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Purpose: Abdominal imaging is frequently performed with breath holds or respiratory triggering to reduce the effects of respiratory motion. Diffusion weighted sequences provide a useful clinical contrast but have prolonged scan times due to low signal‐to‐noise ratio (SNR), and cannot be completed in a single breath hold. Echo‐planar imaging (EPI) is the most commonly used trajectory for diffusion weighted imaging but it is susceptible to off‐resonance artifacts. A respiratory resolved, three‐dimensional (3D) diffusion prepared sequence that obtains distortionless diffusion weighted images during free‐breathing is presented. Techniques to address the myriad of challenges including: 3D shot‐to‐shot phase correction, respiratory binning, diffusion encoding during free‐breathing, and robustness to off‐resonance are described. Methods: A twice‐refocused, M1‐nulled diffusion preparation was combined with an RF‐spoiled gradient echo readout and respiratory resolved reconstruction to obtain free‐breathing diffusion weighted images in the abdomen. Cartesian sampling permits a sampling density that enables 3D shot‐to‐shot phase navigation and reduction of transient fat artifacts. Theoretical properties of a region‐based shot rejection are described. The region‐based shot rejection method was evaluated with free‐breathing (normal and exaggerated breathing), and respiratory triggering. The proposed sequence was compared in vivo with multishot DW‐EPI. Results: The proposed sequence exhibits no evident distortion in vivo when compared to multishot DW‐EPI, robustness to B0 and B1 field inhomogeneities, and robustness to motion from different respiratory patterns. Conclusion: Acquisition of distortionless, diffusion weighted images is feasible during free‐breathing with a b‐value of 500 s/mm2, scan time of 6 min, and a clinically viable reconstruction time. [ABSTRACT FROM AUTHOR]

Purpose: To develop and validate a deep learning‐based reconstruction framework for highly accelerated two‐dimensional (2D) phase contrast (PC‐MRI) data with accurate and precise quantitative measurements. Methods: We propose a modified DL‐ESPIRiT reconstruction framework for 2D PC‐MRI, comprised of an unrolled neural network architecture with a Complex Difference estimation (CD‐DL). CD‐DL was trained on 155 fully sampled 2D PC‐MRI pediatric clinical datasets. The fully sampled data (n=29$$ n=29 $$) was retrospectively undersampled (6–11×$$ \times $$) and reconstructed using CD‐DL and a parallel imaging and compressed sensing method (PICS). Measurements of peak velocity and total flow were compared to determine the highest acceleration rate that provided accuracy and precision within ±5%$$ \pm 5\% $$. Feasibility of CD‐DL was demonstrated on prospectively undersampled datasets acquired in pediatric clinical patients (n=5$$ n=5 $$) and compared to traditional parallel imaging (PI) and PICS. Results: The retrospective evaluation showed that 9×$$ \times $$ accelerated 2D PC‐MRI images reconstructed with CD‐DL provided accuracy and precision (bias, [95%$$ \% $$ confidence intervals]) within ±5%$$ \pm 5\% $$. CD‐DL showed higher accuracy and precision compared to PICS for measurements of peak velocity (2.8%$$ \% $$ [−2.9$$ -2.9 $$, 4.5] vs. 3.9%$$ \% $$ [−11.0$$ -11.0 $$, 4.9]) and total flow (1.8%$$ \% $$ [−3.9$$ -3.9 $$, 3.4] vs. 2.9%$$ \% $$ [−7.1$$ -7.1 $$, 6.9]). The prospective feasibility study showed that CD‐DL provided higher accuracy and precision than PICS for measurements of peak velocity and total flow. Conclusion: In a retrospective evaluation, CD‐DL produced quantitative measurements of 2D PC‐MRI peak velocity and total flow with ≤5%$$ \le 5\% $$ error in both accuracy and precision for up to 9×$$ \times $$ acceleration. Clinical feasibility was demonstrated using a prospective clinical deployment of our 8×$$ \times $$ undersampled acquisition and CD‐DL reconstruction in a cohort of pediatric patients. [ABSTRACT FROM AUTHOR]

T1 mapping is increasingly used in clinical practice and research studies. With limited scan time, existing techniques often have limited spatial resolution, contrast resolution and slice coverage. High fat concentrations yield complex errors in Look–Locker T1 methods. In this study, a dual‐echo 2D radial inversion‐recovery T1 (DEradIR‐T1) technique was developed for fast fat–water separated T1 mapping. The DEradIR‐T1 technique was tested in phantoms, 5 volunteers and 28 patients using a 3 T clinical MRI scanner. In our study, simulations were performed to analyze the composite (fat + water) and water‐only T1 under different echo times (TE). In standardized phantoms, an inversion‐recovery spin echo (IR‐SE) sequence with and without fat saturation pulses served as a T1 reference. Parameter mapping with DEradIR‐T1 was also assessed in vivo, and values were compared with modified Look–Locker inversion recovery (MOLLI). Bland–Altman analysis and two‐tailed paired t‐tests were used to compare the parameter maps from DEradIR‐T1 with the references. Simulations of the composite and water‐only T1 under different TE values and levels of fat matched the in vivo studies. T1 maps from DEradIR‐T1 on a NIST phantom (Pcomp = 0.97) and a Calimetrix fat–water phantom (Pwater = 0.56) matched with the references. In vivo T1 was compared with that of MOLLI: Rcomp2=0.77; Rwater2=0.72. In this work, intravoxel fat is found to have a variable, echo‐time‐dependent effect on measured T1 values, and this effect may be mitigated using the proposed DRradIR‐T1. [ABSTRACT FROM AUTHOR]

Purpose: To enable motion‐robust, ungated, free‐breathing R2∗ mapping of hepatic iron overload in children with 3D multi‐echo UTE cones MRI. Methods: A golden‐ratio re‐ordered 3D multi‐echo UTE cones acquisition was developed with chemical‐shift encoding (CSE). Multi‐echo complex‐valued source images were reconstructed via gridding and coil combination, followed by confounder‐corrected R2∗ (=1/T2∗) mapping. A phantom containing 15 different concentrations of gadolinium solution (0–300 mM) was imaged at 3T. 3D multi‐echo UTE cones with an initial TE of 0.036 ms and Cartesian CSE‐MRI (IDEAL‐IQ) sequences were performed. With institutional review board approval, 85 subjects (81 pediatric patients with iron overload + 4 healthy volunteers) were imaged at 3T using 3D multi‐echo UTE cones with free breathing (FB cones), IDEAL‐IQ with breath holding (BH Cartesian), and free breathing (FB Cartesian). Overall image quality of R2∗ maps was scored by 2 blinded experts and compared by a Wilcoxon rank‐sum test. For each pediatric subject, the paired R2∗ maps were assessed to determine if a corresponding artifact‐free 15 mm region‐of‐interest (ROI) could be identified at a mid‐liver level on both images. Agreement between resulting R2∗ quantification from FB cones and BH/FB Cartesian was assessed with Bland‐Altman and linear correlation analyses. Results: ROI‐based regression analysis showed a linear relationship between gadolinium concentration and R2∗ in IDEAL‐IQ (y = 8.83x − 52.10, R2 = 0.995) as well as in cones (y = 9.19x − 64.16, R2 = 0.992). ROI‐based Bland‐Altman analysis showed that the mean difference (MD) was 0.15% and the SD was 5.78%. However, IDEAL‐IQ R2∗ measurements beyond 200 mM substantially deviated from a linear relationship for IDEAL‐IQ (y = 5.85x + 127.61, R2 = 0.827), as opposed to cones (y = 10.87x − 166.96, R2 = 0.984). In vivo, FB cones R2∗ had similar image quality with BH and FB Cartesian in 15 and 42 cases, respectively. FB cones R2∗ had better image quality scores than BH and FB Cartesian in 3 and 21 cases, respectively, where BH/FB Cartesian exhibited severe ghosting artifacts. ROI‐based Bland‐Altman analyses were 2.23% (MD) and 6.59% (SD) between FB cones and BH Cartesian and were 0.21% (MD) and 7.02% (SD) between FB cones and FB Cartesian, suggesting a good agreement between FB cones and BH (FB) Cartesian R2∗. Strong linear relationships were observed between BH Cartesian and FB cones (y = 1.00x + 1.07, R2 = 0.996) and FB Cartesian and FB cones (y = 0.98x + 1.68, R2 = 0.999). Conclusion: Golden‐ratio re‐ordered 3D multi‐echo UTE Cones MRI enabled motion‐robust, ungated, and free‐breathing R2∗ mapping of hepatic iron overload, with comparable R2∗ measurements and image quality to BH Cartesian, and better image quality than FB Cartesian. [ABSTRACT FROM AUTHOR]

Background: Diffusion‐weighted imaging (DWI) is common for evaluating pediatric musculoskeletal lesions, but suffers from geometric distortion and intense acoustic noise. Purpose To investigate the performance of a near‐silent and distortion‐free DWI sequence (DW‐SD) relative to standard echo‐planar DWI (DW‐EPI) in pediatric extremity MRI. Study Type: Prospective validation study. Subjects: Thirty‐nine children referred for extremity MRI. Field Strength/Sequence: DW‐EPI and DW‐SD, based on a rotating ultrafast sequence modified with sinusoidal diffusion preparation gradients, at 3T. Assessment DW‐SD image quality (Sanat) was assessed from 0 (nondiagnostic) to 5 (outstanding) and comparative image quality (Scomp) (from –2 = DW‐EPI more delineated to +2 = DW‐SD more delineated, 0 = same). ADC measured by DW‐SD and DW‐EPI were compared in bone marrow, muscle, and lesions. Statistical Tests: Wilcoxon rank‐sum test and confidence interval of proportions (CIOP) were calculated for Scomp, Student's t‐test, coefficient of variation (COV), and Bland–Altman analysis for ADC values, and intraclass correlation coefficient (ICC) for interreader agreement. Results: DW‐SD and DW‐EPI ADC values for bone marrow, muscle, and lesions were not significantly different (P = 0.3, P = 0.2, and P = 0.27, respectively) and had an overall ADC COV of 14.8% (95% confidence interval: 12.3%, 16.9%) and no significant proportional bias on Bland–Altman analysis. Sanat CIOP was rated diagnostic or better (score of 3, 4, or 5) in 72–98% of cases for bone marrow, muscle, and soft tissues. DW‐SD was equivalent to or preferred over DW‐EPI in muscles and soft tissues, with CIOP 86–93% and 93%, respectively. Lesions were equally visualized on DW‐SD and DW‐EPI in 40–51%, with DW‐SD preferred in 44–56% of cases. DW‐SD was rated significantly better than DW‐EPI across all comparative variables that included bone marrow, muscle, soft tissue, cartilage, and lesions (P < 0.05). Readers had moderate to near‐perfect (ICC range = 0.45–0.85). Data Conclusion: DW‐SD of the extremities provided similar ADC values and improved image quality compared with conventional DW‐EPI. Level of Evidence 2 Technical Efficacy Stage 2 J. MAGN. RESON. IMAGING 2021;53:504–513. [ABSTRACT FROM AUTHOR]

Background: Quantitative T2 * MRI is the standard of care for the assessment of iron overload. However, patient motion corrupts T2 * estimates.Purpose: To develop and evaluate a motion-robust, simultaneous cardiac and liver T2 * imaging approach using non-Cartesian, rosette sampling and a model-based reconstruction as compared to clinical-standard Cartesian MRI.Study Type: Prospective.Phantom/population: Six ferumoxytol-containing phantoms (26-288 μg/mL). Eight healthy subjects and 18 patients referred for clinically indicated iron overload assessment.Field Strength/sequence: 1.5T, 2D Cartesian and rosette gradient echo (GRE) ASSESSMENT: GRE T2 * values were validated in ferumoxytol phantoms. In healthy subjects, test-retest and spatial coefficient of variation (CoV) analysis was performed during three breathing conditions. Cartesian and rosette T2 * were compared using correlation and Bland-Altman analysis. Images were rated by three experienced radiologists on a 5-point scale.Statistical Tests: Linear regression, analysis of variance (ANOVA), and paired Student's t-testing were used to compare reproducibility and variability metrics in Cartesian and rosette scans. The Wilcoxon rank test was used to assess reader score comparisons and reader reliability was measured using intraclass correlation analysis.Results: Rosette R2* (1/T2 *) was linearly correlated with ferumoxytol concentration (r2 = 1.00) and not significantly different than Cartesian values (P = 0.16). During breath-holding, ungated rosette liver and heart T2 * had lower spatial CoV (liver: 18.4 ± 9.3% Cartesian, 8.8% ± 3.4% rosette, P = 0.02, heart: 37.7% ± 14.3% Cartesian, 13.4% ± 1.7% rosette, P = 0.001) and higher-quality scores (liver: 3.3 [3.0-3.6] Cartesian, 4.7 [4.1-4.9] rosette, P = 0.005, heart: 3.0 [2.3-3] Cartesian, 4.5 [3.8-5.0] rosette, P = 0.005) compared to Cartesian values. During free-breathing and failed breath-holding, Cartesian images had very poor to average image quality with significant artifacts, whereas rosette remained very good, with minimal artifacts (P = 0.001).Data Conclusion: Rosette k-sampling with a model-based reconstruction offers a clinically useful motion-robust T2 * mapping approach for iron quantification. J. MAGN. RESON. IMAGING 2020;52:1688-1698. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been heralded as the next big wave in the computing revolution and touted as a transformative technology for many industries including health care. In radiology, considerable excitement and anxiety are associated with the promise of AI and its potential to disrupt the practice of the radiologist. Radiology has often served as the gateway for medical technological advancements, and AI will likely be no different. We present a brief overview of AI advancements that have driven recent interest, offer a review of the current literature, and examine the most likely ways that AI will change radiology in the coming years. [ABSTRACT FROM AUTHOR]

Quantitative MRI and ultrasound biomarkers of liver fibrosis have become important tools in the diagnosis and clinical management of children with chronic liver disease (CLD). In particular, MR elastography (MRE) is now routinely performed in clinical practice to evaluate the liver for fibrosis. Ultrasound shear-wave elastography has also become widely performed for this purpose, especially in young children. These noninvasive methods are increasingly used to replace liver biopsy for the diagnosis, quantitative staging, and treatment monitoring of patients with CLD. Although ultrasound has advantages of portability and lower equipment cost, available evidence indicates that MRI may have greater reliability and accuracy in liver fibrosis evaluation. In this AJR Expert Panel Narrative Review, we describe how, why, and when to use MRI- and ultrasound-based elastography methods for liver fibrosis assessment in children. Practical approaches are discussed for adapting and optimizing these methods in children, with consideration of clinical indications, patient preparation, equipment requirements, acquisition technique, as well as pitfalls and confounding factors. Guidance is provided for interpretation and reporting, and representative case examples are presented.

Purpose: To enable motion-robust, ungated, free-breathing R 2 ∗ mapping of hepatic iron overload in children with 3D multi-echo UTE cones MRI., Methods: A golden-ratio re-ordered 3D multi-echo UTE cones acquisition was developed with chemical-shift encoding (CSE). Multi-echo complex-valued source images were reconstructed via gridding and coil combination, followed by confounder-corrected R 2 ∗ (=1/ T 2 ∗ ) mapping. A phantom containing 15 different concentrations of gadolinium solution (0-300 mM) was imaged at 3T. 3D multi-echo UTE cones with an initial TE of 0.036 ms and Cartesian CSE-MRI (IDEAL-IQ) sequences were performed. With institutional review board approval, 85 subjects (81 pediatric patients with iron overload + 4 healthy volunteers) were imaged at 3T using 3D multi-echo UTE cones with free breathing (FB cones), IDEAL-IQ with breath holding (BH Cartesian), and free breathing (FB Cartesian). Overall image quality of R 2 ∗ maps was scored by 2 blinded experts and compared by a Wilcoxon rank-sum test. For each pediatric subject, the paired R 2 ∗ maps were assessed to determine if a corresponding artifact-free 15 mm region-of-interest (ROI) could be identified at a mid-liver level on both images. Agreement between resulting R 2 ∗ quantification from FB cones and BH/FB Cartesian was assessed with Bland-Altman and linear correlation analyses., Results: ROI-based regression analysis showed a linear relationship between gadolinium concentration and R 2 ∗ in IDEAL-IQ (y = 8.83x - 52.10, R 2 = 0.995) as well as in cones (y = 9.19x - 64.16, R 2 = 0.992). ROI-based Bland-Altman analysis showed that the mean difference (MD) was 0.15% and the SD was 5.78%. However, IDEAL-IQ R 2 ∗ measurements beyond 200 mM substantially deviated from a linear relationship for IDEAL-IQ (y = 5.85x + 127.61, R 2 = 0.827), as opposed to cones (y = 10.87x - 166.96, R 2 = 0.984). In vivo, FB cones R 2 ∗ had similar image quality with BH and FB Cartesian in 15 and 42 cases, respectively. FB cones R 2 ∗ had better image quality scores than BH and FB Cartesian in 3 and 21 cases, respectively, where BH/FB Cartesian exhibited severe ghosting artifacts. ROI-based Bland-Altman analyses were 2.23% (MD) and 6.59% (SD) between FB cones and BH Cartesian and were 0.21% (MD) and 7.02% (SD) between FB cones and FB Cartesian, suggesting a good agreement between FB cones and BH (FB) Cartesian R 2 ∗ . Strong linear relationships were observed between BH Cartesian and FB cones (y = 1.00x + 1.07, R 2 = 0.996) and FB Cartesian and FB cones (y = 0.98x + 1.68, R 2 = 0.999)., Conclusion: Golden-ratio re-ordered 3D multi-echo UTE Cones MRI enabled motion-robust, ungated, and free-breathing R 2 ∗ mapping of hepatic iron overload, with comparable R 2 ∗ measurements and image quality to BH Cartesian, and better image quality than FB Cartesian., (© 2021 International Society for Magnetic Resonance in Medicine.)

Background: Quantitative T 2 * MRI is the standard of care for the assessment of iron overload. However, patient motion corrupts T 2 * estimates., Purpose: To develop and evaluate a motion-robust, simultaneous cardiac and liver T 2 * imaging approach using non-Cartesian, rosette sampling and a model-based reconstruction as compared to clinical-standard Cartesian MRI., Study Type: Prospective., Phantom/population: Six ferumoxytol-containing phantoms (26-288 μg/mL). Eight healthy subjects and 18 patients referred for clinically indicated iron overload assessment., Field Strength/sequence: 1.5T, 2D Cartesian and rosette gradient echo (GRE) ASSESSMENT: GRE T 2 * values were validated in ferumoxytol phantoms. In healthy subjects, test-retest and spatial coefficient of variation (CoV) analysis was performed during three breathing conditions. Cartesian and rosette T 2 * were compared using correlation and Bland-Altman analysis. Images were rated by three experienced radiologists on a 5-point scale., Statistical Tests: Linear regression, analysis of variance (ANOVA), and paired Student's t-testing were used to compare reproducibility and variability metrics in Cartesian and rosette scans. The Wilcoxon rank test was used to assess reader score comparisons and reader reliability was measured using intraclass correlation analysis., Results: Rosette R2* (1/T 2 *) was linearly correlated with ferumoxytol concentration (r 2 = 1.00) and not significantly different than Cartesian values (P = 0.16). During breath-holding, ungated rosette liver and heart T 2 * had lower spatial CoV (liver: 18.4 ± 9.3% Cartesian, 8.8% ± 3.4% rosette, P = 0.02, heart: 37.7% ± 14.3% Cartesian, 13.4% ± 1.7% rosette, P = 0.001) and higher-quality scores (liver: 3.3 [3.0-3.6] Cartesian, 4.7 [4.1-4.9] rosette, P = 0.005, heart: 3.0 [2.3-3] Cartesian, 4.5 [3.8-5.0] rosette, P = 0.005) compared to Cartesian values. During free-breathing and failed breath-holding, Cartesian images had very poor to average image quality with significant artifacts, whereas rosette remained very good, with minimal artifacts (P = 0.001)., Data Conclusion: Rosette k-sampling with a model-based reconstruction offers a clinically useful motion-robust T 2 * mapping approach for iron quantification. J. MAGN. RESON. IMAGING 2020;52:1688-1698., (© 2020 International Society for Magnetic Resonance in Medicine.)

Magnetic Resonance Imaging (MRI) suffers from several artifacts, the most common of which are motion artifacts. These artifacts often yield images that are of non-diagnostic quality. To detect such artifacts, images are prospectively evaluated by experts for their diagnostic quality, which necessitates patient-revisits and rescans whenever non-diagnostic quality scans are encountered. This motivates the need to develop an automated framework capable of accessing medical image quality and detecting diagnostic and non-diagnostic images. In this paper, we explore several convolutional neural network-based frameworks for medical image quality assessment and investigate several challenges therein.

Xanthomas are rare bone tumors that occur more often in the appendicular skeleton and typically appear radiographically benign, with a narrow zone of transition and a sclerotic rim. We report the case of a 57-year-old woman with hyperlipidemia presenting with bilateral shoulder pain after minor trauma. Radiographic and histopathologic investigation demonstrated intraosseous xanthoma with atypical features, including multifocality, a wide zone of transition and pathologic fractures-characteristics more commonly associated with aggressive lesions such as multiple myeloma or metastasis. The diagnosis, imaging, and histological appearance of xanthoma of bone are reviewed.