Rapid MRI Assessment of Long-Axis Strain to Indicate Systolic Dysfunction in Patients With Sickle Cell Disease.

BACKGROUND: Patients with sickle cell disease (SCD) have a unique form of cardiomyopathy. However, left ventricular ejection fraction (LVEF) is often preserved. Monoplanar long-axis strain (LAS) can be assessed from MRI four-chamber views and may be better at detecting mild systolic dysfunction in these patients. PURPOSE: To compare LAS (monoplanar and biplanar) with LVEF as a marker of systolic dysfunction in SCD patients. STUDY TYPE: Retrospective. SUBJECTS: A total of 20 patients with genetically proven SCD (35 MRI examinations), 39 healthy controls, and 124 patients with systemic iron overload (for validation purposes). FIELD STRENGTH/SEQUENCE: 1.5 T/3 T. Cine balanced steady-state free-precession. ASSESSMENT: Rapidly assessed biplanar LAS from four- and two-chamber views was correlated with age and compared to LVEF by two operators. For validation, biplanar LAS was compared to global longitudinal strain (GLS) using MRI feature-tracking in 124 patients with systemic iron overload. STATISTICAL TESTS: Bland-Altman analysis. Wilcoxon-Mann-Whitney test and Spearman-rank correlation (correlation coefficient, rS ). Receiver-operating-characteristic (ROC) curve analysis (area under the curve, AUC). Bivariate discriminant analysis. Significance level: P < 0.01. RESULTS: There was strong correlation between biplanar LAS and GLS using feature tracking (rS  = 0.73). Interoperator agreement showed nonsignificant bias for biplanar LAS (-0.02%; ±95%-agreement interval -2.2%/2.2%, P = 0.9). Biplanar LAS increased significantly with age in controls (rS  = 0.70). In SCD patients, biplanar LAS was better correlated with age than monoplanar LAS (r2  = 0.53, standard error of estimate, SEE = 1.4% vs. r2  = 0.37;SEE = 2.0%). ROC analysis of LVEF, biplanar LAS, and age-adjusted Z-scores Z (LAS(age)) showed AUCs of 0.69, 0.75, and 0.86 for differentiation between SCD patients and controls. Bivariate discriminant analysis of biplanar Z (LAS(age)) and LVEF revealed a sensitivity of 63% and a specificity of 95%. DATA CONCLUSION: Rapidly assessed biplanar LAS demonstrated high diagnostic accuracy and was an indicator of mild systolic dysfunction in patients with SCD. Biplanar LAS provided more precise measurements than monoplanar, and normalization to age increased diagnostic accuracy. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Vertebral Bone Density Measurements by DXA are Influenced by Hepatic Iron Overload in Patients with Hemoglobinopathies.

Interference from metal hardware (piercings; buttons on clothing; and ingested material, e.g. barium) is well documented in bone health assessments by dual-energy X-ray absorptiometry (DXA). It is unknown if iron in hepatic tissue of highly iron-loaded patients could be mistakenly assessed by DXA as bone, and if this would lead to increased areal bone mineral density (aBMD) lumbar spine Z-scores derived by DXA. Our hypothesis is that iron in the liver of heavily loaded patients will artificially raise aBMD in the spine, and thereby lead to an error in the DXA scan. This study consisted of a retrospective chart review and re-analysis of DXA scans from patients with sickle cell disease and thalassemia combined with prospective DXA and liver iron concentration (LIC) measurements from healthy controls. Patients who previously had both a DXA and LIC measurement were compared with controls. aBMD of individual vertebrae were analyzed and grouped by those that may be covered by the liver (L1 or L1/2) with those typically not (L3/4). Subjects were grouped by diagnosis and LIC severity. Phantoms were created to mimic the geometry of iron loaded liver tissue, and analyzed by DXA. A significant effect was observed in the difference of BMD Z-score of L1 and L 3/4 when patients with LIC < 1000 were compared to those with >5000 µg Fe/g wet tissue (p = 0.043). A significant relationship was also observed in the difference in aBMD Z-score of L1 and 3/4 when controls were compared to the high iron group (p = 0.037). These findings were supported by phantom experiments. These results suggest that there is a relationship between hepatic iron and increased L1 aBMD Z-scores in highly iron-loaded patients. Given patients with hemoglobinopathies are at increased risk for osteoporosis, clinicians should maintain a higher index of suspicion when diagnosing low bone mass.

BOLD MRI in the brain of fetal sheep at 3T during experimental hypoxia.

PURPOSE: To calculate regional fetal brain oxygen saturation (sO2) during hypoxia in sheep. MATERIALS AND METHODS: Eight pregnant ewes were examined at a 3T MR-scanner using blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) to measure signal intensity changes of the fetal brain during a control period and a period of induced hypoxia. Regions of interest were placed in the fetal cerebrum to assess ΔR2* from GRE signal intensity plateaus (S(control), S(hypoxia)) and the relation between ΔR2* and ΔpO2 was analyzed. A probe was placed surgically in the fetal brain to directly measure local pO2 as a reference standard. Baseline and hypoxic pO2 values were recorded and compared (ΔpO2). RESULTS: Mean fetal brain pO2 decreased from 14.3 mmHg (95% confidence interval [CI]: 10-19) to 3.4 mmHg (95% CI: 2-5) during hypoxia (mean ΔpO2 = 10.9 mmHg and ΔR2* = -5s(-1)). A significant correlation between ΔR2* and ΔpO2 was noted (r = 0.93, P < 0.001), and conversion of pO2 into sO2 resulted in a linear regression coefficient of (-0.14 ± 0.01)s(-1)/% (r(2) = 0.91). CONCLUSION: Measured fetal brain BOLD-MRI was compared and converted to pO2, followed by calculation of cerebral sO2.

Mechanisms of plasma non-transferrin bound iron generation: insights from comparing transfused diamond blackfan anaemia with sickle cell and thalassaemia patients.

In transfusional iron overload, extra-hepatic iron distribution differs, depending on the underlying condition. Relative mechanisms of plasma non-transferrin bound iron (NTBI) generation may account for these differences. Markers of iron metabolism (plasma NTBI, labile iron, hepcidin, transferrin, monocyte SLC40A1 [ferroportin]), erythropoiesis (growth differentiation factor 15, soluble transferrin receptor) and tissue hypoxia (erythropoietin) were compared in patients with Thalassaemia Major (TM), Sickle Cell Disease and Diamond-Blackfan Anaemia (DBA), with matched transfusion histories. The most striking differences between these conditions were relationships of NTBI to erythropoietic markers, leading us to propose three mechanisms of NTBI generation: iron overload (all), ineffective erythropoiesis (predominantly TM) and low transferrin-iron utilization (DBA).

Anterior Pituitary Volume in Patients with Transfusion Dependent Anemias: Volumetric Approaches and Relation to Pituitary MRI­R2.

PURPOSE: Anterior pituitary iron overload and volume shrinkage is common in patients with transfusion-dependent anemia and associated with growth retardation and hypogonadotropic hypogonadism. We investigated the accuracy of different MRI-based pituitary volumetric approaches and the relationship between pituitary volume and MRI-R2, particularly with respect to growth and hypogonadism. METHODS: In 43 patients with transfusion-dependent anemia (12-38 years) and 32 healthy controls (12-72 years), anterior pituitary volume was measured by a sagittal T1 GRE 3D sequence at 1.5T and analyzed by 3D semi-automated threshold volumetry (3D-volumetry). This reference method was compared with planimetric 2D-volumetry, approximate volume calculations, and pituitary height. Using a multiple SE sequence, pituitary iron as MRI-R2 was assessed by fitting proton signal intensities to echo times. Growth and hypogonadism were obtained from height percentile tables and patients' medical charts. From body surface area and age adjusted anterior pituitary volumes of controls, Z­scores were calculated for all subjects. Separation of controls and patients with respect to Z and pituitary R2 was performed by bivariate linear discriminant analysis. RESULTS: Tuned 2D volumes showed highest agreement with reference 3D-volumes (bias -4.8%; 95% CI:-8.8%|-0.7%). A linear discriminant equation of Z = -17.8 + 1.45 · R2 revealed optimum threshold sensitivity and specificity of 65% and 100% for discrimination of patients from controls, respectively. Of correctly classified patients 71% and 75% showed hypogonadism and growth retardation, respectively. CONCLUSION: Accurate assessment of anterior pituitary size requires 3D or precise 2D volumetry, with shorter analysis time for the latter. Anterior pituitary volume Z­scores and R2 allow for the identification of patients at risk of pituitary dysfunction.