An MRI cardiac magnetic susceptometry (MRI-CS) technique for assessing cardiac tissue iron concentration based on phase mapping was developed. Normal control subjects (n=9) and thalassemia patients (n = 13) receiving long-term blood transfusion therapy underwent MRI-CS and MRI measurements of the cardiac relaxation rate R2*. Using MRI-CS, subepicardium and subendocardium iron concentrations were quantified exploiting the hemosiderin/ferritin iron specific magnetic susceptibility. The average of subepicardium and subendocardium iron concentrations and R2* of the septum were found to be strongly correlated (r=0.96, p<0.0001), and linear regression analysis yielded CIC (μg Fe/g wet tissue ) = (6.4 ± 0.4) · R2* septum (s -1 ) -(120 ± 40). The results demonstrated that septal R2* indeed measures cardiac iron level.

In this study, the authors examined a possible role of measurements of end-tidal carbon monoxide (CO), corrected for inhaled CO (ETCOc), as a noninvasive screening tool for hemoglobinopathies and as an indicator for when transfusions would be required in patients receiving chronic transfusions. ETCOc measurements were obtained in subjects with sickle cell disease (n = 18), thalassemia (n = 21), and healthy controls (n = 62). ETCOc values less than 3 parts per million (ppm) yielded a positive predictive value of 93% and negative predictive value of 94% in identifying hemoglobinopathies. Subsequently, 7 subjects with thalassemia had laboratory parameters and ETCOc measured over 2 transfusion cycles. ETCOc values were 4.90 +/- 0.32 ppm (mean +/- SD), with 89% of values being above normal (>or=3 ppm). Pretransfusion ETCOc levels significantly correlated with pretransfusion reticulocyte count (r = .96, P <.001), but not with pretransfusion hemoglobin (r = .44, P = .16) or pretransfusion soluble transferrin receptors (sTfR, r = .52, P = .10). In conclusion, we found that patients with hemoglobinopathies have ETCOc values above the range for healthy controls and ETCOc measurements can be used as an adjunct to hemoglobin measurements to determine the proper timing of transfusions.

These data indicate that alterations in iron metabolism are common even in the HAART era and warrant further study to identify individuals at risk for these alterations.

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, Z‑scores 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 Z‑scores and R2 allow for the identification of patients at risk of pituitary dysfunction.