Keywords: DWI/DTI/DKI, Diffusion/other diffusion imaging techniques, Cardiac diffusion MRI, non-Gaussian diffusion, strong gradients, Diffusion Kurtosis imaging

Motivation: Diffusion tensor modeling, which is based on Gaussian diffusion, is commonly used in cardiac diffusion MRI (dMRI). However, the tissue's microstructure (cells, membranes, etc.) restricts the water molecules and deviates the signal from Gaussian behavior.

Goal(s): This effect may be observed for higher b-values, which are presently outside the realm of routine cardiac dMRI due to the limited gradient strength of clinical scanners.

Approach: Cardiac-gated, second-order motion-compensated dMRI were performed with $$$\mathrm{b_{max}=1500\,s/mm^2}$$$ in healthy volunteers on a 3T MRI scanner with $$$\mathrm{G_{max}=300\,mT/m}$$$.

Results: We demonstrate deviation of the signal from Gaussian decay at $$$\mathrm{b>500\,s/mm^2}$$$ confirming the presence of non-Gaussian diffusion at higher b-values.

Impact: This work demonstrates feasibility of quantifying non-Gaussian diffusion in the human heart in vivo $$$\mathrm{\textbf{at realistic echo times}}$$$, using Connectom scanner ($$$\mathrm{G_{max}=300\,mT/m}$$$, 4-8 times stronger than clinical scanners). It may open the field for new biomarkers in cardiac diffusion MRI.

Keywords: Diffusion Analysis & Visualization, Quantitative Imaging, Peripheral nerves, denervation

Motivation: Quantitative muscle MRI (qMRI) metrics (T2, diffusion diameter, and fat fraction (FF)) are sensitive to tissue microstructure, and altered in denervated muscle. However, the time-dependencies of these metrics as they relate to denervated muscle have not yet been analyzed in humans.

Goal(s): Assess patterns of qMRI changes in the lower extremity in denervated muscle.

Approach: Muscles from 24 lower extremity exams (23 patients) were categorized as non-denervated or denervated (chronically- or acutely-involved) using electromyography findings. 

Results: Increased T2 in denervated muscles, and increased FF in chronically-involved muscles, and alternating patterns of diffusion diameter with time.

Impact: Quantitative MRI changes in lower extremity denervated muscles may complement peripheral nerve MRI and electromyography by providing tissue sensitive information relevant to the extent of disease at specific timepoints from initial injury.

Keywords: IVIM, Lung

Motivation: Although most solitary pulmonary lesions (SPLs) are eventually determined to be benign, early differentiation between benign and malignant lesions remains crucial for effective patient management.

Goal(s): This study aimed to  perform simultaneous chest ¹⁸F-FDG PET, APTWI, MEM-DWI, and SEM-DWI scans in patients with SPLs to compare the differences in each parameter between the benign and malignant groups. 

Approach: The AUC was used to assess diagnostic efficacy. The Logistic regression analysis was used to identify independent predictors. 

Results: SUV_max, MTV, TLG, α, and MTRasym(3.5ppm) values were lower and ADC, DDC values were higher in benign SPLs than malignant SPLs (all P < 0.01).  

Impact: Multiparametric PET/MRI based on ¹⁸ F-FDG PET, MEM-DWI, SEM-DWI, and APTWI can effectively evaluate the characteristics of SPLs. The prediction model comprising SUVmax, ADC, and MTRasym (3.5 ppm) demonstrated superior diagnostic efficacy compared with individual parameters. 

Keywords: Diffusion Acquisition, Cancer

Motivation: Decorin (DCN), so called because it decorates collagen fibers, is essential for the mechanical integrity of tissues.  It acts as a guardian of the extracellular matrix (ECM) by sequestering cytokines. 

Goal(s): Our purpose here was to determine the effects of DCN on water diffusion and the expression of immune checkpoints.  

Approach: DTI with MRI in decorin 

Results: .  We found, with diffusion tensor imaging (DTI), that DCN overexpression in tumors altered water diffusion metrics suggesting that increased DCN altered water movement through the ECM that could potentially alter cytokine movement through the ECM.   

Impact: Cancer diagnosis

Keywords: Microstructure, Diffusion/other diffusion imaging techniques, chemotherapy; breast cancer.

Motivation: Chemotherapy can cause cognitive impairment in breast cancer patients. However, the microstructural changes in white matter during chemotherapy remain unknown.

Goal(s): To explore the patterns of white matter microstructural changes during chemotherapy.

Approach: By using three diffusion models (DTI, DKI and NODDI), white matter microstructure of 72 female breast cancer patients was detected at baseline (TP1), at the completion of the first cycle of neoadjuvant chemotherapy (TP2) and at the completion of neoadjuvant chemotherapy but before surgery (TP3).

Results: Different diffusion MRI metrics reflected dynamic changes in white matter microstructure in breast cancer patients receiving neoadjuvant chemotherapy.

Impact: By combining DTI, DKI and NODDI metrics, alterations in white matter microstructure among breast cancer patients were identified from baseline to two subsequent follow-up time points during neoadjuvant chemotherapy. These findings could potentially help the early diagnosis and treatment of chemo-brain.

Keywords: Diffusion Modeling, Tumor

Motivation: Accurate grading of clear cell renal cell carcinoma (ccRCC) is essential for treatment decisions, particularly in patients with comorbidities.

Goal(s): This study aims to investigate time-dependent diffusion MRI to noninvasively characterize the microstructural properties of ccRCC and distinguish between different pathological grades.

Approach: A total of 66 patients with histologically confirmed ccRCC underwent MRI scans, and microstructural parameters were estimated using time-dependent diffusion MRI techniques.

Results:  The study revealed distinct microstructural differences between low-grade and high-grade ccRCC, showing the potential of time-dependent diffusion MRI for preoperative pathological grade characterization.

Impact: This study has the potential to reshape the landscape of preoperative ccRCC grading, promote objectivity in treatment planning.

Keywords: Diffusion Software, Data Processing, distortion correction, cervical cancer, cervix

Motivation: DWI in cervical cancer evaluation suffers from distortions, especially pronounced by intestinal gas, potentially impeding lesion detection/delineation.

Goal(s): To evaluate a combined prospective-retrospective distortion reduction approach, based on distortion correction of female pelvic DWI acquired with reduced-FOV.

Approach: Two correction methods, RPG and Topup, were applied on images from cervical cancer patients and volunteers. Distortion correction performance was evaluated by the concordance between tumour/cervix borders in images before and after correction.

Results: Topup outperformed RPG, with statistically significant but modest improvements of initially small distortions resulting from the reduced-FOV acquisition. Occasional correction failures and limitations in the proton density correction warrant alternative approaches.

Impact: Topup distortion correction, commonly used for brain studies, shows statistically significant but modest improvements in female pelvic reduced-FOV DWI. Despite indications of clinical utility, limited improvements and occasional correction failures suggest alternative approaches and prospective distortion reduction as potential strategies.

Keywords: DWI/DTI/DKI, Tumor

Motivation: Parotid gland tumors require various treatments, and it is essential to assess malignancy before surgery.

Goal(s): To evaluate the effectiveness of diffusion-weighted imaging in diagnosing salivary gland tumors.

Approach: In a retrospective study, Conventional MRI (cMRI)  and DWI data from 85 cases were analyzed.  ADC values were measured and compared among different tumor types. Salivary gland tumors are classified into three categories: pleomorphic adenoma (PA), Warthin tumor, and malignant tumors.

Results: ADC values successfully distinguish PA from other tumors, but they do not differentiate between benign and malignant tumors. Lower ADC values are associated with higher grades of malignancy. 

Impact: DWI, a non-invasive imaging technique, provides critical insights into the cellular structure of tissues, aiding in the differentiation of benign and malignant thyroid nodules. It enhances diagnostic accuracy, reduces unnecessary biopsies, and contributes to the optimization of treatment strategies.

Keywords: Diffusion Reconstruction, Liver, deep learning reconstructed Diffusion Weighted Imaging

Motivation: Deep learning (DL) reconstructions can improve image quality and/or reduce acquisition time in diffusion-weighted imaging (DWI).

Goal(s): This study aims to assess, quantitatively and qualitatively, DL-accelerated DWI in 50 patients with colorectal cancer  undergoing liver examinations.

Approach: Three DWI series are compared: a moderately-accelerated DL-DWI, a corresponding standard reconstruction and a highly-accelerated DL-DWI.

Results: The moderately-accelerated DL reconstruction method provides better image quality than a standard reconstruction. Its ADC estimates in liver, spleen and liver metastases are slightly higher than ADC estimates from the standard reconstruction.

Impact: This study evaluated DL-accelerated DWI in 50 patients undergoing liver examinations by comparing three DWI series. The moderately-accelerated acquisition with DL reconstruction provided better image quality versus the standard reconstruction; its ADC was slightly higher than the standard-based ADC.

Keywords: Microstructure, Diffusion Tensor Imaging, Cardiac MRI, Healthy, Quantitative imaging

Motivation: DT-CMR has emerged as a promising tool for in vivo use in cardiovascular disease diagnosis, but there is currently a lack of reporting on the normal values for comparison.

Goal(s): Our goal was to evaluate the possibility of performing DT-CMR with an ultra-high-performance gradient MR scanner and provide normal ranges of quantitative DT-CMR measures.

Approach: Seventy healthy subjects underwent DT-CMR, and the results were compared between men and women.   

Results: It is feasible to perform in vivo DT-CMR with a maximum gradient strength of 200 mT/m. The MD, FA and HAT for healthy subjects are (1.54±0.02) x10^-3mm²/s, 0.33±0.005 and -0.81±0.02 º/% respectively. 

Impact: Our study reports on the initial experience of conducting DT-CMR on a new investigational ultra-high-performance gradient scanner. The normal ranges of quantitative DT-CMR values are instrumental to establish baseline and distinguish the diseased from healthy in the future.

Keywords: Diffusion Analysis & Visualization, Cancer

Motivation: EOC is highly heterogeneous, meaning the average ADC value of the total tumor cannot reflect its internal components, which vary based on pathology.

Goal(s): This study sought to assess the utility of ADC values from total and functional tumor burdens to determine pathologic prognostic factors in EOC.

Approach: Using k-means clustering to divide the tumor into 2 clusters based on their ADC values, the low ADC cluster was considered to be high cellular. Furthermore, minimum, maximum and average ADC values of functional tumor were calculated.

Results: ADC values derived from functional tumor could be used to assess preoperative prognostic factors in EOC.

Impact: ADC values derived from functional tumor could be used to assess preoperative prognostic factors in EOC.

Keywords: Diffusion Modeling, Diffusion/other diffusion imaging techniques

Motivation: The pathological grade of bladder cancer is closely related to the choice of treatment and the prognosis¹. Diffusion spectrum imaging (DSI) is a newly developed model, which is helpful in distinguish benign and malignant tumors².

Goal(s): This study was to explore the quantitative parameter from DSI in differentiating pathology grade of bladder cancer.

Approach: The differences of DSI quantitative parameter between high-grade and low-grade lesions and the differentiation performance of the indices were evaluated .

Results: Quantitative parameters of DSI could effectively distinguish pathology grade of bladder cancer, and AUC ranged from 0.790 to 0.960.

Impact: The quantitative parameters obtained from Diffusion spectrum imaging are more stable and can predict the pathological grade of bladder cancer better than traditional ADC.

Keywords: Simulation/Validation, Diffusion/other diffusion imaging techniques, Fat suppression

Motivation: Fat signal suppression is essential for breast DWI as the very low diffusion coefficient of fat tends to decrease ADC values. STIR is a popular method, but signal suppression/attenuation is not specific to fat.

Goal(s): To show how ADC values obtained with STIR DWI may be biased toward tissue components with long T1s.

Approach: Results were obtained from simulations and data acquired in a dedicated breast DWI phantom made of vials with water and various concentration of PVP.

Results: ADC values obtained with STIR fat suppression may be over/under estimated depending on the T1 and ADC profile within tissues.

Impact: Fat suppression is essential for DWI. Among techniques STIR leads to low SNR and ADC misestimation depending on the tissues T1/ADC content, as STIR signal attenuation is not specific to fat. Other methods should be preferred, such as SPAIR.

Keywords: DWI/DTI/DKI, Rare disease, Immunoglobulin G4; IgG4-related kidney disease

Motivation: Clinical diagnosis and assessment of immunoglobulin G4 (IgG4)-related disease is difficult. We explored whether diffusion kurtosis imaging (DKI) can resolve this difficulty.

Goal(s): To explore the feasibility of using DKI in the assessment of IgG4-related kidney disease (IgG4-RKD)

Approach: We measured the apparent diffusion coefficient (ADC) and DKI-derived parameters of the renal parenchyma, cortex, and medulla, then analyzed correlations between quantitative image parameters and clinical indicators.

Results: DKI-derived quantitative parameters were correlated with clinical indicators and demonstrated feasibility in the assessment of IgG4-RKD.

Impact: The DKI technique can help to detect IgG4-RKD lesions. DKI-derived quantitative parameters can assess IgG4-RKD clinical activity and facilitate evaluation of IgG4-RKD prognosis.

Keywords: DWI/DTI/DKI, Cancer

Motivation: MUSE-DWI was used to better display breast cancer and histological grade prediction.

Goal(s): This study aim to compare MUSE-DWI and conventional DWI for evaluating invasive breast cancer lesions, focusing on ADC values for preoperative histological grading. 

Approach: It included 63 confirmed lesions, assessed for qualitative parameters like sharpness, artifacts, and distortion, and quantitative measures including SNR and ADC. The results demonstrated that MUSE-DWI significantly reduces artifacts and distortions, enhancing image quality. Moreover, it showed higher diagnostic efficacy in the preoperative histological grading of breast cancer. 

Results: MUSE-DWI was superior to SS-EPI-DWI in image display and histological grade prediction.

Impact: Compared with SS-EPI-DWI, MUSE-DWI can display the lesions of invasive breast cancer more intuitively, and it has higher robustness to the histological grade of invasive breast cancer.

Keywords: Simulation/Validation, Contrast Mechanisms

Motivation: Quantitative diffusion MRI is a proposed marker for assessment of liver fibrosis. However, poor reproducibility and lack of highly controlled validation of liver ADC mapping precludes its clinical utilization.

Goal(s): Introduce hydrogel liver models with pulsatile motion and varying stiffness. These enable controlled validation of ADC accuracy and reproducibility across DWI acquisition parameters and physiological-mimicking motion.

Approach: Conventional monopolar (MONO) and motion-robust M1-optimized diffusion waveforms (MODI) were used to acquire DWI of three hydrogel liver models.

Results: MODI-DWI resulted in less biased DWI and ADC maps than MONO-DWI in areas of motion. A significant inverse relationship was observed between ADC and phantom stiffness.

Impact: Quantitative diffusion MRI may enable assessment of liver fibrosis. However, the relationship between diffusion parameters and stiffness requires controlled evaluation. The proposed phantom-based approach may help validate and optimize diffusion MRI of the liver and other abdominal organs.