MRI is widely used in clinical practice for detecting liver diseases. Since the introduction of gadoxetic acid, MRI has become the most effective modality for the detection and characterization of focal liver lesions. According to previous meta-analyses, the area under the receiver operating characteristic curve (AUROC) was 0.97–0.99 for the diagnosis of small hepatocellular carcinoma (≥ 2 cm) by gadoxetic-acid-enhanced MRI. Moreover, the AUROC for the diagnosis of colorectal liver metastases was significantly high (0.98). Despite gadoxetic acid’s drawbacks, its clinical utility outweighs them, making it the contrast agent of choice in routine liver MRIs. Moreover, clinically, liver MRI has become more prevalent for a quantitative assessment. Liver fibrosis can be evaluated using MR elastography; whereas, hepatic steatosis and iron overload can be evaluated using proton density fat fraction, with high accuracy and reproducibility. This article reviewed the usefulness of liver MRI, which can be a comprehensive imaging modality in clinical practice.

Free-running 5D whole-heart coronary MR angiography (MRA) is gaining in popularity because it reduces scanning complexity by removing the need for specific slice orientations, respiratory gating, or cardiac triggering. At 3T, a gradient echo (GRE) sequence is preferred in combination with contrast injection. However, neither the injection scheme of the gadolinium (Gd) contrast medium, the choice of the RF excitation angle, nor the dedicated image reconstruction parameters have been established for 3T GRE free-running 5D whole-heart coronary MRA. In this study, a Gd injection scheme, RF excitation angles of lipid-insensitive binominal off-resonance RF excitation (LIBRE) pulse for valid fat suppression and continuous data acquisition, and compressed-sensing reconstruction regularization parameters were optimized for contrast-enhanced free-running 5D whole-heart coronary MRA using a GRE sequence at 3T. Using this optimized protocol, contrast-enhanced free-running 5D whole-heart coronary MRA using a GRE sequence is feasible with good image quality at 3T.

Purpose: Brain MRI with high spatial resolution allows for a more detailed delineation of multiple sclerosis (MS) lesions. The recently developed deep learning-based reconstruction (DLR) technique enables image denoising with sharp edges and reduced artifacts, which improves the image quality of thin-slice 2D MRI. We, therefore, assessed the diagnostic value of 1 mm-slice-thickness 2D T2-weighted imaging (T2WI) with DLR (1 mm T2WI with DLR) compared with conventional MRI for identifying MS lesions.

Methods: Conventional MRI (5 mm T2WI, 2D and 3D fluid-attenuated inversion recovery) and 1 mm T2WI with DLR (imaging time: 7 minutes) were performed in 42 MS patients. For lesion detection, two neuroradiologists counted the MS lesions in two reading sessions (conventional MRI interpretation with 5 mm T2WI and MRI interpretations with 1 mm T2WI with DLR). The numbers of lesions per region category (cerebral hemisphere, basal ganglia, brain stem, cerebellar hemisphere) were then compared between the two reading sessions.

Results: For the detection of MS lesions by 2 neuroradiologists, the total number of detected MS lesions was significantly higher for MRI interpretation with 1 mm T2WI with DLR than for conventional MRI interpretation with 5 mm T2WI (765 lesions vs. 870 lesions at radiologist A, < 0.05). In particular, of the 33 lesions in the brain stem, radiologist A detected 21 (63.6%) additional lesions by 1 mm T2WI with DLR.

Conclusion: Using the DLR technique, whole-brain 1 mm T2WI can be performed in about 7 minutes, which is feasible for routine clinical practice. MRI with 1 mm T2WI with DLR enabled increased MS lesion detection, particularly in the brain stem.

Purpose: This study aimed to evaluate whether the image quality of 1.5T magnetic resonance imaging (MRI) of the knee is equal to or higher than that of 3T MRI by applying deep learning reconstruction (DLR).

Methods: Proton density-weighted images of the right knee of 27 healthy volunteers were obtained by 3T and 1.5T MRI scanners using similar imaging parameters (21 for high resolution image and 6 for normal resolution image). Commercially available DLR was applied to the 1.5T images to obtain 1.5T/DLR images. The 3T and 1.5T/DLR images were compared subjectively for visibility of structures, image noise, artifacts, and overall diagnostic acceptability and objectively. One-way ANOVA and Friedman tests were used for the statistical analyses.

Results: For the high resolution images, all of the anatomical structures, except for bone, were depicted significantly better on the 1.5T/DLR compared with 3T images. Image noise scored statistically lower and overall diagnostic acceptability scored higher on the 1.5T/DLR images. The contrast between lateral meniscus and articular cartilage of the 1.5T/DLR images was significantly higher (5.89 ± 1.30 vs. 4.34 ± 0.87, P < 0.001), and also the contrast between medial meniscus and articular cartilage of the 1.5T/DLR images was significantly higher (5.12 ± 0.93 vs. 3.87 ± 0.56, P < 0.001). Similar image quality improvement by DLR was observed for the normal resolution images.

Conclusion: The 1.5T/DLR images can achieve less noise, more precise visualization of the meniscus and ligaments, and higher overall image quality compared with the 3T images acquired using a similar protocol.

Purpose: The Multi-echo Dixon (ME-Dixon) is a non-invasive quantitative MRI technique to diagnose non-alcoholic fatty liver disease (NAFLD). In this study, the hydrogen proton MR spectroscopy (¹H-MRS) was used as a reference to explore the accuracy of the ME-Dixon technique in evaluating hepatic steatosis in NAFLD patients after ingesting formulated food and its correlation with changes in clinical indicators.

Methods: Twenty-seven patients with NAFLD were enrolled. Fifteen patients completed 12 weeks of treatment with prebiotics and dietary fiber. In addition, abdominal MRI scans and blood tests were performed before and after treatment. The MRI-proton density fat fraction (MRI-PDFF) and MRS-PDFF were measured using the ME-Dixon and ¹H-MRS techniques. The Bland–Altman method and Pearson correlation analysis were used to test the consistency of the two techniques for measuring the liver fat content and the changed values. Besides, correlation analysis was conducted between the MRI-PDFF value and metabolic indicators.

Results: In the PDFF quantification of 42 person-times and the monitoring of the PDFF change in 15 patients under treatment, there was a good consistency and a correlation between MRI and MRS. At baseline, MRI-PDFF was positively correlated with insulin resistance index (HOMA-IR), fatty liver index (FLI), and liver enzymes. After treatment, the changes in MRI-PDFF were positively correlated with the recovery degree of FLI and liver enzymes.

Conclusion: ME-Dixon has a good consistency and a correlation with MRS in quantifying the liver fat content and monitoring the treatment effect, which may be used as an accurate indicator for clinical monitoring of changes in the liver fat content.

Purpose: Myelination-related MR signal changes in white matter are helpful for assessing normal development in infants and children. A rule-based myelination evaluation workflow regarding signal changes on T1-weighted images (T1WIs) and T2-weighted images (T2WIs) has been widely used in radiology. This study aimed to simulate a rule-based workflow using a stacked deep learning model and evaluate age estimation accuracy.

Methods: The age estimation system involved two stacked neural networks: a target network-to extract five myelination-related images from the whole brain, and an age estimation network from extracted T1- and T2WIs separately. A dataset was constructed from 119 children aged below 2 years with two MRI systems. A four-fold cross-validation method was adopted. The correlation coefficient (CC), mean absolute error (MAE), and root mean squared error (RMSE) of the corrected chronological age of full-term birth, as well as the mean difference and the upper and lower limits of 95% agreement, were measured. Generalization performance was assessed using datasets acquired from different MR images. Age estimation was performed in Sturge–Weber syndrome (SWS) cases.

Results: There was a strong correlation between estimated age and corrected chronological age (MAE: 0.98 months; RMSE: 1.27 months; and CC: 0.99). The mean difference and standard deviation (SD) were −0.15 and 1.26, respectively, and the upper and lower limits of 95% agreement were 2.33 and −2.63 months. Regarding generalization performance, the performance values on the external dataset were MAE of 1.85 months, RMSE of 2.59 months, and CC of 0.93. Among 13 SWS cases, 7 exceeded the limits of 95% agreement, and a proportional bias of age estimation based on myelination acceleration was exhibited below 12 months of age (P = 0.03).

Conclusion: Stacked deep learning models automated the rule-based workflow in radiology and achieved highly accurate age estimation in infants and children up to 2 years of age.

Clinical MRI systems have continually improved over the years since their introduction in the 1980s. In MRI technical development, the developments in each MRI system component, including data acquisition, image reconstruction, and hardware systems, have impacted the others. Progress in each component has induced new technology development opportunities in other components. New technologies outside of the MRI field, for example, computer science, data processing, and semiconductors, have been immediately incorporated into MRI development, which resulted in innovative applications. With high performance computing and MR technology innovations, MRI can now provide large volumes of functional and anatomical image datasets, which are important tools in various research fields. MRI systems are now combined with other modalities, such as positron emission tomography (PET) or therapeutic devices. These hybrid systems provide additional capabilities.

In this review, MRI advances in the last two decades will be considered. We will discuss the progress of MRI systems, the enabling technology, established applications, current trends, and the future outlook.

The central nervous system (CNS) was previously thought to be the only organ system lacking lymphatic vessels to remove waste products from the interstitial space. Recently, based on the results from animal experiments, the glymphatic system was hypothesized. In this hypothesis, cerebrospinal fluid (CSF) enters the periarterial spaces, enters the interstitial space of the brain parenchyma via aquaporin-4 (AQP4) channels in the astrocyte end feet, and then exits through the perivenous space, thereby clearing waste products. From the perivenous space, the interstitial fluid drains into the subarachnoid space and meningeal lymphatics of the parasagittal dura. It has been reported that the glymphatic system is particularly active during sleep. Impairment of glymphatic system function might be a cause of various neurodegenerative diseases such as Alzheimer’s disease, normal pressure hydrocephalus, glaucoma, and others. Meningeal lymphatics regulate immunity in the CNS. Many researchers have attempted to visualize the function and structure of the glymphatic system and meningeal lymphatics in vivo using MR imaging. In this review, we aim to summarize these in vivo MR imaging studies and discuss the significance, current limitations, and future directions. We also discuss the significance of the perivenous cyst formation along the superior sagittal sinus, which is recently discovered in the downstream of the glymphatic system.

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.

In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).

Cells in the tissues and organs of a living body are subjected to mechanical forces, such as pressure, friction, and tension from their surrounding environment. Cells are equipped with a mechanotransduction mechanism by which they perceive mechanical forces and transmit information into the cell interior, thereby causing physiological or pathogenetic mechano-responses. Endothelial cells (ECs) lining the inner surface of blood vessels are constantly exposed to shear stress caused by blood flow and a cyclic strain caused by intravascular pressure. A number of studies have shown that ECs are sensitive to changes in these hemodynamic forces and alter their morphology and function, sometimes by modifying gene expression. The mechanism of endothelial mechanotransduction has been elucidated, and the plasma membrane has recently been shown to act as a mechanosensor. The lipid order and cholesterol content of plasma membranes change immediately upon the exposure of ECs to hemodynamic forces, resulting in a change in membrane fluidity. These changes in a plasma membrane’s physical properties affect the conformation and function of various ion channels, receptors, and microdomains (such as caveolae and primary cilia), thereby activating a wide variety of downstream signaling pathways. Such endothelial mechanotransduction works to maintain circulatory homeostasis; however, errors in endothelial mechanotransduction can cause abnormalities in vascular physiological function, leading to the initiation and progression of various vascular diseases, such as hypertension, thrombosis, aneurysms, and atherosclerosis. Recent advances in detailed imaging technology and computational fluid dynamics analysis have enabled us to evaluate the hemodynamic forces acting on vascular tissue accurately, contributing greatly to our understanding of vascular mechanotransduction and the pathogenesis of vascular diseases, as well as the development of new therapies for vascular diseases.

Purpose: To compare the quality of dynamic imaging between stack-of-stars acquisition without breath-holding (DISCO-Star) and the breath-holding method (Cartesian LAVA and DISCO).

Methods: This retrospective study was conducted between October 2019 and February 2020. Two radiologists performed visual assessments of respiratory motion or pulsation artifacts, streak artifacts, liver edge sharpness, and overall image quality using a 5-point scale for two datasets: Dataset 1 (n = 107), patients with Cartesian LAVA and DISCO-Star; Dataset 2 (n = 41), patients with DISCO and DISCO-Star at different time points. Diagnosable image quality was defined as ≥ 3 points in overall image quality. Whether the scan timing of the arterial phase (AP) was appropriate was evaluated, and results between the pulse sequences were compared. In cases of inappropriate scan timing in the DISCO-Star group, retrospective reconstruction with a high frame rate (80 phases, 3 s/phase) was added.

Results: The overall image quality of Cartesian LAVA was better than that of DISCO-Star in AP. However, noninferiority was shown in the ratio of diagnosable images between Cartesian LAVA and DISCO-Star in AP. There was no significant difference in the ratio of appropriate scan timing between DISCO-Star and Cartesian LAVA; however, the ratio of appropriate scan timing in DISCO-Star with high frame rate reconstruction was significantly higher than that in Cartesian LAVA in both readers. Overall image quality scores between DISCO and DISCO-Star were not significantly different in AP. There was no significant difference in the ratio of appropriate scan timing between DISCO-Star with high frame rate reconstruction and DISCO in both readers.

Conclusion: The use of DISCO-Star with high frame rate reconstruction is a good solution to obtain appropriate AP scan timing compared with Cartesian LAVA. DISCO-Star showed equivalent image quality in all phases and in the ratio of appropriate AP scan timing compared with DISCO.

Purpose: The purpose of the current study was to clarify the blood flow pattern in the left atrium (LA), potentially causing the formation of thrombosis after left upper lobectomy (LUL). The blood flow in the LA was evaluated and compared between LUL patients with and without thrombosis. For the evaluation, we applied highly accelerated 4D flow MRI with dual-velocity encoding (VENC) scheme, which was expected to be able to capture slow flow components in the LA accurately.

Methods: Eight volunteers and 18 patients subjected to LUL underwent dual-VENC 4D Flow MRI. Eight patients had a history of thrombosis. We measured the blood flow velocity and stasis ratio (proportion in the volume that did not exceed 10 cm/s in any cardiac phase) in the LA and left superior pulmonary vein (LSPV) stump. For visual assessment, the presence of each collision of the blood flow from pulmonary veins and vortex flow in the LA were evaluated. Each acquired value was compared between healthy participants and LUL patients, and in LUL patients with and without thrombosis.

Results: In LUL patients, blood flow velocity near the inflow part of the left superior pulmonary vein (Lt Upp) and mean velocity in the LA were lower, and stasis ratio in the LA was higher compared with healthy volunteers (Lt Upp 9.10 ± 3.09 vs.13.23 ± 14.19 cm/s, mean velocity in the LA 9.81 ± 2.49 vs. 11.40 ± 1.15 cm/s, and stasis ratio 25.28 ± 18.64 vs. 4.71 ± 3.03%, P = 0.008, 0.037, and < 0.001). There was no significant difference in any quantification values between LUL patients with and without thrombosis. For visual assessment, the thrombus formation was associated with no collision pattern (62.5% vs. 10%, P = 0.019) and not with vortex flow pattern (50% vs. 30%, P = 0.751).

Conclusion: The net blood flow velocity was not associated with the thrombus formation. In contrast, a specific blood flow pattern, the absence of blood flow collision from pulmonary veins, correlates to the thrombus formation in the LA.