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) andR 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 andR 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 andR 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 andR 2 * $$ {R}_2^{\ast } $$ measurements.

RESULTS

Simulations and phantom studies demonstrated that the proposed algorithm successfully excluded regions with unreliable PDFF andR 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 andR 2 * $$ {R}_2^{\ast } $$ maps, as identified by confidence maps.

CONCLUSION

A proposed confidence map algorithm that identifies reliable areas of PDFF andR 2 * $$ {R}_2^{\ast } $$ measurements from CSE-MRI acquisitions was successfully developed. It demonstrated technical and clinical feasibility.

Precision of liver and pancreas apparent diffusion coefficients using motion-compensated gradient waveforms in DWI

BACKGROUND

Diffusion weighted imaging (DWI) with optimized motion-compensated gradient waveforms reduces signal dropouts in the liver and pancreas caused by cardiovascular-associated motion, however its precision is unknown. We hypothesized that DWI with motion-compensated DW gradient waveforms would improve apparent diffusion coefficient (ADC)-repeatability and inter-reader reproducibility compared to conventional DWI in these organs.

METHODS

In this IRB-approved, prospective, single center study, subjects recruited between October 2019 and March 2020 were scanned twice on a 3 T scanner, with repositioning between test and retest. Each scan included two respiratory-triggered DWI series with comparable acquisition time: 1) conventional (monopolar) 2) motion- compensated diffusion gradients. Three readers measured ADC values. One-way ANOVA, Bland-Altman analysis were used for statistical analysis.

RESULTS

Eight healthy participants (4 male/4 female), with a mean age of 29 ± 4 years, underwent the liver and pancreas MRI protocol. Four patients with liver metastases (2 male/2 female) with a mean age of 58 ± 5 years underwent the liver MRI protocol. In healthy participants, motion-compensated DWI outperformed conventional DWI with mean repeatability coefficient of 0.14 × 10-3 (CI:0.12-0.17) vs. 0.31 × 10-3 (CI:0.27-0.37) mm2/s for liver, and 0.11 × 10-3 (CI:0.08-0.15) vs. 0.34 × 10-3 (CI:0.27-0.49) mm2/s for pancreas; and with mean reproducibility coefficient of 0.20 × 10-3 (CI:0.18-0.23) vs. 0.51 × 10-3 (CI:0.46-0.58) mm2/s for liver, and 0.16 × 10-3 (CI:0.13-0.20) vs. 0.42 × 10-3 (CI:0.34-0.52) mm2/s for pancreas. In patients, improved repeatability was observed for motion-compensated DWI in comparison to conventional with repeatability coefficient of 0.51 × 10- 3 mm2/s (CI:0.35-0.89) vs. 0.70 × 10-3 mm2/s (CI:0.49-1.20).

CONCLUSION

Motion-compensated DWI enhances the precision of ADC measurements in the liver and pancreas compared to conventional DWI.

Comparative review of algorithms and methods for chemical-shift-encoded quantitative fat-water imaging

PURPOSE

To propose a standardized comparison between state-of-the-art open-source fat-water separation algorithms for proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ quantification using an open-source multi-language toolbox.

METHODS

Eight recent open-source fat-water separation algorithms were compared in silico, in vitro, and in vivo. Multi-echo data were synthesized with varying fat-fractions, B0 off-resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat-water phantoms acquired at 3T and multi-site open-source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model.

RESULTS

In silico and in vitro results proved most algorithms to be not sensitive to fat-water swaps andB 0 $$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s-1 forR 2 * $$ {R}_2^{\ast } $$ . The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and ofR 2 * $$ {R}_2^{\ast } $$ more severely, with errors up to 20 s-1 .

CONCLUSION

In promoting standardized comparisons of MRI-based fat and iron quantification using chemical-shift encoded multi-echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF andR 2 * $$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat-water algorithm appear necessary for reproducibility. This open-source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors.

MRI-based vertebral bone quality score: relationship with age and reproducibility

Vertebral bone quality (VBQ) score is an opportunistic measure of bone mineral density using routine preoperative MRI in spine surgery. VBQ score positively correlates with age and is reproducible across serial scans. However, extrinsic factors, including MRI machine and protocol, affect the VBQ score and must be standardized.

PURPOSE

The purposes of this study were to determine whether VBQ score increased with age and whether VBQ remained consistent across serial MRI studies obtained within 3 months.

METHODS

This retrospective study evaluated 136 patients, age 20-69, who received two T1-weighted lumbar MRI within 3 months of each other between January 2011 and December 2021. VBQ(L1-4) score was calculated as the quotient of L1-L4 signal intensity (SI) and L3 cerebral spinal fluid (CSF) SI. VBQ(L1) score was calculated as the quotient of L1 SI and L1 CSF SI. Regression analysis was performed to determine correlation of VBQ(L1-4) score with age. Coefficient of variation (CV) was used to determine reproducibility between VBQ(L1-4) scores from serial MRI scans.

RESULTS

One hundred thirty-six patients (mean ± SD age 44.9 ± 12.5 years; 53.7% female) were included in this study. Extrinsic factors affecting the VBQ score included patient age, MRI relaxation time, and specific MRI machine. When controlling for MRI relaxation/echo time, the VBQ(L1-4) score was positively correlated with age and had excellent reproducibility in serial MRI with CV of 0.169. There was excellent agreement (ICC > 0.9) of VBQ scores derived from the two formulas, VBQ(L1) and VBQ(L1-4).

CONCLUSION

Extrinsic factors, including MRI technical factors and age, can impact the VBQ(L1-4) score and must be considered when using this tool to estimate bone mineral density (BMD). VBQ(L1-4) score was positively correlated with age. Reproducibility of the VBQ(L1-4) score across serial MRI is excellent especially when controlling for technical factors, supporting use of the VBQ score in estimating BMD. The VBQ(L1) score was a reliable alternative to the VBQ(L1-4) score.

Data adaptive regularization with reference tissue constraints for liver quantitative susceptibility mapping

PURPOSE

To improve repeatability and reproducibility across acquisition parameters and reduce bias in quantitative susceptibility mapping (QSM) of the liver, through development of an optimized regularized reconstruction algorithm for abdominal QSM.

METHODS

An optimized approach to estimation of magnetic susceptibility distribution is formulated as a constrained reconstruction problem that incorporates estimates of the input data reliability and anatomical priors available from chemical shift-encoded imaging. The proposed data-adaptive method was evaluated with respect to bias, repeatability, and reproducibility in a patient population with a wide range of liver iron concentration (LIC). The proposed method was compared to the previously proposed and validated approach in liver QSM for two multi-echo spoiled gradient-recalled echo protocols with different acquisition parameters at 3T. Linear regression was used for evaluation of QSM methods against a reference FDA-approvedR 2 $$ {R}_2 $$ -based LIC measure andR 2 ∗ $$ {R}_2^{\ast } $$ measurements; repeatability/reproducibility were assessed by Bland-Altman analysis.

RESULTS

The data-adaptive method produced susceptibility maps with higher subjective quality due to reduced shading artifacts. For both acquisition protocols, higher linear correlation with bothR 2 $$ {R}_2 $$ - andR 2 ∗ $$ {R}_2^{\ast } $$ -based measurements were observed for the data-adaptive method (r 2 = 0 . 74 / 0 . 69 $$ {r}^2=0.74/0.69 $$ forR 2 $$ {R}_2 $$ ,0 . 97 / 0 . 95 $$ 0.97/0.95 $$ forR 2 ∗ $$ {R}_2^{\ast } $$ ) than the standard method (r 2 = 0 . 60 / 0 . 66 $$ {r}^2=0.60/0.66 $$ and0 . 79 / 0 . 88 $$ 0.79/0.88 $$ ). For both protocols, the data-adaptive method enabled better test-retest repeatability (repeatability coefficients 0.19/0.30 ppm for the data-adaptive method, 0.38/0.47 ppm for the standard method) and reproducibility across protocols (reproducibility coefficient 0.28 vs. 0.53ppm) than the standard method.

CONCLUSIONS

The proposed data-adaptive QSM algorithm may enable quantification of LIC with improved repeatability/reproducibility across different acquisition parameters as 3T.

Monte Carlo modeling of hepatic steatosis based on stereology and spatial distribution of fat droplets

BACKGROUND AND OBJECTIVE

To model hepatic steatosis in adult humans with non-alcoholic fatty liver disease based on stereology and spatial distribution of fat droplets from liver biopsy specimens.

METHODS

Histological analysis was performed on 30 adult human liver biopsy specimens with varying degrees of steatosis. Morphological features of fat droplets were characterized by gamma distribution function (GDF) in both two-dimensional (2D) and three-dimensional (3D) spaces from three aspects: 1) size distribution indicating non-uniformity of fat droplets in radius; 2) nearest neighbor distance distribution indicating heterogeneous accumulation (i.e., clustering) of fat droplets; 3) regional anisotropy indicating inter-regional variability in fat fraction (FF). To generalize the morphological description of hepatic steatosis to different FFs, correlation analysis was performed among the estimated GDF parameters and FFs for all specimens. Finally, Monte Carlo modeling of hepatic steatosis was developed to simulate fat droplet distribution in tissue.

RESULTS

Morphological features, including size and nearest neighbor distance in 2D and 3D spaces as well as regional anisotropy, statistically captured the distribution of fat droplets by the GDF fit (R² > 0.54). The estimated GDF parameters (i.e., scale and shape parameters) and FFs were well correlated, with R² > 0.55. In addition, simulated 3D liver morphological models demonstrated similar sections to real histological samples both visually and quantitatively.

CONCLUSIONS

The morphology of hepatic steatosis is well characterized by stereology and spatial distribution of fat droplets. Simulated models demonstrate similar appearances to real histological samples. Furthermore, the model may help understand MRI signal behavior in the presence of liver steatosis.

Validation of liver quantitative susceptibility mapping across imaging parameters at 1.5 T and 3.0 T using SQUID susceptometry as reference

PURPOSE

To validate QSM-based biomagnetic liver susceptometry (BLS) to measure liver iron overload at 1.5 T and 3.0 T using superconducting quantum interference devices (SQUID)-based BLS as reference.

METHODS

Subjects with known or suspected iron overload were recruited for QSM-BLS at 1.5 T and 3.0 T using eight different protocols. SQUID-BLS was also obtained in each subject to provide susceptibility reference. A recent QSM method based on data-adaptive regularization was used to obtain susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ maps. Measurements of susceptibility and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were obtained in the right liver lobe. Linear mixed-effects analysis was used to estimate the contribution of specific acquisition parameters to QSM-BLS. Linear regression and Bland-Altman analyses were used to assess the relationship between QSM-BLS and SQUID-BLS/ R 2 * $$ {\mathrm{R}}_2^{\ast } $$ .

RESULTS

Susceptibility maps showed high subjective quality for each acquisition protocol across different iron levels. High linear correlation was observed between QSM-BLS and SQUID-BLS at 1.5 T (r² range, [0.82, 0.84]) and 3.0 T (r² range, [0.77, 0.85]) across different acquisition protocols. QSM-BLS and R 2 * $$ {\mathrm{R}}_2^{\ast } $$ were highly correlated at both field strengths (r² range at 1.5 T, [0.94, 0.99]; 3.0 T, [0.93, 0.99]). High correlation (r²  = 0.99) between 1.5 T and 3.0 T QSM-BLS, with narrow reproducibility coefficients (range, [0.13, 0.21] ppm) were observed for each protocol.

CONCLUSION

This work evaluated the feasibility and performance of liver QSM-BLS across iron levels and acquisition protocols at 1.5 T and 3.0 T. High correlation and reproducibility were observed between QSM-BLS and SQUID-BLS across protocols and field strengths. In summary, QSM-BLS may enable reliable and reproducible quantification of liver iron concentration.

Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR

Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.

Motion-robust, blood-suppressed, reduced-distortion diffusion MRI of the liver

PURPOSE

To evaluate feasibility and reproducibility of liver diffusion-weighted (DW) MRI using cardiac-motion-robust, blood-suppressed, reduced-distortion techniques.

METHODS

DW-MRI data were acquired at 3T in an anatomically accurate liver phantom including controlled pulsatile motion, in eight healthy volunteers and four patients with known or suspected liver metastases. Standard monopolar and motion-robust (M1-nulled, and M1-optimized) DW gradient waveforms were each acquired with single-shot echo-planar imaging (ssEPI) and multishot EPI (msEPI). In the motion phantom, apparent diffusion coefficient (ADC) was measured in the motion-affected volume. In healthy volunteers, ADC was measured in the left and right liver lobes separately to evaluate ADC reproducibility between the two lobes. Image distortions were quantified using the normalized cross-correlation coefficient, with an undistorted T2-weighted reference.

RESULTS

In the motion phantom, ADC mean and SD in motion-affected volumes substantially increased with increasing motion for monopolar waveforms. ADC remained stable in the presence of increasing motion when using motion-robust waveforms. M1-optimized waveforms suppressed slow flow signal present with M1-nulled waveforms. In healthy volunteers, monopolar waveforms generated significantly different ADC measurements between left and right liver lobes ( p = 0 . 0078 $$ p=0.0078 $$ , reproducibility coefficients (RPC) =  470 × 1 0 - 6 $$ 470\times 1{0}^{-6} $$ mm 2 $$ {}^2 $$ /s for monopolar-msEPI), while M1-optimized waveforms showed more reproducible ADC values ( p = 0 . 29 $$ p=0.29 $$ , RPC = 220 × 1 0 - 6 $$ \mathrm{RPC}=220\times 1{0}^{-6} $$ mm 2 $$ {}^2 $$ /s for M1-optimized-msEPI). In phantom and healthy volunteer studies, motion-robust acquisitions with msEPI showed significantly reduced image distortion ( p < 0 . 001 $$ p<0.001 $$ ) compared to ssEPI. Patient scans showed reduction of wormhole artifacts when combining M1-optimized waveforms with msEPI.

CONCLUSION

Synergistic effects of combined M1-optimized diffusion waveforms and msEPI acquisitions enable reproducible liver DWI with motion robustness, blood signal suppression, and reduced distortion.

Clinical impact of the suspension of the ERAS protocol on patients undergoing radical cystectomy during the COVID-19 pandemic

INTRODUCTION

During the beginning of the COVID-19 pandemic in our center, neither prehabilitation nor multimodal rehabilitation could be applied due to the excessive patient load on the health system and to reduce SARS-CoV-2 transmission. The objective of our study was to analyze the evolution, complications, and survival up to one year of patients who underwent radical cystectomy in our hospital from March 1st to May 31st, 2020 (period of the first wave COVID-19 pandemic in Spain). We also compared the results with cystectomized patients outside the pandemic period and with application of the ERAS (Enhanced Recovery After Surgery) protocol.

MATERIAL AND METHODS

Single-center, retrospective cohort study of patients scheduled for radical cystectomy from March 1st, 2020 to May 31st, 2020. They were matched with previously operated patients using a 1:2 propensity matching score. The matching variables were demographic data, preoperative and intraoperative clinical conditions.

RESULTS

A total of 23 radical cystectomies with urinary diversion were performed in the period described. In none of the cases the prehabilitation or the follow-up of our ERAS protocol could be applied, and this was the only difference we found between the 2 groups. Although the minimally invasive approach was more frequent in the pandemic group, the difference was not statistically significant. Three patients were diagnosed with COVID-19 during their admission, presenting severe respiratory complications and high in-hospital mortality. Apart from respiratory complications secondary to SARS-CoV-2, we also found statistically significant differences in other postoperative complications. The hospital stay increased by 3 days in the pandemic group.

CONCLUSIONS

Patients who underwent radical cystectomy at our center during the first wave of the COVID-19 pandemic had a higher number and severity of respiratory and non-respiratory complications. Discontinuation of the ERAS protocol was the main difference in treatment between groups.

[CLINICAL IMPACT OF THE SUSPENSION OF THE ERAS PROTOCOL ON PATIENTS UNDERGOING RADICAL CYSTECTOMY DURING THE COVID-19 PANDEMIC.]

INTRODUCTION

During the beginning of the COVID-19 pandemic in our center, neither prehabilitation nor multimodal rehabilitation could be applied due to the excessive patient load on the health system and to reduce SARS-CoV-2 transmission. The objective of our study was to analyze the evolution, complications, and survival up to one year of patients who underwent radical cystectomy in our hospital from March 1st to May 31st, 2020 (period of the first wave COVID-19 pandemic in Spain). We also compared the results with cystectomized patients outside the pandemic period and with application of the ERAS (Enhanced Recovery After Surgery) protocol.

MATERIAL AND METHODS

Single-center, retrospective cohort study of patients scheduled for radical cystectomy from March 1st,2020 to May 31st, 2020. They were matched with previously operated patients using a 1:2 propensity matching score. The matching variables were demographic data, preoperative and intraoperative clinical conditions.

RESULTS

A total of 23 radical cystectomies with urinary diversion were performed in the period described. In none of the cases the prehabilitation or the follow-up of our ERAS protocol could be applied, and this was the only difference we found between the 2 groups. Although the minimally invasive approach was more frequent in the pandemic group, the difference was not statistically significant. Three patients were diagnosed with COVID-19 during their admission, presenting severe respiratory complications and high in-hospital mortality. Apart from respiratory complications secondary to SARS-CoV-2, we also found statistically significant differences in other postoperative complications. The hospital stay increased by 3 days in the pandemic group.

CONCLUSIONS

Patients who underwent radical cystectomy at our center during the first wave of the COVID-19 pandemic had a higher number and severity of respiratory and non-respiratory complications. Discontinuation of the ERAS protocol was the main difference in treatment between groups.

Multicenter Reproducibility of Liver Iron Quantification with 1.5-T and 3.0-T MRI

Background MRI is a standard of care tool to measure liver iron concentration (LIC). Compared with regulatory-approved R2 MRI, R2* MRI has superior speed and is available in most MRI scanners; however, the cross-vendor reproducibility of R2*-based LIC estimation remains unknown. Purpose To evaluate the reproducibility of LIC via single-breath-hold R2* MRI at both 1.5 T and 3.0 T with use of a multicenter, multivendor study. Materials and Methods Four academic medical centers using MRI scanners from three different vendors (three 1.5-T scanners, one 2.89-T scanner, and two 3.0-T scanners) participated in this prospective cross-sectional study. Participants with known or suspected liver iron overload were recruited to undergo multiecho gradient-echo MRI for R2* mapping at 1.5 T and 3.0 T (2.89 T or 3.0 T) on the same day. R2* maps were reconstructed from the multiecho images and analyzed at a single center. Reference LIC measurements were obtained with a commercial R2 MRI method performed using standardized 1.5-T spin-echo imaging. R2*-versus-LIC calibrations were generated across centers and field strengths using linear regression and compared using F tests. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic performance of R2* MRI in the detection of clinically relevant LIC thresholds. Results A total of 207 participants (mean age, 38 years ± 20 [SD]; 117 male participants) were evaluated between March 2015 and September 2019. A linear relationship was confirmed between R2* and LIC. All calibrations within the same field strength were highly reproducible, showing no evidence of statistically significant center-specific differences (P > .43 across all comparisons). Calibrations for 1.5 T and 3.0 T were generated, as follows: for 1.5 T, LIC (in milligrams per gram [dry weight]) = -0.16 + 2.603 × 10-2 R2* (in seconds-1); for 2.89 T, LIC (in milligrams per gram) = -0.03 + 1.400 × 10-2 R2* (in seconds-1); for 3.0 T, LIC (in milligrams per gram) = -0.03 + 1.349 × 10-2 R2* (in seconds-1). Liver R2* had high diagnostic performance in the detection of clinically relevant LIC thresholds (area under the ROC curve, >0.98). Conclusion R2* MRI enabled accurate and reproducible quantification of liver iron overload over clinically relevant ranges of liver iron concentration (LIC). The data generated in this study provide the necessary calibrations for broad clinical dissemination of R2*-based LIC quantification. ClinicalTrials.gov registration no.: NCT02025543 © RSNA, 2022 Online supplemental material is available for this article.

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.

Automated MR Image Prescription of the Liver Using Deep Learning: Development, Evaluation, and Prospective Implementation

BACKGROUND

There is an unmet need for fully automated image prescription of the liver to enable efficient, reproducible MRI.

PURPOSE

To develop and evaluate artificial intelligence (AI)-based liver image prescription.

STUDY TYPE

Prospective.

POPULATION

A total of 570 female/469 male patients (age: 56 ± 17 years) with 72%/8%/20% assigned randomly for training/validation/testing; two female/four male healthy volunteers (age: 31 ± 6 years).

FIELD STRENGTH/SEQUENCE

1.5 T, 3.0 T; spin echo, gradient echo, bSSFP.

ASSESSMENT

A total of 1039 three-plane localizer acquisitions (26,929 slices) from consecutive clinical liver MRI examinations were retrieved retrospectively and annotated by six radiologists. The localizer images and manual annotations were used to train an object-detection convolutional neural network (YOLOv3) to detect multiple object classes (liver, torso, and arms) across localizer image orientations and to output corresponding 2D bounding boxes. Whole-liver image prescription in standard orientations was obtained based on these bounding boxes. 2D detection performance was evaluated on test datasets by calculating intersection over union (IoU) between manual and automated labeling. 3D prescription accuracy was calculated by measuring the boundary mismatch in each dimension and percentage of manual volume covered by AI prescription. The automated prescription was implemented on a 3 T MR system and evaluated prospectively on healthy volunteers.

STATISTICAL TESTS

Paired t-tests (threshold = 0.05) were conducted to evaluate significance of performance difference between trained networks.

RESULTS

In 208 testing datasets, the proposed method with full network had excellent agreement with manual annotations, with median IoU > 0.91 (interquartile range < 0.09) across all seven classes. The automated 3D prescription was accurate, with shifts <2.3 cm in superior/inferior dimension for 3D axial prescription for 99.5% of test datasets, comparable to radiologists' interreader reproducibility. The full network had significantly superior performance than the tiny network for 3D axial prescription in patients. Automated prescription performed well across single-shot fast spin-echo, gradient-echo, and balanced steady-state free-precession sequences in the prospective study.

DATA CONCLUSION

AI-based automated liver image prescription demonstrated promising performance across the patients, pathologies, and field strengths studied.

EVIDENCE LEVEL

4.

TECHNICAL EFFICACY

Stage 1.

Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities

PURPOSE

The purpose of this work was to obtain precise tri-exponential intravoxel incoherent motion (IVIM) quantification in the liver using 2D (b-value and first-order motion moment [M1 ]) IVIM-DWI acquisitions and region of interest (ROI)-based fitting techniques.

METHODS

Diffusion MRI of the liver was performed in 10 healthy volunteers using three IVIM-DWI acquisitions: conventional monopolar, optimized monopolar, and optimized 2D (b-M1 ). For each acquisition, bi-exponential and tri-exponential full, segmented, and over-segmented ROI-based fitting and a newly proposed blood velocity SDdistribution (BVD) fitting technique were performed to obtain IVIM estimates in the right and left liver lobes. Fitting quality was evaluated using corrected Akaike information criterion. Precision metrics (test-retest repeatability, inter-reader reproducibility, and inter-lobar agreement) were evaluated using Bland-Altman analysis, repeatability/reproducibility coefficients (RPCs), and paired sample t-tests. Precision was compared across acquisitions and fitting methods.

RESULTS

High repeatability and reproducibility was observed in the estimations of the diffusion coefficient (Dtri  = [1.03 ± 0.11] × 10-3  mm2 /s; RPCs ≤ 1.34 × 10-4  mm2 /s), perfusion fractions (F1  = 3.19 ± 1.89% and F2  = 16.4 ± 2.07%; RPCs ≤ 2.51%), and blood velocity SDs (Vb,1  = 1.44 ± 0.14 mm/s and Vb,2  = 3.62 ± 0.13 mm/s; RPCs ≤ 0.41 mm/s) in the right liver lobe using the 2D (b-M1 ) acquisition in conjunction with BVD fitting. Using these methods, significantly larger (p < 0.01) estimates of Dtri and F1 were observed in the left lobe in comparison to the right lobe, while estimates of Vb,1 and Vb,2 demonstrated high interlobar agreement (RPCs ≤ 0.45 mm/s).

CONCLUSIONS

The 2D (b-M1 ) IVIM-DWI data acquisition in conjunction with BVD fitting enables highly precise tri-exponential IVIM quantification in the right liver lobe.

Intramyocardial hemorrhage drives fatty degeneration of infarcted myocardium

Sudden blockage of arteries supplying the heart muscle contributes to millions of heart attacks (myocardial infarction, MI) around the world. Although re-opening these arteries (reperfusion) saves MI patients from immediate death, approximately 50% of these patients go on to develop chronic heart failure (CHF) and die within a 5-year period; however, why some patients accelerate towards CHF while others do not remains unclear. Here we show, using large animal models of reperfused MI, that intramyocardial hemorrhage - the most damaging form of reperfusion injury (evident in nearly 40% of reperfused ST-elevation MI patients) - drives delayed infarct healing and is centrally responsible for continuous fatty degeneration of the infarcted myocardium contributing to adverse remodeling of the heart. Specifically, we show that the fatty degeneration of the hemorrhagic MI zone stems from iron-induced macrophage activation, lipid peroxidation, foam cell formation, ceroid production, foam cell apoptosis and iron recycling. We also demonstrate that timely reduction of iron within the hemorrhagic MI zone reduces fatty infiltration and directs the heart towards favorable remodeling. Collectively, our findings elucidate why some, but not all, MIs are destined to CHF and help define a potential therapeutic strategy to mitigate post-MI CHF independent of MI size.

Opportunistic Use of Lumbar Magnetic Resonance Imaging for Osteoporosis Screening

Magnetic resonance imaging (MRI) is a routine assessment before spine surgery. We found that the opportunistic use of MRI with the vertebral bone quality (VBQ) score has good diagnostic ability, with a threshold value of VBQ > 3.0, in recognizing patients who may need further osteoporosis evaluation.

INTRODUCTION

The purpose of this study was to determine whether the opportunistic use of magnetic resonance imaging (MRI) is useful for identifying spine surgical patients who need further osteoporosis evaluation.

METHODS

This retrospective study evaluated 83 thoracolumbar spine surgery patients age ≥ 50 who received T1-weighted MRI. Opportunistic MRI was evaluated with the vertebral bone quality (VBQ) score, VBQ (fat) score, and signal-to-noise ratio (SNR). Each uses the median L1-L4 vertebral body signal intensities (SI) divided by either the L3 cerebrospinal fluid (CSF) SI, average SI of the L1 and S1 dorsal fat, or standard deviation (SD) of the background SI dorsal to the skin. Single-level VBQ was calculated as the ratio of the L1 vertebral body and L1 CSF SIs. Receiver-operator curve analysis was performed to determine diagnostic ability.

RESULTS

The mean age was 70.10, 80% were female, and 96% were Caucasian. The mean ± SD VBQ, single-level VBQ, VBQ (fat), and SNR were 3.39 ± 0.68, 3.56 ± 0.81, 3.95 ± 1.89, and 113.18 ± 77.26, respectively. Using area under the curve, the diagnostic ability of VBQ, single-level VBQ, VBQ (fat), and SNR for clinical osteoporosis were 0.806, 0.779, 0.608, and 0.586, respectively. Diagnostic threshold values identified with optimal sensitivity and specificity were VBQ of 2.95 and single-level VBQ of 3.06.

CONCLUSION

Opportunistic use of MRI is a simple, effective tool that may help recognize patients who are at risk for complications related to bone disease. A VBQ > 3.0 can identify patients who need additional diagnostic evaluation.

Addressing concomitant gradient phase errors in time-interleaved chemical shift-encoded MRI fat fraction and R2 * mapping with a pass-specific phase fitting method

PURPOSE

Concomitant gradients induce phase errors that increase quadratically with distance from isocenter. This work proposes a complex-based fitting method that addresses concomitant gradient phase errors in chemical shift encoded (CSE) MRI estimation of proton density fat fraction (PDFF) and R₂ ^* through joint estimation of pass-specific phase terms. This method is applicable to time-interleaved multi-echo gradient-echo acquisitions (i.e., multi-pass acquisitions) and does not require prior knowledge of gradient waveforms typically needed to address concomitant gradient phase errors.

THEORY AND METHODS

A CSE-MRI spoiled gradient echo signal model, with pass-specific phase terms, is introduced for non-linear least squares estimation of PDFF and R₂ ^* in the presence of concomitant gradient phase errors. Cramér-Rao lower bound analysis was used to determine noise performance tradeoffs of the proposed fitting method, which was then validated in both phantom and in vivo experiments.

RESULTS

The proposed fitting method removed PDFF and R₂ ^* estimation errors up to 12% and 10 s^-1 , respectively, at ±12 cm off isocenter (S/I) in a water phantom. In healthy volunteers, PDFF and R₂ ^* bias was reduced by ~10% (12 cm off-isocenter) and ~30 s^-1 (16 cm off-isocenter), respectively. An evaluation in 29 clinical liver datasets demonstrated reduced PDFF bias and variability (8.4% improvement in the coefficient of variation), even with the imaging volume centered at isocenter.

CONCLUSION

Concomitant gradient induced phase errors in multi-pass CSE-MRI acquisitions can result in PDFF and R₂ ^* estimation biases away from isocenter. The proposed fitting method enables accurate PDFF and R₂ ^* quantification in the presence of concomitant gradient phase errors without knowledge of imaging gradient waveforms.

Contrasting recruitment of skin-associated adipose depots during cold challenge of mouse and human

KEY POINTS

Several distinct strategies produce and conserve heat to maintain the body temperature of mammals, each associated with unique physiologies, with consequences for wellness and disease susceptibility Highly regulated properties of skin offset the total requirement for heat production  We hypothesize that the adipose component of skin is primarily responsible for modulating heat flux; here we evaluate the relative regulation of adipose depots in mouse and human, to test their recruitment to heat production and conservation We found that insulating mouse dermal white adipose tissue accumulates in response to environmentally and genetically induced cool stress; this layer is one of two adipose depots closely apposed to mouse skin, where the subcutaneous mammary gland fat pads are actively recruited to heat production In contrast, the body-wide adipose depot associated with human skin produces heat directly, potentially creating an alternative to the centrally regulated brown adipose tissue ABSTRACT: Mammalian skin impacts metabolic efficiency system-wide, controlling the rate of heat loss and consequent heat production. Here we compare the unique fat depots associated with mouse and human skin, to determine whether they have corresponding functions and regulation. For humans, we assay a skin-associated fat (SAF) body-wide depot to distinguish it from the subcutaneous fat pads characteristic of the abdomen and upper limbs. We show that the thickness of SAF is not related to general adiposity; it is much thicker (1.6-fold) in women than men, and highly subject-specific. We used molecular and cellular assays of β-adrenergic-induced lipolysis and found that dermal white adipose tissue (dWAT) in mice is resistant to lipolysis; in contrast, the body-wide human SAF depot becomes lipolytic, generating heat in response to β-adrenergic stimulation. In mice challenged to make more heat to maintain body temperature (either environmentally or genetically), there is a compensatory increase in thickness of dWAT: a corresponding β-adrenergic stimulation of human skin adipose (in vivo or in explant) depletes adipocyte lipid content. We summarize the regulation of skin-associated adipocytes by age, sex and adiposity, for both species. We conclude that the body-wide dWAT depot of mice shows unique regulation that enables it to be deployed for heat preservation; combined with the actively lipolytic subcutaneous mammary fat pads they enable thermal defence. The adipose tissue that covers human subjects produces heat directly, providing an alternative to the brown adipose tissues.

b value and first-order motion moment optimized data acquisition for repeatable quantitative intravoxel incoherent motion DWI

PURPOSE

To design a b value and first-order motion moment (M₁ ) optimized data acquisition for repeatable intravoxel incoherent motion (IVIM) quantification in the liver.

METHODS

Cramer-Rao lower bound optimization was performed to determine optimal monopolar and optimal 2D samplings of the b-M₁ space based on noise performance. Monte Carlo simulations were used to evaluate the bias and variability in estimates obtained using the proposed optimal samplings and conventional monopolar sampling. Diffusion MRI of the liver was performed in 10 volunteers using 3 IVIM acquisitions: conventional monopolar, optimized monopolar, and b-M₁ -optimized gradient waveforms (designed based on the optimal 2D sampling). IVIM parameter maps of diffusion coefficient, perfusion fraction, and blood velocity SD were obtained using nonlinear least squares fitting. Noise performance (SDs), stability (outlier percentage), and test-retest or scan-rescan repeatability (intraclass correlation coefficients) were evaluated and compared across acquisitions.

RESULTS

Cramer-Rao lower bound and Monte Carlo simulations demonstrated improved noise performance of the optimal 2D sampling in comparison to monopolar samplings. Evaluating the designed b-M₁ -optimized waveforms in healthy volunteers, significant decreases (p < 0.05) in the SDs and outlier percentages were observed for measurements of diffusion coefficient, perfusion fraction, and blood velocity SD in comparison to measurements obtained using monopolar samplings. Good-to-excellent repeatability (intraclass correlation coefficients ≥ 0.77) was observed for all 3 parameters in both the right and left liver lobes using the b-M₁ -optimized waveforms.

CONCLUSIONS

2D b-M₁ -optimized data acquisition enables repeatable IVIM quantification with improved noise performance. 2D acquisitions may advance the establishment of IVIM quantitative biomarkers for liver diseases.

Relaxivity-iron calibration in hepatic iron overload: Reproducibility and extension of a Monte Carlo model

The aim of this study was to reproduce relaxivity-iron calibration in hepatic iron overload using a Monte Carlo model, and further extend the model with multiple spin echo (MSE) imaging. As previously reported, relationships between relaxation rates ( R2* and single spin echo R₂ ) and liver iron concentration (LIC) can be characterized by a Monte Carlo model incorporating realistic liver structure, iron distribution, and proton mobility. In this study, relaxivity-iron calibration curves at 1.5 and 3.0 T were simulated using the Monte Carlo model. Furthermore, the model was extended with MSE imaging, and iron calibrations were evaluated using two different fitting models: mononexponential with a constant offset and nonmonoexponential. Results consistent with previous empirical calibrations and Monte Carlo predictions were accurately reproduced for relaxivity-iron calibration. The predicted R2* and single spin echo R₂ increased by a factor of 2.00 and 1.51, respectively, at 1.5 versus 3.0 T. MSE signals and their corresponding R₂ depended strongly on LIC, interecho time, and field strength. Preliminary results showed that a nonmonoexponential model accurately characterizes the simulated MSE signals, and that strong correlations were found between predicted relaxation parameters and LIC. In conclusion, relaxivity-iron calibration is reproducible using the proposed Monte Carlo model. Furthermore, this model can be readily extended to other important applications, including predicting signal behavior for MSE imaging.

Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T₁ . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.

Proton density water fraction as a reproducible MR-based measurement of breast density

PURPOSE

To introduce proton density water fraction (PDWF) as a confounder-corrected (CC) MR-based biomarker of mammographic breast density, a known risk factor for breast cancer.

METHODS

Chemical shift encoded (CSE) MR images were acquired using a low flip angle to provide proton density contrast from multiple echo times. Fat and water images, corrected for known biases, were produced by a six-echo CC CSE-MRI algorithm. Fibroglandular tissue (FGT) volume was calculated from whole-breast segmented PDWF maps at 1.5T and 3T. The method was evaluated in (1) a physical fat-water phantom and (2) normal volunteers. Results from two- and three-echo CSE-MRI methods were included for comparison.

RESULTS

Six-echo CC-CSE-MRI produced unbiased estimates of the total water volume in the phantom (mean bias 3.3%) and was reproducible across protocol changes (repeatability coefficient [RC] = 14.8 cm³ and 13.97 cm³ at 1.5T and 3.0T, respectively) and field strengths (RC = 51.7 cm³ ) in volunteers, while the two- and three-echo CSE-MRI approaches produced biased results in phantoms (mean bias 30.7% and 10.4%) that was less reproducible across field strengths in volunteers (RC = 82.3 cm³ and 126.3 cm³ ). Significant differences in measured FGT volume were found between the six-echo CC-CSE-MRI and the two- and three-echo CSE-MRI approaches (p = 0.002 and p = 0.001, respectively).

CONCLUSION

The use of six-echo CC-CSE-MRI to create unbiased PDWF maps that reproducibly quantify FGT in the breast is demonstrated. Further studies are needed to correlate this quantitative MR biomarker for breast density with mammography and overall risk for breast cancer.

Quantification of Liver Fat Content with CT and MRI: State of the Art

Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift-encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation.

Limits of Fat Quantification in the Presence of Iron Overload

BACKGROUND

Chemical shift encoded magnetic resonance imaging (CSE-MRI)-based tissue fat quantification is confounded by increased R2* signal decay rate caused by the presence of excess iron deposition.

PURPOSE

To determine the upper limit of R2* above which it is no longer feasible to quantify proton density fat fraction (PDFF) reliably, using CSE-MRI.

STUDY TYPE

Prospective.

POPULATION

Cramér-Rao lower bound (CRLB) calculations, Monte Carlo simulations, phantom experiments, and a prospective study in 26 patients with known or suspected liver iron overload.

FIELD STRENGTH/SEQUENCE

Multiecho gradient echo at 1.5 T and 3.0 T.

ASSESSMENT

CRLB calculations were used to develop an empirical relationship between the maximum R2* value above which PDFF estimation will achieve a desired number of effective signal averages. A single voxel multi-TR, multi-TE stimulated echo acquisition mode magnetic resonance spectroscopy acquisition was used as a reference standard to estimate PDFF. Reconstructed PDFF and R2* maps were analyzed by one analyst using multiple regions of interest drawn in all nine Couinaud segments.

STATISTICAL TESTS

None.

RESULTS

Simulations, phantom experiments, and in vivo measurements demonstrated unreliable PDFF estimates with increased R2*, with PDFF errors as large as 20% at an R2* of 1000 s-1 . For typical optimized Cartesian acquisitions (TE1 = 0.75 msec, ΔTE = 0.67 msec at 1.5 T, TE1 = 0.65 msec, ΔTE = 0.58 msec at 3.0 T), an empirical relationship between PDFF estimation errors and acquisition parameters was developed that suggests PDFF estimates are unreliable above an R2* of ~538 s-1 and ~779 s-1 at 1.5 T and 3 T, respectively. This empirical relationship was further investigated with phantom experiments and in vivo measurements, with PDFF errors at an R2* of 1000 s-1 at 3.0 T as large as 10% with TE1 = 1.24 msec, ΔTE = 1.01 msec compared to 3% with TE1 = 0.65 msec, ΔTE = 0.58 msec.

DATA CONCLUSION

We successfully developed a theoretically-based empirical formula that may provide an easily calculable guideline to identify R2* values above which PDFF is not reliable in research and clinical applications using CSE-MRI to quantify PDFF in the presence of iron overload.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 1.

Spectroscopy-based multi-parametric quantification in subjects with liver iron overload at 1.5T and 3T

PURPOSE

To evaluate the precision profile (repeatability and reproducibility) of quantitative STEAM-MRS and to determine the relationships between multiple MR biomarkers of chronic liver disease in subjects with iron overload at both 1.5 Tesla (T) and 3T.

METHODS

MRS data were acquired in patients with known or suspected liver iron overload. Two STEAM-MRS sequences (multi-TE and multi-TE-TR) were acquired at both 1.5T and 3T (same day), including test-retest acquisition. Each acquisition enabled estimation of R1, R2, and FWHM (each separately for water and fat); and proton density fat fraction. The test-retest repeatability and reproducibility across acquisition modes (multi-TE vs. multi-TE-TR) of the estimates were evaluated using intraclass correlation coefficients, linear regression, and Bland-Altman analyses. Multi-parametric relationships between parameters at each field strength, across field strengths, and with liver iron concentration were also evaluated using linear and nonlinear regression.

RESULTS

Fifty-six (n = 56) subjects (10 to 73 years, 37 males/19 females) were successfully recruited. Both STEAM-MRS sequences demonstrated good-to-excellent precision (intraclass correlation coefficient ≥ 0.81) for the quantification of R1_water , R2_water , FWHM_water , and proton density fat fraction at both 1.5T and 3T. Additionally, several moderate (R² = 0.50 to 0.69) to high (R² ≥ 0.70) correlations were observed between biomarkers, across field strengths, and with liver iron concentration.

CONCLUSIONS

Over a broad range of liver iron concentration, STEAM-MRS enables rapid and precise measurement of multiple biomarkers of chronic liver disease. By evaluating the multi-parametric relationships between biomarkers, this work may advance the comprehensive MRS-based assessment of chronic liver disease and may help establish biomarkers of chronic liver disease.

Quantitative diffusion MRI of the abdomen and pelvis

Diffusion MRI has enormous potential and utility in the evaluation of various abdominal and pelvic disease processes including cancer and noncancer imaging of the liver, prostate, and other organs. Quantitative diffusion MRI is based on acquisitions with multiple diffusion encodings followed by quantitative mapping of diffusion parameters that are sensitive to tissue microstructure. Compared to qualitative diffusion-weighted MRI, quantitative diffusion MRI can improve standardization of tissue characterization as needed for disease detection, staging, and treatment monitoring. However, similar to many other quantitative MRI methods, diffusion MRI faces multiple challenges including acquisition artifacts, signal modeling limitations, and biological variability. In abdominal and pelvic diffusion MRI, technical acquisition challenges include physiologic motion (respiratory, peristaltic, and pulsatile), image distortions, and low signal-to-noise ratio. If unaddressed, these challenges lead to poor technical performance (bias and precision) and clinical outcomes of quantitative diffusion MRI. Emerging and novel technical developments seek to address these challenges and may enable reliable quantitative diffusion MRI of the abdomen and pelvis. Through systematic validation in phantoms, volunteers, and patients, including multicenter studies to assess reproducibility, these emerging techniques may finally demonstrate the potential of quantitative diffusion MRI for abdominal and pelvic imaging applications.

Reproducibility of liver R2* quantification for liver iron quantification from cardiac R2* acquisitions

OBJECTIVES

To evaluate the reproducibility of liver R2* measurements between a 2D cardiac ECG-gated and a 3D breath-hold liver CSE-MRI acquisition for liver iron quantification.

METHODS

A total of 54 1.5 T MRI exams from 51 subjects (18 women, 36 men, age 35.2 ± 21.8) were included. These included two sub-studies with 23 clinical MRI exams from 19 patients identified retrospectively, 24 participants with known or suspected iron overload, and 7 healthy volunteers acquired prospectively. The 2D cardiac and the 3D liver R2* maps were acquired in the same exam. Either acquisitions were reconstructed using a complex R2* algorithm that accounts for the presence of fat and residual phase errors due to eddy currents. Data were analyzed using colocalized ROIs in the liver.

RESULTS

Linear regression analysis demonstrated high Pearson's correlation and Lin's concordance coefficient for the overall study and both sub-studies. Bland-Altman analysis also showed good agreement, except for a slight increase of the mean R2* value above ~ 400 s^-1. The Kolmogorow-Smirnow test revealed a non-normal distribution for (R2* 3D-R2* 2D) values from 0 to 600 s^-1 in contrast to the 0-200 s^-1 and 0-400 s^-1 subpopulations. Linear regression analysis showed no relevant differences other than the intercept, likely due to only 7 measurements above 400 s^-1.

CONCLUSIONS

The results demonstrate that R2*-measurements in the liver are feasible using 2D cardiac R2* maps compared to 3D liver R2* maps as the reference. Liver R2* may be underestimated for R2* > 400 s^-1 using the 2D cardiac R2* mapping method.

Multisite multivendor validation of a quantitative MRI and CT compatible fat phantom

PURPOSE

Chemical shift-encoded magnetic resonance imaging enables accurate quantification of liver fat content though estimation of proton density fat-fraction (PDFF). Computed tomography (CT) is capable of quantifying fat, based on decreased attenuation with increased fat concentration. Current quantitative fat phantoms do not accurately mimic the CT number of human liver. The purpose of this work was to develop and validate an optimized phantom that simultaneously mimics the MRI and CT signals of fatty liver.

METHODS

An agar-based phantom containing 12 vials doped with iodinated contrast, and with a granular range of fat fractions was designed and constructed within a novel CT and MR compatible spherical housing design. A four-site, three-vendor validation study was performed. MRI (1.5T and 3T) and CT images were obtained using each vendor's PDFF and CT reconstruction, respectively. An ROI centered in each vial was placed to measure MRI-PDFF (%) and CT number (HU). Mixed-effects model, linear regression, and Bland-Altman analysis were used for statistical analysis.

RESULTS

MRI-PDFF agreed closely with nominal PDFF values across both field strengths and all MRI vendors. A linear relationship (slope = -0.54 ± 0.01%/HU, intercept = 37.15 ± 0.03%) with an R² of 0.999 was observed between MRI-PDFF and CT number, replicating established in vivo signal behavior. Excellent test-retest repeatability across vendors (MRI: mean = -0.04%, 95% limits of agreement = [-0.24%, 0.16%]; CT: mean = 0.16 HU, 95% limits of agreement = [-0.15HU, 0.47HU]) and good reproducibility using GE scanners (MRI: mean = -0.21%, 95% limits of agreement = [-1.47%, 1.06%]; CT: mean = -0.18HU, 95% limits of agreement = [-1.96HU, 1.6HU]) were demonstrated.

CONCLUSIONS

The proposed fat phantom successfully mimicked quantitative liver signal for both MRI and CT. The proposed fat phantom in this study may facilitate broader application and harmonization of liver fat quantification techniques using MRI and CT across institutions, vendors and imaging platforms.

Characterization and correction of cardiovascular motion artifacts in diffusion-weighted imaging of the pancreas

PURPOSE

To assess the effects of cardiovascular-induced motion on conventional DWI of the pancreas and to evaluate motion-robust DWI methods in a motion phantom and healthy volunteers.

METHODS

3T DWI was acquired using standard monopolar and motion-compensated gradient waveforms, including in an anatomically accurate pancreas phantom with controllable compressive motion and healthy volunteers (n = 8, 10). In volunteers, highly controlled single-slice DWI using breath-holding and cardiac gating and whole-pancreas respiratory-triggered DWI were acquired. For each acquisition, the ADC variability across volunteers, as well as ADC differences across parts of the pancreas were evaluated.

RESULTS

In motion phantom scans, conventional DWI led to biased ADC, whereas motion-compensated waveforms produced consistent ADC. In the breath-held, cardiac-triggered study, conventional DWI led to heterogeneous DW signals and highly variable ADC across the pancreas, whereas motion-compensated DWI avoided these artifacts. In the respiratory-triggered study, conventional DWI produced heterogeneous ADC across the pancreas (head: 1756 ± 173 × 10^-6 mm² /s; body: 1530 ± 338 × 10^-6 mm² /s; tail: 1388 ± 267 × 10^-6 mm² /s), with ADCs in the head significantly higher than in the tail (P < .05). Motion-compensated ADC had lower variability across volunteers (head: 1277 ± 102 × 10^-6 mm² /s; body: 1204 ± 169 × 10^-6 mm² /s; tail: 1235 ± 178 × 10^-6 mm² /s), with no significant difference (P ≥ .19) across the pancreas.

CONCLUSION

Cardiovascular motion introduces artifacts and ADC bias in pancreas DWI, which are addressed by motion-robust DWI.

Impact of ferumoxytol magnetic resonance imaging on the rhesus macaque maternal-fetal interface†

Ferumoxytol is a superparamagnetic iron oxide nanoparticle used off-label as an intravascular magnetic resonance imaging (MRI) contrast agent. Additionally, ferumoxytol-uptake by macrophages facilitates detection of inflammatory sites by MRI through ferumoxytol-induced image contrast changes. Therefore, ferumoxytol-enhanced MRI holds great potential for assessing vascular function and inflammatory response, critical to determine placental health in pregnancy. This study sought to assess the fetoplacental unit and selected maternal tissues, pregnancy outcomes, and fetal well-being after ferumoxytol administration. In initial developmental studies, seven pregnant rhesus macaques were imaged with or without ferumoxytol administration. Pregnancies went to term with vaginal delivery and infants showed normal growth rates compared to control animals born the same year that did not undergo MRI. To determine the impact of ferumoxytol on the maternal-fetal interface (MFI), fetal well-being, and pregnancy outcome, four pregnant rhesus macaques at ~100 gestational day underwent MRI before and after ferumoxytol administration. Collection of the fetoplacental unit and selected maternal tissues was performed 2-3 days following ferumoxytol administration. A control group that did not receive ferumoxytol or MRI was used for comparison. Iron levels in fetal and MFI tissues did not differ between groups, and there was no significant difference in tissue histopathology with or without exposure to ferumoxytol, and no effect on placental hormone secretion. Together, these results suggest that the use of ferumoxytol and MRI in pregnant rhesus macaques does not negatively impact the MFI and can be a valuable experimental tool in research with this important animal model.

Comprehensive non-invasive analysis of lower urinary tract anatomy using MRI

PURPOSE

Anatomic changes that coincide with aging including benign prostatic hyperplasia (BPH) and lower urinary tract symptoms (LUTS) negatively impact quality of life. Use of MRI with its exquisite soft tissue contrast, full field-of-view capabilities, and lack of radiation is uniquely suited for quantifying specific lower urinary tract features and providing comprehensive measurements such as total bladder wall volume (BWV), bladder wall thickness (BWT), and prostate volume (PV). We present a technique for generating 3D anatomical renderings from MRI to perform quantitative analysis of lower urinary tract anatomy.

METHODS

T2-weighted fast-spin echo MRI of the pelvis in 117 subjects (59F;58 M) aged 30-69 (49.5 ± 11.3) without known lower urinary tract symptoms was retrospectively segmented using Materialise software. Virtual 3D models were used to measure BWV, BWT, and PV.

RESULTS

BWV increased significantly between the 30-39 and 60-69 year age group in women (p = 0.01), but not men (p = 0.32). BWV was higher in men than women aged 30-39 and 40-49 (p = 0.02, 0.05, respectively) ,but not 50-59 or 60-69 (p = 0.18, 0.16, respectively). BWT was thicker in men than women across all age groups. Regional differences in BWT were observed both between men and women and between opposing bladder wall halves (anterior/posterior, dome/base, left/right) within each sex in the 50-59 and 60-69 year groups. PV increased from the 30-39 to 60-69 year groups (p = 0.05). BWT was higher in subjects with enlarged prostates (> 40cm³) (p = 0.05).

CONCLUSION

Virtual 3D MRI models of the lower urinary tract reliably quantify sex-specific and age-associated changes of the bladder wall and prostate.

Accuracies of Chemical Shift In/Opposed Phase and Chemical Shift Encoded Magnetic Resonance Imaging to Detect Intratumoral Fat in Hepatocellular Carcinoma

BACKGROUND

Magnetic Resonance Imaging (MRI) being a noninvasive modality may help in preoperative evaluation of intratumoral fat in hepatocellular carcinoma (HCC) using chemical shift encoded (CSE) MRI and in-/opposed-phase (IOP) imaging sequences.

PURPOSE

To compare the diagnostic accuracy of chemical shift encoded fat fraction at three different flip angles (FAs) using quantitative chemical shift encoded MRI (CSE-MRI) with in-/opposed phase (IOP) imaging to evaluate intratumoral fat in HCC.

STUDY TYPE

Retrospective.

POPULATION

Eighty-six patients with 87 pathology proven HCCs.

FIELD STRENGTH/SEQUENCE

IOP (LAVA-Flex) and CSE-MRI (IDEAL IQ) a three-dimensional spoiled gradient-echo pulse sequences acquired at 3 T.

ASSESSMENT

Regions of interest (ROIs) were manually drawn by two observers in the tumors to measure mean fat fractions. Surgical specimens were reassessed for intratumoral fat content. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed for CSE-MRI sequence at FA 3°, 8°, and 9°.

STATISTICAL TESTS

Intraclass correlation coefficient (ICC) was expressed in terms of inter- and intra-observer agreements. Receiver operating characteristic curve analysis was performed for the diagnostic performance followed by combined metric of both. SNR/CNR were analyzed by Kruskal-Wallis test.

RESULTS

Excellent inter- and intra-observer agreements (ICC >0.95, P < 0.001) were observed for both IOP and CSE-MRI. IOP (86.4%) showed higher sensitivity than CSE-MRI at FA 3° (72.5%), FA 8° (76.4%) and FA 9° (76.3%). In contrast, the specificity for CSE-MRI at FA 3° (86%), FA 8° (87%), and FA 9° (87%) were greater than IOP (72%). A combined metric of IOP and CSE-MRI derived fat fractions at FA 8° gave highest AUC of 87% and accuracy of 86%. SNR and CNR for CSE-MRI were significantly higher at FA 8° and FA 9° than FA 3° (P < 0.05).

DATA CONCLUSION

IOP and quantitative CSE-MRI are both feasible methods to detect intratumoral fat in HCC with higher accuracy and SNR for CSE-MRI at FA 8° and 9°.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

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.

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.

Free-breathing R 2 ∗ mapping of hepatic iron overload in children using 3D multi-echo UTE cones MRI

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, 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 R 2 ∗ 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 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, 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 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.

A pilot study of bladder voiding with real-time MRI and computational fluid dynamics

Lower urinary track symptoms (LUTS) affect many older adults. Multi-channel urodynamic studies provide information about bladder pressure and urinary flow but offer little insight into changes in bladder anatomy and detrusor muscle function. Here we present a novel method for real time MRI during bladder voiding. This was performed in a small cohort of healthy men and men with benign prostatic hyperplasia and lower urinary tract symptoms (BPH/LUTS) to demonstrate proof of principle; The MRI urodynamic protocol was successfully implemented, and bladder wall displacement and urine flow dynamics were calculated. Displacement analysis on healthy controls showed the greatest bladder wall displacement in the dome of the bladder while men with BPH/LUTS exhibited decreased and asymmetric bladder wall motion. Computational fluid dynamics of voiding showed men with BPH/LUTS had larger recirculation regions in the bladder. This study demonstrates the feasibility of performing MRI voiding studies and their potential to provide new insight into lower urinary tract function in health and disease.

B0 and B1 inhomogeneities in the liver at 1.5 T and 3.0 T

PURPOSE

The purpose of this work is to characterize the magnitude and variability of B₀ and B₁ inhomogeneities in the liver in large cohorts of patients at both 1.5 T and 3.0 T.

METHODS

Volumetric B₀ and B₁ maps were acquired over the liver of patients presenting for routine abdominal MRI. Regions of interest were drawn in the nine Couinaud segments of the liver, and the average value was recorded. Magnitude and variation of measured averages in each segment were reported across all patients.

RESULTS

A total of 316 B₀ maps and 314 B₁ maps, acquired at 1.5 T and 3.0 T on a variety of GE Healthcare MRI systems in 630 unique exams, were identified, analyzed, and, in the interest of reproducible research, de-identified and made public. Measured B₀ inhomogeneities ranged (5th-95th percentiles) from -31.7 Hz to 164.0 Hz for 3.0 T (-14.5 Hz to 81.3 Hz at 1.5 T), while measured B₁ inhomogeneities (ratio of actual over prescribed flip angle) ranged from 0.59 to 1.13 for 3.0 T (0.83 to 1.11 at 1.5 T).

CONCLUSION

This study provides robust characterization of B₀ and B₁ inhomogeneities in the liver to guide the development of imaging applications and protocols. Field strength, bore diameter, and sex were determined to be statistically significant effects for both B₀ and B₁ uniformity. Typical clinical liver imaging at 3.0 T should expect B₀ inhomogeneities ranging from approximately -100 Hz to 250 Hz (-50 Hz to 150 Hz at 1.5 T) and B₁ inhomogeneities ranging from approximately 0.4 to 1.3 (0.7 to 1.2 at 1.5 T).

Effect of noise and estimator type on bias for analysis of liver proton density fat fraction

PURPOSE

Proton-density fat-fraction (PDFF) is typically measured from PDFF maps by calculating the mean PDFF value within a region of interest (ROI). However, the mean estimator has been shown to result in bias when signal-to-noise ratio (SNR) is low, resulting from a skewed distribution of PDFF noise statistics. Thus, the purpose of this work was to determine the relative performance of three estimation methods (mean, median, maximum likelihood estimators (MLE)) for analysis of liver PDFF maps.

METHODS

Observational study of adult patients (n = 56) undergoing abdominal MRI. Both 2D-sequential CSE-MRI ('low-SNR') and 3D CSE-MRI ('high-SNR') acquisitions were obtained. Single-voxel MRS formed the independent reference measurement of hepatic PDFF. Intra-class correlation was tested on a subset of 'low-SNR' acquisitions. ROIs were semi-automatically co-registered across all acquisitions. Bland-Altman analysis and intra-class correlation coefficients were used for statistical analysis. A p-value of <0.05 was considered significant.

RESULTS

For in vivo low-SNR acquisitions, the mean estimator had a larger error than either the median or MLE values (bias ~ -1% absolute PDFF). The intra-class correlation coefficient was significantly greater for median and maximum likelihood estimators (0.992 and 0.993, respectively) compared to the mean estimator (0.973).

CONCLUSION

Alternative ROI analysis strategies, such as MLE or median estimators, are useful to avoid SNR-related PDFF bias. Median may be the most clinically practical strategy given its ease of calculation.

Design and evaluation of quantitative MRI phantoms to mimic the simultaneous presence of fat, iron, and fibrosis in the liver

PURPOSE

To design, construct, and evaluate quantitative MR phantoms that mimic MRI signals from the liver with simultaneous control of three parameters: proton-density fat fraction (PDFF), R 2 ∗ , and T₁ . These parameters are established biomarkers of hepatic steatosis, iron overload, and fibrosis/inflammation, respectively, which can occur simultaneously in the liver.

METHODS

Phantoms including multiple vials were constructed. Peanut oil was used to modulate PDFF, MnCl₂ and iron microspheres were used to modulate R 2 ∗ , and NiCl₂ was used to modulate the T₁ of water (T_1,water ). Phantoms were evaluated at both 1.5 T and 3 T using stimulated-echo acquisition-mode MRS and chemical shift-encoded MRI. Stimulated-echo acquisition-mode MRS data were processed to estimate T_1,water , T_1,fat , R 2 , water ∗ , and R 2 , fat ∗ for each vial. Chemical shift-encoded MRI data were processed to generate PDFF and R 2 ∗ maps, and measurements were obtained in each vial. Measurements were evaluated using linear regression and Bland-Altman analysis.

RESULTS

High-quality PDFF and R 2 ∗ maps were obtained with homogeneous values throughout each vial. High correlation was observed between imaging PDFF with target PDFF (slope = 0.94-0.97, R² = 0.994-0.997) and imaging R 2 ∗ with target R 2 ∗ (slope = 0.84-0.88, R² = 0.935-0.943) at both 1.5 T and 3 T. The values of R 2 , fat ∗ and R 2 , water ∗ were highly correlated with slope close to 1.0 at both 1.5 T (slope = 0.90, R² = 0.988) and 3 T (slope = 0.99, R² = 0.959), similar to the behavior observed in vivo. The value of T_1,water (500-1200 ms) was controlled with varying NiCl₂ concentration, while T_1,fat (300 ms) was independent of NiCl₂ concentration.

CONCLUSION

Novel quantitative MRI phantoms that mimic the simultaneous presence of fat, iron, and fibrosis in the liver were successfully developed and validated.

Free-breathing liver fat and R 2 ∗ quantification using motion-corrected averaging based on a nonlocal means algorithm

PURPOSE

To propose a motion-robust chemical shift-encoded (CSE) method with high signal-to-noise (SNR) for accurate quantification of liver proton density fat fraction (PDFF) and R 2 ∗ .

METHODS

A free-breathing multi-repetition 2D CSE acquisition with motion-corrected averaging using nonlocal means (NLM) was proposed. PDFF and R 2 ∗ quantified with 2D CSE-NLM were compared to two alternative 2D techniques: direct averaging and single acquisition (2D 1ave) in a digital phantom. Further, 2D NLM was compared in patients to 3D techniques (standard breath-hold, free-breathing and navigated), and the alternative 2D techniques. A reader study and quantitative analysis (Bland-Altman, correlation analysis, paired Student's t-test) were performed to evaluate the image quality and assess PDFF and R 2 ∗ measurements in regions of interest.

RESULTS

In simulations, 2D NLM resulted in lower standard deviations (STDs) of PDFF (2.7%) and R 2 ∗ (8.2  s - 1 ) compared to direct averaging (PDFF: 3.1%, R 2 ∗ : 13.6  s - 1 ) and 2D 1ave (PDFF: 8.7%, R 2 ∗ : 33.2  s - 1 ). In patients, 2D NLM resulted in fewer motion artifacts than 3D free-breathing and 3D navigated, less signal loss than 2D direct averaging, and higher SNR than 2D 1ave. Quantitatively, the STDs of PDFF and R 2 ∗ of 2D NLM were comparable to those of 2D direct averaging (p>0.05). 2D NLM reduced bias, particularly in R 2 ∗ (-5.73 to -0.36  s - 1 ) that arises in direct averaging (-3.96 to 11.22  s - 1 ) in the presence of motion.

CONCLUSIONS

2D CSE-NLM enables accurate mapping of PDFF and R 2 ∗ in the liver during free-breathing.

Motion-robust, high-SNR liver fat quantification using a 2D sequential acquisition with a variable flip angle approach

PURPOSE

Chemical shift encoded (CSE)-MRI enables quantification of proton-density fat fraction (PDFF) as a biomarker of liver fat content. However, conventional 3D Cartesian CSE-MRI methods require breath-holding. A motion-robust 2D Cartesian sequential method addresses this limitation but suffers from low SNR. In this work, a novel free breathing 2D Cartesian sequential CSE-MRI method using a variable flip angle approach with centric phase encoding (VFA-centric) is developed to achieve fat quantification with low T 1 bias, high SNR, and minimal blurring.

METHODS

Numerical simulation was performed for variable flip angle schedule design and preliminary evaluation of VFA-centric method, along with several alternative flip angle designs. Phantom, adults (n = 8), and children (n = 27) were imaged at 3T. Multi-echo images were acquired and PDFF maps were estimated. PDFF standard deviation was used as a surrogate for SNR.

RESULTS

In both simulation and phantom experiments, the VFA-centric method enabled higher SNR imaging with minimal T 1 bias and blurring artifacts. High correlation (slope = 1.00, intercept = 0.04, R 2 = 0.998) was observed in vivo between the proposed VFA-centric method obtained PDFF and reference PDFF (free breathing low-flip angle 2D sequential acquisition). Further, the proposed VFA-centric method (PDFF standard deviation = 1.5%) had a better SNR performance than the reference acquisition (PDFF standard deviation = 3.3%) with P < .001.

CONCLUSIONS

The proposed free breathing 2D Cartesian sequential CSE-MRI method with variable flip angle approach and centric-ordered phase encoding achieved motion robustness, low T 1 bias, high SNR compared to previous 2D sequential methods, and low blurring in liver fat quantification.

Stimulated-echo diffusion-weighted imaging with moderate b values for the detection of prostate cancer

OBJECTIVES

Conventional spin-echo (SE) DWI leads to a fundamental trade-off depending on the b value: high b value provides better lesion contrast-to-noise ratio (CNR) by sacrificing signal-to-noise ratio (SNR), image quality, and quantitative reliability. A stimulated-echo (STE) DWI acquisition is evaluated for high-CNR imaging of prostate cancer while maintaining SNR and reliable apparent diffusion coefficient (ADC) mapping.

METHODS

In this prospective, IRB-approved study, 27 patients with suspected prostate cancer (PCa) were scanned with three DWI sequences (SE b = 800 s/mm², SE b = 1500 s/mm², and STE b = 800 s/mm²) after informed consent was obtained. ROIs were drawn on biopsy-confirmed cancer and non-cancerous tissue to perform quantitative SNR, CNR, and ADC measurements. Qualitative metrics (SNR, CNR, and overall image quality) were evaluated by three experienced radiologists. Metrics were compared pairwise between the three acquisitions using a t test (quantitative metrics) and Wilcoxon rank test (qualitative metrics).

RESULTS

Quantitative measurements showed that STE DWI at b = 800 s/mm² has significantly better SNR compared to SE DWI at b = 1500 s/mm² (p < 0.0001) and comparable CNR to high-b value SE DWI at b = 1500 s/mm² (p < 0.05) in the peripheral zone. Qualitative assessment showed preference to STE b = 800 s/mm² in SNR and SE b = 1500 s/mm² in CNR. The overall image quality and lesion detectability among most readers showed no significant preference between STE b = 800 s/mm² and SE b = 1500 s/mm². Further, STE DWI had similar ADC contrast between lesion and normal tissue as SE DWI at b = 800 s/mm² (p = 0.90).

CONCLUSION

STE DWI has the potential to provide high-SNR, high-CNR imaging of prostate cancer while also enabling reliable ADC mapping.

KEY POINTS

• Quantitative analysis showed that STE DWI at b = 800 s/mm²is able to achieve simultaneously high CNR, high SNR, and reliable ADC mapping, compared to SE b = 800 s/mm²and SE b = 1500 s/mm². • Qualitative assessment by three readers showed that STE DWI at b = 800 s/mm²has significantly higher SNR than SE b = 1500 s/mm². No preference between SE b = 1500 s/mm²and STE b = 800 s/mm²was determined in terms of CNR with no missed lesions were found in both acquisitions. • A single STE DWI acquisition at moderate b value (800-1000 s/mm²) may provide sufficient image quality and quantitative reliability for prostate cancer imaging within a shorter scan time, in place of two DWI acquisitions (one with moderate b value and one with high b value).