Confidence maps for reliable estimation of proton density fat fraction and R 2 * in the liver.

PURPOSE: The objective was to develop a fully automated algorithm that generates confidence maps to identify regions valid for analysis of quantitative proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ maps of the liver, generated with chemical shift-encoded MRI (CSE-MRI). Confidence maps are urgently needed for automated quality assurance, particularly with the emergence of automated segmentation and analysis algorithms. METHODS: Confidence maps for both PDFF and R 2 * $$ {R}_2^{\ast } $$ maps are generated based on goodness of fit, measured by normalized RMS error between measured complex signals and the CSE-MRI signal model. Based on Cramér-Rao lower bound and Monte-Carlo simulations, normalized RMS error threshold criteria were developed to identify unreliable regions in quantitative maps. Simulation, phantom, and in vivo clinical studies were included. To analyze the clinical data, a board-certified radiologist delineated regions of interest (ROIs) in each of the nine liver segments for PDFF and R 2 * $$ {R}_2^{\ast } $$ analysis in consecutive clinical CSE-MRI data sets. The percent area of ROIs in areas deemed unreliable by confidence maps was calculated to assess the impact of confidence maps on real-world clinical PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements. RESULTS: Simulations and phantom studies demonstrated that the proposed algorithm successfully excluded regions with unreliable PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements. ROI analysis by the radiologist revealed that 2.6% and 15% of the ROIs were placed in unreliable areas of PDFF and R 2 * $$ {R}_2^{\ast } $$ maps, as identified by confidence maps. CONCLUSION: A proposed confidence map algorithm that identifies reliable areas of PDFF and R 2 * $$ {R}_2^{\ast } $$ measurements from CSE-MRI acquisitions was successfully developed. It demonstrated technical and clinical feasibility.

Nonlinear Gradient Field Mapping Using a Spherical Grid Phantom for 3 and 7 Tesla MR Imaging Systems Equipped with High-performance Gradient Coils.

Recent high-performance gradient coils are fabricated mainly at the expense of spatial linearity. In this study, we measured the spatial nonlinearity of the magnetic field generated by the gradient coils of two MRI systems with high-performance gradient coils. The nonlinearity of the gradient fields was measured using 3D gradient echo sequences and a spherical phantom with a built-in lattice structure. The spatial variation of the gradient field was approximated to the 3rd order polynomials. The coefficients of the polynomials were calculated using the steepest descent method. The geometric distortion of the acquired 3D MR images was corrected using the polynomials and compared with the 3D images corrected using the harmonic functions provided by the MRI venders. As a result, it was found that the nonlinearity correction formulae provided by the vendors were insufficient and needed to be verified or corrected using a geometric phantom such as used in this study.

Confounder-corrected T1 mapping in the liver through simultaneous estimation of T1 , PDFF, R 2 * , and B 1 + in a single breath-hold acquisition.

PURPOSE: Quantitative volumetric T1 mapping in the liver has the potential to aid in the detection, diagnosis, and quantification of liver fibrosis, inflammation, and spatially resolved liver function. However, accurate measurement of hepatic T1 is confounded by the presence of fat and inhomogeneous B 1 + $$ {B}_1^{+} $$ excitation. Furthermore, scan time constraints related to respiratory motion require tradeoffs of reduced volumetric coverage and/or increased acquisition time. This work presents a novel 3D acquisition and estimation method for confounder-corrected T1 measurement over the entire liver within a single breath-hold through simultaneous estimation of T1 , fat and B 1 + $$ {B}_1^{+} $$ . THEORY AND METHODS: The proposed method combines chemical shift encoded MRI and variable flip angle MRI with a B 1 + $$ {B}_1^{+} $$ mapping technique to enable confounder-corrected T1 mapping. The method was evaluated theoretically and demonstrated in both phantom and in vivo acquisitions at 1.5 and 3.0T. At 1.5T, the method was evaluated both pre- and post- contrast enhancement in healthy volunteers. RESULTS: The proposed method demonstrated excellent linear agreement with reference inversion-recovery spin-echo based T1 in phantom acquisitions at both 1.5 and 3.0T, with minimal bias (5.2 and 45 ms, respectively) over T1 ranging from 200-1200 ms. In vivo results were in general agreement with reference saturation-recovery based 2D T1 maps (SMART1 Map, GE Healthcare). CONCLUSION: The proposed 3D T1 mapping method accounts for fat and B 1 + $$ {B}_1^{+} $$ confounders through simultaneous estimation of T1 , B 1 + $$ {B}_1^{+} $$ , PDFF and R 2 * $$ {R}_2^{\ast } $$ . It demonstrates strong linear agreement with reference T1 measurements, with low bias and high precision, and can achieve full liver coverage in a single breath-hold.

An Intra-individual Comparison between Free-breathing Dynamic MR Imaging of the Liver Using Stack-of-stars Acquisition and the Breath-holding Method Using Cartesian Sampling or View-sharing.

PURPOSE: To compare the quality of dynamic imaging between stack-of-stars acquisition without breath-holding (DISCO-Star) and the breath-holding method (Cartesian LAVA and DISCO). METHODS: This retrospective study was conducted between October 2019 and February 2020. Two radiologists performed visual assessments of respiratory motion or pulsation artifacts, streak artifacts, liver edge sharpness, and overall image quality using a 5-point scale for two datasets: Dataset 1 (n = 107), patients with Cartesian LAVA and DISCO-Star; Dataset 2 (n = 41), patients with DISCO and DISCO-Star at different time points. Diagnosable image quality was defined as ≥ 3 points in overall image quality. Whether the scan timing of the arterial phase (AP) was appropriate was evaluated, and results between the pulse sequences were compared. In cases of inappropriate scan timing in the DISCO-Star group, retrospective reconstruction with a high frame rate (80 phases, 3 s/phase) was added. RESULTS: The overall image quality of Cartesian LAVA was better than that of DISCO-Star in AP. However, noninferiority was shown in the ratio of diagnosable images between Cartesian LAVA and DISCO-Star in AP. There was no significant difference in the ratio of appropriate scan timing between DISCO-Star and Cartesian LAVA; however, the ratio of appropriate scan timing in DISCO-Star with high frame rate reconstruction was significantly higher than that in Cartesian LAVA in both readers. Overall image quality scores between DISCO and DISCO-Star were not significantly different in AP. There was no significant difference in the ratio of appropriate scan timing between DISCO-Star with high frame rate reconstruction and DISCO in both readers. CONCLUSION: The use of DISCO-Star with high frame rate reconstruction is a good solution to obtain appropriate AP scan timing compared with Cartesian LAVA. DISCO-Star showed equivalent image quality in all phases and in the ratio of appropriate AP scan timing compared with DISCO.

Four-dimensional flow magnetic resonance imaging for assessment of hemodynamic changes in the portal venous system before and after balloon-occluded retrograde transvenous obliteration: a pilot feasibility study.

BACKGROUND: The effectiveness of four-dimensional (4D) flow magnetic resonance imaging (MRI) for assessing hemodynamic changes before and after balloon-occluded retrograde transvenous obliteration (BRTO) remains unclear. PURPOSE: To evaluate the feasibility of 4D flow MRI for assessing hemodynamic changes in the portal venous system before and after BRTO. MATERIAL AND METHODS: We included 10 patients (7 men, 3 women; mean age = 67 years) with liver cirrhosis who had a high risk of gastric variceal bleeding or hepatic encephalopathy. Non-contrast 4D flow MRI of the upper abdomen was performed before and after BRTO. In addition, we compared the blood flow rates in the portal vein (PV), superior mesenteric vein (SMV), splenic vein (SV), left renal vein, and inferior vena cava before and after BRTO. Moreover, the flow directions of the SMV and SV before and after BRTO were assessed using both portography and 4D flow MRI. RESULTS: There was a significant post-BRTO increase in the blood flow rate in the PV and SV (P < 0.05). There was no significant post-BRTO change in the blood flow rates in the SMV, inferior vena cava, and left renal vein. In four patients, portography confirmed that hepatofugal flow in the SV and SMV changed to hepatopetal flow after BRTO. Moreover, 4D flow MRI correctly assessed the flow directions in the SMV and SV in 70%-100% of the patients. CONCLUSION: 4D flow MRI can be used to detect hemodynamic changes in the portal venous system before and after BRTO.

Corrigendum: Myosteatosis as a Shared Biomarker for Sarcopenia and Cachexia Using MRI and Ultrasound.

[This corrects the article DOI: 10.3389/fresc.2022.896114.].

Myosteatosis as a Shared Biomarker for Sarcopenia and Cachexia Using MRI and Ultrasound.

Purpose: Establish bedside biomarkers of myosteatosis for sarcopenia and cachexia. We compared ultrasound biomarkers against MRI-based percent fat, histology, and CT-based muscle density among healthy adults and adults undergoing treatment for lung cancer. Methods: We compared ultrasound and MRI myosteatosis measures among young healthy, older healthy, and older adults with non-small cell lung cancer undergoing systemic treatment, all without significant medical concerns, in a cross-sectional pilot study. We assessed each participant's rectus femoris ultrasound-based echo intensity (EI), shear wave elastography-based shear wave speed, and MRI-based proton density fat-fraction (PDFF). We also assessed BMI, rectus femoris thickness and cross-sectional area. Rectus femoris biopsies were taken for all older adults (n = 20) and we analyzed chest CT scans for older adults undergoing treatment (n = 10). We determined associations between muscle assessments and BMI, and compared these assessments between groups. Results: A total of 10 young healthy adults, 10 older healthy adults, and 10 older adults undergoing treatment were recruited. PDFF was lower in young adults than in older healthy adults and older adults undergoing treatment (0.3 vs. 2.8 vs. 2.9%, respectively, p = 0.01). Young adults had significantly lower EI than older healthy adults, but not older adults undergoing treatment (48.6 vs. 81.8 vs. 75.4, p = 0.02). When comparing associations between measures, PDFF was strongly associated with EI (ρ = 0.75, p < 0.01) and moderately negatively associated with shear wave speed (ρ = -0.49, p < 0.01) but not BMI, whole leg cross-sectional area, or rectus femoris cross-sectional area. Among participants with CT scans, paraspinal muscle density was significantly associated with PDFF (ρ = -0.70, p = 0.023). Histological markers of inflammation or degradation did not differ between older adult groups. Conclusion: PDFF was sensitive to myosteatosis between young adults and both older adult groups. EI was less sensitive to myosteatosis between groups, yet EI was strongly associated with PDFF unlike BMI, which is typically used in cachexia diagnosis. Our results suggest that ultrasound measures may serve to determine myosteatosis at the bedside and are more useful diagnostically than traditional weight assessments like BMI. These results show promise of using EI, shear wave speed, and PDFF proxies of myosteatosis as diagnostic and therapeutic biomarkers of sarcopenia and cachexia.

Simultaneous T1 -weighted and T2 -weighted 3D MRI using RF phase-modulated gradient echo imaging.

PURPOSE: T1 -weighted and T2 -weighted (T1w and T2w) imaging are essential sequences in routine clinical practice to detect and characterize a wide variety of pathologies. Many approaches have been proposed to obtain T1w and T2w contrast, although many challenges still remain, including long acquisition time and limitations that favor 2D imaging. In this study, we propose a novel method for simultaneous T1w and T2w imaging using RF phase-modulated 3D gradient-echo imaging. THEORY: Configuration theory is used to derive closed-form equations for the steady state of RF phase-modulated gradient-echo signal. These equations suggest the use of small RF phase increments to provide orthogonal signal contrast with T2w and T1w in the real and imaginary components, respectively. Background phase can be removed using a two-pass acquisition with opposite RF phase increments. METHODS: Simulation and phantom experiments were performed to validate our proposed method. Volunteer images of the brain and knee were acquired to demonstrate the clinical feasibility. The proposed method was compared with T1w and T2w fast spin-echo imaging. RESULTS: The relative signal intensity of images acquired using the proposed method agreed closely with simulations and fast spin-echo imaging in phantoms. Images from volunteer imaging showed very similar contrast compared to conventional fast spin-echo imaging. CONCLUSION: Radiofrequency phase-modulated gradient-echo with small RF phase increments is an alternative method that provides simultaneous T1w and T2w contrast in short scan times with 3D volumetric coverage.

Diagnostic performance and image quality of low-tube voltage and low-contrast medium dose protocol with hybrid iterative reconstruction for hepatic dynamic CT.

OBJECTIVE: To evaluate the diagnostic performance and image quality of the low-tube voltage and low-contrast medium dose protocol for hepatic dynamic CT. METHODS: This retrospective study was conducted between January and May 2018. All patients underwent hepatic dynamic CT using one of the two protocols: tube voltage, 80 kVp and contrast dose, 370   mgI/kg with hybrid iterative reconstruction or tube voltage, 120 kVp and contrast dose, 600  mgI/kg with filtered back projection. Two radiologists independently scored lesion conspicuity and image quality. Another radiologist measured the CT numbers of abdominal organs, muscles, and hepatocellular carcinoma (HCC) in each phase. Lesion detectability, HCC diagnostic ability, and image quality of the arterial phase were compared between the two protocols using the non-inferiority test. CT numbers and HCC-to-liver contrast were compared between the protocols using the Mann-Whitney U test. RESULTS: 424 patients (70.5 ± 10.1 years) were evaluated. The 80-kVp protocol showed non-inferiority in lesion detectability and diagnostic ability for HCC (sensitivity, 85.7-89.3%; specificity, 96.3-98.6%) compared with the 120-kVp protocol (sensitivity, 91.0-93.3%; specificity, 93.6-97.3%) (p < 0.001-0.038). The ratio of fair image quality in the 80-kVp protocol also showed non-inferiority compared with that in the 120-kVp protocol in assessments by both readers (p < 0.001). HCC-to-liver contrast showed no significant differences for all phases (p = 0.309-0.705) between the two protocols. CONCLUSION: The 80-kVp protocol with hybrid iterative reconstruction for hepatic dynamic CT can decrease iodine doses while maintaining diagnostic performance and image quality compared with the 120-kVp protocol. ADVANCES IN KNOWLEDGE: The 80- and 120-kVp protocols showed equivalent hepatic lesion detectability, diagnostic ability for HCC, image quality, and HCC-to-liver contrast.The 80-kVp protocol showed a 38.3% reduction in iodine dose compared with the 120-kVp protocol.

Accelerated Acquisition of High-resolution Diffusion-weighted Imaging of the Brain with a Multi-shot Echo-planar Sequence: Deep-learning-based Denoising.

To accelerate high-resolution diffusion-weighted imaging with a multi-shot echo-planar sequence, we propose an approach based on reduced averaging and deep learning. Denoising convolutional neural networks can reduce amplified noise without requiring extensive averaging, enabling shorter scan times and high image quality. The preliminary experimental results demonstrate the superior performance of the proposed denoising method over state-of-the-art methods such as the widely used block-matching and 3D filtering.

Development of a method for the Bloch image simulation of biological tissues.

PURPOSE: The purpose of this study is to develop a method for the Bloch image simulation of biological tissues including various chemical components and T2* distribution. METHODS: The nuclear spins in the object material were modeled as a spectral intensity function Sr→ω defined by superposition of Lorentz functions with various central precession frequencies and the half width of 1/(πT2'), where 1/T2' is a relaxation rate attributable to microscopic field inhomogeneity in a voxel. Four-dimensional numerical phantoms were created to simulate Sr→ω and used for MRI simulations of the phantoms containing water and fat protons. Single slice multiple (16) gradient-echo sequences (ΔTE = 2.2 and 1.384 ms) were used for experiments at 1.5 T and 3 T and MRI simulations to evaluate the validity of the approach. RESULTS: Experimentally measured image intensities of the multiple gradient-echo imaging sequences were well reproduced by the MRI simulations. The correlation coefficients between the experimentally measured image intensities and those numerically simulated were 0.9895 to 0.9992 for the 4-component phantom at 1.5 T and 0.9580 to 0.9996 for the 7-component phantom at 3 T. CONCLUSION: T2* and chemical shift effects were successfully implemented in the MRI simulator (BlochSolver). Because this approach can be applied to other MRI simulators, the method developed in this study is useful for MRI simulation of biological tissues containing water and fat protons.

Distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma by computed tomography and magnetic resonance imaging using the Bayesian method: a bi-center study.

OBJECTIVES: To determine imaging hallmarks for distinguishing intrahepatic mass-forming biliary carcinomas (IMBCs) from hepatocellular carcinoma (HCC) and to validate their diagnostic ability using Bayesian statistics. METHODS: Study 1 retrospectively identified clinical and imaging hallmarks that distinguish IMBCs (n = 41) from HCC (n = 247) using computed tomography (CT) and magnetic resonance imaging (MRI). Study 2 retrospectively assessed the diagnostic ability of these hallmarks to distinguish IMBCs (n = 37) from HCC (n = 111) using Bayesian statistics with images obtained from a different institution. We also assessed the diagnostic ability of the hallmarks in the patient subgroup with high diagnostic confidence (≥ 80% of post-test probability). Two radiologists independently evaluated the imaging findings in studies 1 and 2. RESULTS: In study 1, arterial phase peritumoral parenchymal enhancement on CT/MRI, delayed enhancement on CT/MRI, diffusion-weighted imaging peripheral hyperintensity, and bile duct dilatation were hallmarks indicating IMBCs, whereas chronic liver disease, non-rim arterial phase hyperenhancement on CT/MRI, enhancing capsule on CT/MRI, and opposed-phase signal drop were hallmarks indicating HCC (p = 0.001-0.04). In study 2, Bayesian statistics-based post-test probability combining all hallmark features had a diagnostic accuracy of 89.2% (132/148) in distinguishing IMBCs from HCC for both readers. In the high diagnostic confidence subgroup (n = 120 and n = 124 for readers 1 and 2, respectively), the accuracy improved (95.0% (114/120) and 93.5% (116/124) for readers 1 and 2, respectively). CONCLUSIONS: Combined interpretation of CT and MRI to identify hallmark features is useful in discriminating IMBCs from HCCs. High post-test probability by Bayesian statistics allows for a more reliable non-invasive diagnosis. KEY POINTS: • Combined interpretation of CT and MRI to identify hallmark features was useful in discriminating intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma. • Bayesian method-based post-test probability combining all hallmark features determined in study 1 showed high (> 90%) sensitivity and specificity for distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma. • If the post-test probability or the confidence was ≥ 80% when combining the imaging features of CT and MRI, the high specificity of > 95% was achieved without any loss of sensitivity to distinguish hepatocellular carcinoma from intrahepatic mass-forming biliary carcinomas.

Diagnostic Performance of the Support Vector Machine Model for Breast Cancer on Ring-Shaped Dedicated Breast Positron Emission Tomography Images.

OBJECTIVE: The aim of this study was to evaluate the diagnostic ability of support vector machine (SVM) for early breast cancer (BC) using dedicated breast positron emission tomography (dbPET). METHODS: We evaluated 116 abnormal fluorodeoxyglucose (FDG) uptakes less than 2 cm on dbPET images in 105 women. Fluorodeoxyglucose uptake patterns and quantitative PET parameters were compared between BC and noncancer groups. Diagnostic accuracy of the SVM model including quantitative parameters was compared with that of visual assessment based on FDG-uptake pattern. RESULTS: Age, maximum standardized uptake value, peak standardized uptake value, total lesion glycolysis, metabolic tumor volume, and lesion-to-contralateral background ratio were significantly different between BC and noncancer groups. Area under the curve, sensitivity, specificity, and accuracy for FDG-uptake pattern of visual assessment were 0.77, 0.57, 0.77, and 0.71, respectively; those of an SVM model including age, maximum standardized uptake value, total lesion glycolysis, and lesion-to-contralateral background ratio were 0.89, 0.94, 0.77, and 0.85, respectively. CONCLUSIONS: Support vector machine showed high diagnostic performance for BC using dbPET.

Texture Analysis in the Diagnosis of Primary Breast Cancer: Comparison of High-Resolution Dedicated Breast Positron Emission Tomography (dbPET) and Whole-Body PET/CT.

Objective: This retrospective study aimed to compare the ability to classify tumor characteristics of breast cancer (BC) of positron emission tomography (PET)-derived texture features between dedicated breast PET (dbPET) and whole-body PET/computed tomography (CT). Methods: Forty-four BCs scanned by both high-resolution ring-shaped dbPET and whole-body PET/CT were analyzed. The primary BC was extracted with a standardized uptake value (SUV) threshold segmentation method. On both dbPET and PET/CT images, 38 texture features were computed; their ability to classify tumor characteristics such as tumor (T)-category, lymph node (N)-category, molecular subtype, and Ki67 levels was compared. The texture features were evaluated using univariate and multivariate analyses following principal component analysis (PCA). AUC values were used to evaluate the diagnostic power of the computed texture features to classify BC characteristics. Results: Some texture features of dbPET and PET/CT were different between Tis-1 and T2-4 and between Luminal A and other groups, respectively. No association with texture features was found in the N-category or Ki67 level. In contrast, receiver-operating characteristic analysis using texture features' principal components showed that the AUC for classification of any BC characteristics were equally good for both dbPET and whole-body PET/CT. Conclusions: PET-based texture analysis of dbPET and whole-body PET/CT may have equally good classification power for BC.

Motion Artifact Reduction Using a Convolutional Neural Network for Dynamic Contrast Enhanced MR Imaging of the Liver.

PURPOSE: To improve the quality of images obtained via dynamic contrast enhanced MRI (DCE-MRI), which contain motion artifacts and blurring using a deep learning approach. MATERIALS AND METHODS: A multi-channel convolutional neural network-based method is proposed for reducing the motion artifacts and blurring caused by respiratory motion in images obtained via DCE-MRI of the liver. The training datasets for the neural network included images with and without respiration-induced motion artifacts or blurring, and the distortions were generated by simulating the phase error in k-space. Patient studies were conducted using a multi-phase T1-weighted spoiled gradient echo sequence for the liver, which contained breath-hold failures occurring during data acquisition. The trained network was applied to the acquired images to analyze the filtering performance, and the intensities and contrast ratios before and after denoising were compared via Bland-Altman plots. RESULTS: The proposed network was found to be significantly reducing the magnitude of the artifacts and blurring induced by respiratory motion, and the contrast ratios of the images after processing via the network were consistent with those of the unprocessed images. CONCLUSION: A deep learning-based method for removing motion artifacts in images obtained via DCE-MRI of the liver was demonstrated and validated.

Utility of Stack-of-stars Acquisition for Hepatobiliary Phase Imaging without Breath-holding.

PURPOSE: Post-contrast liver magnetic resonance imaging is typically performed with breath-hold 3D gradient echo sequences. However, breath-holding for >10 s is difficult for some patients. In this study, we compared the quality of hepatobiliary phase (HBP) imaging without breath-holding using the prototype pulse sequences stack-of-stars liver acquisition with volume acceleration (LAVA) (LAVA Star) with or without navigator echoes (LAVA Starnavi+ and LAVA Starnavi-) and Cartesian LAVA with navigator echoes (Cartesian LAVAnavi+). METHODS: Seventy-two patients were included in this single-center, retrospective, cross-sectional study. HBP imaging using the three LAVA sequences (Cartesian LAVAnavi+, LAVA Starnavi-, and LAVA Starnavi+) without breath-holding was performed for all patients using a 3T magnetic resonance system. Two independent radiologists qualitatively analyzed (overall image quality, liver edge sharpness, hepatic vein clarity, streak artifacts, and respiratory motion/pulsation artifacts) HBP images taken by the three sequences using a five-point scale. Quantitative evaluations were also performed by calculating the liver-to-spleen, -lesion, and -portal vein (PV) signal intensity ratios. The results were compared between the three sequences using the Friedman test. RESULTS: LAVA Starnavi+ showed the best image quality and hepatic vein clarity (P < 0.0001). LAVA Starnavi- showed the lowest image quality (P < 0.0001-0.0106). LAVA Starnavi+ images showed fewer streak artifacts than LAVA Starnavi- images (P < 0.0001), while Cartesian LAVAnavi+ images showed no streak artifacts. Cartesian LAVAnavi+ images showed stronger respiratory motion/pulsation artifacts than the others (P < 0.0001). LAVA Starnavi- images showed the highest liver-to-spleen ratios (P < 0.0001-0.0005). Cartesian LAVAnavi+ images showed the lowest liver-to-lesion and -PV ratios (P < 0.0001-0.0108). CONCLUSION: In terms of image quality, the combination of stack-of-stars acquisition and navigator echoes is the best for HBP imaging without breath-holding.

Clinical Evaluation of Respiratory-triggered 3D MRCP with Navigator Echoes Compared to Breath-hold Acquisition Using Compressed Sensing and/or Parallel Imaging.

PURPOSE: To compare the image quality of three-dimensional magnetic resonance cholangiopancreatography (MRCP) acquired with respiratory triggering against breath-hold 3D MRCP with compressed sensing (CS) and parallel imaging (PI) in a clinical setting. METHODS: This study included 93 patients (45 men, mean age: 69.7 ± 9.3 years), in whom three types of 3D MRCP were performed: 3D breath-hold MRCP with CS and PI reconstruction (BH-CS-MRCP) and PI only reconstruction (BH-PI-MRCP) additionally to 3D respiratory triggered MRCP with navigator echoes (Nav-MRCP). Duct visualization and overall image quality were blindly evaluated on a four-point scale by two independent radiologists. Quantitative analysis was performed by calculating the relative duct-to-periductal contrast (RC) of three main biliary segments. Comparison between the methods was performed using paired t-test. RESULTS: Acquisition time was 23 s for both breath-hold MRCP protocols and 1 min 29 s for Nav-MRCP. Mean grading (Nav/CS/PI) for common bile duct (2.74/2.87/2.94), common hepatic duct (2.82/2.92/3.00), central right hepatic duct (2.75/2.85/2.98), central left hepatic duct (2.75/2.85/2.92) and cystic duct (2.22/2.34/2.42) was higher in BH-CS- and BH-PI-MRCP, whereas Nav-MRCP showed higher grading in the peripheral segments (peripheral right hepatic duct: 2.24/2.01/2.12; peripheral left hepatic duct: 2.23/2.02/2.13). Overall image quality of Nav-MRCP (2.91 ± 0.7) was not different from BH-PI-MRCP (2.92 ± 0.6) (P = 0.163), but higher than BH-CS-MRCP (2.80 ± 0.7) (P = 0.031). Quantitative analysis showed lower RC values for CS- and PI-MRCP than Nav-MRCP (P < 0.001). CONCLUSION: Breath-hold 3D MRCP were feasible using PI and CS. Visualization of the greater ductal system was even superior in breath-hold MRCP than in Nav-MRCP by considerably reducing acquisition time. Both breath-hold methods are suitable for revised MRI protocols notably in patients with irregular respiratory cycle.

Improving the Quality of Diffusion-weighted Imaging of the Left Hepatic Lobe Using Weighted Averaging of Signals from Multiple Excitations.

BACKGROUND: Diffusion-weighted imaging (DWI) is useful for detecting and characterizing liver lesions but is sensitive to organ motion artifact, especially in the left lobe. PURPOSE: To assess the signal intensity (SI) loss in the left hepatic lobe on DWI depending on motion-proving gradient (MPG) pulse direction (preliminary study) and to evaluate the usefulness of modified signal averaging to reduce the SI loss on DWI (application study). METHODS: About 48 (preliminary) and 35 (application) patients were included. In the preliminary study, DWI with four different MPG directions, only a single MPG pulse direction (x-, y-, or z-axis) and all three directions combined (standard DWI), were reconstructed from the original data. In the application study, we examined the usefulness of the weighted averaging number of excitations (wNEX) method, in which a larger weighting factor is applied to the higher signal in pixel-by-pixel NEX signal averaging by comparing four reconstruction methods. We assumed that true signals would be the same in both lobes. The SI and apparent diffusion coefficient (ADC) ratios for the left versus right lobe were calculated by dividing the SI/ADC of the right lobe by that of the left lobe. RESULTS: In the preliminary study, the SI ratio was significantly lower on DWI using only the x-axis but was significantly higher on DWI using only the z-axis (both P < 0.0001) when compared with standard DWI. In the application study, the SI (mean, 1.15-1.17) and ADC (0.90-0.92) ratios on DWI with wNEX were closer to 1.0 than those on standard DWI (SI ratio, 1.32-1.38; ADC ratio 0.80-0.81); the differences were significant (all P < 0.0001). CONCLUSION: The MPG pulse along the z-axis caused signal loss in the left hepatic lobe. The wNEX reconstruction method effectively reduced signal loss in the left lobe on DWI.

Multiparameter estimation using multi-echo spoiled gradient echo with variable flip angles and multicontrast compressed sensing.

PURPOSE: To develop multiparameter mapping including T1 , R2*, and proton density fat fraction with a single breath-hold to evaluate liver disease and liver function. METHODS: A 6-echo spoiled gradient-echo sequence with dual flip angles was used to acquire a 12-set MRI volume data set. To shorten the scan time, undersampling and multicontrast compressed-sensing reconstruction were used. The scan time was 18 seconds. R2* and proton density fat fraction mapping were achieved by using the iterative least-squares method. T1 mapping was estimated using driven equilibrium single-pulse observation of T1 . Quantitative values were validated by performing phantom and volunteer studies. RESULTS: Statistical analysis showed that the quantitative values measured using the proposed methods agreed with those measured using conventional methods. T1 values of water proton measured by the proposed method in phantom and volunteer studies were in good agreement with those by MRS. CONCLUSION: The results showed that accurate quantitative mapping of T1 , R2*, and proton density fat fraction with a single breath-hold was achieved using our approach.