State-of-the-Art Quantification of Liver Iron With MRI-Vendor Implementation and Available Tools.

The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron overload and guiding the titration of chelation therapy is increasingly established for routine clinical practice. However, the existence of multiple MRI-based LIC quantification techniques limits standardization and widespread clinical adoption. In this article, we review the existing and widely accepted MRI-based LIC estimation methods at 1.5 T and 3 T: signal intensity ratio (SIR) and relaxometry (R2 and R2*) and discuss the basic principles, acquisition and analysis protocols, and MRI-LIC calibrations for each technique. Further, we provide an up-to-date information on MRI vendor implementations and available offline commercial and free software for each MRI-based LIC quantification approach. We also briefly review the emerging and advanced MRI techniques for LIC estimation and their current limitations for clinical use. Lastly, we discuss the implications of MRI-based LIC measurements on clinical use and decision-making in the management of patients with iron overload. Some of the key highlights from this review are as follows: 1) Both R2 and R2* can estimate accurate and reproducible LIC, when validated acquisition parameters and analysis protocols are applied, 2) Although the Ferriscan R2 method has been widely used, recent consensus and guidelines endorse R2*-MRI as the most accurate and reproducible method for LIC estimation, 3) Ongoing efforts aim to establish R2*-MRI as the standard approach for quantifying LIC, and 4) Emerging R2*-MRI techniques employ radial sampling strategies and offer improved motion compensation and broader dynamic range for LIC estimation. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Linearity and bias of proton density fat fraction across the full dynamic range of 0-100%: a multiplatform, multivendor phantom study using 1.5T and 3T MRI at two sites.

OBJECTIVE: Performance assessments of quantitative determinations of proton density fat fraction (PDFF) have largely focused on the range between 0 and 50%. We evaluate PDFF in a two-site phantom study across the full 0-100% PDFF range. MATERIALS AND METHODS: We used commercially available 3D chemical-shift-encoded water-fat MRI sequences from three MRI system vendors at 1.5T and 3T and conducted the study across two sites. A spherical phantom housing 18 vials spanning the full 0-100% PDFF range was used. Data at each site were acquired using default parameters to determine same-day and different-day intra-scanner repeatability, and inter-system and inter-site reproducibility, in addition to linear regression between reference and measured PDFF values. RESULTS: Across all systems, results demonstrated strong linearity and minimal bias. For 1.5T systems, a pooled slope of 0.99 with a 95% confidence interval (CI) of 0.981-0.997 and a pooled intercept of 0.61% PDFF with a 95% CI of 0.17-1.04 were obtained. Results for pooled 3T data included a slope of 1.00 (95% CI 0.995-1.005) and an intercept of 0.69% PDFF (95% CI 0.39-0.97). Inter-site and inter-system reproducibility coefficients ranged from 2.9 to 6.2 (in units of PDFF), while intra-scanner same-day and different-day repeatability ranged from 0.6 to 7.8. DISCUSSION: PDFF across the 0-100% range can be reliably estimated using current commercial offerings at 1.5T and 3T.

Organ fat in Latino youth at risk for type 2 diabetes.

PURPOSE: Obesity in youth increases the risk for type 2 diabetes (T2D) and elevated abdominal adipose tissue and organ fat may be particularly deleterious. The purpose of this study was to examine associations among measures of adiposity including total, visceral, and organ fat (hepatic and pancreatic) and whether these measures were independently associated with glycemia in Latino youth at risk for diabetes. METHODS: Latino adolescents (47 boys and 32 girls, 13.7 ± 1.4 years) with obesity (BMIz 2.3 ± 0.3) were assessed for total fat by DXA and visceral and organ fat by 3 T magnetic resonance imaging. Glycemic indicators included HbA1c, fasting glucose (FG), and 2-h glucose (2-HrG) following an oral glucose tolerance test. Pearson correlations and stepwise linear regression analyses controlling for age and sex were used to examine independent associations between adiposity and glycemia. RESULTS: Total fat was associated with visceral (r = 0.66, p = 0.001) and hepatic fat (r = 0.34, p < 0.01) while visceral fat was associated with hepatic (r = 0.42, p < 0.001) and pancreatic fat (r = 0.36, p < 0.001). In stepwise linear regression analysis, hepatic and pancreatic fat were significant predictors of FG, explaining 4.7% and 5.2% of the variance, respectively (total R2  = 0.14, p = 0.02). Hepatic fat was the only significant predictor of 2-HrG explaining 9.9% of the variance in the model (total R2  = 0.12, p = 0.03). No measure of adiposity was retained as a significant predictor of HbA1c. CONCLUSION: Hepatic and pancreatic fat were the only adiposity measures independently associated with glycemia but the small amount of variance explained underscores the need for additional T2D biomarkers in high risk youth.

Validation of automated bone age analysis from hand radiographs in a North American pediatric population.

BACKGROUND: Radiographic bone age assessment by automated software is precise and instantaneous. OBJECTIVE: The aim of this study was to evaluate the accuracy of an automated tool for bone age assessment. MATERIALS AND METHODS: We compared a total of 586 bone age radiographs from 451 patients, which had been assessed by three radiologists from 2013 to 2018, with bone age analysis by BoneXpert, using the Greulich and Pyle method. We made bone age comparisons in different patient groups based on gender, diagnosis and race, and in a subset with repeated bone age studies. We calculated Spearman correlation (r) and accuracy (root mean square error, or R2). RESULTS: Bone age analyses by automated and manual assessments showed a strong correlation (r=0.98; R2=0.96; P<0.0001), with the mean bone age difference of 0.12±0.76 years. Bone age comparisons by the two methods remained strongly correlated (P<0.0001) when stratified by gender, common endocrine conditions including growth disorders and early/precocious puberty, and race. In the longitudinal analysis, we also found a strong correlation between the automated software and manual bone age over time (r=0.7852; R2=0.63; P<0.01). CONCLUSION: Automated bone age assessment was found to be reliable and accurate in a large cohort of pediatric patients in a clinical practice setting in North America.

Advanced imaging use and payment trends in a large pediatric accountable care organization.

BACKGROUND: Pediatric imaging use and payment trends in accountable care organizations (ACOs) are seldom studied but are important for health policy decisions and resource allocation. OBJECTIVE: To evaluate patterns of advanced imaging use and associated payments over a 7-year period at a large ACO in the USA serving a Medicaid population. MATERIALS AND METHODS: We reviewed paid claims data from 2011 through 2017 from an ACO, analyzing the MRI, CT and US use trends and payments from emergency department (ED) and outpatient encounters. We defined "utilization rate" as the number of advanced imaging procedures per 100 enrolled children per calendar year. Average yearly utilization and payments trends were analyzed using Pearson correlation. RESULTS: Across 7 years, 186,552 advanced imaging procedures were performed. The average overall utilization rate was 6.99 (95% confidence interval [CI]: 6.9-7.1). In the ED this was 2.7 (95% CI: 2.6-2.8) and in outpatients 4.3 (95% CI: 4.2-4.3). The overall utilization rate grew by 0.7% yearly (P=0.077), with US growing the most at 4.0% annually (P=0.0005), especially in the ED in the US, where it grew 10.8% annually (P=0.000019). The overall payments were stable from 2011 to 2017, with outpatient MRI seeing the largest payment decrease at 1.8% (P=0.24) and ED US showing the most growth at 3.3% (P=0.00016). Head CT and abdominal US were the two most common procedures. CONCLUSION: Over the study period, advanced imaging utilization at this large pediatric ACO serving the Medicaid population increased, especially with US use in the ED. Overall payments related to advanced imaging remained stable over this period.

Linearity and Bias of Proton Density Fat Fraction as a Quantitative Imaging Biomarker: A Multicenter, Multiplatform, Multivendor Phantom Study.

Background Proton density fat fraction (PDFF) estimated by using chemical shift-encoded (CSE) MRI is an accepted imaging biomarker of hepatic steatosis. This work aims to promote standardized use of CSE MRI to estimate PDFF. Purpose To assess the accuracy of CSE MRI methods for estimating PDFF by determining the linearity and range of bias observed in a phantom. Materials and Methods In this prospective study, a commercial phantom with 12 vials of known PDFF values were shipped across nine U.S. centers. The phantom underwent 160 independent MRI examinations on 27 1.5-T and 3.0-T systems from three vendors. Two three-dimensional CSE MRI protocols with minimal T1 bias were included: vendor and standardized. Each vendor's confounder-corrected complex or hybrid magnitude-complex based reconstruction algorithm was used to generate PDFF maps in both protocols. The Siemens reconstruction required a configuration change to correct for water-fat swaps in the phantom. The MRI PDFF values were compared with the known PDFF values by using linear regression with mixed-effects modeling. The 95% CIs were calculated for the regression slope (ie, proportional bias) and intercept (ie, constant bias) and compared with the null hypothesis (slope = 1, intercept = 0). Results Pooled regression slope for estimated PDFF values versus phantom-derived reference PDFF values was 0.97 (95% CI: 0.96, 0.98) in the biologically relevant 0%-47.5% PDFF range. The corresponding pooled intercept was -0.27% (95% CI: -0.50%, -0.05%). Across vendors, slope ranges were 0.86-1.02 (vendor protocols) and 0.97-1.0 (standardized protocol) at 1.5 T and 0.91-1.01 (vendor protocols) and 0.87-1.01 (standardized protocol) at 3.0 T. The intercept ranges (absolute PDFF percentage) were -0.65% to 0.18% (vendor protocols) and -0.69% to -0.17% (standardized protocol) at 1.5 T and -0.48% to 0.10% (vendor protocols) and -0.78% to -0.21% (standardized protocol) at 3.0 T. Conclusion Proton density fat fraction estimation derived from three-dimensional chemical shift-encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and field strengths, with use of the vendors' product acquisition and reconstruction software. © RSNA, 2021 See also the editorial by Dyke in this issue.

Temperature-corrected proton density fat fraction estimation using chemical shift-encoded MRI in phantoms.

PURPOSE: Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study. THEORY AND METHODS: A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature. RESULTS: Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction. CONCLUSION: Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.

Free-Breathing Volumetric Liver R2* and Proton Density Fat Fraction Quantification in Pediatric Patients Using Stack-of-Radial MRI With Self-Gating Motion Compensation.

BACKGROUND: Stack-of-radial multiecho gradient-echo MRI is promising for free-breathing liver R2* quantification and may benefit children. PURPOSE: To validate stack-of-radial MRI with self-gating motion compensation in phantoms, and to evaluate it in children. STUDY TYPE: Prospective. PHANTOMS: Four vials with different R2* driven by a motion stage. SUBJECTS: Sixteen pediatric patients with suspected nonalcoholic fatty liver disease or steatohepatitis (five females, 13 ± 4 years, body mass index 29.2 ± 8.6 kg/m2 ). FIELD STRENGTH/SEQUENCES: Stack-of-radial, and 2D and 3D Cartesian multiecho gradient-echo sequences at 3T. ASSESSMENT: Ungated and gated stack-of-radial proton density fat fraction (PDFF) and R2* maps were reconstructed without and with self-gating motion compensation. Stack-of-radial R2* measurements of phantoms without and with motion were validated against reference 2D Cartesian results of phantoms without motion. In subjects, free-breathing stack-of-radial and reference breath-hold 3D Cartesian were acquired. Subject inclusion for statistical analysis and region of interest placement were determined independently by two observers. STATISTICAL TESTS: Phantom results were fitted with a weighted linear model. Demographic differences between excluded and included subjects were tested by multivariate analysis of variance. PDFF and R2* measurements were compared using Bland-Altman analysis. Interobserver agreement was assessed by the intraclass correlation coefficient (ICC). RESULTS: Ungated stack-of-radial R2* inside moving phantom vials showed a significant positive bias of 64.3 s-1 (P < 0.00001), unlike gated results (P > 0.31). Subject inclusion decisions for statistical analysis from two observers were consistent. No significant differences were found between four excluded and 12 included subjects (P = 0.14). Compared to breath-hold Cartesian, ungated and gated free-breathing stack-of-radial exhibited mean R2* differences of 18.5 s-1 and 3.6 s-1 . Mean PDFF differences were 1.1% and 1.0% for ungated and gated measurements, respectively. Interobserver agreement was excellent (ICC for PDFF = 0.99, ICC for R2* = 0.90; P < 0.0003). DATA CONCLUSION: Stack-of-radial MRI with self-gating motion compensation seems to allow free-breathing liver R2* and PDFF quantification in children. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 2.

Magnetic resonance imaging of obesity and metabolic disorders: Summary from the 2019 ISMRM Workshop.

More than 100 attendees from Australia, Austria, Belgium, Canada, China, Germany, Hong Kong, Indonesia, Japan, Malaysia, the Netherlands, the Philippines, Republic of Korea, Singapore, Sweden, Switzerland, the United Kingdom, and the United States convened in Singapore for the 2019 ISMRM-sponsored workshop on MRI of Obesity and Metabolic Disorders. The scientific program brought together a multidisciplinary group of researchers, trainees, and clinicians and included sessions in diabetes and insulin resistance; an update on recent advances in water-fat MRI acquisition and reconstruction methods; with applications in skeletal muscle, bone marrow, and adipose tissue quantification; a summary of recent findings in brown adipose tissue; new developments in imaging fat in the fetus, placenta, and neonates; the utility of liver elastography in obesity studies; and the emerging role of radiomics in population-based "big data" studies. The workshop featured keynote presentations on nutrition, epidemiology, genetics, and exercise physiology. Forty-four proffered scientific abstracts were also presented, covering the topics of brown adipose tissue, quantitative liver analysis from multiparametric data, disease prevalence and population health, technical and methodological developments in data acquisition and reconstruction, newfound applications of machine learning and neural networks, standardization of proton density fat fraction measurements, and X-nuclei applications. The purpose of this article is to summarize the scientific highlights from the workshop and identify future directions of work.

Newly Developed Methods for Reducing Motion Artifacts in Pediatric Abdominal MRI: Tips and Pearls.

OBJECTIVE. The purpose of this article is to review established and emerging methods for reducing motion artifacts in pediatric abdominal MRI. CONCLUSION. Clearly understanding the strengths and limitations of motion reduction methods can enable practitioners of pediatric abdominal MRI to select and combine the appropriate techniques and potentially reduce the need for sedation and anesthesia.

MRI of tibial stress fractures: relationship between Fredericson classification and time to recovery in pediatric athletes.

BACKGROUND: Tibial stress fractures are not uncommon in pediatric athletes. The severity of injury may be graded using magnetic resonance imaging (MRI). OBJECTIVE: To determine whether Fredericson MRI grading of tibial stress fractures can differentiate times to recovery across different grades in pediatric athletes. MATERIALS AND METHODS: A medical record search identified all athletes younger than 19 years old who had tibial stress fractures confirmed by MRI and were treated by sports medicine specialists in our clinic system over a 5-year period. Two pediatric radiologists graded MRI exams using the Fredericson system. Time to recovery (in days) was defined in four ways: pain onset to full participation, pain onset to zero pain, first treatment to full sport participation and first treatment to zero pain. Recovery times were compared to tibial stress fracture Fredericson MRI grade and to the use of a recovery device. RESULTS: Thirty-eight pediatric athletes (age range: 7-18 years, mean: 15.4±2.2 years) had 42 tibial stress fractures while participating in 12 different sports. About half (55%) were track and/or cross-country athletes. The mean time from diagnosis to report of no pain for all patients was 55.6±5.0 days. We found no significant difference in time to recovery across stress fracture grade or with the use of a recovery device. CONCLUSION: No differences were noted between Fredericson stress fracture grades and different time periods to recovery or between differences in recovery time and the return to full participation in sports, regardless of the use of assistive devices.

Age-related differences in neural activation and functional connectivity during the processing of vocal prosody in adolescence.

The ability to recognize others' emotions based on vocal emotional prosody follows a protracted developmental trajectory during adolescence. However, little is known about the neural mechanisms supporting this maturation. The current study investigated age-related differences in neural activation during a vocal emotion recognition (ER) task. Listeners aged 8 to 19 years old completed the vocal ER task while undergoing functional magnetic resonance imaging. The task of categorizing vocal emotional prosody elicited activation primarily in temporal and frontal areas. Age was associated with a) greater activation in regions in the superior, middle, and inferior frontal gyri, b) greater functional connectivity between the left precentral and inferior frontal gyri and regions in the bilateral insula and temporo-parietal junction, and c) greater fractional anisotropy in the superior longitudinal fasciculus, which connects frontal areas to posterior temporo-parietal regions. Many of these age-related differences in brain activation and connectivity were associated with better performance on the ER task. Increased activation in, and connectivity between, areas typically involved in language processing and social cognition may facilitate the development of vocal ER skills in adolescence.

Fast data acquisition techniques in magnetic resonance spectroscopic imaging.

Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per TR . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.

Post-contrast T1-weighted spine 3T MRI in children using a golden-angle radial acquisition.

PURPOSE: MRI methods that have reduced sensitivity to motion are attractive in pediatric applications. In spine imaging, physiologic motion such as respiration and cerebrospinal fluid pulsation can hamper diagnostic image quality. We compare a 3D T1-weighted non-Cartesian radial acquisition with a conventional Cartesian 2D turbo-spin-echo (TSE) acquisition in axial post-contrast spine imaging at 3T. METHODS: Thirty-two patients (mean age 12.2 ± 5.3 years) scheduled for routine clinical spine exams with contrast were enrolled. Three pediatric neuroradiologists compared the two sequences and assessed the presence of motion, the conspicuity of nerve roots, and whether one of the sequences was preferred in visualizing pathology using Likert scales. RESULTS: The Fleiss' kappa statistic for inter-rater agreement was 0.29 (95% confidence interval, 0.15-0.43) for the presence of motion, 0.30 (0.21-0.38) for conspicuity, and 0.37 (0.19-0.55) for sequence preference. Radial images were less sensitive to motion than TSE (p < 0.01). Motion and consequent artifacts were present in all TSE cases, while it was absent in 51% of the radial cases. In depicting nerve roots, radial images were superior in the cervical (p < 0.05), thoracic (p < 0.01), and lumbar spines (p < 0.01). Lastly, in 28 of the 32 patients who demonstrated contrast-enhancing pathology, radial images were preferred in 51% of the cases, while both sequences were equally preferred in 41% of the cases. CONCLUSION: We demonstrate the potential utility of radial MRI in post-contrast spine imaging. The free-breathing method is robust in generating diagnostic image quality and is superior in visualizing nerve roots and extramedullary metastases than traditional Cartesian TSE acquisitions.

Techniques and Applications of Magnetic Resonance Imaging for Studying Brown Adipose Tissue Morphometry and Function.

The present review reports on the current knowledge and recent findings in magnetic resonance imaging (MRI) and spectroscopy (MRS) of brown adipose tissue (BAT). The work summarizes the features and mechanisms that allow MRI to differentiate BAT from white adipose tissue (WAT) by making use of their distinct morphological appearance and the functional characteristics of BAT. MR is a versatile imaging modality with multiple contrast mechanisms as potential candidates in the study of BAT, targeting properties of 1H, 13C, or 129Xe nuclei. Techniques for assessing BAT morphometry based on fat fraction and markers of BAT microstructure, including intermolecular quantum coherence and diffusion imaging, are first described. Techniques for assessing BAT function based on the measurement of BAT metabolic activity, perfusion, oxygenation, and temperature are then presented. The application of the above methods in studies of BAT in animals and humans is described, and future directions in MR study of BAT are finally discussed.

2-D magnetic resonance spectroscopic imaging of the pediatric brain using compressed sensing.

BACKGROUND: Magnetic resonance spectroscopic imaging helps to determine abnormal brain tissue conditions by evaluating metabolite concentrations. Although a powerful technique, it is underutilized in routine clinical studies because of its long scan times. OBJECTIVE: In this study, we evaluated the feasibility of scan time reduction in metabolic imaging using compressed-sensing-based MR spectroscopic imaging in pediatric patients undergoing routine brain exams. MATERIALS AND METHODS: We retrospectively evaluated compressed-sensing reconstructions in MR spectroscopic imaging datasets from 20 pediatric patients (11 males, 9 females; average age: 5.4±4.5 years; age range: 3 days to 16 years). We performed retrospective under-sampling of the MR spectroscopic imaging datasets to simulate accelerations of 2-, 3-, 4-, 5-, 7- and 10-fold, with subsequent reconstructions in MATLAB. Metabolite maps of N-acetylaspartate, creatine, choline and lactate (where applicable) were quantitatively evaluated in terms of the root-mean-square error (RMSE), peak amplitudes and total scan time. We used the two-tailed paired t-test along with linear regression analysis to statistically compare the compressed-sensing reconstructions at each acceleration with the fully sampled reference dataset. RESULTS: High fidelity was maintained in the compressed-sensing MR spectroscopic imaging reconstructions from 50% to 80% under-sampling, with the RMSE not exceeding 3% in any dataset. Metabolite intensities and ratios evaluated on a voxel-by-voxel basis showed no statistically significant differences and mean metabolite intensities showed high correlation compared to the fully sampled reference dataset up to an acceleration factor of 5. CONCLUSION: Compressed-sensing MR spectroscopic imaging has the potential to reduce MR spectroscopic imaging scan times for pediatric patients, with negligible information loss.

Advanced neuroimaging in traumatic brain injury: an overview.

Traumatic brain injury (TBI) is a common condition with many potential acute and chronic neurological consequences. Standard initial radiographic evaluation includes noncontrast head CT scanning to rapidly evaluate for pathology that might require intervention. The availability of fast, relatively inexpensive CT imaging has fundamentally changed the clinician's ability to noninvasively visualize neuroanatomy. However, in the context of TBI, limitations of head CT without contrast include poor prognostic ability, inability to analyze cerebral perfusion status, and poor visualization of underlying posttraumatic changes to brain parenchyma. Here, the authors review emerging advanced imaging for evaluation of both acute and chronic TBI and include QuickBrain MRI as an initial imaging modality. Dynamic susceptibility-weighted contrast-enhanced perfusion MRI, MR arterial spin labeling, and perfusion CT are reviewed as methods for examining cerebral blood flow following TBI. The authors evaluate MR-based diffusion tensor imaging and functional MRI for prognostication of recovery post-TBI. Finally, MR elastography, MR spectroscopy, and convolutional neural networks are examined as future tools in TBI management. Many imaging technologies are being developed and studied in TBI, and some of these may hold promise in improving the understanding and management of TBI. ABBREVIATIONS ASL = arterial spin labeling; CNN = convolutional neural network; CTP = perfusion CT; DAI = diffuse axonal injury; DMN = default mode network; DOC = disorders of consciousness; DTI = diffusion tensor imaging; FA = fractional anisotropy; fMRI = functional MRI; GCS = Glasgow Coma Scale; MD = mean diffusivity; MRE = MR elastography; MRS = MR spectroscopy; mTBI = mild TBI; NAA = N-acetylaspartate; SWI = susceptibility-weighted imaging; TBI = traumatic brain injury; UHF = ultra-high field.

Linearity, Bias, and Precision of Hepatic Proton Density Fat Fraction Measurements by Using MR Imaging: A Meta-Analysis.

Purpose To determine the linearity, bias, and precision of hepatic proton density fat fraction (PDFF) measurements by using magnetic resonance (MR) imaging across different field strengths, imager manufacturers, and reconstruction methods. Materials and Methods This meta-analysis was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A systematic literature search identified studies that evaluated the linearity and/or bias of hepatic PDFF measurements by using MR imaging (hereafter, MR imaging-PDFF) against PDFF measurements by using colocalized MR spectroscopy (hereafter, MR spectroscopy-PDFF) or the precision of MR imaging-PDFF. The quality of each study was evaluated by using the Quality Assessment of Studies of Diagnostic Accuracy 2 tool. De-identified original data sets from the selected studies were pooled. Linearity was evaluated by using linear regression between MR imaging-PDFF and MR spectroscopy-PDFF measurements. Bias, defined as the mean difference between MR imaging-PDFF and MR spectroscopy-PDFF measurements, was evaluated by using Bland-Altman analysis. Precision, defined as the agreement between repeated MR imaging-PDFF measurements, was evaluated by using a linear mixed-effects model, with field strength, imager manufacturer, reconstruction method, and region of interest as random effects. Results Twenty-three studies (1679 participants) were selected for linearity and bias analyses and 11 studies (425 participants) were selected for precision analyses. MR imaging-PDFF was linear with MR spectroscopy-PDFF (R2 = 0.96). Regression slope (0.97; P < .001) and mean Bland-Altman bias (-0.13%; 95% limits of agreement: -3.95%, 3.40%) indicated minimal underestimation by using MR imaging-PDFF. MR imaging-PDFF was precise at the region-of-interest level, with repeatability and reproducibility coefficients of 2.99% and 4.12%, respectively. Field strength, imager manufacturer, and reconstruction method each had minimal effects on reproducibility. Conclusion MR imaging-PDFF has excellent linearity, bias, and precision across different field strengths, imager manufacturers, and reconstruction methods. © RSNA, 2017 Online supplemental material is available for this article. An earlier incorrect version of this article appeared online. This article was corrected on October 2, 2017.