Purpose: Most existing multi-contrast MRI super-resolution (MCMSR) methods rely on spatial-domain fusion and global attention, overlooking explicit high-frequency (HF) priors while incurring high computational costs. This work addresses these limitations through a general reference-guided MCMSR framework designed for low computational cost, applicable to any contrast pairing rather than a fixed clinical protocol.

Methods: We introduce a wavelet-guided HF prior modeling block for directional-based decomposition and bounded nonlinear enhancement, enabling precise extraction and controlled amplification of anatomical details from both reference and target contrasts. We further introduce a triple cross-contrast fusion module, based on a windowed cross-contrast attention module, to efficiently transfer high-frequency information between contrasts and reduce computational complexity compared to global attention schemes. Additionally, to reduce feature differences across contrasts, a consistent feature fusion module with selective spatial adaptive modulation is incorporated.

Results: Extensive experiments on IXI and M4Raw datasets demonstrate that our proposed windowed cross-contrast attention network (WCCAN) framework consistently outperforms state-of-the-art single and multi-contrast MRI SR methods in terms of quantitative accuracy and visual fidelity. In addition, the WCCAN model achieves lower computational complexity and faster inference time compared to the other MCMSR methods.

Conclusion: The proposed WCCAN framework provides an efficient and accurate solution for MCMSR, demonstrating superior reconstruction quality with reduced computational cost compared to existing methods.

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.

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: This work aims to overcome an assumption of conventional MR simulators: Individual isochromats should be simulated individually.

Methods: To reduce the computational times of MR simulation, a new simulation method using grouped isochromats is proposed. When multiple isochromats are grouped before simulations, some parts of the simulation can be shared in each group. For a certain gradient type, the isochromats in the group can be easily chosen for ensuring that they behave the same. For example, the group can be defined as the isochromats whose locations along x-axis, T1, T2 and magnetic field inhomogeneity values are the same values. In such groups, simulations can be combined when a pulse sequence with the magnetic field gradient along x-axis only are processed. The processing times of the conventional and proposed methods were evaluated with several sequences including echo-planar imaging (EPI) and spiral sequences.

Results: The simulation times of the proposed method were 1.7 to 161 times faster than those of the conventional methods. In the cases of 2.3 billion isochromats using single instruction, multiple data (SIMD) instructions and multi-threading, the conventional method simulated the EPI and spiral sequences in 5526.7 and 15678.4 seconds, respectively. In the same cases, the proposed method simulated these sequences in 652.2 and 8046.2 seconds, respectively.

Conclusion: The proposed method using grouped isochromats was efficient for reducing the computational times of the simulations.

Purpose: MR cholangiopancreatography (MRCP) often suffers from signal loss because of concentrated bile. Gradient-and-spin-echo (GRASE) MRCP reduces this effect but is limited by breath-holding. We developed MRCP with centric order encoding (MRCP-CORE), a novel free-breathing sequence with shorter TE using centric k-space trajectory, T2 preparation, and velocity encoding, and evaluated its ability to visualize gallbladder.

Methods: In this prospective, single-center study, we enrolled 100 consecutive patients who underwent 3 MRCP sequences (MRCP-CORE, conventional MRCP, and GRASE MRCP) on a 3T system. Two blinded radiologists independently assessed the visibility of anatomical structures, artifacts, and overall image quality. SNR, contrast-to-noise ratio, and contrast ratio of the periductal tissue and gallbladder were measured. The Friedman test was used for comparisons; Jonckheere–Terpstra analysis tested the association between the gallbladder visibility and quantitative metrics.

Results: Ninety-nine patients (mean age, 68.5 ± 10.9 years; 52 men, 47 women) were evaluated. MRCP-CORE showed significantly higher SNR than conventional and GRASE MRCP (20.9 vs. 17.3 vs. 15.8; P < 0.001). Gallbladder visibility was significantly higher with MRCP-CORE than via conventional MRCP (P = 0.02) and comparable to that via GRASE MRCP (P = 1.00). No significant differences in artifact and overall image quality were observed among sequences. Trend analysis revealed gallbladder visibility was significantly influenced by bile concentration in conventional MRCP (P < 0.001), but not in MRCP-CORE (P = 0.12) or GRASE MRCP (P = 0.43).

Conclusion: MRCP-CORE enhanced gallbladder depiction compared with conventional MRCP, offering a robust free-breathing alternative to breath-hold GRASE MRCP.

Purpose: To develop a fast and precise method for searching rectangular regions in brain tumor images.

Methods: The authors propose a new method for searching rectangular tumor regions in brain MR images. The proposed method consisted of a segmentation network and a fast search method with a user-controllable search metric. As the segmentation network, the U-Net whose encoder was replaced by the EfficientNet was used. In the fast search method, summed-area tables were used for accelerating sums of voxels in rectangular regions. Use of the summed-area tables enabled exhaustive search of the 3D offset (3D full search). The search metric was designed for giving priority to nearly isotropic rectangles over undesirable thin rectangles, and assigning better values for higher tumor fractions even if they exceeded target tumor fractions. The proposed computation and metric were compared with those used in a conventional method using the Brain Tumor Image Segmentation dataset.

Results: When the 3D full search was used, the proposed computation (8 seconds) was 100–500 times faster than the conventional computation (11–40 minutes). When the user-controllable parts of the search metrics were changed variously, the tumor fractions of the proposed metric were higher than those of the conventional metric. In addition, the conventional metric preferred undesirable thin rectangles whereas the proposed metric preferred nearly isotropic rectangles.

Conclusion: The proposed method is promising for implementing fast and precise search of rectangular tumor regions, which is useful for brain tumor diagnosis using MRI systems. The proposed computation reduced processing times of the 3D full search, and the proposed metric improved the quality of the assigned rectangular tumor regions.

Purpose: To develop and evaluate short-TR acquisition time-of-flight (STRA-TOF) MR angiography (MRA), which combines an optimized STRA with deep learning–based reconstruction to achieve scan-time reduction while maintaining image quality in the visualization of intracranial arteries.

Methods: Ten healthy volunteers and 3 patients with moyamoya disease were examined using 3D TOF MRA with the clinical moyamoya protocol and 2 STRA-TOF protocols employing 4-slab (STRA4) and 9-slab (STRA9) configurations. STRA-TOF employed a TR of approximately 10 ms with variable-density Poisson-disc sampling and unrolled deep learning reconstruction. Bloch equation simulations validated the theoretical basis for STRA. Quantitative assessment included SNR and contrast-to-noise ratio measurements. Two radiologists independently evaluated image quality using a 3-point scale across 9 vascular territories and overall image quality, with blinded assessment. Statistical analysis was performed using the Friedman test with post hoc Wilcoxon signed-rank tests.

Results: STRA-TOF achieved approximately a 50% reduction in scan time compared with conventional protocols. Both STRA sequences demonstrated significantly higher SNR and contrast-to-noise ratio than conventional TOF (P < 0.001). Overall image quality scores were higher for STRA4 and STRA9 compared with conventional TOF in both readers. Across the 9 vascular territories, both readers consistently rated STRA sequences equal to or superior to conventional TOF, particularly for distal branches. In the small patient cohort with moyamoya disease (n = 3), STRA-TOF demonstrated feasibility for visualizing complex arterial pathology, including stenotic vessels, collateral circulation, and postsurgical vascular changes.

Conclusion: STRA-TOF achieved approximately a 50% reduction in scan time while maintaining or improving image quality compared with conventional 3D TOF MRA. This technique addresses the fundamental scan-time limitations of the conventional method, with potential for significant clinical benefits in terms of patient comfort, workflow efficiency, and improved access to intracranial artery evaluation.

Purpose: The ability to accurately detect and characterize intramammary micro- and macrocalcifications without ionized radiation has significant clinical implications for early breast cancer assessment. The aim of this prospective study was to investigate the feasibility of detecting intramammary calcifications using 3D multi-echo gradient echo (ME-GRE) magnitude and true susceptibility-weighted images (tSWI) compared to digital mammography (DM) in patients with different breast sizes and densities of breast parenchyma at 1.5T.

Methods: Two board-certified radiologists evaluated digital mammograms of 70 patients and compared them to the corresponding SW-based images concerning detection of intramammary calcifications and determination of their sizes. The clinical performance of both SW-based techniques in accurately detecting and assessing intramammary calcifications was determined. In addition an interobserver agreement was performed.

Results: Compared to DM, visualization of calcification lesions using both SW-based techniques is influenced by: 1) Morphology (shape and homogeneity) of calcifications; 2) Spatial arrangement of calcifications. Closely adjacent calcifications may not be distinguishable in the SW-based images as individual lesions. Overlapping susceptibility effects resulted in a single, larger lesion; 3) The (in-phase or out-of-phase cycle) echo time value selected in the imaging protocol plays a crucial role in visualizing the lesions; and 4) Lesion size was overestimated by up to 2.0 mm when comparing SW-based techniques to DM. An almost perfect interobserver agreement was found for the analysis. Microcalcifications could not be visualized. A sensitivity of 13.0% and specificity of 99.7% for the diagnosis of macrocalcifications could be provided with both SW-based techniques.

Conclusion: Our findings highlight the potentials and limitations of SW-based techniques at 1.5 T for characterizing intramammary micro- and macrocalcifications. The high specificity of SW-based techniques in combination with higher magnetic field strengths could revolutionize breast cancer screening and management.

This study presents a novel data augmentation approach to improve deep learning (DL)-based segmentation for 3D phase-contrast magnetic resonance angiography (PC-MRA) images affected by pulsation artifacts. Augmentation was achieved by simulating pulsation artifacts through the addition of periodic errors in k-space magnitude. The approach was evaluated on PC-MRA datasets from 16 volunteers, comparing DL segmentation with and without pulsation artifact augmentation to a level-set algorithm. Results demonstrate that DL methods significantly outperform the level-set approach and that pulsation artifact augmentation further improves segmentation accuracy, especially for images with lower velocity encoding. Quantitative analysis using Dice-Sørensen coefficient, Intersection over Union, and Average Symmetric Surface Distance metrics confirms the effectiveness of the proposed method. This technique shows promise for enhancing vascular segmentation in various anatomical regions affected by pulsation artifacts, potentially improving clinical applications of PC-MRA.

Purpose: Diffusion models (DMs) excel in pixel-level and spatial tasks and are proven feature extractors for 2D image discriminative tasks when pretrained. However, their capabilities in 3D MRI discriminative tasks remain largely untapped. This study seeks to assess the effectiveness of DMs in this underexplored area.

Methods: We use 59830 T1-weighted MR images (T1WIs) from the extensive, yet unlabeled, UK Biobank dataset. Additionally, we apply 369 T1WIs from the BraTS2020 dataset specifically for brain tumor classification, and 421 T1WIs from the ADNI1 dataset for the diagnosis of Alzheimer’s disease. Firstly, a high-performing denoising diffusion probabilistic model (DDPM) with a U-Net backbone is pretrained on the UK Biobank, then fine-tuned on the BraTS2020 and ADNI1 datasets. Afterward, we assess its feature representation capabilities for discriminative tasks using linear probes. Finally, we accordingly introduce a novel fusion module, named CATS, that enhances the U-Net representations, thereby improving performance on discriminative tasks.

Results: Our DDPM produces synthetic images of high quality that match the distribution of the raw datasets. Subsequent analysis reveals that DDPM features extracted from middle blocks and smaller timesteps are of high quality. Leveraging these features, the CATS module, with just 1.7M additional parameters, achieved average classification scores of 0.7704 and 0.9217 on the BraTS2020 and ADNI1 datasets, demonstrating competitive performance with that of the representations extracted from the transferred DDPM model, as well as the 33.23M parameters ResNet18 trained from scratch.

Conclusion: We have found that pretraining a DM on a large-scale dataset and then fine-tuning it on limited data from discriminative datasets is a viable approach for MRI data. With these well-performing DMs, we show that they excel not just in generation tasks but also as feature extractors when combined with our proposed CATS module.

Multiparametric quantitative MRI (MP-qMRI) methods, which measure multiple relaxation times simultaneously, are becoming into practical tools, but the relationship between different MP-qMRI methods has not been clarified. In particular, since 2D multidynamic multiple-echo (2D-MDME) was provided by multiple major MRI vendors, many patient studies have been reported, but its relationship with 3D-QALAS (3D-QuAntification using an interleaved Look-Locker Acquisition Sequence with T₂ preparation pulse), which is expected to be its 3D version successor, is unknown. In this study, we implemented 2D-MDME and 3D-QALAS on an originally designed 1.5T and a clinical 3T MRI systems, and measured relaxation times of phantoms, focusing on the effect of magnetization transfer (MT) effect on T₁ measurements. As a result, in 2D-MDME, T₁ shortening effects of around 20%–35% was observed due to the MT effect, and in 3D-QALAS, no effect of the MT effect on the T₁ measurements was observed. Therefore, we concluded that the MT effect needs to be considered when comparing MP-qMRI methods in clinical studies.

Purpose: T₂ values are hypothesized to be reduced where protein accumulates in the cerebrospinal fluid (CSF). We aimed to verify the accuracy of Carr-Purcell-Meiboom-Gil (CPMG) pulses and non-negative least squares (NNLS) analysis in visualizing protein concentrations by mapping the T₂ values.

Methods: We first dissolved 1.2g of bovine serum albumin powder in 4 mL of artificial CSF to purify an albumin solution with a concentration of 4.5 mM. Artificial CSF was added thereto, and eight types of albumin solutions, with concentrations of 0.002–4.5 mM, were purified. We acquired this albumin solution with CPMG pulses and NNLS, decomposed the T₂ values per pixel, and derived 25 T₂ component values of 60–2000 ms. We assessed the change of T₂ values by the difference in albumin concentration of a single voxel. Finally, we used the method to assess T₂ values from two patients, one with a subdural hematoma and one with a suprasellar cystic tumor. T₂ component values were plotted graphically, presented individually, and created in color maps.

Results: T₂ component values for albumin concentrations ranging from 0.056 to 4.55 mM showed different T₂ peaks, whereas, for concentrations 0.002 to 0.019 mM, the peaks were similar heights and overlapped. Peak width was similar for all concentrations. The color maps successfully reflected the changes in T₂ values across both RGB color patterns. T₂ components for albumin samples with 2.5 mM and 6.1 mM concentrations within a single voxel were represented separately and reflected the ratio of the two samples in nine different regions of interest within one slice. In the clinical cases, the T₂ component map imaged differences in albumin concentrations, similar to those observed in the albumin samples.

Conclusion: The present method with CPMG sequences and NNLS provide adequate images to differentiate accumulating protein concentrations in the CSF, even at the level of a single pixel.

Purpose: The aim of our study was to investigate the technical accuracy of susceptibility-weighted imaging (SWI) and quantitative susceptibility mapping (QSM) created to detect intramammary-like calcifications depending on different TEs, volume, and type of calcification samples at 1.5T.

Methods: Jello-embedded particles of blackboard chalk and ostrich eggshell ranging in size from 4 to 25 mm² were used to simulate intramammary calcifications after testing different base substances and calcifications for their suitability to be used in breast phantoms. Breast phantoms were systematically examined using CT and an optimized 3D multi-echo gradient echo pulse sequence with following parameters: TR/TE, 22/1.88–15.52 ms in 1.24 ms increments; reconstructed voxel, 0.5 × 0.5 × 1.1 mm³; receiver bandwidth, 1120 Hz/Px; flip angle, 15°; integrated parallel imaging technique with a GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA) factor of 2/24; and a total acquisition time of 3:00 min. A qualitative evaluation of the dependence of the visualization of calcification samples on volume and TE value was followed by a calculation of the SNR, the contrast-to-noise ratio (CNR) and the creation of SWI and QSM in the sense of a (semi)-quantitative analysis of the images.

Results: Jello proved to be a suitable base substance for preparing breast phantoms for SW MRI. Blackboard chalk and ostrich eggshell proved to be suitable for mimicking intramammary-like calcifications. The decrease in the median SNR of the blackboard chalk samples was significantly higher than the corresponding value of the ostrich eggshell samples over the entire TE range (47.5 to 17.0 vs. 16.0 to 6.56, P < 0.0001). The increase in the median CNR of the blackboard chalk samples was significantly higher than the corresponding value of the ostrich eggshell samples over the entire TE range (2.46 to 35.0 vs. 20.2 to 36.8, P = 0.007). With increasing TE value, the signal void volume of the calcification particle increases in the magnitude images as well as in SWI and QSM. Due to the blooming effect, the median gradients of the TE-based changes in signal void volumes were higher in SWI than in magnitude images and in QSM, regardless of the type of calcification particle examined. The maximum magnetic susceptibility of ostrich eggshell samples varied in a TE range of 1.88 to 15.52 ms from −7.2 to −2.51 ppm and that of blackboard chalk from −2.0 to −1.7 ppm. Compared to the manually measured volumes of the calcification particles, both MR-based measurements and CT examinations overestimated the actual sample size. The (non)-significant overestimation in the MRI-data is dependent on the set TE. The CT-based hyperdense volumes were overestimated compared to the corresponding manually measured sample volumes in a range of 109.8%–315.2% for ostrich eggshell samples (P = 0.016) and in a range of 39.9%–156.4% for blackboard chalk samples (P = 0.69).

Conclusion: Our systematic in-vitro investigation of magnitude images, SWI, and QSM revealed that various set TE values, different volumes, and compositions of calcifications have a significant impact on visualizing intramammary(-like) calcifications.

The quantitative analysis of pulsed-chemical exchange saturation transfer (CEST) using a full model-based method is computationally challenging, as it involves dealing with varying RF values in pulsed saturation. A power equivalent continuous approximation of B₁ power was usually applied to accelerate the analysis. In line with recent consensus recommendations from the CEST community for pulsed-CEST at 3T, particularly recommending a high RF saturation power (B₁ = 2.0 µT) for the clinical application in brain tumors, this technical note investigated the feasibility of using average power (AP) as the continuous approximation. The simulated results revealed excellent performance of the AP continuous approximation in low saturation power scenarios, but discrepancies were observed in the z-spectra for the high saturation power cases. Cautions should be taken, or it may lead to inaccurate fitted parameters, and the difference can be more than 10% in the high saturation power cases.

Purpose: We developed new deep learning-based hierarchical brain segmentation (DLHBS) method that can segment T1-weighted MR images (T1WI) into 107 brain subregions and calculate the volume of each subregion. This study aimed to evaluate the repeatability and reproducibility of volume estimation using DLHBS and compare them with those of representative brain segmentation tools such as statistical parametric mapping (SPM) and FreeSurfer (FS).

Methods: Hierarchical segmentation using multiple deep learning models was employed to segment brain subregions within a clinically feasible processing time. The T1WI and brain mask pairs in 486 subjects were used as training data for training of the deep learning segmentation models. Training data were generated using a multi-atlas registration-based method. The high quality of training data was confirmed through visual evaluation and manual correction by neuroradiologists. The brain 3D-T1WI scan–rescan data of the 11 healthy subjects were obtained using three MRI scanners for evaluating the repeatability and reproducibility. The volumes of the eight ROIs—including gray matter, white matter, cerebrospinal fluid, hippocampus, orbital gyrus, cerebellum posterior lobe, putamen, and thalamus—obtained using DLHBS, SPM 12 with default settings, and FS with the “recon-all” pipeline. These volumes were then used for evaluation of repeatability and reproducibility.

Results: In the volume measurements, the bilateral thalamus showed higher repeatability with DLHBS compared with SPM. Furthermore, DLHBS demonstrated higher repeatability than FS in across all eight ROIs. Additionally, higher reproducibility was observed with DLHBS in both hemispheres of six ROIs when compared with SPM and in five ROIs compared with FS. The lower repeatability and reproducibility in DLHBS were not observed in any comparisons.

Conclusion: Our results showed that the best performance in both repeatability and reproducibility was found in DLHBS compared with SPM and FS.

Purpose: The present study aimed to investigate whether diffusion-weighted imaging (DWI) can qualify and quantify cerebrospinal fluid (CSF) dynamics in the brains of healthy subjects. For this purpose, we developed new DWI-based fluidography and compared the CSF dynamics seen on the fluidography with two apparent diffusion coefficients obtained with different DWI signal models at anatomical spaces filled by CSF.

Methods: DWI with multiple b values was performed for 10 subjects using a 7T MRI scanner. DWI-fluidography based on the DWI signal variations in different motion probing gradient directions was developed for visualizing the CSF dynamics voxel-by-voxel. DWI signals were measured using an ROI in the representative CSF-filled anatomical spaces in the brain. For the multiple DWI signals, the mono-exponential and kurtosis models were fitted and two kinds of apparent diffusion coefficients (ADC_C and ADC_K) were estimated in each space using the Gaussian and non-Gaussian diffusion models, respectively.

Results: DWI-fluidography could qualitatively represent the features of CSF dynamics in each anatomical space. ADCs indicated that the motions at the foramen of Monro, the cistern of the velum interpositum, the quadrigeminal cistern, the Sylvian cisterns, and the fourth ventricle were more drastic than those at the subarachnoid space and anterior horns of the lateral ventricle. Those results seen in ADCs were identical to the findings on DWI-fluidography.

Conclusion: DWI-fluidography based on the features of DWI signals could show differences of CSF dynamics among anatomical spaces.

Purpose: Neuromelanin is visualized by optimizing the conditions of longitudinal relaxation (T1)-weighted imaging (T1WI). Although it was originally developed in 2D imaging, 3D imaging has been also reported, and T1WI sequences with magnetization transfer (MT) pulses are now widely used in 3D gradient echo (GRE) sequences. In this study, we assert that the use of spectral presaturation with inversion recovery (SPIR) may also be useful as an alternative to MT pulses, and we optimize SPIR and compare it with MT.

Methods: Neuromelanin images with MT pulse and SPIR (flip angles [FAs] = 19º, 22º, and 25º) were acquired from 30 healthy volunteers. To achieve the same acquisition time of 5 min, the slab thickness of the MT images was less than 1/3 of those of the SPIR images; the acquisition areas for MT and SPIR were the brainstem and the whole brain, respectively. Visual and quantitative evaluation was performed and compared on the four sequences acquired for the substantia nigra pars compacta (SNc) and the locus coeruleus (LC). For visual assessment, we used the mean score from a 3-point scale by two evaluators. For quantitative evaluation, the contrast ratios of SNc and LC were calculated in comparison with the background tissue signal.

Results: In visual assessments, the mean scores of the SPIR FA19º and FA22º images were better than others in the SNc. Regarding LC, the SPIR FA22º image yielded the best mean score. In quantitative evaluations, the MT image was significantly lower than the other three images in SNc. Regarding LC, there were no significant differences among the four acquired images (MT and SPIR FA19º, FA22º, and FA25º).

Conclusions: Detection of neuromelanin in SNc and LC was improved by the use of SPIR compared to MT pulse in 3D neuromelanin imaging.

Purpose: Polarity-corrected inversion time preparation (PCTIP), a myocardial T1 mapping technique, is expected to reduce measurement underestimation in the modified Look-Locker inversion recover method. However, measurement precision is reduced, especially for heart rate variability. We devised an analysis using a recurrence formula to overcome this problem and showed that it improved the measurement accuracy, especially at high heart rates. Therefore, this study aimed to determine the effect of this analysis on the accuracy and precision of T1 measurements for irregular heart rate variability.

Methods: A PCTIP scan using a 3T MRI scanner was performed in phantom experiment. We generated the simulated R-waves required for electrocardiogram (ECG)-gated acquisition using a signal generator set to 30 combinations. T1 map was generated using the signal train of the PCTIP images by nonlinear curve fitting using conventional and recurrence formulas. Accuracy against reference T1 and precision of heart rate variability were evaluated. To evaluate the fitting accuracy of both analyses, the relative fitting error was calculated.

Results: For the longer T1, the fitting error was larger than the short T1, with the conventional analysis showing 10.1±2.0%. The recurrence formula analysis showed a small fitting error less than 1%, which was consistent for all heart rate variability patterns. In the conventional analysis, the accuracy, especially for longer T1, showed a large underestimation of the measurements and poor linearity. However, in the recurrence formula analysis, the accuracy improved at a long T1, and linearity also improved. The Bland–Altman plot showed that it varied greatly depending on the heart rate variability pattern for the longer T1 in the conventional analysis, whereas the recurrence formula analysis suppressed this variation.

Conclusion: T1 analysis of PCTIP using the recurrence formula analysis achieved accurate and precise T1 measurements, even for irregular heart rate variability.

Gadoxetic acid is both an extracellular- and hepatocyte-specific contrast agent. Signals from the extracellular space may lower the contrast between lesions and the surrounding hepatic parenchyma. To improve hepatocyte-specific enhancement, we developed an intracellular contrast-enhancing fat-saturated T1-weighted gradient-echo nature of the sequence (ICE-TIGRE). It incorporates the motion-sensitized driven-equilibrium (MSDE) pulse to suppress signals from the blood flow. We investigated the optimal ICE-TIGRE scanning parameters, i.e., the order of the MSDE and the fat saturation pulses, the duration time, and the b value of the MSDE pulse, using a phantom and three volunteers without applying gadoxetic acid. ICE-TIGRE successfully increased the contrast between the liver parenchyma and the portal vein. To maintain fat saturation, the preparation pulse order should be MSDE–fat saturation. A duration time of 21 ms should be applied to minimize the effect of the T2 factor on the T1 contrast, and a b value of 60 s/mm² should be applied to maximize the diffusion contrast for ICE-TIGRE with the imaging system used in this study.

Purpose: This study aimed to facilitate research progress in MR elastography (MRE) by providing a versatile and convenient application for MRE reconstruction, namely the MRE research tool (MRE-rTool). It can be used for a series of MRE image analyses, including phase unwrapping, arbitrary bandpass and directional filtering, noise assessment of the wave propagation image (motion SNR), and reconstruction of the elastogram in both 2D and 3D MRE acquisitions. To reinforce the versatility of MRE-rTool, the conventional method of motion SNR was modified into a new method that reflects the effects of image filtering.

Methods: MRE tests of the phantom and liver were performed using different estimation algorithms for stiffness value (algebraic inversion of the differential equation [AIDE], local frequency estimation [LFE] in MRE-rTool, and multimodel direct inversion [MMDI] in clinical reconstruction) and acquiring dimensions (2D and 3D acquisitions). This study also tested the accuracy of masking low SNR regions using modified and conventional motion SNR under various mechanical vibration powers.

Results: The stiffness values estimated using AIDE/LFE in MRE-rTool were comparable to that of MMDI (phantom, 3.71 ± 0.74, 3.60 ± 0.32, and 3.60 ± 0.54 kPa in AIDE, LFE, and MMDI; liver, 2.26 ± 0.31, 2.74 ± 0.16, and 2.21 ± 0.26 kPa in AIDE, LFE, and MMDI). The stiffness value in 3D acquisition was independent of the direction of the motion-encoding gradient and was more accurate than that of 2D acquisition. The masking of low SNR regions using the modified motion SNR worked better than that in the conventional motion SNR for each vibration power, especially when using a directional filter.

Conclusion: The performance of MRE-rTool on test data reached the level required in clinical MRE studies. MRE-rTool has the potential to facilitate MRE research, contribute to the future development of MRE, and has been freely released online.