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This study aimed to assess the feasibility for applying enhanced acceleration-selective arterial spin labeling (eAccASL) to non-electrocardiogram-gated and non-enhanced peripheral MRA. We compared eAccASL and background suppressed single shot turbo field echo (TFE)-triggered angiography non-contrast-enhanced sequence (BASS TRANCE) required electrocardiographic-gating in eight volunteers and three patients. In the volunteer study, eAccASL demonstrated a comparable arterial visualization compared with BASS TRANCE. In patient observation, the advantages with eAccASL were found in arterial visualization on the collateral vessels and without artifacts affected by arrhythmia events.

Purpose Diffusion-weighted imaging (DWI) plays an important role in the preoperative assessment of gliomas; however, the diagnostic performance of histogram-derived parameters from mono-, bi-, and stretched-exponential DWI models in the grading of gliomas has not been fully investigated. Therefore, we compared these models’ ability to differentiate between high-grade and low-grade gliomas. Methods This retrospective study included 22 patients with diffuse gliomas (age, 23–74 years; 12 males; 11 high-grade and 11 low-grade gliomas) who underwent preoperative 3 T-magnetic resonance imaging from October 2014 to August 2019. The apparent diffusion coefficient was calculated from the mono-exponential model. Using 13 b-values, the true-diffusion coefficient, pseudo-diffusion coefficient, and perfusion fraction were obtained from the bi-exponential model, and the distributed-diffusion coefficient and heterogeneity index were obtained from the stretched-exponential model. Region-of-interests were drawn on each imaging parameter map for subsequent histogram analyses. Results The skewness of the apparent diffusion, true-diffusion, and distributed-diffusion coefficients was significantly higher in high-grade than in low-grade gliomas (0.67 ± 0.67 vs. − 0.18 ± 0.63, 0.68 ± 0.74 vs. − 0.08 ± 0.66, 0.63 ± 0.72 vs. − 0.15 ± 0.73; P = 0.0066, 0.0192, and 0.0128, respectively). The 10th percentile of the heterogeneity index was significantly lower (0.77 ± 0.08 vs. 0.88 ± 0.04; P = 0.0004), and the 90th percentile of the perfusion fraction was significantly higher (12.64 ± 3.44 vs. 7.14 ± 1.70%: P Conclusion The bi-exponential model exhibited the best diagnostic performance for differentiating high-grade from low-grade gliomas.

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.

To evaluate the correlation between HeF obtained from gadoxetic acid-enhanced MR imaging and clinical biomarkers for the assessment of liver function. This prospective study was approved by our Institutional Review Board, and written informed consent was obtained from the patients. We recruited 48 patients carrying a known or suspected liver disease to undergo gadoxetic acid-enhanced MR imaging. The new model of the HeF was calculated from ΔR1 values of the liver and spleen. The HeF, quantitative liver-to-spleen contrast ratio (Q-LSC), and ΔT1 value (the reduction rate of the T1 value between the pre- and post-contrast images) were compared with the Child–Pugh and end-stage liver disease (MELD) scores. Among 48 patients, 40 were in Child–Pugh class A and 8 were in class B. The median HeF (P = 0.0001), Q-LSC (P = 0.015), and ΔT1 value (P = 0.0023) in patients in Child–Pugh class A were significantly higher than those in class B. The sensitivities, specificities, and area under the receiver-operating-characteristic curves for differentiating Child–Pugh class A and B were 95.0%, 87.5%, and 0.93 in the HeF; 77.5%, 75.0%, and 0.78 in the Q-LSC; and 57.5%, 100.0%, and 0.84 in the ΔT1 value, respectively. The HeF was significantly correlated with Child–Pugh (r = − 0.58, P

Purpose Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretable way, in contrast to deep learning (DL) techniques. Methods HC was constructed using mp-MR including intravoxel incoherent motion, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI from 40 tumor and normal tissues in peripheral zone (PZ) and 23 tumor and normal tissues in transition zone (TZ). HC model was optimized by assessing the combinations of several dissimilarity and linkage methods. Goodness of HC model was validated by internal methods. Results Accuracy for differentiating tumor and normal tissue by optimal HC model was 96.3% in PZ and 97.8% in TZ, comparable to current clinical standards. Relationship between input (DWI and permeability parameters) and output (tumor and normal tissue cluster) was shown by heat maps, consistent with literature. Conclusion HC can accurately differentiate PCa and normal tissue, comparable to state-of-the-art diffusion based parameters. Contrary to DL techniques, HC is an operator-independent ML technique producing results that can be interpreted such that the results can be knowledgeably judged.

To evaluate pancreatic T1 mapping and extracellular volume (ECV) fraction’s feasibility to assess impaired glucose tolerance (IGT) patients. A total of 45 consecutive patients with known or suspected pancreatic disease underwent contrast-enhanced magnetic resonance (MR) imaging, including T1 mapping, using saturation recovery sequence. Patients were classified into three groups based on the American Diabetes Association criteria: no-diabetes subjects, HbA1c

To evaluate the feasibility of assessment of microvessel perfusion of pituitary adenomas with intravoxel incoherent motion (IVIM) imaging using single-shot turbo spin-echo-based diffusion-weighted imaging (SS-TSE-DWI). We examined 51 consecutive patients with pituitary adenomas (35 non-functioning and 16 functioning) and 32 patients with normal pituitary glands using SS-TSE-DWI IVIM. The diffusion coefficient (D), the perfusion fraction (f), and the pseudo-diffusion coefficient (D*) were calculated pixel-by-pixel for each adenoma and normal pituitary gland. We also obtained the pathological microvessel area (MVA) of each adenoma. The IVIM parameters in adenomas were compared with those in normal pituitary glands using the Mann–Whitney U test. The correlation between the MVA and IVIM f of adenomas was analyzed using Spearman’s rank correlation coefficient. The mean D (× 10−3 mm2/s) in adenomas was 0.723 ± 0.253, which was significantly lower than that in normal pituitary glands (0.862 ± 0.128; p

To evaluate the feasibility, image quality, and apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) using echo planar imaging (EPI) with Compressed SENSE (EPICS-DWI) of the abdomen and to compare them with conventional single-shot EPI with parallel imaging (PI) technique (PI-DWI).This prospective study included 46 participants with known or suspected upper abdominal diseases (19 men and 27 women, mean age, 68 years) who underwent MRI. DWI acquisition was performed using free-breathing two-dimensional fat-suppressed PI-DWI and EPICS-DWI with SENSE or compressed sensing (CS) factor, 3.0. Moreover, image noise and contour of liver and pancreas were qualitatively evaluated using a five-point scale. The mean ADC value and standard deviation (SD) of the liver, pancreas, and spleen were measured, and the coefficient of variation (CV) was calculated. Qualitative and quantitative parameters were compared between PI-DWI and EPICS-DWI using the Wilcoxon test.The mean image quality scores for image noise and contour of liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P 0.0001). Moreover, the mean ADC values of the liver and pancreas were higher in EPICS-DWI compared with PI-DWI (P 0.0001), but that of spleen was not significantly different. The mean SD and CV of the liver, pancreas, and spleen were lower in EPICS-DWI compared with PI-DWI (P 0.0001-0.032).EPICS-DWI could be feasible in MRI of the abdomen and significantly improve image quality compared with PI-DWI in aggressive setting. ADC value measurements were higher in EPICS-DWI compared with PI-DWI.

This study aims to compare the diagnostic values of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) in differentiating hepatic hemangiomas and liver metastases.This prospective study was approved by our institutional review board, and written informed consent was obtained from all patients. In this study, 244 patients with known or suspected liver disease underwent magnetic resonance imaging. Among them, 37 patients who had focal hepatic lesions with a maximum diameter of ≥10 mm were evaluated. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for the 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 hepatic hemangiomas and liver metastases.In total, 64 focal hepatic lesions were evaluated, of which 22 were identified to be hepatic hemangiomas and 42 were liver metastases. ADC, D, f, and DDC values were significantly lower in liver metastases than in hepatic hemangiomas (P 0.0001, 0.0001, 0.015, and 0.0001, respectively); whereas, the α value was significantly higher in liver metastases than in hepatic hemangiomas (P = 0.028). The areas under the ROC curve (AUCs) for differentiating hepatic hemangiomas and liver metastases in ADC, D, D*, f, DDC, and α were 0.940, 0.908, 0.608, 0.686, 0.952, and 0.667, respectively. The AUC values of ADC and DDC were significantly greater than those of D* (P 0.0001), f (P = 0.0001), and α values (P = 0.0001).ADC and DDC values from the mono-exponential and stretched exponential models could be considered as quantitative imaging biomarkers for differentiating hepatic hemangiomas and liver metastases.

To compare the estimated quantity of intratumor gadoxetic acid retention using T1 mapping of gadoxetic acid-enhanced magnetic resonance imaging (MRI) versus conventional processing methods for the differential diagnosis of focal liver lesions.Seventy patients with hepatic lesions (colorectal metastasis (CRM) [n = 28], hepatocellular carcinoma (HCC) [n = 20], hemangioma [n = 12], and intrahepatic cholangiocarcinoma (ICC) [n = 10]) underwent gadoxetic acid-enhanced MRI, including pre- and post-contrast T1-weighted imaging and T1 mapping. Quantitative analyses included the lesion-to-liver signal intensity ratio (SIR) on hepatobiliary phase images, the pre- and post-contrast lesion T1 value difference (ΔT1 [ms]), and the lesion retention index (LRI [%]), which was the estimated intralesional gadoxetic acid retention calculated on pre- and post-contrast T1 maps using a two-compartment pharmacokinetic model. Results were compared between the four subcategories of focal liver lesions using the Kruskal-Wallis test, followed by the post-hoc Dunn's test and receiver operating characteristic (ROC) analysis to distinguish between pairs of the four lesion subcategories.This study identified significant differences in the LRI of the four lesion subcategories (p 0.01), without significant differences in ΔT1 or SIR. Post-hoc analysis demonstrated significant differences in CRM vs. hemangioma (p 0.01), hemangioma vs. ICC (p 0.01), and HCC vs. ICC (p = 0.047) for the LRI.The quantity of intratumor gadoxetic acid retention estimated using pre- and post- contrast T1 mapping could distinguish focal liver lesions, unlike conventional processing methods, and captured unique lesion characteristics.

Differentiation of glioblastomas (GBMs) and solitary brain metastases (SBMs) is an important clinical problem. The aim of this study was to determine whether amide proton transfer–weighted (APTW) imaging is useful for distinguishing GBMs from SBMs. We examined 31 patients with GBM and 17 with SBM. For each tumor, enhancing areas (EAs) and surrounding non-enhancing areas with T2-prolongation (peritumoral high signal intensity areas, PHAs) were manually segmented using fusion images of the post-contrast T1-weighted and T2-weighted images. The mean amide proton transfer signal intensities (APTSIs) were compared among the EAs, PHAs, and contralateral normal appearing white matter (NAWM) within each tumor type. Furthermore, we analyzed APTSI histograms to compare the EAs and PHAs of GBMs and SBMs. In GBMs, the mean APTSI in EAs (2.92 ± 0.74%) was the highest, followed by that in PHAs (1.64 ± 0.83%, p

Purpose A new sequence for intracranial MRA is developed, named enhanced acceleration-selective arterial spin labeling (eAccASL), to improve main artery visualization at middle cerebral artery (MCA). The aim of this study is to assess the visualization improvement using eAccASL, compared with the previously developed AccASL. Methods eAccASL and AccASL were performed in 8 healthy volunteers and images were compared between the 2 sequences. One patient with Moyamoya disease was evaluated by eAccASL and time of flight. For the volunteer images, vessel visualization was assessed by measuring the contrast-to-noise ratio between MCA M1 to M4 and white matter and by counting the peripheral arteries. Venous artifact level was assessed by measuring the contrast-to-noise ratio between the confluence of the sinuses and white matter and by evaluating cortical vein visualization. For the patient images, qualitative assessment of peripheral and collateral vessel visualization was conducted. Results In the MCA main trunk, higher arterial signal intensity, with reduced flow void, was observed in eAccASL compared with AccASL. Contrast-to-noise ratios of M1 to M3 for eAccASL were significantly higher than those of AccASL. There was no significant difference between AccASL and eAccASL for venous artifact. Conclusion eAccASL could produce better MCA main trunk visualization compared with AccASL, while maintaining good venous signal suppression.