most robust against noise. 

Results: A new metric was proposed to have the best achievable robustness for IVIM model parameter fitting.

Impact: We proposed a new metric that attains the best achievable robustness for IVIM model parameter fitting. This study addressed the large uncertainty and poor reproducibility issue in IVIM fitting.

Keywords: Diffusion Acquisition, Quantitative Imaging, Liver, Perfusion, Modeling, Relaxometry, Velocity & Flow

Motivation: The intravoxel incoherent motion (IVIM) signal is known to depend on first-order motion moment (M₁) and TE, which may contribute to observed poor precision of conventional (b-value only) IVIM quantification.

Goal(s): Design an optimized 3D (b-M₁-TE) IVIM acquisition for precise (repeatable) IVIM and R₂ quantification in the liver.

Approach: 3D (b-M₁-TE) noise-optimized IVIM acquisitions were acquired using a test-retest approach. IVIM estimates were obtained using a recently proposed advanced fitting technique. Test-retest repeatability and interlobar agreement were evaluated.

Results: The optimized 3D (b-M₁-TE) IVIM acquisition demonstrated moderate to good repeatability and interlobar agreement of IVIM and R₂ estimates (coefficients of variation < 32.0%).

Impact: A noise-optimized 3D (b-M₁-TE) IVIM acquisition is proposed for simultaneous and repeatable IVIM and R₂ quantification in the liver. Accounting for M₁ and TE dependencies in the IVIM signal may enable improved diagnostic performance and treatment monitoring of IVIM quantification.

Keywords: IVIM, Motion Correction

Motivation: The existing fitting methods of lntravoxel incoherent motion (IVI M) parameter maps can already achieve good performance, but they all ignore the impact of internal heart beat or breathing movements on multiple b-value images for the fitting performance. 

Goal(s): We expect to incorporate motion correction in the fitting process to improve fitting performance.

Approach: In this study, we propose an end-to-end deep network structure that combines self-supervised learning and motion correction for fitting IVIM parameters.

Results: The quantitative and qualitative comparative experimental results indicate that using self-supervised motion correction can improve the fitting performance.

Impact: For the first time, we consider incorporating motion correction into IVIM parameter fitting, and the self-supervised and end-to-end network design does not require training data, which can be extended to clinical applications.

Keywords: IVIM, Diffusion/other diffusion imaging techniques

Motivation: Intravoxel incoherent motion (IVIM) measurements are often performed with various acquisition parameters among different studies. Previous studies showed differences in f during the application of simultaneous multislice (SMS). 

Goal(s): The goal is to investigate the influence of SMS and the concomitant T₁-effects due to the reduction of TR.

Approach: Diffusion-weighted images of the liver were acquired for conventional and SMS excitation with long and short TR each. Results were verified with a biophysical model.

Results: The evaluation indicates no dependence of IVIM parameters on SMS. Yet, the reduction of TR appears to be relevant for small gaps between slices in the simulations.

Impact: This study indicates that while comparing different IVIM studies, TR and gaps between slices must be taken into account, as they may substantially alter the measured f. IVIM parameters for SMS excitation are well comparable with conventional excitation, though.

Keywords: IVIM, Perfusion, IVIM post processing

Motivation: Despite the IVIM model’s ability to noninvasively provide insight into tissue microstructure and perfusion, estimation of IVIM parameters in low-perfused tissues such as bone marrow remains a challenge.

Goal(s): In this work, we propose an optimized analytical segmented (opAS) approach for extracting IVIM diffusion (Ds) and perfusion (Df and f). 

Approach: We compare the performance of this new approach against the analytical segmented (AS) method previously proposed for low-perfused tissues using numerical simulations and a piglet model.

Results: Our findings indicate that opAS outperforms AS in the estimation of all IVIM parameters (Ds, Df, and f), particularly in the low perfusion regime. 

Impact: The proposed opAS method outperforms the prior AS method in estimating IVIM diffusion (Ds) and perfusion (Df and f) parameters, bringing IVIM a step closer to being a clinically useful non-contrast-enhanced technique to assess bone marrow perfusion.

Keywords: IVIM, Diffusion/other diffusion imaging techniques, Sarcoma

Motivation: Intra-voxel incoherent motion imaging (IVIM) suffers from long acquisition times due to the number of low b-values typically required, which limits clinical use.

Goal(s): To develop a faster linearised method of IVIM modelling requiring fewer b-values to approximate the perfusion fraction with uncertainty estimation.

Approach: Compare our linear IVIM fitting using 4 b-values and with conventional biexponential modelling using 8 b-values in 26 patients with retroperitoneal sarcoma.

Results: Strong agreement in perfusion fraction estimates between the two models.

Impact: The proposed linear model could estimate the perfusion fraction and associated uncertainty in a broader range of clinical applications where acquisition time may be constrained (body DWI for example).

Keywords: Diffusion Analysis & Visualization, Kidney

Motivation: Diffusion components and the initial values must be specified in advance in IVIM, which might not be sensible in tissues with complicated diffusion characteristics.

Goal(s): To reveal the changes of diffusion patterns of kidney in acute kidney injury (AKI).

Approach: Non-negative least squares (NNLS) method shown to derive the number of compartments from the data, rather than to impose it in the analysis of diffusion signals was employed.

Results:  The volume fraction of tubular or/and vascular decreased significantly and restricted tissue water diffusion was detected in AKI.

Impact: Our results suggest that NNLS model is potentially a valuable tool for accurate description of diffusion in kidney.

Keywords: Microstructure, Microstructure, IVIM, DTI, Renal

Motivation: Kidney microstructure has received relatively less attention compared to other organs due to EPI artifacts convolved with motion and cardiac pulsatility. Recently, mitigations of these artifacts have enabled more microstructural explorations of the kidney.

Goal(s): The study aimed at deriving estimates of microstructure and microcirculation from the perspective of concentric layers segmentations.

Approach: We scrutinized the dependence of renal DWI parameters from conventional representations (DTI, IVIM), an advanced hybrid DTI-IVIM approach and a multiple encoded FC-IVIM model on concentric layers.

Results: The most significant layer dependence was observed for pseudodiffusion parameters and structural fractional anisotropy, with weaker dependences observed for structural diffusivity parameters.

Impact: Potential extrapolations to kidney microstructure using in vivo MRI could be highly impactful in the study of renal dysfunction.

Keywords: IVIM, Perfusion, Peripheral Artery Disease

Motivation: Peripheral artery disease (PAD) is associated with diabetes, significant comorbidities and mortality-related to coexisting microvascular-disease (MVD) and injury.

Goal(s):  To better understand and phenotype PAD, we developed a novel method for intravascular incoherent motion (IVIM) that is clinically feasible and can calculate accurate IVIM-parameter maps  reflective of perfusion and tissue viability.

Approach:  Our method uses mixture prior for estimating IVIM-parameters. This prior draws statistical power from all voxels to improve the estimate of every voxel's IVIM-parameters.

Results: The proposed method calculates IVIM-parameter maps with plausible range of estimated f and D*. It improves the ability to distinguish between baseline and post-intervention perfusion changes.

Impact: To better characterize and phenotype PAD, we developed a novel method based on mixture-prior for intravascular incoherent motion (IVIM). It shows improved ability to distinguish between baseline and post-intervention images, and could facilitate the early-diagnosis of PAD and coexisting MVD.

Keywords: Diffusion Analysis & Visualization, Myocardium

Motivation: The purpose of this study was to evaluate the robustness of IVIM mapping using aMoCo-EPICS-AI-DWI-FEIR.

Goal(s): Determine how to achieve better image quality, robustness to motion, and quantitative accuracy in myocardial IVIM-DWI.

Approach: MoCo-TSE-DWI and aMoCo-EPICS-AI-DWI on a 3.0T MR clinical imager for image comparison. 

Results: aMoCo-EPICS-AI-DWI-FEIR demonstrated reduced individual and site-specific differences in the parameters obtained from IVIM-DWI imaging, compared with MoCo-TSE-DWI-FEIR.

Impact: aMoCo-EPICS-AI-DWI-FEIR might be the best method for myocardial IVIM-DWI with better image quality, motion robustness and improved quantitative accuracy.

Keywords: IVIM, Diffusion/other diffusion imaging techniques, Readout-segmented EPI; super-resolution

Motivation: Readout-segmented (rs-) EPI typically yields improved DWI image quality compared to single-shot EPI, but it is time-consuming. This presently precludes its clinical use for multiple b-value diffusion modeling like IVIM.

Goal(s): To accelerate rs-EPI image acquisition without compromising quality using convolutional neural networks (CNNs) trained on high-resolution and under-sampled low-resolution images.

Approach: Three CNNs were trained and tested on synthetic and in vivo DWI datasets. The CNNs were tasked with reconstructing high-resolution images at multiple b values, and IVIM parameter maps were estimated for comparison.

Results: The CNNs reconstructed high-resolution DWI images and IVIM parameter maps of comparable quality to the fully-sampled data.

Impact: This approach could substantially reduce the scan times of readout-segmented EPI when used for multiple b-value diffusion modeling. It therefore offers the potential for improved image quality for IVIM imaging, at scan times comparable to conventional single-shot EPI acquisition.

Keywords: Microstructure, Microstructure

Motivation: The microstructure properties obtained through advanced dMRI technology can be affected by MRI scanning parameter echo time’s changes.

Goal(s): This study aims to investigate the impact of increasing TE on microstructure properties derived from different dMRI techniques across various tissues and health conditions.

Approach: NODDI, FreeWater DTI, and IVIM were used to evaluate the TE dependence of tissue microstructure parameters from ten subjects with different health conditions.

Results: As TE increases in different brain tissues (GM, SGM, WM, and CSF), FW, FWF, and NDI increase, while FA and perfusion fraction decrease. ODI remains relatively consistent in most brain regions for various health conditions.

Impact: This research examines the influence of different echo times on microstructural properties derived from advanced dMRI techniques in various brain regions and health states. The findings could aid in the interpretation of TE-dependence microstructural estimation.

Keywords: Simulation/Validation, Quantitative Imaging

Motivation: There are large variations in perfusion-related quantifications using the IVIM model in disease diagnosis and therapeutic response evaluation. 

Goal(s): This study aims to improve the reliability of applying IVIM model in hypoxic level classification by considering the model parameter collinearity. 

Approach: We introduced a Bayesian inference method to estimate IVIM parameter probability distribution, followed by a linear discrimination analysis. This analysis produces a robust metric for distinguishing hypoxic and non-hypoxic tumor tissues. 

Results: A reliable metrics, as a linear combination of two IVIM parameters (D_t and F_p), accurately reflects tumor tissue hypoxia levels using established outcomes as training dataset and a reference. 

Impact: We addressed the challenge of uncertainty in IVIM parameter fitting arising from the strong collinearity inherent in the IVIM biexponential model. Additionally, we introduced a robust metric, H-index, for distinguishing between hypoxic and non-hypoxic tumors, referencing previous histopathologically confirmed data.

Keywords: IVIM, Diffusion/other diffusion imaging techniques

Motivation: Early symptoms of obesity-related glomerulopathy (ORG) are atypical and diagnosis depends on invasive kidney biopsy. 

Goal(s): This study assessed the potential of intravoxel incoherent motion (IVIM) to detect renal injury induced by ORG and monitor renal function after weight loss therapy.

Approach: IVIM were performed in high fat diet (HF) and standard diet (St) rats’ kidney before and after therapy.

Results: Compared with St group, significant decreases in D, D*, f in kidney of HF group were observed, and D was the first to decrease. After therapy, D, D*, f and the renal function were increased simultaneously.

Impact: Obesity with high metabolic demand leads to renal injury and obesity-related glomerulopathy (ORG). Early symptoms of ORG are not obvious, which may increase the risk of chronic kidney diseases. Non-invasively detecting ORG-induced renal injury can prevent poor prognosis.