Purpose: Multiple sclerosis (MS) is a demyelinating disease of the central nervous system influenced by both genetic and environmental factors. Although a polygenic risk score for MS (MS-PRS) is associated with disease susceptibility, its relationship with white matter (WM) microstructure and cognition in neurologically healthy individuals remains unclear. This study investigated associations of MS-PRS with diffusion MRI metrics and cognitive function in healthy individuals.

Methods: This cross-sectional study included 35952 neurologically healthy UK Biobank participants with available MS-PRS, diffusion MRI, and cognitive data. Associations between MS-PRS and 11 cognitive measures were tested using generalized linear models adjusted for age, age squared, sex, genetic principal components, body mass index, and intracranial volume, with false discovery rate (FDR) correction. Participants were then stratified by MS-PRS quartiles. For cognitive measures showing significant associations in the highest MS-PRS group, follow-up analyses evaluated associations between MS-PRS and diffusion MRI metrics in WM regions previously associated with reaction time (RT). Mediation analysis was then performed.

Results: In the full sample, MS-PRS was not significantly associated with any cognitive measure after multiple-comparison correction. In the highest MS-PRS group, the higher MS-PRS was significantly associated with longer RT (β = 0.048, FDR-corrected P = 0.047). In the highest MS-PRS group, the higher MS-PRS was associated with higher mean diffusivity (MD) in the splenium of the corpus callosum (CC) (β = 0.021, FDR-corrected P = 0.024). MD in the splenium of the CC showed a small partial mediation effect on the association between MS-PRS and RT in the highest MS-PRS group (mediation effect 3.0%).

Conclusion: In neurologically healthy individuals, a higher genetic burden for MS was associated with slower information processing speed in the highest-risk subgroup and with altered WM microstructure in the splenium of the CC. These findings suggest that subtle WM differences may partly underlie the association between MS genetic susceptibility and cognitive performance.

Purpose: Pseudo-continuous arterial spin labeling (pCASL) MRI is a widely used, noninvasive, contrast-agent-free technique for measuring cerebral blood flow (CBF) and assessing vascular dysfunction across diverse clinical settings and murine disease models. In practice, arterial-transit artifacts that generate hyperintense signal in CBF maps warrant careful consideration. While these effects are well characterized in humans, they are less well understood in mice owing to the marked interspecies physiological differences.

Methods: To address this knowledge gap, we systematically characterized pCASL hyperintense signal as a function of post-labeling delay (PLD) and crusher-gradient strength in mice. Numerical simulations were also performed to validate the experimental findings.

Results: We found that hyperintense signals in mice extend to arteries, major veins, and ventricular structures. Such a pattern was different from human pCASL images, where hyperintense signals are predominantly present in arteries. Statistical analyses supported a PLD of 500 milliseconds as a pragmatic balance between detection sensitivity and suppression of vascular contamination. Additional experiments and numerical simulations showed that, within the tested range, stronger crusher gradients provided little extra vascular suppression—primarily because large vessel calibers relative to small voxels limit intravoxel phase dispersion.

Conclusion: These findings refine the interpretation of murine pCASL signals and facilitate more accurate perfusion imaging in preclinical pathophysiological studies.

Purpose: Synthetic Q-space learning (synQSL), which uses only synthetic data in the training of regressors, has demonstrated promising results in parameter estimation for brain diffusion MRI (dMRI). This study aimed to evaluate the performance of synQSL in breast dMRI for intravoxel incoherent motion–diffusional kurtosis imaging (IVIM–DKI) parameter estimation, with comparing several types of regressors and conventional fitting by nonlinear least squares fitting (NL-LSF).

Methods: In synthesizing data for synQSL, IVIM–DKI parameters were sampled from uniform distributions and substituted into the signal model along with b-values to generate diffusion-weighted imaging (DWI) signals. In addition, Rician noise was mixed to the signals. We prepared datasets of 10⁵ and 10⁶ samples, and trained multi-layer perceptron (MLP), Kolmogorov–Arnold networks (KAN), and random forest (RF) regressors for synQSL. The performance of the parameter estimation methods including NL-LSF was evaluated using a digital phantom including various value combinations of IVIM–DKI parameters and clinical data of 67 cases (13 benign and 54 malignant lesions) through quantitative analysis and visual assessment.

Results: In the digital phantom, the regressors of synQSL achieved significantly lower root mean square error (RMSE) for f, D^∗, and D than NL-LSF (P < 0.05) with less variation among the parameter sets. In clinical datasets, synQSL not only improved the visual quality of parameter maps but also showed significant differences between benign and malignant lesions in parameters while the NL-LSF failed. Furthermore, the estimation times for all synQSL regressors were substantially shorter than that of NL-LSF. Among the synQSL regressors, MLP showed superior properties including computational cost.

Conclusion: synQSL demonstrated superior parameter estimation performance compared to NL-LSF in breast IVIM–DKI analysis. In this study, MLP was considered the most suitable regressor for synQSL among those we examined, based on the balance between estimation accuracy and computational costs.

This study aimed to demonstrate the technical feasibility of a dedicated prostate phantom for standardized qualitative evaluation of diffusion-weighted MRI sequences, focusing on signal-to-noise characteristics and image artifacts. A custom-designed phantom simulating prostate tissue, tumor lesions, and rectal gas was used to evaluate 6 diffusion-weighted imaging techniques at 1.5 and 3.0 tesla. Quantitative assessments included signal-to-noise measurements and susceptibility artifacts, while spatial distortion was evaluated by comparison with T2-weighted imaging. Qualitative image quality was assessed using corresponding clinical images as references. Clinical images were evaluated by a radiologist and a urologist, and phantom images were evaluated by 2 radiological technologists. The phantom demonstrated high inter-reader agreement for qualitative image assessment. Clinical image evaluation was performed to confirm whether artifact trends observed in the phantom were similarly observed in clinical images and showed comparable tendencies across sequences. These findings indicate that the proposed prostate phantom provides a practical and reproducible platform for qualitative evaluation.

Chronic kidney disease (CKD) is a major global health burden, encompassing a heterogeneous group of disorders with diverse etiologies and pathophysiological mechanisms. Conventional biomarkers such as serum creatinine, estimated glomerular filtration rate (eGFR), and proteinuria are indispensable for detection and staging, yet they may be insensitive to early CKD including diabetic kidney disease (DKD) and can be discordant with underlying structural damage. Over the past 15 years, functional renal MRI has gained attention as a promising noninvasive approach to quantify complementary domains of renal pathology without ionizing radiation or gadolinium-based contrast agents, enabling repeated assessments even in patients with impaired renal function. This review provides a comprehensive overview of multiparametric MRI techniques for evaluating renal microstructure and physiology across CKD, including T1 and T2 mapping for interstitial expansion and inflammatory activity, blood oxygenation level dependent MRI for oxygenation and corticomedullary gradients, diffusion-based methods (apparent diffusion coefficient [ADC], diffusion tensor imaging, intravoxel incoherent motion) for microstructural injury and microvascular components, and arterial spin labeling for perfusion. Corticomedullary differentiation (CMD) is highlighted as an integrative feature across modalities, including signal-intensity-based CMD using noncontrast steady-state free precession (SSFP) with spatially selective inversion recovery and individualized optimal inversion time (multi-TI). Across CKD populations, many MRI-derived metrics correlate with contemporaneous kidney function, and diffusion-derived indices—particularly cortical ADC—have been associated with subsequent eGFR decline, suggesting potential value for progression-risk assessment. DKD is discussed as an important illustrative subtype in which complex pathophysiology may highlight the added value of multiparametric approaches. Clinical translation will depend on standardized acquisition, quality control, and multicenter validation to establish reproducibility and outcome-based thresholds.

Purpose: To investigate the effects of free-water (FW) correction on mean diffusivity (MD) values in glioblastomas using diffusion tensor imaging (DTI) with different b-value settings. We also examined regional differences between contrast-enhanced (CE) tumor and peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintense regions.

Methods: DTI data from 787 participants with glioblastoma were obtained from 2 open-source datasets: the University of California, San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM; b-value, 2000) and the Multi-parametric Magnetic Resonance Imaging Scans for De Novo Glioblastoma Patients from the University of Pennsylvania Health System (UPENN-GBM; b-value, 1000). Conventional and FW-corrected MD maps were generated, and median MD values were calculated from CE and FLAIR hyperintense regions. The impact of FW correction was assessed via the Wilcoxon matched-pairs signed rank test, Bland–Altman plot, and Spearman’s correlation analysis. Multivariate Cox regression was used to evaluate prognostic significance, adjusting for age and CE volume.

Results: Both median MD values were significantly lower in the CE regions than in the FLAIR hyperintense regions. In the UCSF-PDGM dataset, FW correction caused a greater reduction of MD in the CE regions, whereas the greater reduction occurred in the FLAIR hyperintense regions in the UPENN-GBM dataset. Bland–Altman plot also indicated lesions with lower MD values showing greater FW correction in the UCSF-PDGM dataset, whereas those with relatively high MD values showed greater FW correction in the UPENN-GBM dataset. The correlation between both MD values was high (Rs > 0.98). Neither conventional MD nor FW-corrected MD values in the CE regions were significantly associated with overall survival. (Ps > 0.30).

Conclusion: A paradoxical relationship of MD values with and without FW correction was identified depending on regional characteristics and b-value settings, underscoring the importance of acquisition parameters when interpreting FW correction.

Purpose: To evaluate the performance of a Transformer-based U-Net, TransDisCo, for distortion correction in clinical diffusion-weighted imaging (DWI), including high b-value DWI, diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) and, furthermore, to compare its efficacy with an established U-Net–based method (Synb0) on a clinical dataset including lesion cases.

Methods: This study utilized a clinical dataset acquired at the University of Tokyo Hospital, comprising DWI data from patients (including cases with brain tumors and cerebrovascular disorders) suitable for DTI and DKI analysis. We compared the distortion-correction performance of our proposed TransDisCo with that of Synb0, a U-Net–based model. Both methods were trained on T1-weighted images and uncorrected DWI images, with FMRIB Software Library–corrected DWI images used as ground truth. To assess the contribution of the self-attention mechanism in TransDisCo, an ablation study was conducted using a convolutional neural network (CNN)–based variant, in which encoder Transformer blocks were replaced with convolutional blocks. We evaluated corrected DWI images and derived DTI/DKI maps using peak SNR, structural similarity, mutual information, and Dice coefficients.

Results: All 3 models corrected distortions in the clinical DWI datasets, including high b-value images and derived DTI/DKI maps. Furthermore, TransDisCo demonstrated significantly superior performance compared to Synb0 across quantitative metrics, particularly in preserving anatomical details and reducing artifacts, even in the presence of pathological changes. Additionally, in the ablation study, TransDisCo outperformed the CNN-based variant trained under identical conditions, indicating that the self-attention mechanism, which enables content-adaptive long-range feature interactions, of the Transformer-based encoder contributed to the observed performance gains.

Conclusion: TransDisCo alleviates limitations of existing CNN-based models and represents a promising approach to DWI distortion correction that surpasses conventional U-Net–based methods on clinical data with diverse pathologies. It has the potential to improve the precision and reliability of diffusion MRI across a wide range of imaging conditions and clinical applications.

Purpose: To evaluate whether reverse encoding distortion correction (RDC) improves image quality and maintains apparent diffusion coefficient (ADC) measurements in diffusion-weighted imaging (DWI) on female pelvic MRI using a 1.5-T in in vitro and in vivo studies.

Methods: This retrospective, institutional review board-approved study included both in vitro and in vivo analyses of 31 women (mean age, 41 ± 15 years; range, 24–80 years) who underwent pelvic MRI between January and March 2022. T2-weighted image (T2WI) and DWI with and without RDC were acquired, and ADC maps were generated. Quantitative metrics included SNR, contrast-to-noise ratio (CNR), ADC values, and deformation ratio (DR), defined as the proportional area discrepancy between DWI and T2WI for the uterine corpus, cervix, ovary, and lesions. Qualitative assessments—overall image quality (OIQ), deformation severity (DS), and diagnostic confidence level (DCL)—were independently scored by 2 blinded radiologists using 5-point scales.

Results: In vitro SNR and ADC values showed no significant differences between DWI with and without RDC, with strong correlations to reference measurements (ρ = 0.99, P < 0.001). In vivo, SNR, CNR, and ADC values of the myometrium, cervix, and ovary did not differ significantly between 2 methods (P > 0.05). DRs were significantly lower in DWI with RDC than in DWI without RDC (P ≤ 0.0003). ADC values showed strong correlations between DWI with and without RDC on uterine corpus, cervix, ovary and lesions (ρ = 0.82–0.90, P < 0.001). Qualitative scores improved with RDC: higher OIQ (P = 0.0004), lower DS (P = 0.0004), and higher DCL (P = 0.03). Interobserver agreement ranged from substantial to almost perfect (κ = 0.78–0.97).

Conclusion: RDC improves image quality and reduces image distortion in DWI on female pelvic MRI at a 1.5-T, while maintaining ADC measurements in in vitro and in vivo settings.

Purpose: To evaluate the monitoring value of T1 and T2 mapping in assessing kidney injury associated with chronic liver disease and the therapeutic efficacy of bone marrow mesenchymal stem cells (BMSCs) treatment.

Methods: Thirty-six rats were divided into 6 subgroups (n = 6/group) and underwent MRI scanning at 0, 2, 4, 6, 8, and 12 weeks, respectively, followed by biochemical and histological analyses. Seven rats underwent continuous MRI scanning to monitor changes in imaging parameters. Twenty-four rats divided into BMSC and control group. Six rats per group were subjected to serial MRI scans at weeks 13, 14, 15, and 16, another six rats per group were scanned at week 14 and then sacrificed for biochemical and renal histological analysis.

Results: From baseline to 12 weeks, renal hematoxylin and eosin (HE) scores and α-smooth muscle actin (α-SMA) levels increased significantly, and similar trends were found in renal T1 and T2 values. Following BMSCs injection, both BMSC and control groups exhibited reductions in HE scores and α-SMA levels, with BMSC group demonstrating more substantial decreases. Renal T1 and T2 values declined in both groups, with the BMSC group showing significantly lower T2 values than the control group. Strong correlations were found between renal T1/T2 values and HE scores, α-SMA levels (|r|=0.419–0.724). The area under the curve values for T1 and T2 in differentiating renal injury severity across different renal strips were from 0.793 to 0.930.

Conclusion: T1 and T2 mapping can effectively monitor renal injury progression in chronic liver disease, with T2 values demonstrating greater potential for assessing the therapeutic efficacy of BMSCs.

Purpose: The present study directly compared the quantitative capabilities of regional perfusion and pulmonary functional change assessments among electrocardiography (ECG)- and photoplethysmography (PPG)-monitored phase-resolved functional lung (PREFUL) MRI and dynamic contrast-enhanced (CE) perfusion MRI in thoracic oncologic patients.

Methods: Seventeen thoracic oncologic patients prospectively underwent ECG- and PPG-monitored PREFUL MRI, dynamic CE-perfusion MRI, and pulmonary function tests. ECG- and PPG-monitored perfusion-weighted PREFUL MRI (PW-MRI) and quantitative perfusion maps from dynamic CE-perfusion MRI were generated. Regional perfusions were determined using ROI measurements. For each patient, the overall perfusion from each method was determined as the average ROI measurement value. To determine the relationship between regional perfusion among all methods, Pearson’s correlations were performed. Tukey’s honest significant difference test was performed to compare regional perfusion among ventral, middle, and dorsal slice positions on ECG- and PPG-monitored PW-MRI and quantitative perfusion maps. To assess the pulmonary functional loss evaluation capability of each MRI method, each overall perfusion was correlated with %VC and %FEV₁ using Pearson’s correlation.

Results: The correlation of regional perfusion between ECG- and PPG-monitored PW-MRI was significant and good (r = 0.79, P < 0.0001). However, the correlations between ECG- or PPG-monitored PW-MRI and quantitative perfusion maps were assessed as significant and fair (ECG: r = 0.4, P < 0.0001; PPG: r = 0.36, P < 0.0001). ECG- and PPG-monitored PW-MRI demonstrated significantly higher perfusion than the quantitative perfusion map (P < 0.0001). Furthermore, ECG-and PPG-monitored PW-MRI and quantitative perfusion maps had significant and moderate correlations (%VC: 0.60 ≤ r ≤ 0.63, P < 0.05; %FEV₁: 0.52 ≤ r ≤ 0.69, P < 0.05).

Conclusion: ECG- and PPG-monitored PREFUL MRI had similar potential to dynamic CE-perfusion MRI for quantitatively assessing regional perfusion and pulmonary functional changes in thoracic oncologic patients. Furthermore, PPG-monitored PREFUL MRI showed little difference in regional perfusion evaluation compared with ECG-monitored PREFUL MRI and the potential to play a complementary role in this setting.

Purpose: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder influenced by genetic factors, with a long preclinical phase characterized by subtle alterations in brain microstructure. Although the apolipoprotein E ε4 allele is a well-established genetic risk factor, AD is increasingly recognized as a polygenic condition. However, how polygenic risk manifests in white matter (WM) microstructure and cognition remains unclear. This study aims to investigate the associations between AD polygenic risk scores (ADPRS), WM microstructure, and cognitive performance in clinically asymptomatic adults.

Methods: Data from 36400 individuals (aged 45–83 years) in the UK Biobank were analyzed. Diffusion tensor imaging and neurite orientation dispersion and density imaging metrics were extracted from 48 WM tracts. General linear models were used to examine associations between ADPRS, WM integrity, and 10 cognitive measures. Mediation analyses were conducted to test whether WM microstructure mediated the relationship between ADPRS and cognitive performance.

Results: Higher ADPRS was significantly associated with reduced fractional anisotropy and intracellular volume fraction, and with increased mean, axial, and radial diffusivity, as well as isotropic volume fraction across limbic and association fibers, particularly in the cingulum hippocampus, fornix, posterior thalamic radiation, and superior fronto-occipital fasciculus. Higher ADPRS was also associated with poorer cognitive performance, most prominently on tests of executive function (Trail Making Test B), episodic memory (Paired Associate Learning), and processing speed (Symbol Digit Substitution). Mediation analysis revealed that WM microstructural alterations, especially increased radial diffusivity and reduced fractional anisotropy in the posterior thalamic radiation, partially mediated the association between ADPRS and cognitive performance, accounting for up to 4.88% of the total effect.

Conclusion: ADPRS is linked to selective WM microstructural alterations and subtle cognitive difference in clinically asymptomatic adults. WM microstructural changes partially mediate the association between ADPRS and cognitive performance.

Purpose: Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis. O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation is a critical biomarker for guiding chemotherapy decisions, yet current testing requires invasive tissue sampling. This study aimed to systematically evaluate the diagnostic accuracy of artificial intelligence (AI) models using MRI for non-invasive prediction of MGMT promoter methylation status in GBM.

Methods: We conducted a systematic search of PubMed, ScienceDirect, Scopus, Google Scholar, Cochrane, Web of Science and EMBASE, identifying 480 records. After duplicate removal and screening, 14 studies met inclusion criteria. Data extracted included AI model architecture, MRI sequences, segmentation methods, and diagnostic metrics. A bivariate random-effects model was used to pool sensitivity and specificity. Meta-regression analyses assessed the effect of AI model type on diagnostic performance. Study quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool.

Results: The bivariate random-effects model yielded a pooled sensitivity of 0.536 (95% confidence interval [95% CI]: 0.509–0.563) and a pooled specificity of 0.514 (95% CI: 0.454–0.574), indicating moderate between-study heterogeneity, with an area under the curve of 0.56. The best-performing models included MGMT-net and transformer-based architectures, particularly when using multimodal MRI inputs. Studies employing automated segmentation and single-sequence input (e.g., T2-weighted only) generally demonstrated lower performance. QUADAS-2 assessment indicated a low risk of bias in most domains, with concerns regarding index test thresholds and external validation in some studies.

Conclusion: AI-based MRI models show moderate-to-high potential for non-invasive MGMT methylation prediction in GBM. However, heterogeneity in study design, imaging protocols, and validation approaches highlights the need for standardized methodologies and robust external validation before clinical adoption.

Purpose: The primary objective of this study was to determine the relationship between Wingate test, athletic performance, and MRI parameters in athletes. Additionally, we examined whether there were significant differences in these parameters between athletes and non-athletes during dorsiflexion exercises.

Methods: Twenty-two male athletes and 9 non-athletes performed dorsiflexion exercises with a 4-kg load. MRI scans, including T2* mapping and diffusion tensor imaging, were conducted pre-exercise, immediately after exercise, and 30 minutes post-exercise. Quantitative parameters, including T2* values, fractional anisotropy, mean diffusivity, and eigenvalues (λ2, λ3), were analyzed. Wingate test results and athletics scoring based on the 2022 World Athletics Scoring Tables were used to evaluate anaerobic power and sprint performance.

Results: MRI parameters, particularly T2* changes and λ3, showed significant correlations with Wingate test results and athletic performance. Pre-exercise λ3, reflecting muscle fiber orientation and thickness, emerged as a key predictor of athletic performance alongside T2* changes and Wingate power. The integration of MRI-derived metrics with Wingate test results improved the prediction of athletic scores compared to Wingate power alone. Although differences between athletes and non-athletes in T2* and λ2 were observed, these findings serve as supplementary evidence supporting the role of MRI in identifying muscle characteristics critical for athletic performance.

Conclusion: MRI-derived parameters combined with performance tests can provide valuable insights into muscle recovery, structure, and athletic performance, with potential for predicting athlete scores and optimizing training strategies.

Purpose: This study aims to extend the general kinetic model (GKM) for perfusion signal analysis using multi-pulsed arterial spin labeling (mPASL) acquisitions with multiple post-labeling delays (mPLD). The approach aims to improve accuracy and gain potential for broader experimental and clinical applications.

Methods: The magnetization vector evolution of the mPASL technique was analyzed using sequence diagrams and numerical simulation, supplemented by static phantom experiments. The GKM was adapted to support different configurations of mPASL tagging pulses in “dark” and “bright” methods. The proposed approach was validated on a constant-flow phantom and applied to in-vivo foot perfusion measurements in a cohort of 5 healthy subjects.

Results: Simulations showed that the ratio between “dark” and “bright” mPASL methods is determined by fluid T₁ relaxation time, the number of selective pulses, and labeling efficiency. Experiments with a constant-flow phantom demonstrated that GKM with mPASL enables semi-quantitative perfusion analysis, providing high-temporal-resolution perfusion curves. Estimated perfusion coefficients of constant flow phantom were consistent across acquisitions (5.1% variation), confirming the robustness of the GKM extension for mPASL with multiple post-labeling delays. However, in-vivo results deviated from simulation and constant flow experiments, highlighting potential physiological complexities, and model limitations.

Conclusion: Extending the GKM to mPASL acquisitions demonstrates reliable performance under controlled constant flow conditions. Phantom experiments confirmed the accuracy of the approach, while in-vivo measurements in feet revealed deviations from simulation and constant flow results, suggesting the need to account for physiological factors and potential model extension due to pulsatile flow.

The interpretation of abdominal diffusion images remains difficult because different types of tissue coexist within each voxel. In this study, we estimated the distribution of the diffusion coefficient (D) within each voxel using non-negative least squares from diffusion-weighted images with multiple b-values. Additionally, a method for visualizing the results as a set of images representing the D ranges was developed. This method was tested on healthy volunteers.

Purpose: Acupuncture is believed to significantly modify neural circuits in the brain. However, the effects of moxibustion stimulation remain unclear. Therefore, we used functional MRI to investigate brain activation sites induced by moxibustion stimulation using an electric moxibustion device that mimics Japanese Tonetsu-kyu half-grain-sized direct moxibustion.

Methods: Twenty-two healthy adult participants underwent 6 rounds of 7-s moxibustion stimulations on the right acupuncture point ST36 using electric moxibustion during functional MRI measurement. The maximum output temperature of electric moxibustion was 67.5°C. However, the contact surface temperature was adjusted to 58.6 ± 0.1°C using cooking wrap to avoid small burns caused by heating. The ON time was divided into 3 periods: ON1, 2s from the start of moxibustion stimulation (<45°C); ON2, 5s from 2s after the start of output to the end of stimulation (>45°C); and ON3, 3s after the completion of stimulation. Each block was designed with all options other than ON set to OFF.

Results: Common and different activations were observed in all ON times. During stimulation, common activation was observed in the insula, S1, and supramarginal gyrus. Activation in the central operculum, frontal operculum and supplementary motor area was observed only in the ON1 condition, while activation in the frontal pole, cerebellum, and right S2 was observed only in the ON2 condition. Using electric moxibustion that mimics a grain-sized direct moxa cone, common and different activations were confirmed from the start of output to 45°C and above 45°C, and the activation was sustained after the completion of stimulation.

Conclusion: This study showed that moxibustion could affect almost the same areas of pain-related regions. Based on the findings of this study, further research on moxibustion-induced brain activation may help elucidate the mechanism of its therapeutic effects.

Purpose: To compare diagnostic reliability between an intravoxel incoherent motion (IVIM) imaging and an arterial spin labeling (ASL) in assessment of renal blood flow in rodents.

Methods: We first evaluated 3 different fitting methods on 5 datasets of diffusion-weighted imaging (DWI) with 10 b-values (0–1000 s/mm²) for bi-exponential analysis in IVIM imaging to calculate pseudo-diffusion parameters. Coefficient of variation (CV) for each parameter and correlation among the parameters was assessed to test the robustness of the 3 fitting methods. Subsequently, DWI and ASL methods were performed before and 14 days after onset of acute kidney injury (AKI) in a rat model. Temporal change before and after AKI onset in the pseudo-diffusion parameters in 3 fitting methods was compared with that in the renal blood flow (RBF) derived in the ASL method.

Results: The CVs in all IVIM parameters were the lowest in the fitting method that estimated pseudo-diffusion parameters after a fixed true-diffusion was determined where the pseudo- and true-diffusion coefficients had no correlation. The RBF substantially reduced (~50%, P < 0.001) due to the AKI onset; however, no pseudo-diffusion parameters in any of 3 fitting methods could not detect the change. Further, any pseudo-diffusion parameters showed no correlation with the RBF.

Conclusion: Pseudo-diffusion parameters in the IVIM concept were not reliable to estimate RBF in the study. Since the kidney has a unique profile in the “tissue flow”, our data indicate that study design and interpretation of results needs to be carefully considered when IVIM imaging is used for evaluation of blood flow in tissue, especially in the kidney.

Purpose: This study aims to evaluate the predictive value of MRI features for pathologic complete response (pCR) and survival outcomes in patients with breast cancer (BC) undergoing neoadjuvant chemotherapy (NAC).

Methods: A retrospective analysis was conducted on 168 BC patients treated with NAC between 2018 and 2022. Pre-NAC breast MRI scans were evaluated for enhancement patterns, time-intensity curve (TIC), peritumoral edema, and background enhancement. Both pre- and post-NAC MRIs were assessed for Epeak %, mean apparent diffusion coefficient (ADC) value, and ADC ratio (mean ADC of lesion/contralateral normal breast parenchyma). Survival outcomes were analyzed using Kaplan−Meier and Cox regression models.

Results: pCR was achieved in 34% of patients. MRI demonstrated a sensitivity of 74% and a specificity of 86% in predicting pCR, with an overall accuracy of 82%. The post-NAC percentage of initial peak enhancement (Epeak) was significantly lower in the pCR group (P < 0.001). Multivariate analysis identified a pre-NAC Epeak ≤ 96 (hazard ratio [HR]: 6.26, P < 0.001) and a post-NAC Epeak > 188 (HR: 18.40, P < 0.001) as independent risk factors for disease-free survival. Additionally, a lower pre-NAC ADC ratio (≤0.65) was associated with poorer overall survival (HR: 2.8, P: 0.041). Pre-NAC peritumoral edema, background enhancement, and TIC were not significant predictors of survival outcomes.

Conclusion: MRI features, including Epeak % and ADC ratio, are important predictors of pCR and survival outcomes in BC patients undergoing NAC. Incorporating these biomarkers into clinical practice may improve treatment planning and optimize patient outcomes.

Purpose: To evaluate the clinical value of early renal changes in type 2 diabetes mellitus (T2DM) using multiparameter MRI.

Methods: The study included 41 diabetics (normoalbuminuria: n = 23; microalbuminuria: n = 18) and 30 healthy controls. All subjects underwent intravoxel incoherent motion diffusion-weighted imaging (IVIM), blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) examinations. One-way analysis of variance was used to compare MRI parameters among the three groups. Pearson correlation analysis was used to evaluate the relationship between MRI parameters and estimated glomerular filtration rate (eGFR) and albumin–creatinine ratio (ACR). Receiver operating characteristic analysis was performed to assess the diagnostic performance.

Results: There were statistical differences in cortical D, D*, f, renal blood flow (RBF) and medulla D, D*, f, R2* among the three groups (P < 0.05). The cortical or medullary D, cortical f, and RBF were significantly positively correlated with eGFR (all P < 0.01). The cortical or medullary D, D*, f, cortical RBF were negatively correlated with ACR (all P < 0.05).

To evaluate early kidney changes and degree of diabetes, cortical combined D and RBF (AUC [area under the curve]  = 0.796 and 0.947, respectively) was better than single D or RBF (all P > 0.05); medullary combined D and R2* (AUC = 0.899 and 0.923, respectively) was better than single D or R2* (all P > 0.05), except single D (P = 0.005) in differentiating normoalbuminuria group from control group.

Conclusion: The early changes of renal diffusion and perfusion, oxygenation level, and blood flow in T2DM could be evaluated noninvasively and quantitatively using IVIM, BOLD and ASL. Renal medullary combined IVIM-derived D and BOLD-derived R2* and cortical combined IVIM-derived D and ASL-derived RBF were better for evaluating early renal changes in T2DM.

Purpose: This study aimed to evaluate the feasibility of single-shot echo planar diffusion-weighted imaging with compressed SENSE (EPICS-DWI) for pancreas assessment by comparing with single-shot echo planar DWI with parallel imaging (PI-DWI).

Methods: This multicenter prospective study included 27 consecutive participants with untreated pancreatic ductal adenocarcinoma (PDAC) (15 men; mean age, 67 ± 10 years) who underwent pancreatic protocol MRI including both PI-DWI and EPICS-DWI. Two radiologists independently and randomly reviewed the high b-value DWI images and qualitatively assigned confidence scores for overall image quality, image noise, pancreas conspicuity, and PDAC conspicuity using a 5-point scale. One radiologist measured the PDAC-to-pancreas contrast-to-noise-ratio (CNR) on high b-value DWI images and the apparent diffusion coefficient (ADC) value of PDAC. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon signed-rank test.

Results: The confidence scores for overall image quality (P < 0.001 in both radiologists) and image noise (P < 0.001 in both radiologists) were higher in EPICS-DWI than in PI-DWI. The pancreas conspicuity was better in EPICS-DWI than in PI-DWI in one of the radiologists (P = 0.02 and 0.06). The PDAC conspicuity was comparable between PI-DWI and EPICS-DWI (P > 0.99 in both radiologists). The PDAC-to-pancreas CNR was higher in EPICS-DWI than in PI-DWI (P = 0.02), while the ADC value of PDAC in PI-DWI was not significantly different compared to that in EPICS-DWI (P = 0.48).

Conclusion: The image quality and PDAC-to-pancreas CNR was improved in EPICS-DWI compared to PI-DWI. However, the conspicuity and ADC value of PDAC were comparable between PI-DWI and EPICS-DWI.