Ultra‐short echo time images quantify high liver iron

Doyle, Eamon K.; Toy, Kristin A.; Valdez, Bertin; Chia, Jonathan M.; Coates, Thomas D.; Wood, John C.

doi:10.1002/mrm.26791

Cited by 42 publications

(42 citation statements)

References 28 publications

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“…13 There have been a few studies performing R * 2 mapping using stack-of-radial trajectories in the liver. [20][21][22][23][24] Improved image quality using an FB stack-of-radial technique was previously observed for hepatic R * 2 mapping compared to conventional BH Cartesian techniques in a population who could not perform a BH. 22 One challenge to utilizing non-Cartesian stack-of-radial sampling is its sensitivity to gradient errors.…”

mentioning

confidence: 74%

“…Non‐Cartesian trajectories, such as 3D stack‐of‐radial trajectories, have inherent robustness to motion, potentially allowing for FB

{normalR}_{2}^{*}

mapping throughout the entire placenta . There have been a few studies performing

{normalR}_{2}^{*}

mapping using stack‐of‐radial trajectories in the liver . Improved image quality using an FB stack‐of‐radial technique was previously observed for hepatic

{normalR}_{2}^{*}

mapping compared to conventional BH Cartesian techniques in a population who could not perform a BH .…”

mentioning

confidence: 99%

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3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

Armstrong

Liu

Martin

et al. 2018

Magnetic Resonance Imaging

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mentioning

confidence: 74%

“…Non‐Cartesian trajectories, such as 3D stack‐of‐radial trajectories, have inherent robustness to motion, potentially allowing for FB

{normalR}_{2}^{*}

mapping throughout the entire placenta . There have been a few studies performing

{normalR}_{2}^{*}

mapping using stack‐of‐radial trajectories in the liver . Improved image quality using an FB stack‐of‐radial technique was previously observed for hepatic

{normalR}_{2}^{*}

mapping compared to conventional BH Cartesian techniques in a population who could not perform a BH .…”

mentioning

confidence: 99%

3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

Armstrong

Liu

Martin

et al. 2018

Magnetic Resonance Imaging

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“…UTE‐A is implemented as a 2D multiecho UTE with five interleaved echo trains with ΔTE shifts of 0.25 msec between interleaves (0.80 msec between the last interleave and the next echo) to create denser sampling, and it fits R2* using a quadratic monoexponential model . UTE‐B acquires a 3D UTE sequence with seven single echoes and fits R2* using a monoexponential model with constant offset . The acquisition parameters and signal models for all these methods are summarized in Table .…”

Section: Methodsmentioning

confidence: 99%

“…The above two steps served to identify the most suited sequence among the five analyzed acquisition methods that demonstrated the highest accuracy and precision over the widest range of R2* values. For this sequence, further Monte Carlo simulations were performed to evaluate the performance of the reported R2* signal models—constant offset, noise subtraction, and quadratic—by varying the following sequence parameters: SNR (25, 50, 75, and 100), ΔTE (echo spacing: 0.25, 0.5, 1.0, and 1.8 msec), and TE max (maximum TE: 2.1, 4.7, 10.1, and 20.9 msec).…”

Section: Methodsmentioning

confidence: 99%

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

Tipirneni-Sajja

Loeffler

Krafft

et al. 2018

Magnetic Resonance Imaging

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Background Current R2*‐MRI techniques for measuring hepatic iron content (HIC) use various acquisition types and fitting models. Purpose To evaluate the accuracy and precision of R2*‐HIC acquisition and fitting methods. Study Type Signal simulations, phantom study, and prospective in vivo cohort. Population In all, 132 patients (58/74 male/female, mean age 17.7 years). Field Strength/Sequence 2D‐multiecho gradient‐echo (GRE) and ultrashort echo time (UTE) acquisitions at 1.5T. Assessment Synthetic MR signals were created to mimic published GRE and UTE methods, using different R2* values (25–2000 s−1) and signal‐to‐noise ratios (SNR). Phantoms with varying iron concentrations were scanned at 1.5T. In vivo data were analyzed from 132 patients acquired at 1.5T. R2* was estimated by fitting using three signal models. Accuracy and precision of R2* measurements for UTE acquisition parameters (SNR, echo spacing [ΔTE], maximum echo time [TEmax]) and fitting methods were compared for simulated, phantom, and in vivo datasets. Statistical Tests R2* accuracy was determined from the relative error and by linear regression analysis. Precision was evaluated using coefficient of variation (CoV) analysis. Results In simulations, all models had high R2* accuracy (error <5%) and precision (CoV <10%) for all SNRs, shorter ΔTE (≤0.5 msec), and longer TEmax (≥10.1 msec); except the constant offset model overestimated R2* at the lowest SNR. In phantoms and in vivo, all models produced similar R2* values for different SNRs and shorter ΔTEs (slopes: 0.99–1.06, R2 > 0.99, P < 0.001). In all experiments, R2* results degraded for high R2* values with longer ΔTE (≥1 msec). In vivo, shorter and longer TEmax gave similar R2* results (slopes: 1.02–1.06, R2 > 0.99, P < 0.001) for the noise subtraction model for 25≤R2*≤2000 s−1. However, both quadratic and constant offset models, using shorter TEmax (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (<250 s−1). Data Conclusion UTE with TEmax ≥ 10.1 msec and ΔTE ≤ 0.5 msec yields accurate R2* estimates over the entire clinical HIC range. Monoexponential fitting with noise subtraction is the most robust signal model to changes in UTE parameters and achieves the highest R2* accuracy and precision. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1475–1488.

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“…In addition to PDFF estimation, R 2 * (1/T 2 *) can be obtained from CSE‐MRI acquisitions as a biomarker for liver iron overload . The UTE‐based R 2 * mapping has been proposed for quantifying liver iron overload but has not considered the effect of ST2 on R 2 * estimation . It is possible that the presence of ST2 signals may confound R2* quantification if not included in the liver signal model at short echo times.…”

Section: Discussionmentioning

confidence: 99%

Characterizing a short T₂* signal component in the liver using ultrashort TE chemical shift‐encoded MRI at 1.5T and 3.0T

Zhu

Hernando

Johnson

et al. 2019

Magnetic Resonance in Med

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Purpose Recent studies have suggested the presence of short‐T2* signals in the liver, which may confound chemical shift‐encoded (CSE) fat quantification when using short echo times (TEs). The purpose of this study was to characterize the liver signal at short echo times and to determine its impact on liver fat quantification. Methods An ultrashort echo time (UTE) chemical shift‐encoded MRI (CSE‐MRI) technique and a multicomponent reconstruction were developed to characterize short‐T2* liver signals. Subsequently, liver fat fraction was quantified using a short‐TE (first TE = 0.7 ms) and UTE CSE‐MRI acquisitions and compared with a standard CSE‐MRI (first TE = 1.2 ms). Results Short‐T2* signals were consistently observed in the liver of all healthy volunteers imaged at both 1.5T and 3.0T. At 3.0T, short‐T2* signal fractions of 9.6 ± 1.5%, 7.0 ± 1.7%, and 7.4 ± 1.7% with T2* of 0.23 ± 0.05 ms, 0.20 ± 0.05 ms, and 0.10 ± 0.02 ms were measured in healthy volunteers, patients with liver cirrhotic disease, and patients with hepatic steatosis (but no cirrhosis), respectively. For proton density fat fraction (PDFF) estimation, 1.7% (P < .01) and 3.4% (P < .01) biases were observed in subjects imaged using short‐TE CSE‐MRI and using UTE CSE‐MRI at 1.5T, respectively. The biases were reduced to 0.4% and −0.7%, respectively, by excluding short echoes less than 1 ms. A 3.2% bias (P < .01) was observed in subjects imaged using UTE CSE‐MRI at 3.0T, which was reduced to 0.1% by excluding short echoes <1 ms. Conclusions A liver short‐T2* signal component was consistently observed and was shown to confound liver fat quantification when short echo times were used with CSE‐MRI.

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Ultra‐short echo time images quantify high liver iron

Abstract: 3T-UTE imaging can reliably estimate high liver iron burdens. In conjunction with 3T-GRE, 3T-UTE allows clinical LIC estimation across a wide range of liver iron loads. Magn Reson Med 79:1579-1585, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Cited by 42 publications

References 28 publications

3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

Characterizing a short T₂* signal component in the liver using ultrashort TE chemical shift‐encoded MRI at 1.5T and 3.0T

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Ultra‐short echo time images quantify high liver iron

Abstract: 3T-UTE imaging can reliably estimate high liver iron burdens. In conjunction with 3T-GRE, 3T-UTE allows clinical LIC estimation across a wide range of liver iron loads. Magn Reson Med 79:1579-1585, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Cited by 42 publications

References 28 publications

3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

3D mapping of the placenta during early gestation using free‐breathing multiecho stack‐of‐radial MRI at 3T

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data

Characterizing a short T2* signal component in the liver using ultrashort TE chemical shift‐encoded MRI at 1.5T and 3.0T

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Characterizing a short T₂* signal component in the liver using ultrashort TE chemical shift‐encoded MRI at 1.5T and 3.0T