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.

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

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.

Purpose: MRI of endolymphatic hydrops (EH) 4 h after intravenous administration of a single dose of gadolinium-based contrast agent is used for clinical examination in some institutions; however, further improvement in image quality would be valuable for wider clinical utility. Denoising using deep learning reconstruction (Advanced Intelligent Clear-IQ Engine [AiCE]) has been reported for CT and MR. The purpose of this study was to compare the contrast-to-noise ratio of endolymph to perilymph (CNR_EP) between the improved hybrid of reversed image of the positive endolymph signal and the native image of the perilymph signal multiplied with the heavily T₂-weighted MR cisternography (iHYDROPS-Mi2) images, which used AiCE for the three source images (i.e. positive endolymph image [PEI], positive perilymph image [PPI], MR cisternography [MRC]) to those that did not use AiCE. We also examined if there was a difference between iHYDROPS-Mi2 images with and without AiCE for degree of visual grading of EH and in endolymphatic area [EL] ratios.

Methods: Nine patients with suspicion of EH were imaged on a 3T MR scanner. iHYDROPS images were generated by subtraction of PEI images from PPI images. iHYDROPS-Mi2 images were then generated by multiplying MRC with iHYDROPS images. The CNR_EP and EL ratio were measured on the iHYDROPS-Mi2 images. Degree of radiologist visual grading for EH was evaluated.

Results: Mean CNR_EP ± standard deviation was 1681.8 ± 845.2 without AiCE and 7738.6 ± 5149.2 with AiCE (P = 0.00002). There was no significant difference in EL ratio for images with and without AiCE. Radiologist grading for EH agreed completely between the 2 image types in both the cochlea and vestibule.

Conclusion: The CNR_EP of iHYDROPS-Mi2 images with AiCE had more than a fourfold increase compared with that without AiCE. Use of AiCE did not adversely affect radiologist grading of EH.

To accelerate high-resolution diffusion-weighted imaging with a multi-shot echo-planar sequence, we propose an approach based on reduced averaging and deep learning. Denoising convolutional neural networks can reduce amplified noise without requiring extensive averaging, enabling shorter scan times and high image quality. The preliminary experimental results demonstrate the superior performance of the proposed denoising method over state-of-the-art methods such as the widely used block-matching and 3D filtering.

Purpose: To compare the diagnostic value of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) for differentiating benign and malignant hepatic lesions.

Methods: This prospective study was approved by our Institutional Review Board and the patients provided written informed consent. Magnetic resonance imaging was acquired for 56 patients with suspected liver disease. This identified 90 focal liver lesions with a maximum diameter >10 mm, of which 47 were benign and 43 were malignant. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for three models: the apparent diffusion coefficient (ADC) from a mono-exponential model; the true diffusion coefficient (D), pseudo-diffusion coefficient (D^*), and perfusion fraction (f) from a bi-exponential model; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) from a stretched exponential model. The parameters were compared between benign and malignant hepatic lesions.

Results: ADC, D, D^*, f, and DDC values were significantly lower for malignant hepatic lesions than for benign lesions (P < 0.0001–0.03). Although logistic regression analysis demonstrated that DDC was the only statistically significant parameter for differentiating benign and malignant lesions (P = 0.039), however, the areas under the receiver operating characteristic curve for differentiating benign and malignant lesions were comparable between ADC (0.98) and DDC (0.98) values.

Conclusion: DDC values obtained from the stretched exponential model could be also used as a quantitative imaging biomarker for differentiating benign and malignant hepatic lesions, however, the diagnostic performance was comparable with ADC values.

Since the first pioneering report of hyperpolarized [1-¹³C]pyruvate magnetic resonance imaging (MRI) of the Warburg effect in prostate cancer patients, clinical dissemination of the technique has been rapid; close to 10 sites worldwide now possess a polarizer fit for the clinic, and more than 30 clinical trials, predominantly for oncological applications, are already registered on the US and European clinical trials databases. Hyperpolarized ¹³C probes to study pathophysiological processes beyond the Warburg effect, including tricarboxylic acid cycle metabolism, intra-cellular pH and cellular necrosis have also been demonstrated in the preclinical arena and are pending clinical translation, and the simultaneous injection of multiple co-polarized agents is opening the door to high-sensitivity, multi-functional molecular MRI with a single dose. Here, we review the biomedical applications to date of the two polarization methods that have been used for in vivo hyperpolarized ¹³C molecular MRI; namely, dissolution dynamic nuclear polarization and parahydrogen-induced polarization. The basic concept of hyperpolarization and the fundamental theory underpinning these two key ¹³C hyperpolarization methods, along with recent technological advances that have facilitated biomedical realization, are also covered.

T₂-fluid-attenuated inversion recovery images (FLAIR) mismatch sign is now known to be a specific yet insensitive image feature for IDH-mutant, 1p19q non-codeleted astrocytoma. The current study revealed that lesion presenting T₂-FLAIR mismatch exhibited extremely long T₁- and T₂-relaxation time while T₂-FLAIR matched lesions showed low to moderate values. On the other hand, IDH-wildtype tumors presented noticeably short T₁- and T₂-relaxation time. These different relaxation time characteristics seemed to render T₂-FLAIR mismatch sign of becoming such a unique and specific image feature for IDH-mutant, 1p19q non-codeleted astrocytoma.