Purpose: To evaluate the feasibility of ultrafast dynamic contrast-enhanced (UF-DCE) magnetic resonance imaging (MRI) with compressed sensing (CS) for the separate identification of breast arteries/veins and perform temporal evaluations of breast arteries and veins with a focus on the association with ipsilateral cancers. Materials and Methods: Our Institutional Review Board approved this study with retrospective design. Twenty-five female patients who underwent UF-DCE MRI at 3T were included. UF-DCE MRI consisting of 20 continuous frames was acquired using a prototype 3D gradient-echo volumetric interpolated breath-hold sequence including a CS reconstruction: temporal resolution, 3.65 sec/frame; spatial resolution, 0.9 3 1.3 3 2.5 mm. Two readers analyzed 19 maximum intensity projection images reconstructed from subtracted images, separately identified breast arteries/veins and the earliest frame in which they were respectively visualized, and calculated the time interval between arterial and venous visualization (A-V interval) for each breast. Results: In total, 49 breasts including 31 lesions (breast cancer, 16; benign lesion, 15) were identified. In 39 of the 49 breasts (breasts with cancers, 16; breasts with benign lesions, 10; breasts with no lesions, 13), both breast arteries and veins were separately identified. The A-V intervals for breasts with cancers were significantly shorter than those for breasts with benign lesions (P 5 0.043) and no lesions (P 5 0.007). Conclusion: UF-DCE MRI using CS enables the separate identification of breast arteries/veins. Temporal evaluations calculating the time interval between arterial and venous visualization might be helpful in the differentiation of ipsilateral breast cancers from benign lesions. Level of Evidence: 3 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;47:97-104. B reast magnetic resonance imaging (MRI) has become an established modality for the identification of breast cancer with high sensitivity (90-100%). [1][2][3][4][5][6][7] The specificity of MR, however, varies widely across studies (65-97%) 1-5 and remains only moderate with 72-75% pooled specificity in meta-analyses. 6,7 The diagnosis of breast MRI is mainly based on morphological evaluation and kinetic curve assessment in clinical practice. 8,9 As a completely different approach to diagnose breast cancer, previous studies have demonstrated an increased breast vascularity associated with ipsilateral breast cancer on MR angiograms generated from conventional dynamic contrast- enhanced (C-DCE) MRI. 10-17 Possible mechanisms for this observation include decreased flow resistance in tumor vessels, high tumor metabolism, and angiogenic stimulation of the entire breast harboring the tumor. 10,12 One of the limitations in these previous reports was the limited temporal resolution. On C-DCE MRI, it is not possible to differentiate breast arteries from veins because of the long scan time (60-120 sec) required for acceptable spatial resolution (in-plane pixel size, 1.0 3 1.0 mm; through-plane...

The purpose of this study is to evaluate whether thin-slice high-resolution 2D fat-suppressed proton density-weighted image of the knee joint using denoising approach with deep learning-based reconstruction (dDLR) with MPR is more useful than 3D FS-PD multi planar voxel image. Twelve patients who underwent MRI of the knee at 3T and 13 knees were enrolled. Denoising effect was quantitatively evaluated by comparing the coefficient of variation (CV) before and after dDLR. For the qualitative assessment, two radiologists evaluated image quality, artifacts, anatomical structures, and abnormal findings using a 5-point Likert scale between 2D and 3D. All of them were statistically analyzed. Gwet’s agreement coefficients were also calculated. For the scores of abnormal findings, we calculated the percentages of the cases with agreement with high confidence. The CV after dDLR was significantly lower than the one before dDLR (p < 0.05). As for image quality, artifacts and anatomical structure, no significant differences were found except for flow artifact (p < 0.05). The agreement was significantly higher in 2D than in 3D in abnormal findings (p < 0.05). In abnormal findings, the percentage with high confidence was higher in 2D than in 3D (p < 0.05). By applying dDLR to 2D, almost equivalent image quality to 3D could be obtained. Furthermore, abnormal findings could be depicted with greater confidence and consistency, indicating that 2D with dDLR can be a promising imaging method for the knee joint disease evaluation.

Purpose: To assess the impact of the number of iterations of compressed sensing (CS) reconstruction on the kinetic parameters and image quality in dynamic contrast-enhanced (DCE)-MRI of the breast, with prospectively undersampled CS-accelerated scans. Materials and Methods: Breast examinations including ultrafast DCE-MRI using CS were conducted for 21 patients. Images were reconstructed with different numbers of iterations. The peak enhancement ratio of the aorta and wash-in slope, initial area under the curve, and K trans of the breast lesions were measured. The root mean square error and structural similarity between the images using 50 iterations and images with a lower number of iterations were evaluated as criterion for quantitative image evaluation. Results: Using an insufficient number of iterations, the contrast-enhanced effect was highly underestimated. In all semi-quantitative parameters, the number of iterations that stabilized the parameters in malignant lesions was higher than that in benign lesions. At least 15 iterations were needed for semi-quantitative parameters. For K trans , there were no significant differences between 10 and 50 iterations in both malignant and benign lesions. Conclusion: The kinetic parameters using ultrafast DCE-MRI with CS are affected by the number of iterations, especially in malignant lesions. However, if the images are reconstructed with an adequate number of iterations, ultrafast DCE-MRI with CS can be a powerful technique having high temporal and spatial resolution.

Diffusion-weighted magnetic resonance imaging is prone to have susceptibility artifacts in an inhomogeneous magnetic field. We compared distortion and artifacts among three diffusion acquisition techniques (single-shot echo-planar imaging [SS-EPI DWI], readout-segmented EPI [RESOLVE DWI], and 2D turbo gradient- and spin-echo diffusion-weighted imaging with non-Cartesian BLADE trajectory [TGSE-BLADE DWI]) in healthy volunteers and in patients with a cerebral aneurysm clip. Seventeen healthy volunteers and 20 patients who had undergone surgical cerebral aneurysm clipping were prospectively enrolled. SS-EPI DWI, RESOLVE DWI, and TGSE-BLADE DWI of the brain were performed using 3 T scanners. Distortion was the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI near air–bone interfaces in healthy volunteers (P < 0.001). Length of clip-induced artifact and distortion near the metal clip were the least in TGSE-BLADE DWI, and lower in RESOLVE DWI than SS-EPI DWI (P < 0.01). Image quality scores for geometric distortion, susceptibility artifacts, and overall image quality in both healthy volunteers and patients were the best in TGSE-BLADE DWI, and better in RESOLVE DWI than SS-EPI DWI (P < 0.001). Among the three DWI sequences, image quality was the best in TGSE-BLADE DWI in terms of distortion and artifacts, in both healthy volunteers and patients with an aneurysm clip.

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