Comparison of Turbo Spin Echo and Echo Planar Imaging for intravoxel incoherent motion and diffusion tensor imaging of the kidney at 3Tesla.

Echo Planar Imaging (EPI) is most commonly applied to acquire diffusion-weighted MR-images. EPI is able to capture an entire image in very short time, but is prone to distortions and artifacts. In diffusion-weighted EPI of the kidney severe distortions may occur due to intestinal gas. Turbo Spin Echo (TSE) is robust against distortions and artifacts, but needs more time to acquire an entire image compared to EPI. Therefore, TSE is more sensitive to motion during the readout. In this study we compare diffusion-weighted TSE and EPI of the human kidney with regard to intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI). Images were acquired with b-values between 0 and 750s/mm2 with TSE and EPI. Distortions were observed with the EPI readout in all volunteers, while the TSE images were virtually distortion-free. Fractional anisotropy of the diffusion tensor was significantly lower for TSE than for EPI. All other parameters of DTI and IVIM were comparable for TSE and EPI. Especially the main diffusion directions yielded by TSE and EPI were similar. The results demonstrate that TSE is a worthwhile distortion-free alternative to EPI for diffusion-weighted imaging of the kidney at 3Tesla.

Intravoxel incoherent motion magnetic resonance imaging of the knee joint in children with juvenile idiopathic arthritis.

BACKGROUND: MRI of synovitis relies on use of a gadolinium-based contrast agent. Diffusion-weighted MRI (DWI) visualises thickened synovium but is of limited use in the presence of joint effusion. OBJECTIVE: To investigate the feasibility and diagnostic accuracy of diffusion-weighted MRI with intravoxel incoherent motion (IVIM) for diagnosing synovitis in the knee joint of children with juvenile idiopathic arthritis. MATERIALS AND METHODS: Twelve consecutive children with confirmed or suspected juvenile idiopathic arthritis (10 girls, median age 11 years) underwent MRI with contrast-enhanced T1-weighted imaging and DWI at 1.5 T. Read-out segmented multi-shot DWI was acquired at b values of 0 s/mm2, 200 s/mm2, 400 s/mm2 and 800 s/mm2. We calculated the IVIM parameters perfusion fraction (f) and tissue diffusion coefficient (D). Diffusion-weighted images at b=800 s/mm2, f parameter maps and post-contrast T1-weighted images were retrospectively assessed by two independent readers for synovitis using the Juvenile Arthritis MRI Scoring system. RESULTS: Seven (58%) children showed synovial hypertrophy on contrast-enhanced imaging. Diagnostic ratings for synovitis on DWI and on f maps were fully consistent with contrast-enhanced imaging, the diagnostic reference. Two children had equivocal low-confidence assessments on DWI. Median f was 6.7±2.0% for synovitis, 2.1±1.2% for effusion, 5.0±1.0% for muscle and 10.6±5.7% for popliteal lymph nodes. Diagnostic confidence was higher based on f maps in three (25%) children and lower in one child (8%), as compared to DWI. CONCLUSION: DWI with IVIM reliably visualises synovitis of the knee joint. Perfusion fraction maps differentiate thickened synovium from joint effusion and hence increase diagnostic confidence.

An intravoxel oriented flow model for diffusion-weighted imaging of the kidney.

By combining intravoxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) we introduce a new diffusion model called intravoxel oriented flow (IVOF) that accounts for anisotropy of diffusion and the flow-related signal. An IVOF model using a simplified apparent flow fraction tensor (IVOFf ) is applied to diffusion-weighted imaging of human kidneys. The kidneys of 13 healthy volunteers were examined on a 3 T scanner. Diffusion-weighted images were acquired with six b values between 0 and 800 s/mm(2) and 30 diffusion directions. Diffusivity and flow fraction were calculated for different diffusion models. The Akaike information criterion was used to compare the model fit of the proposed IVOFf model to IVIM and DTI. In the majority of voxels the proposed IVOFf model with a simplified apparent flow fraction tensor performs better than IVIM and DTI. Mean diffusivity is significantly higher in DTI compared with models that account for the flow-related signal. The fractional anisotropy of diffusion is significantly reduced when flow fraction is considered to be anisotropic. Anisotropy of the apparent flow fraction tensor is significantly higher in the renal medulla than in the cortex region. The IVOFf model describes diffusion-weighted data in the human kidney more accurately than IVIM or DTI. The apparent flow fraction in the kidney proved to be anisotropic.

Accelerated radial Fourier-velocity encoding using compressed sensing.

PURPOSE: Phase Contrast Magnetic Resonance Imaging (MRI) is a tool for non-invasive determination of flow velocities inside blood vessels. Because Phase Contrast MRI only measures a single mean velocity per voxel, it is only applicable to vessels significantly larger than the voxel size. In contrast, Fourier Velocity Encoding measures the entire velocity distribution inside a voxel, but requires a much longer acquisition time. For accurate diagnosis of stenosis in vessels on the scale of spatial resolution, it is important to know the velocity distribution of a voxel. Our aim was to determine velocity distributions with accelerated Fourier Velocity Encoding in an acquisition time required for a conventional Phase Contrast image. MATERIALS AND METHODS: We imaged the femoral artery of healthy volunteers with ECG-triggered, radial CINE acquisition. Data acquisition was accelerated by undersampling, while missing data were reconstructed by Compressed Sensing. Velocity spectra of the vessel were evaluated by high resolution Phase Contrast images and compared to spectra from fully sampled and undersampled Fourier Velocity Encoding. By means of undersampling, it was possible to reduce the scan time for Fourier Velocity Encoding to the duration required for a conventional Phase Contrast image. RESULTS: Acquisition time for a fully sampled data set with 12 different Velocity Encodings was 40 min. By applying a 12.6-fold retrospective undersampling, a data set was generated equal to 3:10 min acquisition time, which is similar to a conventional Phase Contrast measurement. Velocity spectra from fully sampled and undersampled Fourier Velocity Encoded images are in good agreement and show the same maximum velocities as compared to velocity maps from Phase Contrast measurements. CONCLUSION: Compressed Sensing proved to reliably reconstruct Fourier Velocity Encoded data. Our results indicate that Fourier Velocity Encoding allows an accurate determination of the velocity distribution in vessels in the order of the voxel size. Thus, compared to normal Phase Contrast measurements delivering only mean velocities, no additional scan time is necessary to retrieve meaningful velocity spectra in small vessels.