The purpose of this study was to establish and provide guidelines for the standardized acquisition and interpretation of diffusion-weighted magnetic resonance imaging (DW-MRI) to improve the image quality and reduce the variability of the results interpretation. The standardized protocol includes the use of high-resolution DW-MRI with advanced techniques and post-processing. The aim of the protocol is to increase the effectiveness of the medical image information exchange involved in the construction, activation, and exchange of clinical information for healthcare use. An organized interpretation form could make DW-MRIs' interpretation easier and more familiar. Herein, the authors briefly review the basic principles, optimized image acquisition, standardized interpretation guidelines, false negative and false positive cases of DW-MRI, and provide a standard interpretation form and examples of various cases to help users become more familiar with the DW-MRI.

Purpose: The survival of organisms critically depends on avoidance responses to life-threatening stimuli. Information about dangerous situations needs to be remembered to produce defensive behavior. To investigate underlying brain regions to process information of danger, manganese-enhanced MRI (MEMRI) was used in olfactory fear-conditioned rats. Materials and Methods: Fear conditioning was conducted in male Sprague-Dawley rats. The animals received nasal injections of manganese chloride solution to monitor brain activation for olfactory information processing. Twenty-four hours after manganese injection, rats were exposed to electric foot shocks with odor cue for one hour. Control rats were exposed to the same odor cue without foot shocks. Forty-eight hours after the conditioning, rats were anesthetized and their brains were scanned with 9.4T MRI. Acquired images were processed and statistical analyses were performed using AFNI. Results: Manganese injection enhanced brain areas involved in olfactory information pathways in T1 weighted images. Rats that received foot shocks showed higher brain activation in the central nucleus of the amygdala, septum, primary motor cortex, and preoptic area. In contrast, control rats displayed greater signals in the orbital cortex and nucleus accumbens. Conclusion: Nasal delivery of manganese solution enhanced olfactory signal pathways in rats. Odor cue paired with foot shocks activated amygdala, the central brain region in fear, and related brain circuits. Use of MEMRI in fear conditioning provides a reliable monitoring technique of brain activation for fear learning.

The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm²) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (D_m) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean D_m, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for D_m, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.

Purpose: In this study, we provide a way to assess even a slight effect of exercise on trunk-muscle activity. Materials and Methods: Seven healthy male participants (mean age, 24.7 ± 3.2 years; height, 171.2 ± 9.8 cm; and weight, 63.8 ± 11.9 kg) performed 15 sets of an exercise with 20 repetitions of 90° hip and right-knee flexion while lying supine. The exercise intensity was measured using the 10-point Rating of Perceived Exertion Scale after the first and 15th sets of exercises. Although cross-sectional areas and functional T2 mapping using ultrafast imaging (fast-acquired muscle functional magnetic resonance imaging, fast-mfMRI) have been proposed for imaging to evaluate exercise-induced muscle activity in real time, no previous studies have reported on the evaluation of trunk-muscle activity using functional T2 mapping. As a method for assessing trunk-muscle activity, we compared functional T2 mapping using ultrafast imaging (fast-mfMRI) with cross-sectional areas. Results: Although the muscle cross-sectional areas were increased by the exercise, there was no significant difference at rest. On the other hand, for all sets, the changes in T2 were significant compared with those at rest (P < 0.01). These results demonstrate that T2, calculated from fast-mfMRI images can be used to detect even a small amount of muscle activity induced by acute exercise, which was impossible to do with cross-sectional areas. Conclusion: Fast-mfMRI, which can also display functional information with detailed forms, enabled non-invasive real-time imaging for identifying and evaluating the degree of deep trunk-muscle activity induced by exercise.

Purpose: The aim of this study was to investigate the change in signal sensitivity over different acquisition start times and optimize the scanning window to provide the maximal signal sensitivity of [1-¹³C]pyruvate and its metabolic products, lactate and alanine, using spatially localized hyperpolarized 3D ¹³C magnetic resonance spectroscopic imaging (MRSI). Materials and Methods: We acquired 3D ¹³C MRSI data from the brain (n = 3), kidney (n = 3), and liver (n = 3) of rats using a 3T clinical scanner and a custom RF coil after the injection of hyperpolarized [1-¹³C]pyruvate. For each organ, we obtained three consecutive 3D ¹³C MRSI datasets with different acquisition start times per animal from a total of three animals. The mean signal-to-noise ratios (SNRs) of pyruvate, lactate, and alanine were calculated and compared between different acquisition start times. Based on the SNRs of lactate and alanine, we identified the optimal acquisition start timing for each organ. Results: For the brain, the acquisition start time of 18 s provided the highest mean SNR of lactate. At 18 s, however, the lactate signal predominantly originated from not the brain, but the blood vessels; therefore, the acquisition start time of 22 s was recommended for 3D ¹³C MRSI of the rat brain. For the kidney, all three metabolites demonstrated the highest mean SNR at the acquisition start time of 32 s. Similarly, the acquisition start time of 22 s provided the highest SNRs for all three metabolites in the liver. Conclusion: In this study, the acquisition start timing was optimized in an attempt to maximize metabolic signals in hyperpolarized 3D ¹³C MRSI examination with [1-¹³C] pyruvate as a substrate. We investigated the changes in metabolic signal sensitivity in the brain, kidney, and liver of rats to establish the optimal acquisition start time for each organ. We expect the results from this study to be of help in future studies.

Purpose: To assess clinically significant imaging findings of malignant intramammary lymph nodes (IMLNs) in breast cancer patients and to evaluate their diagnostic performance in predicting malignant IMLN. Materials and Methods: A total of 110 cases with IMLN of BI-RADS category 3 or more, not typical benign IMLN, in MR of breast cancer patients between January 2016 and January 2021 were retrospectively reviewed. After excluding 33 cases, 77 cases were finally included. Among them, 58 and 19 were confirmed as benign and malignant, respectively. Qualitative and quantitative MR imaging features of the IMLN were retrospectively analyzed. Sizes and final assessment categories of IMLN on MRI, mammography, and ultrasound were reviewed. Diagnostic performances of imaging features on MRI, mammography, and ultrasound were then evaluated. Results: For qualitative MR features, shape, margin, and preserved central hilum were significantly different between benign and malignant groups (P < 0.05). For quantitative MR features, long diameter over 6 mm, short diameter over 4 mm, and cortical thickening over 3 mm showed high sensitivities in predicting malignant IMLNs (89.5%, 94.7%, and 100%, respectively). Size exceeding 1 cm showed high specificity and accuracy in predicting malignant IMLN on MR, mammography, and ultrasound (91.4% and 80.5%; 96.6% and 79.25; 98.3% and 80.5%, respectively). Conclusion: Various MR imaging features and size can be helpful for predicting malignant IMLN in breast cancer patients.