Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Soudabeh Kargar, Eric A. Borisch, Adam T. Froemming, Akira Kawashima, Lance A. Mynderse, Eric G. Stinson, Joshua D. Trzasko, Stephen J. Riederer Purpose To describe an efficient numerical optimization technique using non-linear least squares to estimate perfusion parameters for the Tofts and extended Tofts models from dynamic contrast enhanced (DCE) MRI data and apply the technique to prostate cancer. Methods Parameters were estimated by fitting the two Tofts-based perfusion models to the acquired data via non-linear least squares. We apply Variable Projection (VP) to convert the fitting problem from a multi-dimensional to a one-dimensional line search to improve computational efficiency and robustness. Using simulation and DCE-MRI studies in twenty patients with suspected prostate cancer, the VP-based solver was compared against the traditional Levenberg-Marquardt (LM) strategy for accuracy, noise amplification, robustness to converge, and computation time. Results The simulation demonstrated that VP and LM were both accurate in that the medians closely matched assumed values across typical signal to noise ratio (SNR) levels for both Tofts models. VP and LM showed similar noise sensitivity. Studies using the patient data showed that the VP method reliably converged and matched results from LM with approximate 3 × and 2 × reductions in computation time for the standard (two-parameter) and extended (three-parameter) Tofts models. While LM failed to converge in 14% of the patient data, VP converged in the ideal 100%. Conclusion The VP-based method for non-linear least squares estimation of perfusion parameters for prostate MRI is equivalent in accuracy and robustness to noise, while being more reliably (100%) convergent and computationally about 3 × (TM) and 2 × (ETM) faster than the LM-based method.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Yuanliang Xie, Hongfeng Zhang, Chaoling Jin, Xiang Wang, Xiaoqi Wang, Jingting Chen, Yikai Xu To assess the value of T1ρ,T1ρ on hepatobiliary phase (HBP) and diffusion metrics in staging of Non-alcoholic fatty liver disease (NAFLD) activity scores, inflammation, fibrosis in NASH rabbits model. Non-alcoholic steatohepatitis (NASH) rabbits model was induced by feeding a varied duration of high-fat, high-cholesterol diet. T1ρ,T1ρ (HBP) 20 min after administration of Gd-EOB-DTPA, and Intravoxel incoherent motion imaging (IVIM) diffusion-weighted imaging were performed on a 3.0 T magnetic resonance (MR) imaging unit. The diagnostic value of each parameter for NAS, inflammation and fibrosis severity were determined. T1ρ (r = 0.658) and T1ρ (HBP) (r = 0.750) have strong association with NASH overall activity, T1ρ (HBP) is strongly relevant to inflammation stage (r = 0.812). There was negative association between f and inflammation (r = − 0.480), whilst no significant relation between other three parameters (apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and true diffusion coefficient (D)) and inflammation or overall activity. The areas under the receiver operating characteristic curves (AUCs) of f, ADC, T1ρ and T1ρ-HBP were 0.871, 0.728, 0.849 and 0.949 for differentiating NASH; 0.731, 0.552, 0.925 and 0.922 for G2–3 inflammation; and 0.767, 0.625, 0.816, and 0.882 for S1–2 fibrosis. Comparison of ROC curve showed T1ρ (HBP) had an optimal diagnostic performance for NASH [T1ρ (HBP) vs ADC, AUC:0.949 vs 0.728, P = 0.043], inflammation [T1ρ (HBP) vs ADC, AUC:0.922 vs 0.552, P = 0.003], fibrosis [T1ρ (HBP) vs ADC, AUC:0.882 vs 0.625, P = 0.046]. The combination of T1ρ (HBP) + perfusion fraction (f) showed highest diagnostic value for NASH (AUC:0.971), inflammation (AUC:0.935). Among T1ρ imaging and IVIM diffusion metrics, combination of T1rho (HBP) + f was found to be superior noninvasive imaging biomarker for NASH activity assessment.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Nora Kassner, Meike Weis, Katrin Zahn, Thomas Schaible, Stefan O. Schoenberg, Lothar R. Schad, Frank G. Zöllner Objectives To investigate a histogram based approach to characterize the distribution of perfusion in the whole left and right lung by descriptive statistics and to show how histograms could be used to visually explore perfusion defects in two year old children after Congenital Diaphragmatic Hernia (CDH) repair. Methods 28 children (age of 24.2 ± 1.7 months; all left sided hernia; 9 after extracorporeal membrane oxygenation therapy) underwent quantitative DCE-MRI of the lung. Segmentations of left and right lung were manually drawn to mask the calculated pulmonary blood flow maps and then to derive histograms for each lung side. Individual and group wise analysis of histograms of left and right lung was performed. Results Ipsilateral and contralateral lung show significant difference in shape and descriptive statistics derived from the histogram (Wilcoxon signed-rank test, p 〈 0.05) on group wise and individual level. Subgroup analysis (patients with vs without ECMO therapy) showed no significant differences using histogram derived parameters. Conclusions Histogram analysis can be a valuable tool to characterize and visualize whole lung perfusion of children after CDH repair. It allows for several possibilities to analyze the data, either describing the perfusion differences between the right and left lung but also to explore and visualize localized perfusion patterns in the 3D lung volume. Subgroup analysis will be possible given sufficient sample sizes.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Yunju Kim, Sung Hun Kim, Hye Won Lee, Byung Joo Song, Bong Joo Kang, Ahwon Lee, Yoonho Nam Purpose To determine the diagnostic performance of intravoxel incoherent motion (IVIM) diffusion-weighted (DW) magnetic resonance imaging (MRI) parameters in predicting response to neoadjuvant chemotherapy (NAC) in breast cancer patients. Materials and methods Forty-six patients with stage II or III breast cancer underwent MRI including DW imaging with 10 b values before and after 2 cycles of NAC. Apparent diffusion coefficient (ADC) and IVIM parameters (D, D*, and f ) were obtained using histogram analysis derived from whole-tumor volumes. After surgery, imaging parameters were compared with histopathologic responses using the Miller-Payne grading system. Results Before NAC, D mean , D 50 , and D 75 were higher in good responders than in minor responders ( P ≤ 0.043). After NAC, ADC mean , ADC 50 , ADC 75 , D mean , D 25 , D 50 , and D 75 were higher in good responders ( P ≤ 0.037). Skewness of ADC and D were lower in good responders after NAC ( P ≤ 0.005). Most histogram metrics of posttreatment ADC and D had similar AUC values with reasonable accuracy for prediction of good response (AUC ≥ 0.7, P 〈 0.05). Conclusion D and ADC are useful for the prediction of response to NAC in breast cancer patients. Additional information is obtained by application of the IVIM model in DW imaging analysis and histogram analysis using whole-tumor volume data.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Michael Gadermayr, Constantin Disch, Madlaine Müller, Dorit Merhof, Burkhard Gess Severity and progression of degenerative neuromuscular diseases can be sensitively captured by evaluating the fat infiltration of muscle tissue in T1-weighted MRI scans of human limbs. For computing the fat fraction, the original muscle needs to be first separated from other tissue. Five conceptionally different approaches were investigated and evaluated with respect to the segmentation of muscles of human thighs. Besides a rather basic thresholding approach, local (level set) as well as global (graph cut) energy-minimizing segmentation approaches with and without a shape prior energy term were examined. For experimental evaluations, a dataset containing 37 subjects was divided into four classes according to the degree of fat infiltration. Results show that the choice of the best method depends on the severity of fat infiltration. In severe cases, the best results were obtained with shape prior based graph cuts, whereas in marginal cases thresholding was sufficient. With the best approach, the worst-case error in fat fraction computation was always below 11% and on average between 2% for tissue showing no fat infiltrations and 6% for heavily infiltrated tissue. The obtained Dice similarity coefficients, measuring the segmentation quality, were on average between 0.85 and 0.92. Although segmentation of heavily infiltrated muscle tissue is extremely difficult, an approach for reasonably segmenting these image data was identified. Especially the negative impact on the calculated fat fraction can be reduced significantly.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Evan McNabb, Raimond Wong, Michael D. Noseworthy The goal of this work was to use an undersampled, dual-plane centre-out radial sampling acquisition pulse sequence, with off-resonance reception, to localize fiducial markers with reduced acquisition time. Two iterative reconstruction techniques, conjugate gradient CG-SENSE and the variational penalty Total Generalized Variation (TGV), were investigated to minimize the undersampling artifacts in off-resonant radial imaging. Simulations of a field perturber were performed at sub-millimeter resolution and reconstructed to display signal pileups that can be radially compressed towards the geometric centre of the perturber for high contrast visualization, but contrast is non-recoverable as the echo time increases. A cylindrical platinum fiducial marker, placed in a phantom parallel and perpendicular to the B 0 -field was imaged with a short-TE half-echo readout. Contrast-to-Noise (CNR) between the signal of the fiducial its adjacent surrounding shell and half-maximum area were used to compare reconstruction methods and undersampling factors. For single slice acquisitions centred about the fiducial, each slice can be performed in as little as 2.8 s. The total acquisition time to localize the fiducial marker in a phantom was reduced to 73 s by undersampling (R=8) 37 axial and 15 coronal slices, effectively encoding 1.4 s/slice. The noise present in undersampled images, for both scan planes and fiducial orientations, decreased significantly using TGV and CG-SENSE reconstructions, with TGV displaying better spatial resolution from reduced half-maximum area.

Description: Publication date: April 2018 Source: Magnetic Resonance Imaging, Volume 47 Author(s): Ioannis Papadopoulos, Jonathan Phillips, Rhodri Evans, Neil Fenn, Sophie Shermer Data from a multi-parametric MRI study of patients with possible early-stage prostate cancer was assessed with a view to creating a more efficient clinical protocol. Based on a correlation analysis suggesting that diffusion-weighted imaging (DWI) scores are more strongly correlated with overall PIRADS scores than other modalities such as dynamic contrast enhanced imaging or spectroscopy, we investigate the combination of T2-weighted imaging (T2w) and DWI as a potential diagnostic tool for prostate cancer detection, staging and guided biopsies. Quantification of the noise floor in the DWI images and careful fitting of the data suggests that the mono-exponential model provides a very good fit to the data and there is no evidence of non-Gaussian diffusion for b -values up to 1000 s/mm 2 . This precludes the use of kurtosis or other non-Gaussian measures as a biomarker for prostate cancer in our case. However, the ADC scores for healthy and probably malignant regions are significantly lower for the latter in all 20 but one patient. The results suggest that a simplified mp-MRI protocol combining T2w and DWI may be a good compromise for a cost and time efficient, early-stage prostate cancer diagnostic programme, combining robust MR biomarkers for prostate cancer that can be reliably quantified and appear well-suited for general clinical practice.

Description: Publication date: May 2018 Source: Magnetic Resonance Imaging, Volume 48 Author(s): Alexandra Cristobal-Huerta, Dirk H.J. Poot, Mika W. Vogel, Gabriel P. Krestin, Juan A. Hernandez-Tamames Purpose To propose and evaluate new k-space trajectories for 3D-GRASE to improve scan time over 3D-FSE/TSE for high resolution structural imaging. Methods Five different Cartesian k-space trajectories were developed and evaluated. They combine ideas of existing k-space trajectories for 3D-GRASE and 3D-FSE/TSE. T2 and T2* are linearly or radially modulated in k-space to achieve the desired contrast while including the autocalibration region needed for the parallel imaging reconstruction technique. Phase modulation among echoes was corrected in reconstruction to remove remaining artefacts. Simulation and in-vivo experiments on a 3T scanner were conducted to evaluate the performance of the different k-space trajectories. Results Two of the proposed k-space trajectories for high resolution structural imaging with 3D-GRASE obtained images comparable to 3D-FSE with lower specific absorption rate (PD/T2: 41%/75%) and shorter acquisition time (PD/T2: 27%/20%). Conclusions 3D-GRASE image quality strongly depends on the k-space trajectory. With an optimal trajectory, 3D-GRASE may be preferable over 3D-FSE/TSE for structural high-resolution MRI.

Description: Publication date: April 2018 Source: Magnetic Resonance Imaging, Volume 47 Author(s): Adam Bush, Yaqiong Chai, So Young Choi, Lena Vaclavu, Scott Holland, Aart Nederveen, Thomas Coates, John Wood Purpose To investigate possible sources of quantification errors in global cerebral blood flow (CBF) measurements by comparing pseudo continuous arterial spin labeling (PCASL) and phase contrast (PC) MRI in anemic, hyperemic subjects. Methods All studies were performed on a Philips 3T Achieva MRI scanner. PC and PCASL CBF examinations were performed in 10 healthy, young adult subjects and 18 young adults with chronic anemia syndromes including sickle cell disease and thalassemia. CBF estimates from single and two compartment ASL kinetic models were compared. Numerical simulation and flow phantom experiments were used to explore the effects of blood velocity and B1 + on CBF quantification and labeling efficiency. Results PCASL CBF underestimated PC in both populations using a single compartment model (30.1 ± 9.2% control, 45.2 ± 17.2% anemia). Agreement substantially improved using a two-compartment model (− 8.0 ± 6.0% control, 11.7 ± 12.3% anemia). Four of the anemic subjects exhibited venous outflow of ASL signal, suggestive of cerebrovascular shunt, possibly confounding PC-PCASL comparisons. Additionally, sub-study experiments demonstrated that B1 + was diminished at the labeling plane (82.9 ± 5.1%), resulting in suboptimal labeling efficiency. Correcting labeling efficiency for diminished B1 + , PCASL slightly overestimated PC CBF in controls (− 15.4 ± 6.8%) and resulted in better matching of CBF estimates in anemic subjects (0.7 ± 10.0% without outflow, 10.5 ± 9.4% with outflow). Conclusions This work demonstrates that a two-compartment model is critical for PCASL quantification in hyperemic subjects. Venous outflow and B1 + under-excitation may also contribute to flow underestimation, but further study of these effects is required.

Description: Publication date: April 2018 Source: Magnetic Resonance Imaging, Volume 47 Author(s): Candace C. Fleischer, Xiaodong Zhong, Hui Mao Parallel imaging using phased array coils facilitates accelerated magnetic resonance imaging (MRI) and spectroscopy (MRS). Parallel data reconstruction requires the combination of data from individual coil elements, but limited combination algorithms currently exist for higher-order phased arrays and MRS data. Here, we present a systematic framework for identifying coil proximity-related signal inhomogeneities and noise levels in phased array coils that may affect sensitivity of parallel MRS. Single-voxel MRS was acquired in nine voxel positions in a brain spectroscopy phantom on a 3 T whole-body MR scanner using commercially available 64-, 32-, and 20-channel phased array coils. Spectra produced by individual coil elements were combined using both a signal-to-noise ratio (SNR) threshold and based on the position of individual coil elements. SNR and metabolite Cramer-Rao lower bounds (CRLBs) from the final combined spectra were used as metrics to compare combination strategies and the effects of the phased array geometry and individual coil proximity. Comparisons were performed using one-way repeated measures ANOVA and post-hoc Tukey's range test (p 〈 0.05). The 32-channel phased array coil produced the highest overall SNR compared to the 64-channel (p = 0.0009) or 20-channel coils (p = 0.003). Low SNR spectra from individual coil elements in the 64-channel coil can reduce the overall SNR when simply combining spectra from all elements. SNR varied significantly as a function of voxel position (F = 58.3, p 〈 0.0001) and SNR threshold for all phased arrays (p 〈 0.05 for 64-, 32-, and 20-channel coils). Metabolite CRLBs were dependent on the combination strategy. We demonstrate the importance of the sampling voxel position and coil proximity on overall SNR in parallel MRS data acquisition, with significant SNR improvements after selectively filtering individual spectra based on pre-determined SNR thresholds which must be optimized for each phased array coil element and volume of interest.