Evaluation of respiratory liver and kidney movements for MRI navigator gating

Purpose To determine the tracking factor by studying the relationship between kidney and diaphragm motions and to compare the efficiency of the gating-and-following and gating-only algorithms in reducing motion artifacts in navigator-gated scans. Materials and Methods Diaphragm and kidney motions were measured by using real-time TrueFISP sequences from 10 healthy human volunteers to determine tracking factors at different acceptance windows. Mean tracking factors were used to calculate mean residual errors and improvement factors for the gating-and-following and gating-only algorithms. Results Mean tracking factors for ±4, ±6, ±8 mm and full acceptance windows ranged from 0.6 to 0.7, with large interindividual variations. Acceptance rates increased as the size of the acceptance window increased (acceptance rate for a 4 mm window ∼ 50%). There was a greater reduction of motion errors by gating-and-following (maximum of 1.86 mm) than gating-only (maximum of 7.05 mm). Conclusion Mean tracking factors obtained in this study can be used as a guideline for using the gating-and-following algorithm in navigator-gated kidney scans. The gating-and-following and gating-only algorithms were quantitatively compared, and it was found that the former is more effective in reducing motion errors. © 2010 Wiley-Liss, Inc

Automated vessel exclusion technique for quantitative assessment of hepatic iron overload by R2*-MRI

Background: Extraction of liver parenchyma is an important step in the evaluation of R *2 -based hepatic iron content (HIC). Traditionally, this is performed by radiologists via whole-liver contouring and T *2 -thresholding to exclude hepatic vessels. However, the vessel exclusion process is iterative, time-consuming, and susceptible to interreviewer variability. Purpose: To implement and evaluate an automatic hepatic vessel exclusion and parenchyma extraction technique for accurate assessment of R *2 -based HIC. Study Type: Retrospective analysis of clinical data. Subjects: Data from 511 MRI exams performed on 257 patients were analyzed. Field Strength/Sequence: All patients were scanned on a 1.5T scanner using a multiecho gradient echo sequence for clinical monitoring of HIC. Assessment: An automated method based on a multiscale vessel enhancement filter was investigated for three input data types—contrast-optimized composite image, T *2 map, and R *2 map—to segment blood vessels and extract liver tissue for R *2 -based HIC assessment. Segmentation and R *2 results obtained using this automated technique were compared with those from a reference T *2 -thresholding technique performed by a radiologist. Statistical Tests: The Dice similarity coefficient was used to compare the segmentation results between the extracted parenchymas, and linear regression and Bland-Altman analyses were performed to compare the R *2 results, obtained with the automated and reference techniques. Results: Mean liver R *2 values estimated from all three filter-based methods showed excellent agreement with the reference method (slopes 1.04–1.05, R 2 \u3e 0.99, P \u3c 0.001). Parenchyma areas extracted using the reference and automated methods had an average overlap area of 87–88%. The T *2 -thresholding technique included small vessels and pixels at the vessel/tissue boundaries as parenchymal area, potentially causing a small bias (\u3c5%) in R *2 values compared to the automated method. Data Conclusion: The excellent agreement between reference and automated hepatic vessel segmentation methods confirms the accuracy and robustness of the proposed method. This automated approach might improve the radiologist\u27s workflow by reducing the interpretation time and operator dependence for assessing HIC, an important clinical parameter that guides iron overload management. Level of Evidence: 3. Technical Efficacy: Stage 2. J. Magn. Reson. Imaging 2018;47:1542–1551

Autoregressive moving average modeling for hepatic iron quantification in the presence of fat

Background: Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient-echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. Purpose: To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Study Type: Phantom study and in vivo cohort. Population: Twenty iron–fat phantoms covering clinically relevant R2* (30–800 s-1) and fat fraction (FF) ranges (0–40%), and 10 patients (four male, six female, mean age 18.8 years). Field Strength/Sequence: 2D mGRE acquisitions at 1.5 T and 3 T. Assessment: Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Statistical Tests: Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex-domain nonlinear least squares (NLSQ) fat–water model, and biopsy. Results: In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89–1.07), but NLSQ overestimated R2* (slopes: 1.14–1.36) and produced false FFs (12–17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02–1.16) outperformed monoexponential and ARMA models (slopes: 1.23–1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96–1.04). In patients, mean R2*-HIC estimates for monoexponential and ARMA models were close to biopsy-HIC values (slopes: 0.90–0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4–28%) with very high SDs (15–222%) in patients with high iron overload and no steatosis. Data Conclusion: ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. Level of Evidence: 2. Technical Efficacy Stage: 2. J. Magn. Reson. Imaging 2019;50:1620–1632

Autoregressive moving average modeling for hepatic iron quantification in the presence of fat

Background: Measuring hepatic R2* by fitting a monoexponential model to the signal decay of a multigradient-echo (mGRE) sequence noninvasively determines hepatic iron content (HIC). Concurrent hepatic steatosis introduces signal oscillations and confounds R2* quantification with standard monoexponential models. Purpose: To evaluate an autoregressive moving average (ARMA) model for accurate quantification of HIC in the presence of fat using biopsy as the reference. Study Type: Phantom study and in vivo cohort. Population: Twenty iron–fat phantoms covering clinically relevant R2* (30–800 s-1) and fat fraction (FF) ranges (0–40%), and 10 patients (four male, six female, mean age 18.8 years). Field Strength/Sequence: 2D mGRE acquisitions at 1.5 T and 3 T. Assessment: Phantoms were scanned at both field strengths. In vivo data were analyzed using the ARMA model to determine R2* and FF values, and compared with biopsy results. Statistical Tests: Linear regression analysis was used to compare ARMA R2* and FF results with those obtained using a conventional monoexponential model, complex-domain nonlinear least squares (NLSQ) fat–water model, and biopsy. Results: In phantoms and in vivo, all models produced R2* and FF values consistent with expected values in low iron and low/high fat conditions. For high iron and no fat phantoms, monoexponential and ARMA models performed excellently (slopes: 0.89–1.07), but NLSQ overestimated R2* (slopes: 1.14–1.36) and produced false FFs (12–17%) at 1.5 T; in high iron and fat phantoms, NLSQ (slopes: 1.02–1.16) outperformed monoexponential and ARMA models (slopes: 1.23–1.88). The results with NLSQ and ARMA improved in phantoms at 3 T (slopes: 0.96–1.04). In patients, mean R2*-HIC estimates for monoexponential and ARMA models were close to biopsy-HIC values (slopes: 0.90–0.95), whereas NLSQ substantially overestimated HIC (slope 1.4) and produced false FF values (4–28%) with very high SDs (15–222%) in patients with high iron overload and no steatosis. Data Conclusion: ARMA is superior in quantifying R2* and FF under high iron and no fat conditions, whereas NLSQ is superior for high iron and concurrent fat at 1.5 T. Both models give improved R2* and FF results at 3 T. Level of Evidence: 2. Technical Efficacy Stage: 2. J. Magn. Reson. Imaging 2019;50:1620–1632

Radial ultrashort TE imaging removes the need for breath-holding in hepatic iron overload quantification by R2∗ MRI

OBJECTIVE. The objective of this study is to evaluate radial free-breathing (FB) multiecho ultrashort TE (UTE) imaging as an alternative to Cartesian FB multiecho gradient-recalled echo (GRE) imaging for quantitative assessment of hepatic iron content (HIC) in sedated patients and subjects unable to perform breath-hold (BH) maneuvers. MATERIALS AND METHODS. FB multiecho GRE imaging and FB multiecho UTE imaging were conducted for 46 test group patients with iron overload who could not complete BH maneuvers (38 patients were sedated, and eight were not sedated) and 16 control patients who could complete BH maneuvers. Control patients also underwent standard BH multiecho GRE imaging. Quantitative R2∗ maps were calculated, and mean liver R2∗ values and coefficients of variation (CVs) for different acquisitions and patient groups were compared using statistical analysis. RESULTS. FB multiecho GRE images displayed motion artifacts and significantly lower R2∗ values, compared with standard BH multiecho GRE images and FB multiecho UTE images in the control cohort and FB multiecho UTE images in the test cohort. In contrast, FB multiecho UTE images produced artifact-free R2∗ maps, and mean R2∗ values were not significantly different from those measured by BH multiecho GRE imaging. Motion artifacts on FB multiecho GRE images resulted in an R2∗ CV that was approximately twofold higher than the R2∗ CV from BH multiecho GRE imaging and FB multiecho UTE imaging. The R2∗ CV was relatively constant over the range of R2∗ values for FB multiecho UTE, but it increased with increases in R2∗ for FB multiecho GRE imaging, reflecting that motion artifacts had a stronger impact on R2∗ estimation with increasing iron burden. CONCLUSION. FB multiecho UTE imaging was less motion sensitive because of radial sampling, produced excellent image quality, and yielded accurate R2∗ estimates within the same acquisition time used for multiaveraged FB multiecho GRE imaging. Thus, FB multiecho UTE imaging is a viable alternative for accurate HIC assessment in sedated children and patients who cannot complete BH maneuvers

Ventricular diastolic dysfunction in sickle cell anemia is common but not associated with myocardial iron deposition

Background. Cardiac failure from myocardial iron deposition is a severe complication in patients with transfusion-related iron overload. Progressive heart damage from iron overload can cause left ventricular systolic and diastolic dysfunction in patients with hematologic disorders. Since nontransfused patients with sickle cell anemia (SCA) have a high incidence of diastolic dysfunction, we investigated the relationships among transfusional iron burden, myocardial iron deposition, and diastolic ventricular dysfunction by T2*-MRI and tissue Doppler echocardiography in iron-overloaded children with SCA. Procedure. Children (≥7 years) with SCA and iron overload (serum ferritin \u3e1,000 ng/ml or ≥18 lifetime transfusions) were eligible. Serum ferritin and hepatic iron content (HIC) were measured and participants underwent nonsedated T2*-MRI of the heart, echocardiogram, electrocardiogram, and multi-uptake gated acquisition (MUGA) scan. Age-matched normative echocardiographic data were used for comparison. Results. Among 30 children with SCA (median age, 13 years) and iron overload, mean (±SD) HIC and serum ferritin were 10.8mg Fe/g (±5.9mgFe/g) and 3,089 ng/ml (±2,167 ng/ml), respectively. Mean T2*-MRI was 33 msec (±7 msec, range, 22-49). Echocardiography showed a high prevalence of diastolic dysfunction (77% and 45% abnormally low mean mitral annular velocity and mean tricuspid annular velocity, respectively); however, echocardiogram and MUGA scan findings were not significantly associated with HIC or T2*-MRI. Conclusions. Diastolic dysfunction is not associated with transfusional iron burden or myocardial iron deposition among children with SCA. Diastolic dysfunction likely results from disease pathophysiology and severity rather than iron overload. © 2010 Wiley-Liss, Inc

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

Background: Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. Objective: To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. Materials and methods: This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Results: Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. Conclusion: We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations

Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla

Purpose: Hepatic iron content (HIC) quantification via transverse relaxation rate (R2*)-MRI using multi-gradient echo (mGRE) imaging is compromised toward high HIC or at higher fields due to the rapid signal decay. Our study aims at presenting an optimized 2D ultrashort echo time (UTE) sequence for R2* quantification to overcome these limitations. Methods: Two-dimensional UTE imaging was realized via half-pulse excitation and radial center-out sampling. The sequence includes chemically selective saturation pulses to reduce streaking artifacts from subcutaneous fat, and spatial saturation (sSAT) bands to suppress out-of-slice signals. The sequence employs interleaved multi-echo readout trains to achieve dense temporal sampling of rapid signal decays. Evaluation was done at 1.5 Tesla (T) and 3T in phantoms, and clinical applicability was demonstrated in five patients with biopsy-confirmed massively high HIC levels (\u3e25 mg Fe/g dry weight liver tissue). Results: In phantoms, the sSAT pulses were found to remove out-of-slice contamination, and R2* results were in excellent agreement to reference mGRE R2* results (slope of linear regression: 1.02/1.00 for 1.5/3T). UTE-based R2* quantification in patients with massive iron overload proved successful at both field strengths and was consistent with biopsy HIC values. Conclusion: The UTE sequence provides a means to measure R2* in patients with massive iron overload, both at 1.5T and 3T. Magn Reson Med 78:1839–1851, 2017. © 2017 Wiley Periodicals, Inc