What can we see with IVIM MRI?

Noninvasive grading of renal interstitial fibrosis and prediction of annual renal function loss in chronic kidney disease: the optimal solution of seven MR diffusion models

OBJECTIVES

To explore the optimal choice of seven diffusion models (DWI, IVIM, DKI, CTRW, FROC, SEM, and sADC) to assess renal interstitial fibrosis (IF) and annual renal function loss in chronic kidney disease (CKD).

METHODS

One hundred thirty-three CKD patients and 30 controls underwent multi-b diffusion sequence scans. Patients were divided into the training, testing, and temporal external validation sets. Least absolute shrinkage and selection operator regression and logistic regression were used to select the optimal metrics for distinguishing the mild from moderate-to-severe IF. The performances of imaging, clinical, and combined models were compared. A linear mixed-effects model calculated estimated glomerular filtration rate (eGFR) slope, and multiple linear regression assessed the association between metrics and 1-3-year eGFR slopes.

RESULTS

The training, testing, and temporal external validation sets had 75, 30, and 28 patients, respectively. The combined model incorporating cortical fIVIM, MKDKI and eGFR was superior to the clinical model combining the eGFR and 24-hour urinary protein in all sets (net reclassification index [NRI] > 0, p < 0.05). Decision curve analysis showed the combined model provided greater net clinical benefit across most thresholds. Fifty-two, 35, and 16 patients completed 1-, 2-, and 3-year follow-ups. After adjusting for covariates, cortical fIVIM correlated with the 1-year eGFR slope (β = 30.600, p = 0.001), and cortical αSEM correlated with the 2- and 3-year eGFR slopes (β = 44.859, p = 0.002; β = 95.631, p = 0.019).

CONCLUSIONS

A combined model of cortical fIVIM, MKDKI and eGFR provides a useful comprehensive tool for grading IF, with cortical fIVIM and αSEM as potential biomarkers for CKD progression.

Prediction early recurrence of hepatocellular carcinoma after hepatectomy using gadoxetic acid-enhanced MRI and IVIM

Objectives

This study aims to develop and validate a predictive nomogram for early recurrence in hepatocellular carcinoma (HCC), utilizing gadoxetic acid-enhanced MRI and intravoxel incoherent motion (IVIM) imaging to improve preoperative assessment and decision-making.

Materials and methods

From March 2018 and June 2022, a total of 245 patients with pathologically confirmed HCC, who underwent preoperative gadoxetic acid-enhanced MRI and IVIM, were retrospectively enrolled from two hospitals. These patients were divided into a training cohort (n = 160) and a validation cohort (n = 85). All patients were followed until death or the last follow-up date, with a minimum follow-up period of two years. Clinical indicators and pathologic information were compared between train cohort and validation cohort. Radiological features and diffusion parameters were compared between recurrence and non-recurrence groups using the chi-square test, Mann-Whitney U test and independent sample t test in training cohort. Univariate and multivariate analyses were performed to identify significant clinical-radiological variables associated with early recurrence in the training cohort. Based on these findings, a predictive nomogram integrating risk factors and diffusion parameters was developed. The predictive performance of the nomogram was evaluated in both the training and validation cohorts.

Results

No statistically significant difference in clinical and pathologic characteristics were observed between the training and validation cohorts. In training cohort, significant differences were identified between the recurrence and non-recurrence groups in tumor size, nodule-in-nodule architecture, mosaic architecture, non-smooth tumor margin, intratumor necrosis, satellite nodule, and peritumoral hypo-intensity in the hepatobiliary phase (HBP). The results of multivariate analysis identified tumor size (HR, 1.435; 95 % CI, 0.702-2.026; p < 0.05), mosaic architecture (HR, 0.790; 95 % CI, 0.421-1.480; p < 0.05), non-smooth tumor margin (HR, 1.775; 95 % CI, 0.941-3.273; p < 0.05), intratumor necrosis (HR, 1.414; 95 % CI, 0.807-2.476; p < 0.05), satellite nodule (HR, 0.648; 95 % CI, 0.352-1.191; p < 0.01), peritumoral hypo-intensity on HBP (HR, 2.786; 95 % CI, 1.141-6.802; p < 0.001) and D (HR, 0.658; 95 % CI,0.487-0.889; p < 0.01) were the independent risk factor for recurrence. The nomogram exhibited excellent predictive performance with C-index of 0.913 and 0.875 in the training cohort and validation cohort, respectively. Also, based on the nomogram score, the patients were classified according to risk factor and the Kaplan-Meier curve analysis also showed that the nomogram had a good predictive efficacy.

Conclusion

The nomogram, integrating radiological risk factors and diffusion parameters, offers a reliable tool for preoperative prediction of early recurrence in HCC patients.

Accelerating spin-echo EPI through combined patterned multislice excitation and simultaneous multislice acquisition

PURPOSE

To demonstrate further acceleration of spin echo MRI by combining the simultaneous multi-slice approach with the recently introduced patterned multislice excitation (PME) technique and evaluate application for rapid diffusion-weighted MRI.

THEORY AND METHODS

Implementation at 3T involved the design of RF pulses simultaneously acting on four separate slices within hardware limits on peak amplitude. This was accomplished by time-shifted sub-pulses and a dedicated switching scheme of the slice-select gradient. The new technique was evaluated on two clinical MRI systems with differing maximum gradient strength.

RESULTS

Four-fold acceleration was successfully achieved by combining PME with rate-2 SMS. Within fixed measurement time, the proposed approach allows increased averaging or more elaborate sampling of diffusion tensor space. Depending on implementation, gains in SNR per unit time were modest or small, which is attributed to out-of-slice saturation effects of the RF pulses.

CONCLUSION

Combination of PME with SMS-2 for further acceleration of diffusion imaging is feasible at 3T.

A Pilot Study on Deep Learning With Simplified Intravoxel Incoherent Motion Diffusion-Weighted MRI Parameters for Differentiating Hepatocellular Carcinoma From Other Common Liver Masses

OBJECTIVES

To develop and evaluate a deep learning technique for the differentiation of hepatocellular carcinoma (HCC) using "simplified intravoxel incoherent motion (IVIM) parameters" derived from only 3 b-value images.

MATERIALS AND METHODS

Ninety-eight retrospective magnetic resonance imaging data were collected (68 men, 30 women; mean age 59 ± 14 years), including T2-weighted imaging with fat suppression, in-phase, out-of-phase, and diffusion-weighted imaging (b = 0, 100, 800 s/mm2). Ninety percent of data were used for stratified 10-fold cross-validation. After data preprocessing, diffusion-weighted imaging images were used to compute simplified IVIM and apparent diffusion coefficient (ADC) maps. A 17-layer 3D convolutional neural network (3D-CNN) was implemented, and the input channels were modified for different strategies of input images.

RESULTS

The 3D-CNN with IVIM maps (ADC, f, and D*) demonstrated superior performance compared with other strategies, achieving an accuracy of 83.25 ± 6.24% and area under the receiver-operating characteristic curve of 92.70 ± 8.24%, significantly surpassing the baseline of 50% (P < 0.05) and outperforming other strategies in all evaluation metrics. This success underscores the effectiveness of simplified IVIM parameters in combination with a 3D-CNN architecture for enhancing HCC differentiation accuracy.

CONCLUSIONS

Simplified IVIM parameters derived from 3 b-values, when integrated with a 3D-CNN architecture, offer a robust framework for HCC differentiation.

Microstructural and microvascular features of white matter hyperintensities and their association with small vessel disease markers

White matter hyperintensities (WMH) are the most prominent imaging feature of small vessel disease (SVD). WMH and other imaging features of SVD are likely the result of ongoing insults associated with cognitive decline and cerebrovascular events. Emerging evidence suggests degradation of the neurovascular unit may underlie the pathogenesis of SVD. This prospective pilot study employed MRI in 19 subjects (68.2 ± 11.5 years of age) for diffusion-weighted imaging, applied to intravoxel incoherent motion (IVIM) modeling, to characterize microstructural and microvascular properties throughout the brain and arterial spin labeling, using multiple labeling and delay times, to measure dynamic perfusion properties including blood-brain barrier permeability (PS) in gray matter (GM). IVIM revealed WMH to have significantly greater blood volume fraction and lower pseudodiffusion and bulk diffusion than normal-appearing white matter (NAWM). IVIM parameters and PS, in canonical GM network regions, correlated with WMH volume with at least moderate effect size. Findings suggest the potential for neovascularization and evidence of restricted diffusion in WMH compared to surrounding NAWM. Regional changes in GM pertaining to the NVU scale in proportion to WMH load. Observed GM changes precede visible MR imaging abnormalities. Their early detection could elucidate SVD mechanisms of brain injury and inform future preventative measures.

Circulating and Magnetic Resonance Imaging Biomarkers of Intestinal Fibrosis in Small Bowel Crohn's Disease

BACKGROUND

We previously identified circulating and MRI biomarkers associated with the surgical management of Crohn's disease (CD). Here we tested associations between these biomarkers and ileal resection inflammation and collagen content.

METHODS

Fifty CD patients undergoing ileal resection were prospectively enrolled at 4 centers. Circulating CD64, extracellular matrix protein 1 (ECM1), GM-CSF autoantibodies (GM-CSF Ab), and fecal calprotectin were measured by ELISA. Ileal 3-dimensional magnetization transfer ratio (3D MTR), modified Look-Locker inversion recovery (MOLLI) T1 relaxation, diffusion-weighted intravoxel incoherent motion (IVIM), and the simplified magnetic resonance index of activity (sMaRIA) were measured by MRI. Ileal resection specimen acute inflammation was graded, and collagen content was measured quantitatively using second harmonic imaging microscopy. Associations between biomarkers and ileal collagen content were tested.

RESULTS

Median (interquartile range [IQR]) age was 19.5 (16-33) years. We observed an inverse relationship between ileal acute inflammation and collagen content (r = -0.39 [95% confidence interval {CI}: -0.61, -0.10], P = .008). Most patients (33 [66%]) received biologics, with no variation in collagen content with treatment exposures. In the univariate analysis, CD64, GM-CSF Ab, fecal calprotectin, and sMaRIA were positively associated with acute inflammation and negatively associated with collagen content (P < .1). The multivariable model for ileal collagen content (R2 = 0.31 [95% CI: 0.11, 0.52]) included log CD64 (β = -.27; P = .19), log ECM1 (β = .47; P = .06), log GM-CSF Ab (β = -.15; P = .01), IVIM f (β = .29, P = .10), and IVIM D* (β = 1.69, P = .13).

CONCLUSIONS

Clinically available and exploratory circulating and MRI biomarkers are associated with the degree of inflammation versus fibrosis in CD ileal resections. With further validation, these biomarkers may be used to guide medical and surgical decision-making for refractory CD.

Leveraging deep learning for improving parameter extraction from perfusion MR images: A narrative review

BACKGROUND

Perfusion magnetic resonance imaging (MRI) is a non-invasive technique essential for assessing tissue microcirculation and perfusion dynamics. Various perfusion MRI techniques like Dynamic Contrast-Enhanced (DCE), Dynamic Susceptibility Contrast (DSC), Arterial Spin Labeling (ASL), and Intravoxel Incoherent Motion (IVIM) provide critical insights into physiological and pathological processes. However, traditional methods for quantifying perfusion parameters are time-consuming, often prone to variability, and limited by noise and complex tissue dynamics. Recent advancements in artificial intelligence (AI), particularly in deep learning (DL), offer potential solutions to these challenges. DL algorithms can process large datasets efficiently, providing faster, more accurate parameter extraction with reduced subjectivity.

AIM

This paper reviews the state-of-the-art DL-based techniques applied to perfusion MRI, considering DCE, DSC, ASL and IVIM acquisitions, focusing on their advantages, challenges, and potential clinical applications.

MAIN FINDINGS

DL-driven methods promise significant improvements over conventional approaches, addressing limitations like noise, manual intervention, and inter-observer variability. Deep learning techniques such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs) are particularly valuable in handling spatial and temporal data, enhancing image quality, and facilitating precise parameter extraction.

CONCLUSIONS

These innovations could revolutionize diagnostic accuracy and treatment planning, offering a new frontier in perfusion MRI by integrating DL with traditional imaging methods. As the demand for precise, efficient imaging grows, DL's role in perfusion MRI could significantly improve clinical outcomes, making personalized treatment a more realistic goal.

SpinFlowSim: A blood flow simulation framework for histology-informed diffusion MRI microvasculature mapping in cancer

Diffusion Magnetic Resonance Imaging (dMRI) sensitises the MRI signal to spin motion. This includes Brownian diffusion, but also flow across intricate networks of capillaries. This effect, the intra-voxel incoherent motion (IVIM), enables microvasculature characterisation with dMRI, through metrics such as the vascular signal fraction fV or the vascular Apparent Diffusion Coefficient (ADC) D∗. The IVIM metrics, while sensitive to perfusion, are protocol-dependent, and their interpretation can change depending on the flow regime spins experience during the dMRI measurements (e.g., diffusive vs ballistic), which is in general not known for a given voxel. These facts hamper their practical clinical utility, and innovative vascular dMRI models are needed to enable the in vivo calculation of biologically meaningful markers of capillary flow. These could have relevant applications in cancer, as in the assessment of the response to anti-angiogenic therapies targeting tumour vessels. This paper tackles this need by introducing SpinFlowSim, an open-source simulator of dMRI signals arising from blood flow within pipe networks. SpinFlowSim, tailored for the laminar flow patterns within capillaries, enables the synthesis of highly-realistic microvascular dMRI signals, given networks reconstructed from histology. We showcase the simulator by generating synthetic signals for 15 networks, reconstructed from liver biopsies, and containing cancerous and non-cancerous tissue. Signals exhibit complex, non-mono-exponential behaviours, consistent with in vivo signal patterns, and pointing towards the co-existence of different flow regimes within the same network, as well as diffusion time dependence. We also demonstrate the potential utility of SpinFlowSim by devising a strategy for microvascular property mapping informed by the synthetic signals, and focussing on the quantification of blood velocity distribution moments and of an apparent network branching index. These were estimated in silico and in vivo, in healthy volunteers scanned at 1.5T and 3T and in 13 cancer patients, scanned at 1.5T. In conclusion, realistic flow simulations, as those enabled by SpinFlowSim, may play a key role in the development of the next-generation of dMRI methods for microvascular mapping, with immediate applications in oncology.

Diffusion Tensor Imaging in Neurofluids

In this review article, we describe the development and application of diffusion-based MR imaging methods for studying glymphatic physiology. Fluid exchange and solute transport are the 2 key components of the glymphatic system. Here we describe the use of low b-value imaging, free water fraction imaging, and diffusion time sensitization to leverage cerebral spinal fluid, as well as interstitial fluid motion in the parenchyma. We also describe multiple b-value diffusion imaging to better delineate diffusion components within the brain. Finally, we touch upon newer approaches that use advanced models of the diffusion signal, including high b-value imaging.

Predicting sentinel lymph node metastatic burden with intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging in clinical early-stage breast cancer patients

PURPOSE

The goal of this study was to investigate the value of IVIM-MRI and DCE-MRI in predicting SLN metastatic burden in clinical practice for early-stage breast cancer patients.

METHODS

The clinicopathologic and MRI data from 132 early-stage breast cancer patients were retrospectively reviewed and analyzed using logistic regression to identify risk factors for a high SLN metastatic burden. The diagnostic performance of those factors was then assessed via receiver operating characteristic (ROC) curve analysis.

RESULTS

Lymphovascular invasion (OR, 0.220; 95 % CI, 0.076-0.642; p = 0.006), Ktrans (OR, 0.971; 95 % CI, 0.944-0.998; p = 0.034) and D (OR, 1.010; 95 % CI, 1.003-1.017; p = 0.004) were independently associated with high metastatic burden. The area under the curve (AUC) for combined MRI & pathologic features (0.893; 95 % CI, 0.830-0.956; p < 0.001) and combined MRI (0.870; 95 % CI, 0.802-0.937; p < 0.001) was significantly higher than for each single MRI parameter alone (p = 0.002, 0.004), while the difference in AUCs between the combined MRI & pathologic features and combined MRI was not significant ((p = 0.154).

CONCLUSION

IVIM-MRI and DCE-MRI can be used to predict SLN metastatic burden in early-stage breast cancer patients in clinical practice.

Evaluation of infrapatellar fat pad elasticity in knee osteoarthritis using IVIM-DWI-based virtual MR elastography: repeatability and reproducibility analysis

BACKGROUND

Fibrosis of the infrapatellar fat pad (IPFP) leads to changes in its stiffness, which may impact knee osteoarthritis. However, few studies have utilized virtual MR elastography to assess the variations of the IPFP. This study aimed to evaluate the value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI)-based virtual MR elastography (vMRE) in the IPFP by assessing the test-retest repeatability, as well as intra- and inter-observer reproducibility.

METHODS

A total of 71 subjects underwent IVIM-DWI examinations, which were conducted twice with an interval of 30-60 min using an 18-channel knee coil at 3T. Shifted apparent diffusion coefficient (sADC) was calculated from two different sets of b-values (b = 200/800 sec/mm2 and 200/1500 sec/mm2) and then converted to IVIM-DWI MRI-based virtual shear modulus (μdiff_800 and μdiff_1500). Two readers independently delineated regions of interest (ROI) within the IPFP on the vMRE stiffness map to obtain the mean and standard deviation (SD) values of μdiff. Short-term test-retest repeatability, as well as intra- and inter-observer agreement were assessed using the intra-class correlation coefficient (ICC), the coefficient of variation (CoV), and Bland-Altman limits of agreement (LoA).

RESULTS

The mean and SD values of μdiff_1500, along with the mean value of μdiff_800 exhibited excellent intra- and inter-observer reproducibility agreement (ICC ≥ 0.90 and CoV ≤ 10%, P˂ 0.001). The intra- and inter-observer ICCs for the mean values of μdiff_800 were 0.917 and 0.901, respectively, while the ICCs for the SD values of μdiff_800 were 0.870 and 0.863, with CoV exceeding 10% (P˂ 0.001). The test-retest repeatability of the average value of μdiff_1500 was excellent (ICC = 0.902; CoV = 6.8%) compared to μdiff_800 (ICC = 0.877; CoV = 15.3%). Test-retest repeatability of SD for μdiff_1500 was good (ICC = 0.803; CoV = 11.5%) in comparison to SD for μdiff_800 (ICC = 0.796; CoV = 13.5%).

CONCLUSIONS

IVIM-DWI-based vMRE demonstrated significant potential as a reliable tool for measuring tissue elasticity in the IPFP, exhibiting higher repeatability for μdiff_1500 than for μdiff_800.

Differentiating rectal cancer grades using virtual magnetic resonance elastography and fractional order calculus diffusion model

BACKGROUND

To investigate the value of virtual magnetic resonance elastography (vMRE), fractional order calculus (FROC) model, and diffusion-weighted imaging (DWI) in differentiating rectal cancer grades.

METHODS

This prospective study included 74 patients with rectal cancer who underwent a pelvic MRI. The Mann-Whitney U test or independent samples t-test was employed to compare the parameters of vMRE (µMRE), the FROC model (D, β, and µ), and DWI (ADC). Logistic regression analysis and area under the receiver operating characteristic curve (AUC) were utilized separately for multiparameter co-diagnosis and to assess diagnostic performance. Pearson's correlation analysis was conducted to evaluate the relationship of different parameters.

RESULTS

Compared to the low-grade group, the high-grade group had higher µMRE and µ values and lower D, β, and ADC values (all P < 0.05). In terms of the different parameters, the D value demonstrated the highest diagnostic efficacy with an AUC of 0.852(95% CI: 0.750-0.924). In terms of the various methods, the FROC model (D + β + µ) had the highest diagnostic performance with an AUC of 0.943(95% CI: 0.864-0.984), which was significantly higher than those of DWI and vMRE (Z = 3.586, 2.430, and 2.081, all P < 0.05). µMRE showed moderately negative correlations with ADC, D, and β (r = - 0.553, - 0.683, and - 0.530, respectively, all P < 0.05) and a moderately positive correlation with µ (r = 0.443, P < 0.05).

CONCLUSION

FROC, vMRE, and DWI can be utilized for assessing rectal cancer grades, with FROC offering comparatively better diagnostic performance.

The self-supervised fitting method based on similar neighborhood information of voxels for intravoxel incoherent motion diffusion-weighted MRI

BACKGROUND

The intravoxel incoherent motion (IVIM) parameter estimation is affected by noise, while existing CNN-based fitting methods utilize neighborhood spatial features around voxels to obtain more robust parameters. However, due to the heterogeneity of tissue, neighborhood features with low similarity can lead to excessively smooth parameter maps and even loss of tissue details.

PURPOSE

To propose a novel neural network fitting approach, IVIM-CNNsimilar, which utilizes similar neighborhood information of voxels to assist in the estimation of IVIM parameters in diffusion-weighted imaging (DWI).

METHODS

The proposed fitting model is based on convolutional neural network (CNN), which first identifies the similar neighborhoods of voxels through cluster analysis and then uses CNN to learn the spatial features of similar neighborhoods to reduce the impact of noise on the parameter estimation of the voxel. To evaluate the performance of the proposed method, comparisons were conducted with the least squares (LSQ), Bayesian, PI-DNN, and IVIM-CNNunet algorithms on both simulated and in vivo brains, including 23 healthy brains and three brain tumors, in terms of root mean square error (RMSE) of IVIM parameters and the parameter contrast ratio between the tumor and normal regions.

RESULTS

The CNN-based methods, such as IVIM-CNNsimilar and IVIM-CNNunet, yield smoother parameter maps compared to voxel-based methods like nonlinear least squares, segmented nonlinear least squares, Bayesian, and PI-DNN. Additionally, the IVIM-CNNsimilar retains more local tissue details while maintaining smoothness of parameter maps compared to the IVIM-CNNunet. In simulated experiments, IVIM-CNNsimilar outperforms IVIM-CNNunet in terms of parameter estimation accuracy (SNR = 30; RMSE [ D $D$ ] = 0.0168 vs. 0.0253; RMSE ( F $F$ ) = 0.0001 vs. 0.0002; RMSE [D ∗ $D^{*}$ ] = 0.0266 vs. 0.0416). In addition, compared with other methods, the proposed IVIM-CNNsimilar is more robust to noise, which is reflected in the lower RMSE of each parameter at different SNRs. For in vivo brains, compared to other methods, IVIM-CNNsimilar achieved the highest PCR for most parameters when comparing the normal and tumor regions.

CONCLUSIONS

The IVIM-CNNsimilar method uses similar neighborhood information to assist IVIM parameter fitting by reducing the impact of noise on voxel parameter estimation, thereby improving the accuracy of parameter estimation and increasing the potential for IVIM clinical application.

Imaging brain fluid dynamics and waste clearance involving perivascular spaces in cerebral small vessel disease

Cerebral small vessel disease (SVD) is recognized as a major vascular contributor to cognitive decline, ultimately leading to dementia and stroke. While the pathogenesis of SVD remains unclear, emerging evidence suggests that waste clearance involving perivascular space (PVS) - also known as the glymphatic system - dysfunction may play a role. Among SVD radiological markers, the increased presence of dilated PVS is recognized as a marker of waste clearance disruption. Recently developed neuroimaging methods have been proposed as indirect measures of brain fluid dynamics, but they currently lack formal validation. Here, we provide a comprehensive overview of the latest neuroimaging advancements for assessing brain fluid dynamics, including waste clearance involving PVS function in SVD. We review the mechanisms by which clearance dysfunction might contribute to SVD. Finally, we argue that robust, multimodal, and longitudinal studies are essential for understanding the waste clearance (involving PVS) function and for establishing a diagnostic gold standard. HIGHLIGHTS: The majority of PVS are not visible on MRI, making it crucial to understand how and why they become dilated. The origin of waste clearance involving PVS disruption in SVD may be multifactorial. The BBB and waste clearance (involving PVS) dysfunction likely affect each other, forming a vicious cycle, promoting further amyloid beta accumulation. Yet their direct association in humans over time remains to be studied. Comparative studies can aid in the standardization of methods for assessing waste clearance involving PVS function.

Preoperative risk stratification of early-stage endometrial cancer assessed by multimodal magnetic resonance functional imaging

Endometrial cancer is a common disease in women. Stratifying the risk of early-stage endometrial cancer can aid in personalized treatment for patients. Risk stratification is primarily based on tumor grade, histological type, lymph node metastasis, and depth of myometrial invasion. Multimodal magnetic resonance functional imaging (including DCE-MRI, DWI, IVIM, DTI, DKI) has significant value in assessing the extent of myometrial and cervical infiltration, extrauterine involvement range, determining lymph node metastasis and tumor size. This article provides a brief overview of these techniques.

Incorporating spatial information in deep learning parameter estimation with application to the intravoxel incoherent motion model in diffusion-weighted MRI

In medical image analysis, the utilization of biophysical models for signal analysis offers valuable insights into the underlying tissue types and microstructural processes. In diffusion-weighted magnetic resonance imaging (DWI), a major challenge lies in accurately estimating model parameters from the acquired data due to the inherently low signal-to-noise ratio (SNR) of the signal measurements and the complexity of solving the ill-posed inverse problem. Conventional model fitting approaches treat individual voxels as independent. However, the tissue microenvironment is typically homogeneous in a local environment, where neighboring voxels may contain correlated information. To harness the potential benefits of exploiting correlations among signals in adjacent voxels, this study introduces a novel approach to deep learning parameter estimation that effectively incorporates relevant spatial information. This is achieved by training neural networks on patches of synthetic data encompassing plausible combinations of direct correlations between neighboring voxels. We evaluated the approach on the intravoxel incoherent motion (IVIM) model in DWI. We explored the potential of several deep learning architectures to incorporate spatial information using self-supervised and supervised learning. We assessed performance quantitatively using novel fractal-noise-based synthetic data, which provide ground truths possessing spatial correlations. Additionally, we present results of the approach applied to in vivo DWI data consisting of twelve repetitions from a healthy volunteer. We demonstrate that supervised training on larger patch sizes using attention models leads to substantial performance improvements over both conventional voxelwise model fitting and convolution-based approaches.

The fuzzy MAD stroke conjecture, using Fuzzy C Means to classify multimodal apparent diffusion for ischemic stroke lesion stratification

BACKGROUND

In conjunction with an epidemiologically determined treatment window, current radiological acute ischemic stroke practice discerns two lesion (stage) types: core (dead tissue, identified by diffusion-weighted imaging (DWI)) and penumbra (tissue region receiving just enough blood flow to be potentially salvageable, identified by the perfusion diffusion mismatch). However, advancements in preclinical and clinical studies have indicated that this approach may be too rigid, warranting a more fine-grained patient-tailored approach. This study aimed to demonstrate the ability to noninvasively provide insights into the current in vivo stroke lesion cascade.

METHODS

To elucidate a finer-grained depiction of the acute focal ischemic stroke cascade in vivo, we retrospectively applied our multimodal apparent diffusion (MAD) method to multi-b-value DWI, up to a b-value of 10,000 s/mm2 in 34 patients with acute focal ischemic stroke. Fuzzy C Means was used to cluster the MAD parameters.

RESULTS

We discerned 18 clusters consistent with normal appearing tissue (NAT) types and 14 potential ischemic lesion (stage) types, providing insights into the variability and aggressiveness of lesion progression and current anomalous stroke-related imaging features. Of the 529 ischemic stroke lesion instances previously identified by two radiologists, 493 (92 %) were autonomously identified; 460 (87 %) were identified as efficaciously or better than the radiologists.

CONCLUSIONS

The data analyzed included a small number of clinical patients without follow-up or contemporaneous histology; therefor, the findings and theorizing should be treated as conjecture. Nevertheless, each identified NAT and lesion type is consistent with the known underpinnings of physiological tissues and pathological ischemic stroke lesion (stage) types. Several findings should be considered in current clinical imaging: WM fluid accumulation, BBB compromise conundrum, b1000 identified core may not be dead tissue, and a practical reason for DWI (pseudo) normalization.

The effects of maternal flow on placental diffusion-weighted MRI and intravoxel incoherent motion parameters

PURPOSE

To investigate and explain observed features of the placental DWI signal in healthy and compromised pregnancies using a mathematical model of maternal blood flow.

METHODS

Thirteen healthy and nine compromised third trimester pregnancies underwent pulse gradient spin echo DWI MRI, with the results compared to MRI data simulated from a 2D mathematical model of maternal blood flow through the placenta. Both sets of data were fitted to an intravoxel incoherent motion (IVIM) model, and a rebound model (defined within text), which described voxels that did not decay monotonically. Both the in vivo and simulated placentas were split into regions of interest (ROIs) to analyze how the signal varies and how IVIM and rebounding parameters change across the placental width.

RESULTS

There was good agreement between the in vivo MRI data, and the data simulated from the mathematical model. Both sets of data included voxels showing a rebounding signal and voxels showing fast signal decay focused near the maternal side of the placenta. In vivo we found higherf IVIM $$ {f}_{IVIM} $$ in the uterine wall and near the maternal side of the placenta, with the slow diffusion coefficientD $$ D $$ reduced in all ROIs in compromised pregnancy.

CONCLUSION

A simulation based entirely on maternal blood explains key features observed in placental DWI, indicating the importance of maternal blood flow in interpreting placental MRI data, and providing potential new metrics for understanding changes in compromised placentas.

Intravoxel incoherent motion imaging and dynamic susceptibility contrast perfusion MRI in differentiation between recurrent intracranial tumor and treatment-induced changes

PURPOSE

To compare intravoxel incoherent motion (IVIM) imaging to dynamic susceptibility-weighted contrast (DSC) perfusion MRI in differentiating tumor recurrence from treatment-induced changes.

METHODS

Our prospective study included patients previously treated with radiotherapy for intracranial tumors who later developed a new or increasing contrast-enhancing lesion. The final diagnosis was based on neuropathology or 6-month follow-up. MR examinations were performed for calculation of the perfusion fraction (f) using the IVIM technique and relative blood volume (rCBV) using DSC perfusion. Measurements of f and rCBV were made by two independent readers in hotspots when possible, but otherwise in the whole enhancing region. Measures of rCBV were normalized to the contralateral region. Receiver operating characteristics (ROC) analysis was performed.

RESULTS

Sixty patients (35 men, median age 49, range 20-77) were evaluated. Forty-four patients had tumor recurrence and 16 had treatment-induced changes. Mean f was 0.090 for tumors and 0.058 for treatment-induced changes (p = 0.002). Mean rCBV was 3.52 and 1.79, respectively (p = 0.002). The area under the curve (AUC) in the ROC analysis was 0.72 for f and 0.77 for rCBV. Cutoff values of 0.073 for f and 2.26 for rCBV yielded equal values for sensitivity (73%), specificity (75%), and accuracy (73%). The 90th percentile value of rCBV was 4.77 for tumors and 2.53 for treatment-induced changes (p = 0.0004) and yielded the highest AUC (0.79) and a sensitivity/specificity/accuracy of 80%/75%/78% at cutoff value 3.25.

CONCLUSION

The accuracy of the IVIM parameter f is similar to that of rCBV in differentiating tumor recurrence from treatment-induced changes.

Grading of clear cell renal cell carcinoma using diffusion MRI with a multimodal apparent diffusion model

Objective

To assess the feasibility of utilizing parameters derived from a multimodal apparent diffusion (MAD) model to distinguish between low- and high-grade clear cell renal cell carcinoma (ccRCC).

Method

Diffusion-weighted imaging (DWI) scans with 12 b-values (0 - 3000 s/mm²) were conducted on 54 patients diagnosed with ccRCC (30 low-grade and 24 high-grade). The MAD model parameters, including diffusion coefficients (Dr, Dh, Dui, Df) representing restricted diffusion, hindered diffusion, unimpeded diffusion, and flow, respectively, were computed. Proportions corresponding to these diffusion types (fr, fh, fui, ff) and the heterogeneous nature of hindered diffusion (αh) were also obtained. Parameters were compared between low- and high-grade groups. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of these parameters, compared with the apparent diffusion coefficient (ADC) from a mono-exponential model.

Result

Significant differences between low- and high-grade ccRCC were observed in Dh (low-grade: 1.360 ± 0.11 μm2/ms; high-grade group, 1.254 ± 0.13 μm2/ms; P = 0.0327), fr (low-grade: 0.06 ± 0.005; high-grade: 0.08 ± 0.009; P = 0.0233), and αh (low-grade: 0.872 ± 0.22; high-grade: 0.896 ± 0.39; P = 0.0294). Additionally, the ADC values (low-grade: 0.924 ± 0.08 μm2/ms; high-grade group, 0.854 ± 0.04 μm2/ms; P = 0.0323) showed statistical significance. The combination of Dh, fr, and αh provided the highest diagnostic accuracy of 0.667, with a sensitivity of 0.750, specificity of 0.734, and area under the curve of 0.796, outperforming individual parameters and ADC.

Conclusion

The MAD diffusion model shows promise as a non-invasive imaging tool for distinguishing between low- and high-grade ccRCC, which may aid in preoperative planning and personalized treatment strategies.

Apparent Diffusion Coefficient fMRI shines light on white matter resting-state connectivity compared to BOLD

Resting-state functional magnetic resonance imaging (fMRI) is used to derive functional connectivity (FC) between brain regions. Typically, blood oxygen level-dependent (BOLD) contrast is used. However, BOLD's reliance on neurovascular coupling poses challenges in reflecting brain activity accurately, leading to reduced sensitivity in white matter (WM). WM BOLD signals have long been considered physiological noise, although recent evidence shows that both stimulus-evoked and resting-state WM BOLD signals resemble those in gray matter (GM), albeit smaller in amplitude. We introduce apparent diffusion coefficient fMRI (ADC-fMRI) as a promising functional contrast for GM and WM FC, capturing activity-driven neuromorphological fluctuations. Our study compares BOLD-fMRI and ADC-fMRI FC in GM and WM, showing that ADC-fMRI mirrors BOLD-fMRI connectivity in GM, while capturing more robust FC in WM. ADC-fMRI displays higher average clustering and average node strength in WM, and higher inter-subject similarity, compared to BOLD. Taken together, this suggests that ADC-fMRI is a reliable tool for exploring FC that incorporates gray and white matter nodes in a novel way.

High b-Value and Ultra-High b-Value Diffusion Weighted MRI in Stroke

PURPOSE

To explore the application value of high-b-value and ultra-high b-value DWI in noninvasive evaluation of ischemic infarctions.

STUDY TYPE

Prospective.

SUBJECTS

Sixty-four patients with clinically diagnosed ischemic lesions based on symptoms and DWI.

FIELD STRENGTH/SEQUENCE

3.0 T/T2-weighted fast spin-echo, fluid-attenuated inversion recovery, pre-contrast T1-weighted magnetization prepared rapid gradient echo sequence, multi-b-value trace DWI and q-space sampling sequences.

ASSESSMENT

Lesions were segmented on standard b-value DWI (SB-DWI, 1000 s/mm2), high b-value DWI (HB-DWI, 4000 s/mm2) and ultra-high b-value DWI (UB-DWI, 10,000 s/mm2), and cumulative segmented areas were the final abnormality volumes. Normal white matter (WM) areas were obtained after binarization of segmented brain. In 47 patients, fractional anisotropy (FA) and apparent diffusion coefficients (ADCs) at b values of 1000, 4000, and 10,000 s/mm2 were extracted from symmetrical WM masks and lesion masks of contralateral WM (CWM) and lesion-side WM (LWM).

STATISTICAL TESTS

Wilcoxon matched-pairs signed-rank test and Pearson correlation analysis. Two-tailed P-values <0.05 were considered statistically significant.

RESULTS

Various signals of HB-/UB-DWI (hypo-, iso- or hyper-intensity) were observed in strokes compared with SB-DWI, and some areas with iso-intensity of SB-DWI manifested with hyper-intensity on HB-/UB-DWI. Abnormality volumes from SB-DWI were significantly smaller than those from HB-DWI and UB-DWI (10.32 ± 16.45 cm3, vs. 12.25 ± 19.71 cm3 and 11.83 ± 19.41 cm3), while no significant difference exist in volume between HB-DWI and UB-DWI (P = 0.32). In CWM, FA significantly correlated with ADC4000 and ADC10,000 (maximum r = -0.51 and -0.64), but did not significantly correlate with ADC1000 (maximum r = -0.20, P = 0.17). ADC1000 or ADC4000 of LWM not significant correlated with FA of CWM (maximum r = -0.28, P = 0.06), while ADC10,000 of LWM significantly correlated with FA of CWM (maximum r = -0.46).

DATA CONCLUSION

HB- and UB-DWI have potential to be supplementary tools for the noninvasive evaluation of stroke lesions in clinics.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Diffusion-derived intravoxel-incoherent motion anisotropy relates to CSF and blood flow

This study investigates the feasibility of multi-b-value, multi-directional diffusion MRI for assessing the anisotropy of the cerebral pseudo-diffusion (D*)-tensor. We examine D*-tensor's potential to (1) reflect CSF and blood flow, and (2) detect microvascular architectural alterations in cerebral small vessel disease (cSVD) and aging.

METHODS

Multi-b-value diffusion MRI was acquired in 32 gradient directions for 11 healthy volunteers, and in six directions for 29 patients with cSVD and 14 controls at 3 T. A physics-informed neural network was used to estimate intravoxel incoherent motion (IVIM)-DTI model parameters, including the parenchymal slow diffusion (D-)tensor and the pseudo-diffusion (D*)-tensor, from which the fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were derived. Comparisons of D*-tensor metrics were made between lateral, third, and fourth ventricles and between the middle cerebral arteries and superior sagittal sinus. Group differences in D*-tensor metrics in normal-appearing white matter were analyzed using multivariable linear regression, correcting for age and sex.

RESULTS

D*-anisotropy aligned well with CSF flow and arterial blood flow. FA(D*), MD(D*), AD(D*), and RD(D*) were highest in the third, moderate in the fourth, and lowest in the lateral ventricles. The arteries showed higher MD(D*), AD(D*), and RD(D*) than the sagittal sinus. Higher FA(D*) in the normal-appearing white matter was related to cSVD diagnosis and older age, suggesting microvascular architecture alterations.

CONCLUSION

Multi-b-value, multi-directional diffusion analysis using the IVIM-DTI model enables assessment of the cerebral microstructure, fluid flow, and microvascular architecture, providing information on neurodegeneration, glymphatic waste clearance, and the vasculature in one measurement.

Retrospective BReast Intravoxel Incoherent Motion Multisite (BRIMM) multisoftware study

Introduction

The intravoxel incoherent motion (IVIM) model of diffusion weighted imaging (DWI) provides imaging biomarkers for breast tumor characterization. It has been extensively applied for both diagnostic and prognostic goals in breast cancer, with increasing evidence supporting its clinical relevance. However, variable performance exists in literature owing to the heterogeneity in datasets and quantification methods.

Methods

This work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1st order radiomics of IVIM parameters perfusion fraction (fp ), pseudo-diffusion (Dp ) and tissue diffusivity (Dt ). Pearson correlation (r) coefficients between software pairs were computed while logistic regression model was implemented to test malignancy detection and assess robustness of the IVIM metrics.

Results

Dt and fp maps generated from different software showed consistency across platforms while Dp maps were variable. The average correlation between the three software pairs at three different sites for 1st order radiomics of IVIM parameters were Dtmin/Dtmax/Dtmean/Dtvariance/Dtskew/Dtkurt: 0.791/0.891/0.98/0.815/0.697/0.584; fpmax/fpmean/fpvariance/fpskew/fpkurt: 0.615/0.871/0.679/0.541/0.433; Dpmax/Dpmean/Dpvariance/Dpskew/Dpkurt: 0.616/0.56/0.587/0.454/0.51. Correlation between least-squares algorithms were the highest. Dtmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. Dt metrics were highly diagnostic as well as consistent along with fp metrics.

Discussion

Multiple 1st order radiomic features of Dt and fp obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.

Dynamic diffusion-weighted imaging of intracranial cardiac impulse propagation along arteries to arterioles in the aging brain

Intracranial cardiac impulse propagation along penetrating arterioles is vital for both nutrient supply via blood circulation and waste clearance via CSF circulation. However, current neuroimaging methods are limited to simultaneously detecting impulse propagation at pial arteries, arterioles, and between them. We hypothesized that this propagation could be detected via paravascular CSF dynamics and that it may change with aging. Using dynamic diffusion-weighted imaging (dynDWI), we detected oscillatory CSF motion synchronized with the finger photoplethysmography in the subarachnoid space (SAS) and cerebral cortex, with a delay revealing an impulse propagation pathway from the SAS to the cortex, averaging 84 milliseconds. Data from 70 subjects aged 18 to 85 years showed a bimodal age-related change in the SAS-Cortex travel time: it initially increases with age, peaks around 45 years, then decreases. Computational biomechanical modeling of the cardiovascular system was performed and replicated this 84-millisecond delay. Sensitivity analysis suggests that age-related variations in travel time are primarily driven by changes in arteriolar compliance. These findings support the use of dynDWI for measuring intracranial impulse propagation and highlight its potential in assessing related vascular and waste clearance functions.

Exercise MR of Skeletal Muscles, the Heart, and the Brain

Magnetic resonance (MR) imaging (MRI) is routinely used to evaluate organ morphology and pathology in the human body at rest or in combination with pharmacological stress as an exercise surrogate. With MR during actual physical exercise, we can assess functional characteristics of tissues and organs under real-life stress conditions. This is particularly relevant in patients with limited exercise capacity or exercise intolerance, and where complaints typically present only during physical activity, such as in neuromuscular disorders, inherited metabolic diseases, and heart failure. This review describes practical and physiological aspects of exercise MR of skeletal muscles, the heart, and the brain. The acute effects of physical exercise on these organs are addressed in the light of various dynamic quantitative MR readouts, including phosphorus-31 MR spectroscopy (31P-MRS) of tissue energy metabolism, phase-contrast MRI of blood flow and muscle contraction, real-time cine MRI of cardiac performance, and arterial spin labeling MRI of muscle and brain perfusion. Exercise MR will help advancing our understanding of underlying mechanisms that contribute to exercise intolerance, which often proceed structural and anatomical changes in disease. Its potential to detect disease-driven alterations in organ function, perfusion, and metabolism under physiological stress renders exercise MR stress testing a powerful noninvasive imaging modality to aid in disease diagnosis and risk stratification. Although not yet integrated in most clinical workflows, and while some applications still require thorough validation, exercise MR has established itself as a comprehensive and versatile modality for characterizing physiology in health and disease in a noninvasive and quantitative way. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Instrumental assessment of INPH: structural and functional neuroimaging

INTRODUCTION

For the accurate diagnosis of idiopathic normal pressure hydrocephalus (iNPH) an accurate neuroimaging is essential. Disproportionately enlarged subarachnoid-space hydrocephalus (DESH) is a key neuroradiological feature and novel imaging techniques, including voxel-based morphometry and AI-assisted analyses are emerging as powerful tools to investigate iNPH pathophysiology. Converging evidence also suggests a role for dopaminergic dysfunction in iNPH. Molecular imaging of the dopamine transporter (DaT) enables the investigation of dopaminergic function and holds potential for advancing differential diagnosis and guiding treatment decisions in iNPH.

EVIDENCE ACQUISITION

A comprehensive literature search was conducted using MeSH key words. Studies assessing the role of structural and functional neuroimaging in iNPH. The evidence was summarized, and key results were provided.

EVIDENCE SYNTHESIS

DESH is crucial for accurate diagnosis and treatment planning. Advanced structural and functional imaging techniques are expanding our understanding of iNPH pathophysiology. Only few functional imaging studies have directly examined the dopaminergic dysfunction in iNPH and severe methodological limitations exist in both clinical classification and imaging processing. Nonetheless, evidence supports the presence of dopaminergic dysfunction in iNPH, which may be linked to specific clinical symptoms, aid in differential diagnosis, and be reversed with shunt surgery treatment.

CONCLUSIONS

This review covers the structural and functional imaging data in iNPH, providing a comprehensive outlook of the current knowledge, highlighting the limitations and possible future perspectives.

Meta-Analysis of MRI in Predicting Early Response to Radiotherapy and Chemotherapy in Esophageal Cancer

RATIONALE AND OBJECTIVES

At present, the application of magnetic resonance imaging (MRI) in the prediction of response to neoadjuvant therapy and concurrent chemoradiotherapy for the treatment of esophageal cancer still needs to be further explored, and its early differential value remains controversial, thus we carried out this systematic review with a meta-analysis. In the application, different MRI sequences and corresponding parameters are used for the differential diagnosis of the response to neoadjuvant therapy and concurrent chemoradiotherapy.

METHODS

All relevant studies evaluated the efficacy and response to MRI in neoadjuvant therapy or concurrent chemoradiotherapy for esophageal cancer on Pubmed, Embase, Cohrane Library, and Web of Science databases published before October 10, 2023 (inclusive) were systematically searched. A revised tool was used to assess the quality of diagnostic accuracy studies (QUADAS-2) to assess the risk of bias in the included original studies. A subgroup analysis of MRI sequences diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and their corresponding different parameters, as well as the acquisition timepoints (before and after treatment) for different parameters, was performed during the meta-analysis. The bivariate mixed-effects model was used for meta-analysis.

RESULTS

21 studies were finally included, involving 1128 patients with esophageal cancer. The sensitivity, specificity, and area under receiver operating characteristic curve (ROC curve) of DWI sequence for identifying response to concurrent chemoradiotherapy were 0.82 (95% CI: 0.74-0.87), 0.81 (95% CI: 0.72-0.87) and 0.88 (95% CI: 0.56-0.98), respectively. The sensitivity, specificity, and area under ROC curve of DCE sequence for identifying response to concurrent chemoradiotherapy were 0.78 (95% CI: 0.70-0.84), 0.65 (95% CI: 0.59-0.70) and 0.73 (95% CI: 0.50-0.88), respectively. In patients with esophageal cancer, the sensitivity, specificity, and area under the ROC curve of DWI sequences for identifying response to neoadjuvant therapy were 0.80 (95% CI: 0.69 - 0.88), 0.81 (95% CI: 0.69 - 0.89), and 0.88 (95% CI: 0.34 - 0.99), respectively; the sensitivity, specificity, and area under the ROC curve of DCE sequences for identifying response to neoadjuvant therapy were 0.84 (95% CI: 0.76 - 0.90), 0.61 (95% CI: 0.53 - 0.68), and 0.70 (95% CI: 0.27 - 0.94), respectively.

CONCLUSIONS

Based on the available evidence, MRI had a very good value in the early identification of response to neoadjuvant therapy and concurrent chemoradiotherapy for esophageal cancer, especially DWI. Apparent diffusion coefficient (ADC) value changes before and after treatment could be used as predictors of pathological response. Also, ADC value changes before and after treatment could be used as a tool to guide clinical decision-making.

Imaging characteristics of brain microstructure and cerebral perfusion in Crohn's disease patients with anxiety: A prospective comparative study

BACKGROUND

Anxiety is a common comorbidity in patients with Crohn's disease (CD). Data on the imaging characteristics of brain microstructure and cerebral perfusion in CD with anxiety are limited.

AIM

To compare the imaging characteristics of brain microstructure and cerebral perfusion among CD patients with or without anxiety and healthy individuals.

METHODS

This prospective comparative study enrolled consecutive patients with active CD and healthy individuals who visited the study hospital between January 2022 and January 2023. Anxiety was measured using the Hospital Anxiety and Depression Scale-Anxiety. The imaging characteristics of brain microstructure and cerebral perfusion were measured by diffusion kurtosis imaging and intravoxel incoherent motion.

RESULTS

A total of 57 participants were enrolled. Among the patients with active CD, 16 had anxiety. Compared with healthy individuals, patients with active CD demonstrated significantly lower radial kurtosis values in the right cerebellar region 6, lower axial kurtosis (AK) values in the right insula, left superior temporal gyrus, and right thalamus, and higher slow and fast apparent diffusion coefficients (ADCslow and ADCfast) in the bilateral frontal lobe, bilateral temporal lobe, and bilateral insular lobe (all P < 0.05). Compared with patients with CD without anxiety, patients with CD and anxiety exhibited significantly higher ADCslow values in the left insular lobe and lower AK values in the right insula and right anterior cuneus (all P < 0.05).

CONCLUSION

There are variations in brain microstructure and perfusion among CD patients with/without anxiety and healthy individuals, suggesting potential use in assessing anxiety-related changes in active CD.

Assessing blood flow in uterine fibroids using intravoxel incoherent motion imaging compared with dynamic contrast-enhanced MRI

To assess the utility of IVIM parameters in evaluating uterine fibroid blood flow compared to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived blood flow. Sixteen premenopausal women with uterine fibroids were enrolled in this prospective study. Pelvic MRI scans were obtained for each subject, both with and without continuous intravenous infusion of oxytocin, known to decrease significantly uterine fibroid blood flow, to assess the changes in blood flow of uterine fibroids. IVIM and DCE analyses were conducted using separate dedicated software. The bi-exponential IVIM model was used to estimate perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D). DCE blood flow values were derived via T1 perfusion deconvolution arithmetic, utilizing a first pass of an AIF curve. The correlation between the parameters were analyzed by Spearman's rank correlation analysis due to small sample size. Means of the parameters were compared with a nonparametric Wilcoxon sign rank method for each pair. Statistically significant positive correlations were found between perfusion fraction values and DCE blood flow values with oxytocin (Spearson's ρ = 0.78, p = 0.0004), and between fD* values and DCE blood flow values with oxytocin (Spearson's ρ = 0.64, p = 0.0071). Significant differences in blood flow were detected across most IVIM parameters: f, D*, and fD* (p < 0.001, p = 0.0027, and p = 0.0002, respectively) when comparing the values without oxytocin and with oxytocin. IVIM imaging shows promise for assessing blood flow in uterine fibroids.

Assessment of hypoxia status in a rat chronic liver disease model using IVIM and T1 mapping

Objectives

This study was aimed to assess the diagnostic performance of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and T1 mapping in detecting hypoxia status of chronic liver disease using a carbon tetrachloride (CCl4)-induced rat model.

Materials and methods

The hypoxia group of chronic liver disease consisted of eight rats induced by injection of CCl4 and the control group consisted of nine rats injected with pure olive oil. All 17 rats underwent MRI examination at week 13 after injection, using T1 mapping and IVIM. Liver specimens were subjected to immunohistochemical staining for the exogenous hypoxia marker pimonidazole and the endogenous hypoxia marker HIF-1α and scored semi-quantitatively. Differences in MRI multiparameters, pimonidazole H-scores, and HIF-1α were analyzed between the control and hypoxia groups. Correlations between MRI multiparameters and H-score, and MRI multiparameters and HIF-1α, were analyzed, and the diagnostic performance of multiparameter MRI was evaluated by receiver operating characteristic (ROC) curve analysis.

Results

There were significant differences between the control group and the hypoxia group in D* values (p = 0.01) and f values (p = 0.025) of IVIM parameters, T1 mapping (p = 0.003), HIF-1α (p < 0.001) and pimonidazole scores (p = 0.004). D* (r = 0.508, p = 0.037) and T1 mapping (r = 0.489, p = 0.046) values positively correlated with pimonidazole scores. D* (r = 0.556, p = 0.020) and T1 mapping (r = 0.505, p = 0.039) showed a positive correlation with HIF-1α. The optimal cut-off value of T1 mapping was 941.527, and the sensitivity, specificity, and AUC were 87.5, 77.8, and 0.889 (95% confidence interval [CI]: 0.734-1), respectively.

Conclusion

IVIM and T1 Mapping are promising methods for non-invasive detection of hypoxia status in chronic liver diseases.

Nyquist ghost elimination for diffusion MRI by dual-polarity readout at low b-values

Dual-polarity readout is a simple and robust way to mitigate Nyquist ghosting in diffusion-weighted echo-planar imaging but imposes doubled scan time. We here propose how dual-polarity readout can be implemented with little or no increase in scan time by exploiting an observed b-value dependence and signal averaging. The b-value dependence was confirmed in healthy volunteers with distinct ghosting at low b-values but of negligible magnitude atb= 1000 s/mm2. The usefulness of the suggested strategy was exemplified with a scan using tensor-valued diffusion encoding for estimation of parameter maps of mean diffusivity, and anisotropic and isotropic mean kurtosis, showing that ghosting propagated into all three parameter maps unless dual-polarity readout was applied. Results thus imply that extending the use of dual-polarity readout to low non-zero b-values provides effective ghost elimination and can be used without increased scan time for any diffusion MRI scan containing signal averaging at low b-values.

Assessment of Hypoxia in Breast Cancer: Emerging Functional MR Imaging and Spectroscopy Techniques and Clinical Applications

Breast cancer is one of the most prevalent forms of cancer affecting women worldwide. Hypoxia, a condition characterized by insufficient oxygen supply in tumor tissues, is closely associated with tumor aggressiveness, resistance to therapy, and poor clinical outcomes. Accurate assessment of tumor hypoxia can guide treatment decisions, predict therapy response, and contribute to the development of targeted therapeutic interventions. Over the years, functional magnetic resonance imaging (fMRI) and magnetic resonance spectroscopy (MRS) techniques have emerged as promising noninvasive imaging options for evaluating hypoxia in cancer. Such techniques include blood oxygen level-dependent (BOLD) MRI, oxygen-enhanced MRI (OE) MRI, chemical exchange saturation transfer (CEST) MRI, and proton MRS (1H-MRS). These may help overcome the limitations of the routinely used dynamic contrast-enhanced (DCE) MRI and diffusion-weighted imaging (DWI) techniques, contributing to better diagnosis and understanding of the biological features of breast cancer. This review aims to provide a comprehensive overview of the emerging functional MRI and MRS techniques for assessing hypoxia in breast cancer, along with their evolving clinical applications. The integration of these techniques in clinical practice holds promising implications for breast cancer management. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

Evaluation of radiation induced brain injury in nasopharyngeal carcinoma patients based on multi-parameter quantitative MRI: A prospective longitudinal study

PURPOSE

Three dimensional pulsed continuous arterial spin labeling (3D-pCASL) and incoherent movement within voxels (IVIM) imaging was combined to assess dynamic microscopic structure changes of the hippocampus and temporal lobe white matter (TLWM) of nasopharyngeal carcinoma (NPC) patients post intensity-modulated radiation therapy (IMRT).

METHODS

Forty-six patients who were first diagnosed with NPC and underwent IMRT were prospectively enrolled. 3D-CASL and IVIM were performed pre-RT, within 1 week (1 W) post-RT, 3 months (3 M) post-RT, 6 months (6 M) post-RT, and 18 months (18 M) post-RT. Twenty-seven patients completed follow-ups for all time periods, and their data were analyzed. The cerebral flow (CBF) derived from ASL, and apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (F) derived from IVIM of hippocampus and TLWM were analyzed. The quantitative parameters were measured before RT as the baseline, and the corresponding parameter values and change rates at each time point post-RT were compared using the non-parametric Wilcoxon rank sum test.

RESULTS

At 1 W post-RT, CBF showed a significant increase and peaked in both the hippocampus and TLWM (p < 0.05) with change rate of 30.3 % and 24.1 %. In the hippocampus, both D and D* were significantly increased from pre-RT to 6 M post-RT with change rate of 6.66 % and 34.7 %, while D*-values remained significantly higher than pre-RT at 12 months post-RT with change rate of 41.2 %. In the TLWM, the F firstly increased and then decreased, and was significantly decreased from pre-RT to 6 M post-RT with change rate of 20.2 %.

CONCLUSION

3D-PCASL and IVIM can indirectly reflecting the developmental pattern and molecular mechanism of RT induced brain injury.

Quantitative magnetic resonance imaging responses in head and neck cancer patients treated with magnetic resonance-guided hypofractionated radiation therapy

Background and purpose

Quantitative MRI (qMRI) has been explored for detecting tumor changes during radiation therapy (RT) in head and neck squamous cell cancer (HNSCC). Clinical trials show prolonged survival with PD-1 targeted immune checkpoint inhibition. Hypofractionated radiation regimens are being studied to counteract radioresistant clonogen formation. This study aims to use daily qMRI monitoring in these therapies. The objective of this exploratory study was to investigate if qMRI can detect tumor microenvironment changes during hypofractionated RT in a phase I trial of Dose-Escalated Hypofractionated Adaptive Radiotherapy (DEHART).

Materials and methods

Seventeen subjects with advanced HNSCC underwent MR-guided RT with daily qMRI using a 15-fraction regimen to a cumulative dose of 50, 55, or 60 Gy. A 1.5 T MRI-Linac collected daily intravoxel incoherent motion (IVIM), T1, and T2 mappings. Median primary tumor ADC, D, D*, f, T1, and T2 were calculated, using paraspinal muscle as a control. qMRI parameters were analyzed by treatment condition and length using linear mixed effect models and nonparametric tests.

Results

Significant (p < 0.05) increases in ADC, D, f, and T2 were observed over treatment duration for multiple conditions. Daily monitoring enhanced result significance compared to weekly collection.

Conclusions

Daily qMRI effectively monitors tumor response over short periods and varying treatment conditions. Further studies on radiation and systemic therapy combinations in HNSCC could benefit from daily qMRI data collection.

Research Progress on Glioma Microenvironment and Invasiveness Utilizing Advanced Multi-Parametric Quantitative MRI

Magnetic resonance imaging (MRI) currently serves as the primary diagnostic method for glioma detection and monitoring. The integration of neurosurgery, radiation therapy, pathology, and radiology in a multi-disciplinary approach has significantly advanced its diagnosis and treatment. However, the prognosis remains unfavorable due to treatment resistance, inconsistent response rates, and high recurrence rates after surgery. These factors are closely associated with the complex molecular characteristics of the tumors, the internal heterogeneity, and the relevant external microenvironment. The complete removal of gliomas presents challenges due to their infiltrative growth pattern along the white matter fibers and perivascular space. Therefore, it is crucial to comprehensively understand the molecular features of gliomas and analyze the internal tumor heterogeneity in order to accurately characterize and quantify the tumor invasion range. The multi-parameter quantitative MRI technique provides an opportunity to investigate the microenvironment and aggressiveness of glioma tumors at the cellular, blood perfusion, and cerebrovascular response levels. Therefore, this review examines the current applications of advanced multi-parameter quantitative MRI in glioma research and explores the prospects for future development.

Magnetic Resonance Imaging Techniques for Post-Treatment Evaluation After External Beam Radiation Therapy of Prostate Cancer: Narrative Review

Background/Objectives: This study aimed to investigate the prognostic value of advanced techniques of magnetic resonance imaging (MRI) biochemical recurrence (BCR) after radiotherapy in patients with prostate cancer (PCa). Methods: A comprehensive literature review was conducted to evaluate the role of MRI in detecting BCR of PCa patients after external beam radiation therapy. Results: National guidelines do not recommend imaging techniques in clinical follow-up PCa. However, in 2021, the European Association of Urogenital Radiology (ESUR), the European Association of Urological Imaging (ESUI), and the PI-RADS Steering Committee introduced the Prostate Imaging for Recurrence Reporting (PI-RR) system. PI-RR incorporates the MRI biomarkers in the post-treatment process. In the last decade, a growing number of clinical researchers have investigated the role of various MRI techniques in BCR. Conclusions: The integration of advanced MRI technologies into clinical routine marks the beginning of a new era of BCR with accuracy.

Enabling brain-wide mapping of layer-specific functional connectivity at 3T via layer-dependent fMRI with draining-vein suppression

Layer-dependent functional magnetic resonance imaging (fMRI) is a promising yet challenging approach for investigating layer-specific functional connectivity (FC). Achieving a brain-wide mapping of layer-specific FC requires several technical advancements, including sub-millimeter spatial resolution, sufficient temporal resolution, functional sensitivity, global brain coverage, and high spatial specificity. Although gradient echo (GE)-based echo planar imaging (EPI) is commonly used for rapid fMRI acquisition, it faces significant challenges due to the draining-vein contamination. In this study, we addressed these limitations by integrating velocity-nulling (VN) gradients into a GE-BOLD fMRI sequence to suppress vascular signals from the vessels with fast-flowing velocity. The extravascular contamination from pial veins was mitigated using a GE-EPI sequence at 3T rather than 7T, combined with phase regression methods. Additionally, we incorporated advanced techniques, including simultaneous multislice (SMS) acceleration and NOise Reduction with DIstribution Corrected principal component analysis (NORDIC PCA) denoising, to improve temporal resolution, spatial coverage, and signal sensitivity. This resulted in a VN fMRI sequence with 0.9-mm isotropic spatial resolution, a repetition time (TR) of 4 seconds, and brain-wide coverage. The VN gradient strength was determined based on results from a button-pressing task. Using resting-state data, we validated layer-specific FC through seed-based analyses, identifying distinct connectivity patterns in the superficial and deep layers of the primary motor cortex (M1), with significant inter-layer differences. Further analyses with a seed in the primary sensory cortex (S1) demonstrated the reliability of the method. Brain-wide layer-dependent FC analyses yielded results consistent with prior literature, reinforcing the efficacy of VN fMRI in resolving layer-specific functional connectivity. Given the widespread availability of 3T scanners, this technical advancement has the potential for significant impact across multiple domains of neuroscience research.

Breast Cancer: Multi-b-Value Diffusion Weighted Habitat Imaging in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy

RATIONALE AND OBJECTIVES

The aim of this study was to ascertain whether the utilization of multiple b-value diffusion-weighted habitat imaging, a technique that depicts tumor heterogeneity, could aid in identifying breast cancer patients who would derive substantial benefit from neoadjuvant chemotherapy (NAC).

MATERIALS AND METHODS

This prospective study enrolled 143 women (II-III breast cancer), who underwent multi-b-value diffusion-weighted imaging (DWI) in 3-T magnetic resonance (MR) before NAC. The patient cohort was partitioned into a training set (consisting of 100 patients, of which 36 demonstrated a pathologic complete response [pCR]) and a test set (featuring 43 patients, 16 of whom exhibited pCR). Utilizing the training set, predictive models for pCR, were constructed using different parameters: whole-tumor radiomics (ModelWH), diffusion-weighted habitat-imaging (ModelHabitats), conventional MRI features (ModelCF), along with combined models ModelHabitats+CF. The performance of these models was assessed based on the area under the receiver operating characteristic curve (AUC) and calibration slope.

RESULTS

In the prediction of pCR, ModelWH, ModelHabitats, ModelCF, and ModelHabitats+CF achieved AUCs of 0.733, 0.722, 0.705, and 0.756 respectively, within the training set. These scores corresponded to AUCs of 0.625, 0.801, 0.700, and 0.824 respectively in the test set. The DeLong test revealed no significant difference between ModelWH and ModelHabitats (P = 0.182), between ModelHabitats and ModelHabitats+CF (P = 0.113).

CONCLUSION

The habitat model we developed, incorporating first-order features along with conventional MRI features, has demonstrated accurate predication of pCR prior to NAC. This model holds the potential to augment decision-making processes in personalized treatment strategies for breast cancer.

Preliminary investigations into human neurofluid transport using multiple novel non-contrast MRI methods

We discuss two potential non-invasive MRI methods to study phenomena related to subarachnoid cerebrospinal fluid (CSF) motion and perivascular fluid transport, and their association with sleep and aging. We apply diffusion-based intravoxel incoherent motion (IVIM) imaging to evaluate pseudodiffusion coefficient, D*, or CSF movement across large spaces like the subarachnoid space (SAS). We also performed perfusion-based multi-echo, Hadamard encoded arterial spin labeling (ASL) to evaluate whole brain cortical cerebral blood flow (CBF) and trans-endothelial exchange (Tex) of water from the vasculature into the perivascular space and parenchyma. Both methods were used in young adults (N = 9, 6 F, 23 ± 3 years old) in the setting of sleep and sleep deprivation. To study aging, 10 older adults (6 F, 67 ± 3 years old) were imaged after a night of normal sleep and compared with the young adults. D* in SAS was significantly (p < 0.05) reduced with sleep deprivation (0.016 ± 0.001 mm2/s) compared to normal sleep (0.018 ± 0.001 mm2/s) and marginally reduced with aging (0.017 ± 0.001 mm2/s, p = 0.029). Cortical CBF and Tex were unchanged with sleep deprivation but significantly lower in older adults (37 ± 3 ml/100 g/min, 578 ± 61 ms) than in young adults (42 ± 2 ml/100 g/min, 696 ± 62 ms). IVIM was sensitive to sleep physiology and aging, and multi-echo, multi-delay ASL was sensitive to aging.

Contralateral renal change in a unilateral ureteral obstruction rat model using intravoxel incoherent motion diffusion-weighted imaging

OBJECTIVES

Most functional magnetic resonance research has primarily examined alterations in the affected kidney, often neglecting the contralateral kidney. Our study aims to investigate whether imaging parameters accurately depict changes in both the renal cortex and medulla in a unilateral ureteral obstruction rat model, thereby showcasing the utility of intravoxel incoherent motion (IVIM) in evaluating contralateral renal changes.

METHODS

Six rats underwent MR scans and were subsequently sacrificed for baseline histological examination. Following the induction of left ureteral obstruction, 48 rats were scanned, and the histopathological examinations were conducted on days 3, 7, 10, 14, 21, 28, 35, and 42. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudodiffusion (D*), and perfusion fraction (f) values were measured using IVIM.

RESULTS

On the 10th day of obstruction, both cortical and medullary ADC values differed significantly between the UUO10 group and the sham group (p < 0.01). The cortical D values showed statistically significant differences between UUO3 group and sham group (p < 0.01) but not among UUO groups at other time point. Additionally, the cortical and medullary f values were statistically significant between the UUO21 group and the sham group (p < 0.01). Especially, the cortical f values exhibited significant differences between the UUO21 group and the UUO groups with shorter obstruction time (at time point of 3, 7, 10, 14 day) (p < 0.01).

CONCLUSIONS

Significant hemodynamic alterations were observed in the contralateral kidney following renal obstruction. IVIM accurately captures changes in the unobstructed kidney. Particularly, the cortical f value exhibits the highest potential for assessing contralateral renal modifications.

Diffusion-weighted imaging in addition to contrast-enhanced MRI in identifying complete response in HER2-positive breast cancer

OBJECTIVES

The aim of this study is to investigate the added value of diffusion-weighted imaging (DWI) to dynamic-contrast enhanced (DCE)-MRI to identify a pathological complete response (pCR) in patients with HER2-positive breast cancer and radiological complete response (rCR).

MATERIALS AND METHODS

This is a single-center observational study of 102 patients with stage I-III HER2-positive breast cancer and real-world documented rCR on DCE-MRI. Patients were treated between 2015 and 2019. Both 1.5 T/3.0 T single-shot diffusion-weighted echo-planar sequence were used. Post neoadjuvant systemic treatment (NST) diffusion-weighted images were reviewed by two readers for visual evaluation and ADCmean. Discordant cases were resolved in a consensus meeting. pCR of the breast (ypT0/is) was used to calculate the negative predictive value (NPV). Breast pCR-percentages were tested with Fisher's exact test. ADCmean and ∆ADCmean(%) for patients with and without pCR were compared using a Mann-Whitney U-test.

RESULTS

The NPV for DWI added to DCE is 86% compared to 87% for DCE alone in hormone receptor (HR)-/HER2-positive and 67% compared to 64% in HR-positive/HER2-positive breast cancer. Twenty-seven of 39 non-rCR DWI cases were false positives. In HR-positive/HER2-positive breast cancer the NPV for DCE MRI differs between MRI field strength (1.5 T: 50% vs. 3 T: 81% [p = 0.02]). ADCmean at baseline, post-NST, and ∆ADCmean were similar between patients with and without pCR.

CONCLUSION

DWI has no clinically relevant effect on the NPV of DCE alone to identify a pCR in early HER2-positive breast cancer. The added value of DWI in HR-positive/HER2-positive breast cancer should be further investigated taken MRI field strength into account.

CLINICAL RELEVANCE STATEMENT

The residual signal on DWI after neoadjuvant systemic therapy in cases with early HER2-positive breast cancer and no residual pathologic enhancement on DCE-MRI breast should not (yet) be considered in assessing a complete radiologic response.

KEY POINTS

Radiologic complete response is associated with a pathologic complete response (pCR) in HER2+ breast cancer but further improvement is warranted. No relevant increase in negative predictive value was observed when DWI was added to DCE. Residual signal on DW-images without pathologic enhancement on DCE-MRI, does not indicate a lower chance of pCR.

Simultaneous non-contrast assessment of cardiac microstructure and perfusion in vivo in the human heart

BACKGROUND

Intravoxel incoherent motion (IVIM) imaging can provide information on cardiac microstructure and microvascular perfusion from a single examination. However, the spin echo-based approaches typically used for cardiac IVIM suffer from low sensitivity to changes in perfusion. The aim of this work was to develop a stimulated-echo (STEAM)-based method for IVIM and diffusion tensor cardiovascular magnetic resonance to simultaneously provide biomarkers of microstructure and perfusion in vivo in the human heart.

METHODS

Here we introduce a novel STEAM-IVIM sequence incorporating phase cycling to obtain true non-diffusion weighted images (b = 0 s/mm2). STEAM-IVIM imaging was performed at 20 b-values (0 to 1000 s/mm2) to enable accurate estimation of the IVIM parameters, and with six diffusion encoding directions to enable reconstruction of the diffusion tensor. 20 healthy subjects (8 female, median age 31 years) were imaged on a clinical 3T system with STEAM-IVIM. A simulation study was performed to investigate the optimal fitting algorithms for the IVIM parameters, which was subsequently used to create pixel-wise IVIM parameter maps for the in vivo acquisitions.

RESULTS

Good image quality across the myocardium was obtained for all b-values. Mean(±SD) IVIM parameter estimates were: diffusivity D = 0.83 ± 0.07 × 10-3 mm2/s, perfusion coefficient D* = 19.08 ± 6.48 × 10-3 mm2/s, perfusion fraction f = 19.72 ± 4.11%, and mean diffusion tensor parameters were: mean diffusivity = 0.88 ± 0.06 × 10-3 mm2/s, fractional anisotropy = 0.45 ± 0.04, absolute E2 angle = 55.29 ± 6.38º, helix angle gradient = -0.68 ± 0.18º/%.

CONCLUSION

Phase-cycled STEAM-IVIM enables fitting of cardiac diffusion tensor and perfusion parameters in healthy subjects and shows promise for the simultaneous detection of microstructural aberration and perfusion abnormalities in the presence of cardiac disease without the need for exogenous contrast agents.

Intravoxel incoherent motion imaging in stroke infarct core and penumbra is related to long-term clinical outcome

Intravoxel incoherent motion (IVIM) imaging, a contrast agent-free magnetic resonance imaging technique, enables the evaluation of microvascular perfusion abnormalities in acute stroke. Prior research reported reduced IVIM values within the infarct core in acute stroke. However, findings concerning IVIM characteristics in the penumbra have been mixed and the relationship between IVIM and clinical outcomes remains unknown. We employed a longitudinal multimodal imaging approach for ischemic stroke patients (n analyzed=24; pre-/post-treatment and 90-day post-stroke assessments) including IVIM, diffusion-weighted, and contrast-enhanced perfusion-weighted imaging. We evaluated IVIM in relevant stroke areas after endovascular treatment. Reduced post-treatment IVIM perfusion fraction in infarct core and recanalized penumbra was associated with poorer functional recovery at 90-days post-stroke (NIH Stroke Scale [NIHSS]; r=-0.64 and r=-0.69). Including IVIM perfusion fraction increased the explained variance of NIHSS from 42% up to 83% compared to well-known prognostic factors core volume and patient age. Additionally, IVIM perfusion fraction was reduced in the core and recanalized penumbra compared to contralateral healthy tissue, suggesting impaired microvascular reperfusion after endovascular treatment. In conclusion, IVIM characteristics of the infarct core and recanalized penumbra are strong prognostic factors for long-term outcome in stroke patients and IVIM shows promise for characterizing microvascular perfusion in relevant stroke areas.

Relaxation-exchange magnetic resonance imaging (REXI): a non-invasive imaging method for evaluating trans-barrier water exchange in the choroid plexus

BACKGROUND

The choroid plexus (CP) plays a crucial role in cerebrospinal fluid (CSF) production and brain homeostasis. However, non-invasive imaging techniques to assess its function remain limited. This study was conducted to develop a novel, contrast-agent-free MRI technique, termed relaxation-exchange magnetic resonance imaging (REXI), for evaluating CP-CSF water transport, a potential biomarker of CP function.

METHODS

REXI utilizes the inherent and large difference in magnetic resonance transverse relaxation times (T2s) between CP tissue (e.g., blood vessels and epithelial cells) and CSF. It uses a filter block to remove most CP tissue magnetization (shorter T2), a mixing block for CP-CSF water exchange with mixing time tm, and a detection block with multi-echo acquisition to determine the CP/CSF component fraction after exchange. The REXI pulse sequence was implemented on a 9.4 T preclinical MRI scanner. For validation of REXI's ability to measure exchange, we conducted preliminary tests on urea-water proton-exchange phantoms with various pH levels. We measured the steady-state water efflux rate from CP to CSF in rats and tested the sensitivity of REXI in detecting CP dysfunction induced by the carbonic anhydrase inhibitor acetazolamide.

RESULTS

REXI pulse sequence successfully captured changes in the proton exchange rate (from short-T2 component to long-T2 component [i.e., ksl]) of urea-water phantoms at varying pH, demonstrating its sensitivity to exchange processes. In rat CP, REXI significantly suppressed the CP tissue signal, reducing the short-T2 fraction (fshort) from 0.44 to 0.23 (p < 0.0001), with significant recovery to 0.28 after a mixing time of 400 ms (p = 0.014). The changes in fshort at various mixing times can be accurately described by a two-site exchange model, yielding a steady-state water efflux rate from CP to CSF (i.e., kbc) of 0.49 s-1. A scan-rescan experiment demonstrated that REXI had excellent reproducibility in measuring kbc (intraclass correlation coefficient = 0.90). Notably, acetazolamide-induced CSF reduction resulted in a 66% decrease in kbc within rat CP.

CONCLUSIONS

This proof-of-concept study demonstrates the feasibility of REXI for measuring trans-barrier water exchange in the CP, offering a promising biomarker for future assessments of CP function.

Application of functional magnetic resonance imaging to evaluate renal structure and function in type 2 cardiorenal syndrome

BACKGROUND

There is a lack of diagnostic non-invasive imaging technology for assessing the early structural and functional changes of the kidney in type 2 cardiorenal (CRS) patients. This study aims to explore the value of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for clinical application in type 2 CRS patients, to provide imaging markers for the assessment of kidney damage.

METHODS

This is a retrospective observational clinical study conducted in Nanjing, China. The clinical characteristics, including age, gender, medical history, laboratory results, and ultrasound and magnetic resonance imaging results were collected from the electronic medical record. Thirty-one patients with type 2 CRS, 20 patients with chronic heart failure (HF) and 20 healthy controls were enrolled and divided into type 2 CRS, HF and control groups. All the participants underwent magnetic resonance imaging (MRI) scanning. The apparent diffusion coefficient (ADC) value and IVIM-DWI parameters including true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were obtained. The correlation between estimated glomerular filtration rate (eGFR), renal size and imaging parameters was evaluated by Spearman correlation analysis.

RESULTS

ADC and D of the renal cortex in patients with type 2 CRS were lower than those in the healthy control group. ADC and f in the HF group were lower than those in the control group. D was positively correlated with the length (r = 0.3752, P = 0.0013) and transverse diameter (r = 0.3258, P = 0.0056) of the kidney. ADC (r = 0.2964, P = 0.0121) and D (r = 0.3051, P = 0.0097) were positively correlated with eGFR. Renal cortical ADC and D values could distinguish type 2 CRS patients from the healthy controls with area under the curve (AUC) of 0.723 and 0.706, respectively.

CONCLUSION

The ADC and D values were not only correlated with renal function, but also had lower levels in type 2 CRS. The IVIM-DWI parameter D was also related to kidney size, but further research is needed to determine whether it can be used as a novel imaging marker for type 2 CRS.

MRI and Blood-based Biomarkers Are Associated With Surgery in Children and Adults With Ileal Crohn's Disease

BACKGROUND

Despite advances in medical therapy, many children and adults with ileal Crohn's disease (CD) progress to fibrostenosis requiring surgery. We aimed to identify MRI and circulating biomarkers associated with the need for surgical management.

METHODS

This prospective, multicenter study included pediatric and adult CD cases undergoing ileal resection and CD controls receiving medical therapy. Noncontrast research MRI examinations measured bowel wall 3-dimensional magnetization transfer ratio normalized to skeletal muscle (normalized 3D MTR), modified Look-Locker inversion recovery (MOLLI) T1 relaxation, intravoxel incoherent motion (IVIM) diffusion-weighted imaging metrics, and the simplified magnetic resonance index of activity (sMaRIA). Circulating biomarkers were measured on the same day as the research MRI and included CD64, extracellular matrix protein 1 (ECM1), and granulocyte-macrophage colony-stimulating factor (GM-CSF) autoantibodies (Ab). Associations between MRI and circulating biomarkers and need for ileal resection were tested using univariate and multivariable LASSO regression.

RESULTS

Our study sample included 50 patients with CD undergoing ileal resection and 83 patients with CD receiving medical therapy; mean participant age was 23.9 ± 13.1 years. Disease duration and treatment exposures did not vary between the groups. Univariate biomarker associations with ileal resection included log GM-CSF Ab (odds ratio [OR], 2.87; P = .0009), normalized 3D MTR (OR, 1.05; P = .002), log MOLLI T1 (OR, 0.01; P = .02), log IVIM perfusion fraction (f; OR, 0.38; P = .04), and IVIM apparent diffusion coefficient (ADC; OR, 0.3; P = .001). The multivariable model for surgery based upon corrected Akaike information criterion included age (OR, 1.03; P = .29), BMI (OR, 0.91; P = .09), log GM-CSF Ab (OR, 3.37; P = .01), normalized 3D MTR (OR, 1.07; P = .007), sMaRIA (OR, 1.14; P = .61), luminal narrowing (OR, 10.19; P = .003), log C-reactive protein (normalized; OR, 2.75; P = .10), and hematocrit (OR, 0.90; P = .13).

CONCLUSION

After accounting for clinical and MRI measures of severity, normalized 3D MTR and GM-CSF Ab are associated with the need for surgery in ileal CD.

Early and late assessment of renal allograft dysfunction using intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI): a prospective study

PURPOSE

To evaluate the ability of the Intravoxel Incoherent Motion (IVIM) and monoexponentially ADC in renal allograft function in the early and late phases of transplantation, and to predict their effectiveness in discrimination of the graft pathology.

METHODS

This is a prospective study included participants scanned with quantitative diffusion and perfusion sequences on a 3-T MR scanner (Philips, Ingenia); the ADC and IVIM parameters; were calculated. Correlations and regression analysis with the eGFR, transplantation periods, and pathology were assessed.

RESULTS

This study included 105 renal allograft recipients (85 males, and 20 females with mean age = 32.4 ± 11.9 years and age range = 22-61 years). There was a significant positive correlation between the whole parameters of the ADC and IVIM with eGFR however, the cortical parameters showed higher significant correlation coefficients (p < 0.001). Regression analysis revealed the most significant model can predict eGFR groups included cortical pseudo diffusion (D*) and cortical ADC (p < 0.001). In graft dysfunction eGFR was 61.5 ml/min and normal graft was 64 ml/min. This model demonstrates a high performance of an AUC 96% [0.93-0.97]. In the late transplantation, there is a higher correlation with D* compared to ADC, p-values = 0.001.

CONCLUSION

IVIM and ADC Values are significant biomarkers for renal allograft function assessment, cortical ADC, and D* had the highest performance even in situations with mild impairment that is not affect the eGFR yet as cases of proteinuria with normal eGFR. Furthermore, D* is superior to ADC in the late assessment of the renal transplant.

A timeline study on vascular co-morbidity induced cerebral endothelial dysfunction assessed by perfusion MRI

Endothelial dysfunction is considered a key element in the early pathogenesis of neurodegenerative disorders. Dysfunction of the cerebral endothelial cells can result in dysregulation of cerebral perfusion and disruption of the Blood Brain Barrier (BBB), leading to brain damage, neurodegeneration and cognitive decline. It has been shown that the presence of modifiable risk factors exacerbates endothelial dysfunction. This study primarily aimed to identify which among various perfusion MRI methodologies could be effectively utilized to non-invasively identify early pathological alterations as a result of endothelial dysfunction. We compared these perfusion MRI measurements to invasive immunohistochemistry to detect early pathological alterations in the cerebral vasculature of a rat model of multiple cardiovascular co-morbidities (the ZSF1 Obese rat) at several stages of the cerebrovascular pathology. We observed cerebral hyperperfusion, expressed by increased Cerebral Blood Flow (CBF) and increased BBB permeability in the ZSF1 Obese rats, at an early stage of disease development. The increase in CBF observed with Arterial Spin Labeling (ASL) was lost during later stages of disease progression. These findings are in line with recent clinical findings in early stages of Alzheimer's disease (AD), that also show early increases in CBF.

iRGD-mediated liposomal nanoplatforms for improving hepatocellular carcinoma targeted combination immunotherapy and monitoring tumor response via IVIM-MRI

The combination therapy of targeted treatments and immune checkpoint blockade (ICB) holds great promise for hepatocellular carcinoma (HCC) treatment. However, challenges such as immunogenicity, off-target toxicity of ICB antibodies, low drug co-delivery efficiency, and lack of effective biomarkers to monitor treatment response limit the efficacy of existing targeted immunotherapies. Herein, we synthesized iRGD-modified pH-sensitive liposomal nanoparticles co-encapsulating lenvatinib (Len) and the small molecule PD-1/PD-L1 inhibitor BMS-202 (iRGD-lip@Len/BMS-202) to address issues related to inadequate tumor enrichment and distinct pharmacokinetics of these drugs. Furthermore, intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI), which is calculated using a biexponential model, can simultaneously reflect both the diffusion of water molecules within the tissue and the microcirculatory perfusion of capillaries. Consequently, we further assessed the feasibility of using IVIM-MRI to monitor the cancer treatment response in nanodrug therapy. These results demonstrated that the iRGD-targeted liposomal nanodrug effectively accumulated in tumors and released in acidic microenvironments. The sustained release of Len facilitated tumor vascular normalization, decreased the presence of Tregs and MDSCs and activated the IFN-γ signaling pathway. This led to increased PD-L1 expression in tumor cells, enhancing the sensitivity of BMS-202. Consequently, there was a synergistic amplification of antitumor immune therapy, resulting in the shrinkage of subcutaneous and orthotopic HCC and inhibition of lung metastasis. Furthermore, IVIM-MRI technology facilitated the non-invasive monitoring of the tumor microenvironment (TME), revealing critical therapeutic response indicators such as the normalization of tumor blood vessels and the degree of hypoxia. Collectively, the combination of Food and Drug Administration (FDA)-approved drugs with iRGD-modified liposomes presents a promising strategy for HCC treatment. Simultaneously, IVIM-MRI provides a non-invasive method to accurately predict the response to this nanodrug.