Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques, cancer

Motivation: The heterogeneity of T₂ in tumors and its influences on estimates of tissue microstructure using diffusion MRI are poorly understood.

Goal(s): Assessing how T₂ heterogeneity biases IMPULSED-derived metrics of tumor microstructure and evaluating the potential of estimating multi-compartmental T₂ and microstructural parameters simultaneously.

Approach: This study quantifies the impact of T₂ relaxation on IMPULSED-derived microstructural parameters using simulations and in vivo animal MRI in five tumor models, including brain, breast, prostate, melanoma, and colon cancer.

Results: TE has a negligible impact on IMPULSED-derived cell sizes, and the TE-dependence of IMPULSED-derived intracellular volume fractions can be used to estimate the compartmental T₂ values.

Impact: Findings in this study contribute to the ongoing development and refinement of practical, non-invasive MRI techniques for characterizing tissue microstructure.

Keywords: Diffusion Acquisition, Data Acquisition

Motivation: Single breath-hold simultaneous T1, T2, and ADC MRF allows comprehensive tissue characterization in a single scan. However, this technique has not been demonstrated at 0.55T.

Goal(s): Investigate the feasibility of T1, T2, and ADC MRF sequence for simultaneous T1, T2, and ADC mapping at 0.55T taking full advantage of the low-field scanner hardware.

Approach: The proposed approach uses a bSSFP radial sequence with varying IR, T2-preparation, and optimized ADC-preparation pulses over 16 heartbeats. Experiments were performed on phantoms and compared with spin-echo references.

Results: T1, T2, and ADC MRF at 0.55T was tested in a phantom, showing excellent agreement with reference values.

Impact: Simultaneous quantification of T1, T2, and ADC is feasible with the proposed MRF sequence in a single breathold, allowing for a more comprehensive tissue characterization through co-registered multiparametric imaging at 0.55T with a low-performance gradient system.

Keywords: Diffusion Acquisition, New Signal Preparation Schemes, Spherical b-tensor encoding, oscillating gradient diffusion encoding

Motivation: Lack of spectral selectivity in spherical tensor diffusion encoding impairs the specificity of the measurement.

Goal(s): The goal of this work was to design diffusion gradient waveforms yielding a spherical b-tensor with frequency-specific and isotropic spectral projections.

Approach: Gradient waveform designs derived from oscillating gradient diffusion methodology were conceived by shifting and overlapping cosine-modulated trapezoidal oscillations along the three coordinate axes to achieve orthonormality of the b-tensor.

Results: The proposed gradient waveforms achieved frequency-specific and isotropic diffusion encoding, permitting frequency-dependent diffusion measurements in the in vivo human brain in the same manner as is conventionally performed using multidirectional linear tensor diffusion encoding.

Impact: The proposed diffusion gradient waveforms for spectrally specific and isotropic spherical tensor encoding offer selective frequency measurements that can isolate the signatures of time-dependent diffusion, thereby enabling the study of diffusion dispersion in the framework of tensor-valued encoding.

Keywords: Microstructure, Rare disease

Motivation: In the healthy brain, lactate compartmentation and exchange are crucial for neurotransmission. In Huntington’s disease (HD), lactate metabolism appears to be impaired, but lactate compartmentation is unkown.

Goal(s): To assess lactate compartmentation between intracellular and extracellular spaces under pathological conditions in vivo. 

Approach: Using time-dependent DW-MRS, which may probe lactate exchange and compartmentation, we measured diffusivity and kurtosis in a cohort of zQ175 mice, a model of HD, versus control mice at 3, 6 and 12 months.

Results: Results suggest a larger extracellular fraction in zQ175 mice at 12 months, while no other microstructural changes would be measurable using DW-MRS.

Impact: DW-MRS allows probing brain lactate compartmentation, thus unravelling some crucial aspect of lactate metabolism. Results suggest that, while no microstructural alteration can be observed in the zQ175 mouse model of Huntington’s disease, impaired lactate compartmentation is detected with DW-MRS.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, Tensor-valued encoding, Spiral imaging

Motivation: Improvement of the quantification of the microstructure in the human brain with tensor-valued encoded diffusion MRI.

Goal(s): Obtain whole-brain macro- and microscopic diffusion tensor distribution metrics using spiral k-space trajectories at 7T.

Approach: Two diffusion-weighted sequences realizing the QTI approach were designed with Pulseq. They were compared to each other and to an additionally acquired DTI sequence including a ROI analysis.

Results: Accurate metric maps were obtained which are in accordance with the literature and DTI values.

Impact: Combining a multiband spiral sequence with advanced diffusion weighting enables fast whole-brain mapping of microscopic fractional anisotropy in 11-12 minutes.

Keywords: Microstructure, White Matter, Spherical Deconvolution, Spatial Regularization

Motivation: Constrained Spherical Deconvolution (CSD) is a state-of-the-art method for estimating the fiber orientation distribution function (fODF) in white matter from diffusion MRI data. However, CSD faces limitations in resolving fiber crossings with small inter-fiber angles when using low spherical harmonic order and produces noisy fODFs when using high order.

Goal(s): This study aims to improve the stability and angular resolution of fODFs from CSD.

Approach: We extend the CSD estimation framework by including a spatial regularization term that promotes fiber continuity, using a J-invariant auto-calibrated total variation denoiser.

Results: The proposed method enhances fiber crossing estimation and reduces spurious fibers.

Impact: The improved stability of the proposed method enables the utilization of higher spherical harmonic orders, with a superior ability to solve complex fiber crossings. This work has the potential to increase the accuracy of fiber-tracking algorithms and brain connectivity estimations.

Keywords: Tractography, Tractography & Fibre Modelling

Motivation: The currently available tools to describe changes in structural connectivity preclude an in-depth topography study of the brain’s white matter. We sought to quantify the degree of change in structural connectivity through the mathematical notion of directional derivatives. 

Goal(s): To define and compute the directional derivatives of tractograms.

Approach: We defined a measure of connectivity at a point in the brain, that is expressed on the brain's surface. By using numerical differentiation, we computed directional derivatives of connectivity.

Results: Our directional derivative method allows a comprehensive topographic study of the brain and highlights potential topographic patterns in structural organization.

Impact: Directional derivatives quantify connectivity changes, enabling systematic topographic study of the brain. The computational neuroimaging tool developed may aid in neurosurgical planning, precise brain stimulation, and biomarkers identification. This versatility may contribute significantly to both neuroscience research and clinical practice.

Keywords: Diffusion Acquisition, Challenges

Motivation: Probing brain microstructure with high-b-value brain diffusion imaging was mainly performed at 3T. At higher field strength, the long echo times prohibited a significant SNR boost over 3T. At 7T, a high-performance gradient allows much shorter echo times and harvesting of the field-related signal gain.

Goal(s): Determine SNR and explore feasibility of high b-value DWI.

Approach: The SNR was measured in high b-value DWI at whole-body and high-performance 7T scanners.

Results: The SNR improvement on the high-performance 7T is 2.76 ±0.12 and 1.73 ±0.05 compared to the whole-body 7T and high-performance Connectome 3T respectively, allowing even higher spatial resolution and higher b-value imaging.

Impact: The shortcoming of 7T for high b-value diffusion MRI can be overcome when leveraging a high-performance gradient system, effectively reducing scan time 7.6-fold compared to a whole-body 7T scanner. This enables the next generation of diffusion imaging.

Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques, oscillating gradient, OGSE, universality, asymptotic limit, high frequency

Motivation: Existing theory for OGSE-DWI has been developed under the assumption of an ideal cosinusoidal gradient waveform, but it is impossible to implement such a waveform in practice.

Goal(s): The purpose of this work was to investigate how the high-frequency asymptotic behaviour of the ADC is affected when an approximate cosinusoidal waveform is used for OGSE-DWI measurements.

Approach: A theoretical study was performed that derived the asymptotic behaviour of the ADC from first principles for three MPG waveforms.

Results: The difference in predicted behaviour between an approximate cosinusoidal waveform and an ideal waveform may be important when making precise measurements of the surface-to-volume ratio.

Impact: The microstructure of a complex medium can be characterised by measuring the high-frequency limit of the ADC with OGSE-DWI. However, it is important to understand how the limitations of the gradient hardware affect the interpretation of the data.

Keywords: Diffusion Reconstruction, Diffusion Tensor Imaging, 2D navigator, eddy current, phase correction, High Angular Resolution Diffusion Imaging

Motivation: The time-varying eddy current caused by diffusion gradient can induce additional phase difference between imaging and navigator echoes. These inaccurate measurements may cause residual artifacts in the subsequently reconstructed data.

Goal(s): This study aims to verify the presence of the eddy-current-induced phase differences in navigator echoes and the phase correction can improve reconstruction performance on in-vivo DTI and HARDI.

Approach: We proposed a procedure to calibrate eddy-current-induced phase difference from a phantom and considered the additional phase difference when using k-d SVD method for reconstruction.

Results: The robust reconstruction performance can be achieved by using phase-corrected navigator data to recover highly-undersampled data.

Impact: This study demonstrates that the eddy-current-induced phase differences between imaging and navigator echoes can be calibrated in advance, and then corrected during the k-d SVD reconstruction method to enable highly-accelerated multi-shot high angular resolution diffusion imaging (HARDI).

Keywords: Diffusion Reconstruction, Image Reconstruction, Diffusion

Motivation: We explore the potential of deep learning reconstruction (DLR) to overcome challenges for readout-segmented EPI (rs-EPI)  , ultimately leading to more efficient and high-quality diffusion-weighted imaging (DWI).

Goal(s): We evaluate DLR's applicability for rs-EPI, aiming to improve image quality, reduce scan durations, and expand rs-EPI's clinical utility.

Approach: We adapted the successful DLR method used in single-shot EPI (ss-EPI) to rs-EPI, conducting experiments for head and prostate diffusion imaging.

Results: Our study demonstrates that DLR can improve image quality and reduce scan times in rs-EPI DWI, promising more efficient clinical imaging and potential applications in diverse diffusion imaging scenarios.

Impact: The successful implementation of DLR in readout-segmented EPI DWI promises accelerated, high-quality diagnostics, directly benefiting clinicians and patients. Furthermore, DLR's potential for diverse diffusion imaging applications opens new research horizons, enhancing the field of MR imaging.

Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques, fat suppresstion

Motivation: One of the drawbacks of IRIS is its low SNR compared with ss-DWI. High b-value DWI improves the ability of prostate cancer detection by increased cancer conspicuity. However, such high b value images may also suffer from decreased SNR.

Goal(s): We hypothesized that using only slice selection gradient reversal (SSGR, LIPO) technique without fat suppression pre-pulse (LIpo-ONly :LION) could improve the SNR of high b-value IRIS DWI.

Approach: SNR,CR and ADC values were calculated with ROIs placed in internal obturator muscle and prostate region in peripheral zone.

Results: LION IRIS-DWI could provide high quality distortion-free high b-value prostate DWI sufficient SNR.

Impact: The present findings suggest that LION IRISs-DWI sequence demonstrated improved image distortion and blurring compared to ss-DWI, with having sufficient SNR and CR.It may help to further assess the prostate cancer pathology.

Keywords: Microstructure, Stroke

Motivation: The long scanning time of multi-shell diffusion MRI precludes many promising microstructural models to be applied in acute diseases.

Goal(s): To achieve high-resolution microstructural mapping in acute ischemic stroke.

Approach: We fine-tuned the previously proposed DeepHIBRID method with a multi-shell protocol of 5-minute constraint.

Results: 14 maps from 4 diffusion models were obtained, with whole brain coverage and 1.3mm isotropic voxel size. Preliminary results showed decent contrasts to reveal lesions, and the microstructural information indicated was in agreement with the expected pathologies for both chronic and acute cases.

Impact: High-resolution microstructural mapping based on multi-shell diffusion MRI should be now feasible for acute diseases, which is rarely possible either with compromised spatial resolution or brain coverage.

Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques

Motivation: Multi-shell diffusion sequences can support data models that help provide greater specificity to tissue microstructure when standard-of-care clinical diffusion acquisition schemes (using b=0, 1000) fail. 

Goal(s): To show that multi-shell acquisitions can produce results comparable to those of standard-of-care clinical acquisitions in addition to supporting the implementation of higher order diffusion models.  

Approach: Standard DTI metrics like FA and MD were compared in specific regions of interest in participant data collected using both a, (1) standard diffusion acquisition and (2) multishell diffusion sequence. NODDI metrics were also calculated for our multishell data.

Results: FA and MD metrics obtained from both acquisitions were comparable. 

Impact: Our study shows that a multishell diffusion sequence is suitable to meet standard clinical outcomes but is also capable of greater data acquisition (within regular scan time) which enables complex diffusion model implementations and hence, quantify tissue microstructure more precisely. 

Keywords: Diffusion Acquisition, Diffusion/other diffusion imaging techniques

Motivation: High-resolution diffusion-weighted imaging (DWI) is crucial for diagnosing neurological pathologies, but traditionally requires long scan times due to low SNR, hindering its application in clinical settings.

Goal(s): To evaluate how our new non-local principal-component-analysis (PCA)-based denoising method can help achieve high-resolution DWI at 7 Tesla within a clinically viable timeframe.

Approach: We compared our method to two existing local-PCA-based approaches by collecting whole-brain DWI at 1.2-mm isotropic resolutions from a healthy volunteer and a patient with multiple sclerosis.

Results: Our non-local PCA method provided improved denoising performances, producing quality DWI where the lesion was identifiable even with 1-minute acquisition.

Impact: Demonstrated capable of enabling high-resolution DWI under 1-minute scan at 7 Tesla, our non-local PCA method is believed to promote the utility of DWI in clinical settings while having the potential to improve many other neuroimaging applications.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Motivation: Amyotrophic Lateral Sclerosis (ALS) significantly impacts global human health, but its etiology remains unclear.

Goal(s): To develop a novel diffusion-weighted MRI technique to detect early changes in ALS-affected spinal cord in vivo.

Approach: We applied ultra-high b-values by using long diffusion time to examine the restricted diffusion in spinal white matter tracts in SOD1^G93A mice at ages of 75 and 90 days.

Results: Significant differences were found in diffusion of ventral roots between SOD1^G93A mice and control at ages of 75 and 90 days. A shift of diffusion distribution was observed in SOD1^G93A mice between 75 and 90 days.

Impact: This in vivo study potentially presents a novel view in non-invasive evaluating alterations in spinal cord tissue associated with ALS pathology, thus benefiting investigations related to drug delivery and therapeutic response monitoring of ALS.

Keywords: Diffusion Acquisition, High-Field MRI

Motivation: The SNR benefits of diffusion weighted imaging (DWI) at 7T are unclear. Previous studies comparing across field strengths involved varying scanner hardware and acquisition protocols. 

Goal(s): To characterise the spatial SNR differences of brain DWI at 3T and 7T.

Approach: Participants were scanned back-to-back on 3T and 7T scanners with well-matched hardware and acquisition protocols. SNR and DTI metrics were compared between field strengths in white and grey matter regions.

Results: SNR is higher at 7T in WM but comparable or lower in GM. DTI metrics also vary between field strengths, and fitting error is lower at 7T.

Impact: This study indicates that there is tangible SNR benefit to studying white matter using diffusion-weighted imaging at 7T in humans. However, we caution researchers when studying grey matter structures, especially in the pallidum and close to the air-tissue interfaces.

Keywords: Microstructure, Data Analysis, Ultra-high b-values, NODDI

Motivation: The benefits of using ultra-high b-values diffusion MRI (b>6000s/mm²) on characterizing and resolving brain microstructure are still unclear. 

Goal(s): To determine if the NODDI metrics computed from ultra-high b-values can help characterizing and providing more biological information related to brain microstructure.   

Approach: NODDI metrics are compared between different b-schemes, and between the corpus callosum and hippocampal subfields. 

Results: NODDI metrics computed with ultra-high b-value data can help characterize different subfields. Higher NDI and ODI differences in the corpus callosum and hippocampal subfields are observed with larger b-values.  

Impact: We show that NODDI models can work with ultra-high b-values and help characterizing and providing more biological information related to brain microstructure.

Keywords: Microstructure, Diffusion/other diffusion imaging techniques

Motivation: Understand echo time (TE) dependence of microscopic fractional anisotropy (µFA) in white matter (WM), cortical grey matter (GM), and deep GM. 

Goal(s): Measure µFA at varying TEs and observe the trends in WM, cortical GM, and deep GM. 

Approach: Healthy volunteers were scanned with dMRI at 3T using a spiral imaging sequence with linear tensor encoding and spherical tensor encoding. µFA was calculated with and without free water elimination (FWE).

Results: Linear regression fitting showed a downward trend in µFA in cortical GM and deep GM with increasing TE, both with and without FWE. 

Impact: We observed reducing µFA with increasing TE in grey matter for the first time, which was enabled by a spiral readout that greatly reduced the minimum TE (~20 ms). This TE-dependence can potentially be exploited for improved microstructural modelling.

Keywords: Diffusion Reconstruction, Pancreas

Motivation: To prove the feasibility of DWI using echo planar imaging with Compressed SENSE (EPICS-DWI).

Goal(s): Are the images and values obtained by EPICS-DWI reliable?

Approach: Taking both conventional DWI using parallel imaging (PI-DWI) and EPICS-DWI images for the same patient with untreated PDAC within the same examination and compare them.

Results: The ADC value of PDAC did not differ between PI-DWI and EPICS-DWI. EPICS-DWI can improve the qualitative overall image quality and PDAC-to-pancreas CNR compared to PI-DWI. The qualitative PDAC conspicuity was comparable between PI-DWI and EPICS-DWI.

Impact: EPICS could improve image quality of high-b value DWI images without any worries about significant changing of ADC values of PDAC.