Purpose: To compare four free-breathing scan techniques for gadoxetic acid-enhanced hepatobiliary phase imaging with conventional breath-hold scans.

Materials and Methods: Gadoxetic acid-enhanced hepatobiliary phase imaging with six image acquisition sets performed in 50 patients. Image acquisition sets included fat-suppressed 3D T₁-weighted turbo field echo with free-breathing pseudo-golden-angle radial stack-of-stars (FBRS) acquisition, FBRS with track (FBRS_T), FBRS with gate and track (FBRS_G&T), thin-slice FBRS with gate and track (thin-slice FBRS_G&T), free-breathing Cartesian acquisition (Cartesian_FB), and breath-hold Cartesian acquisition (Cartesian_BH). Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and image quality compared to the six-image acquisition sets.

Results: Signal-to-noise ratio and CNR were significantly higher in FBRS, FBRS_T, FBRS_G&T, and thin-slice FBRS_G&T than in Cartesian_FB and Cartesian_BH (P < 0.001). Based on sharpness, motion artifacts, visibility of intrahepatic vessels, and overall image quality, thin-slice FBRS_G&T had the highest image quality followed by Cartesian_BH and FBRS_G&T (P < 0.001). Severe motion artifacts were observed in 25 patients in Cartesian_FB and three patients in Cartesian_BH, whereas image quality remained above the acceptable range in FBRS_G&T, FBRS_T, FBRS, and thin-slice FBRS_G&T in all cases.

Conclusion: Thin-slice FBRS_G&T demonstrated excellent image quality compared with conventional Cartesian_BH in gadoxetic acid-enhanced hepatobiliary phase imaging. It can be apply to supplemental sequences of patients with unstable breath holding.

Purpose: We sought to use non-contrast-enhanced T₁ mapping to determine the native T₁ values required to identify myocardial fibrosis in patients with dilated cardiomyopathy (DCM).

Methods: A total of 25 patients with DCM and 15 healthy controls were enrolled. All subjects underwent T₁ mapping using modified look–locker inversion recovery, and the patients underwent late gadolinium-enhancement (LGE) imaging. Basal and mid-ventricular levels were divided into eight segments and the T₁ value was measured in each segment. The T₁ values of septal segments with LGE were compared with those of the septal segments without LGE, the minimum T₁ value of each patient, and the T₁ values of the normal septal myocardium.

Results: Late gadolinium-enhancement was present in 12 septal segments (24.0%) from 10 patients (40.0%). T₁ values were significantly higher in septal segments with LGE than in those without (1373.7 vs. 1288.0 ms; P = 0.035) or in normal septal myocardium (1209.1 ms; P < 0.01). A receiver operating characteristic analysis revealed the appropriate cutoff value of 1349.4 ms for identifying LGE with a sensitivity of 75% and specificity of 92.1%. When the minimum T₁ value + 1.2 standard deviation (SD) was used as the threshold, the sensitivity was 75% and specificity was 89.5%.

Conclusion: Non-contrast-enhanced T₁ mapping can be used for assessment of myocardial fibrosis associated with DCM by using the appropriate threshold.

Purpose: Dynamic MR techniques, such as cardiac cine imaging, benefit from shorter acquisition times. The goal of the present study was to develop a method that achieves short acquisition times, while maintaining a cost-effective reconstruction, for dynamic MRI. k − t sensitivity encoding (SENSE) was identified as the base method to be enhanced meeting these two requirements.

Methods: The proposed method achieves a reduction in acquisition time by estimating the spatiotemporal (x − f) sensitivity without requiring the acquisition of the alias-free signals, typical of the k − t SENSE technique. The cost-effective reconstruction, in turn, is achieved by a computationally efficient estimation of the x − f sensitivity from the band-limited signals of the aliased inputs. Such band-limited signals are suitable for sensitivity estimation because the strongly aliased signals have been removed.

Results: For the same reduction factor 4, the net reduction factor 4 for the proposed method was significantly higher than the factor 2.29 achieved by k − t SENSE. The processing time is reduced from 4.1 s for k − t SENSE to 1.7 s for the proposed method. The image quality obtained using the proposed method proved to be superior (mean squared error [MSE] ± standard deviation [SD] = 6.85 ± 2.73) compared to the k − t SENSE case (MSE ± SD = 12.73 ± 3.60) for the vertical long-axis (VLA) view, as well as other views.

Conclusion: In the present study, k − t SENSE was identified as a suitable base method to be improved achieving both short acquisition times and a cost-effective reconstruction. To enhance these characteristics of base method, a novel implementation is proposed, estimating the x − f sensitivity without the need for an explicit scan of the reference signals. Experimental results showed that the acquisition, computational times and image quality for the proposed method were improved compared to the standard k − t SENSE method.

Purpose: This study is to compare the accuracy of four different black-blood T₂ mapping sequences in carotid vessel wall.

Methods: Four different black-blood T₂ mapping sequences were developed and tested through phantom experiments and 17 healthy volunteers. The four sequences were: 1) double inversion-recovery (DIR) prepared 2D multi-echo spin-echo (MESE); 2) DIR-prepared 2D multi-echo fast spin-echo (MEFSE); 3) improved motion-sensitized driven-equilibrium (iMSDE) prepared 3D FSE and 4) iMSDE prepared 3D fast spoiled gradient echo (FSPGR). The concordance correlation coefficient and Bland–Altman statistics were used to compare the sequences with a gold-standard 2D MESE, without blood suppression in phantom studies. The volunteers were scanned twice to test the repeatability. Mean and standard deviation of vessel wall T₂, signal-to-noise (SNR), the coefficient of variance and interclass coefficient (ICC) of the two scans were compared.

Results: The phantom study demonstrated that T₂ measurements had high concordance with respect to the gold-standard (all r values >0.9). In the volunteer study, the DIR 2D MEFSE had significantly higher T₂ values than the other three sequences (P < 0.01). There was no difference in T₂ measurements obtained using the other three sequences (P > 0.05). iMSDE 3D FSE had the highest SNR (P < 0.05) compared with the other three sequences. The 2D DIR MESE has the highest repeatability (ICC: 0.96, [95% CI: 0.88–0.99]).

Conclusion: Although accurate T₂ measurements can be achieved in phantom by the four sequences, in vivo vessel wall T₂ quantification shows significant differences. The in vivo images can be influenced by multiple factors including black-blood preparation and acquisition method. Therefore, a careful choice of acquisition methods and analysis of the confounding factors are required for accurate in vivo carotid vessel wall T₂ measurements. From the settings in this study, the iMSDE prepared 3D FSE is preferred for the future volunteer/patient scans.

Purpose: To compare the accuracy of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values between reduced FOV or so-called zonally oblique multislice (ZOOM) and conventional diffusion tensor imaging (DTI) in the cervical spinal cord.

Methods: Both ZOOM and conventional DTI were performed on 10 healthy volunteers. Intraclass correlation coefficient (ICC) was used to evaluate the reliability of the measurements obtained. Four radiologists evaluated the FA and ADC values at each cervical cord level and classified the visibility by 4 ranks. The geometric distortion ratios of the long axis and short axis were compared between ZOOM and conventional DTI. The imaging parameters were as follows: b-value = 600 s/mm²; TR = 4500 ms; TE = 81 ms; FOV = 70 × 47 mm² / 200 × 200 mm²; matrix = 80 × 51 / 128 × 126 (ZOOM and conventional DTI, respectively). The region of interest was carefully drawn inside the spinal cord margin to exclude the spinal cord component, without excluding the white matter fiber tracts.

Results: The average FA value decreased in both ZOOM and conventional DTI in lower spinal cord levels; in contrast, the ADC value increased in lower spinal cord levels. Zonally oblique multislice DTI was superior to conventional DTI with regard to inter-rater and intra-rater reliability; further, visibility was better and the standard deviation was smaller in ZOOM DTI. On both the long and short axis, the geometric distortion ratio was lower in ZOOM DTI at all cervical spinal cord levels compared with the conventional DTI. There was a significant difference in the distortion ratios of the long and short axis between ZOOM and conventional DTI.

Conclusion: Conventional DTI is unreliable owing to its susceptibility to the surrounding magnetic field. ZOOM DTI is reliable for performing highly accurate evaluations.

Purpose: Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classification by support vector machine, a method of traditional machine learning, using texture features computed from contrast-enhanced T₁-weighted images.

Methods: This retrospective study on preoperative brain tumor MRI included 76 consecutives, initially treated patients with glioblastoma (n = 55) or PCNSL (n = 21) from one institution, consisting of independent training group (n = 60: 44 glioblastomas and 16 PCNSLs) and test group (n = 16: 11 glioblastomas and 5 PCNSLs) sequentially separated by time periods. A total set of 67 texture features was computed on routine contrast-enhanced T₁-weighted images of the training group, and the top four most discriminating features were selected as input variables to train support vector machine classifiers. These features were then evaluated on the test group with subsequent image classification.

Results: The area under the receiver operating characteristic curves on the training data was calculated at 0.99 (95% confidence interval [CI]: 0.96–1.00) for the classifier with a Gaussian kernel and 0.87 (95% CI: 0.77–0.95) for the classifier with a linear kernel. On the test data, both of the classifiers showed prediction accuracy of 75% (12/16) of the test images.

Conclusions: Although further improvement is needed, our preliminary results suggest that machine learning-based image classification may provide complementary diagnostic information on routine brain MRI.

Purpose: This study aimed to determine whether whole-tumor histogram analysis of normalized cerebral blood volume (nCBV) and apparent diffusion coefficient (ADC) for contrast-enhancing lesions can be used to differentiate between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL).

Methods: From 20 patients, 9 with PCNSL and 11 with GBM without any hemorrhagic lesions, underwent MRI, including diffusion-weighted imaging and dynamic susceptibility contrast perfusion-weighted imaging before surgery. Histogram analysis of nCBV and ADC from whole-tumor voxels in contrast-enhancing lesions was performed. An unpaired t-test was used to compare the mean values for each type of tumor. A multivariate logistic regression model (LRM) was performed to classify GBM and PCNSL using the best parameters of ADC and nCBV.

Results: All nCBV histogram parameters of GBMs were larger than those of PCNSLs, but only average nCBV was statistically significant after Bonferroni correction. Meanwhile, ADC histogram parameters were also larger in GBM compared to those in PCNSL, but these differences were not statistically significant. According to receiver operating characteristic curve analysis, the nCBV average and ADC 25th percentile demonstrated the largest area under the curve with values of 0.869 and 0.838, respectively. The LRM combining these two parameters differentiated between GBM and PCNSL with a higher area under the curve value (Logit (P) = −21.12 + 10.00 × ADC 25th percentile (10⁻³ mm²/s) + 5.420 × nCBV mean, P < 0.001).

Conclusion: Our results suggest that whole-tumor histogram analysis of nCBV and ADC combined can be a valuable objective diagnostic method for differentiating between GBM and PCNSL.

Purpose: To verify whether a new grading based on time-of-flight magnetic resonance angiography source images (TOF-MRAsi) can reflect the abundance of pial collaterals, in patients with total occlusion of M1 segment of middle cerebral artery in the chronic stage.

Methods: In this single-center retrospective study, consecutive patients with total occlusion of M1 segment of middle cerebral artery, with both magnetic resonances angiography and digital subtraction angiography image were included. Time-of-flight magnetic resonance angiography source images were evaluated in a blinded fashion for pial collaterals (PCs) that were graded on a four-point scale. Good and poor PCs were defined as TOF-MRAsis grade <2 and ≥2, respectively. Receiver operating characteristic curve analysis was done to calculate the area under curve, sensitivity, and specificity.

Results: A total of 26 patients were included. The inter-reader agreement for time TOF-MRAsi and digital subtraction angiography images were 0.930 and 0.843, respectively. Compared with digital subtraction angiography grading, the area under curve of pial collateral grading based on TOF-MRAsi was 0.830 (0.636–1.000; P = 0.006). The sensitivity and specificity were 0.700 and 0.933, respectively. The modified Rankin Scale at follow-up was lower in patients with good PCs than in those with poor PCs (0[0, 1] vs. 1[1, 3], P = 0.055), although statistical significance was not reached.

Conclusion: The grading scale based on TOF-MRAsi could be a new empirical approach for pial collateral evaluation. The clinical use of the proposed approach for identifying patients with total occlusion of middle cerebral artery with a high risk of poor outcome requires evaluation in further studies.

Purpose: To improve imaging, a reliable setup method is critical for the accurate localization of lesions and surface markers. Because an anisotropic marker has not yet been validated for MRI, direct localization of surface markers is not yet feasible in fractional anisotropy (FA) maps. This study aimed to develop an anisotropic surface marker using wood for an FA map and to determine whether a wood marker is useful for various sequences.

Methods: Wood infiltrated with water was used to develop an anisotropic surface marker. The wood marker was compared with phantoms composed of clinically available markers, including MR-SPOTS Packets (Beekley Medical, Bristol, CT, USA), Breath Care Oral Refreshing Capsules (Kobayashi Pharmaceutical Co., Ltd., Osaka, Japan), and baby oil (Johnson & Johnson, New Brunswick, NJ, USA). Magnetic resonance images were acquired using the Achieva 3T TX MRI System (Philips HealthCare, Best, Netherlands) equipped with a QD head coil including T₁- and T₂-weighted imaging, proton-density-weighted imaging, T₂*-weighted imaging, T₁-weighted imaging spectral pre-saturation with inversion recovery, T₂-weighted imaging spectral attenuated inversion recovery, proton-density-weighted imaging spectral attenuated inversion recovery, diffusion weighted imaging, and diffusion tensor imaging. Apparent diffusion coefficient, FA values, and signal-to-noise ratio (SNR) were measured and recorded, and the coefficient of variation was calculated for two consecutive imaging scans. The wood was observed using a microscope.

Results: Breath Care Oral Refreshing Capsules and baby oil were not observed in the FA map. The FA value of the MR-SPOTS Packets was 0.18. The FA value of the wood marker was 0.80. The coefficient of variation of the MR-SPOTS Packets and the wood marker were 0.0263 and 0.0013, respectively, in the FA map. Microscopic observation revealed a wood anisotropic structure.

Conclusion: The wood maker enabled direct localization in the FA map. Hence, wood markers may be useful to radiologists and contribute to obtaining useful findings.

Purpose: Gadobutrol is a gadolinium-based contrast material (GBCM) with a high concentration of gadolinium and high relaxivity. Our purpose was to evaluate the signal intensity profiles in brain tissue for the bolus width and degree of signal change after bolus injection using an echo planar dynamic susceptibility contrast (DSC) sequence. We compared gadobutrol to gadoteridol using various injection speeds and saline flush volumes.

Methods: We studied 97 patients who underwent brain MRI. Datasets for perfusion studies were acquired using a 3T scanner with an echo planar imaging (EPI) sequence. The injection protocols were set up with combinations of injection speed and saline flush volume for both gadobutrol and gadoteridol. The full width at half maximum (FWHM) and the maximum signal change ratio (SCR_max) of the time intensity curves were measured.

Results: The FWHM did not show a statistically significant difference according to injection speed, flush volume, or type of GBCM. The SCR_max showed a greater change with a faster injection speed, larger saline flush, and gadobutrol administration. The difference between gadobutrol and gadoteridol became smaller with a faster injection speed and a larger saline flush.

Conclusion: The maximum signal drop was larger with gadobutrol when the injection speed was slow and the saline flush was small. Thus, gadobutrol may be useful to obtain a better profile for DSC perfusion MRI in conditions requiring a slower injection speed and/or a smaller volume of saline flush.

We evaluated the value of magnetic resonance elastography (MRE) for the prediction of response to magnetic resonance-guided focused ultrasound (MRgFUS) for uterine fibroids. Eleven patients were enrolled. A fractional change of >30% in Symptoms Severity Score (SSS) was defined as a ‘substantial symptomatic improvement’ at 12 months after treatment. The fractional stiffness value reduction in the patients with a substantial improvement in SSS was significantly higher than that in those without (P = 0.0446).

We developed ultrashort echo-time (UTE) imaging sequences with 3D Cones trajectories for a home-built compact MRI system using a 1.5T superconducting magnet and an unshielded gradient coil set. We achieved less than 7 min imaging time and obtained clear in vivo images of a human forearm with a TE of 0.4 ms. We concluded that UTE imaging using 3D Cones acquisition was successfully implemented in our 1.5T MRI system.

Magnetic resonance fingerprinting (MRF) is a promising framework that allows the quantification of multiple magnetic resonance parameters with a single scan. MRF using fast imaging with steady-state precession (MRF-FISP) has robustness to off-resonance artifacts and has many applications in inhomogeneous fields. However, the spoiler gradient used in MRF-FISP is sensitive to diffusion motion, and may lead to quantification errors when the spoiler moment increases. In this study, we examined the effect of the diffusion weighting in MRF-FISP caused by spoiler gradients. The T₂ relaxation times were greatly underestimated when large spoiler moments were used. The T₂ underestimation was prominent for tissues with large values of T₂ and diffusion coefficients. The T₂ bias was almost independent of the apparent diffusion coefficient (ADC) and T₂ values when the ADC map was measured and incorporated into the matching process. These results reveal that the T₂ underestimation resulted from the diffusion weighting caused by the spoiler gradients.