Background-Microcomputed tomography (micro-CT) has been used extensively in research to generate high-resolution 3D images of calcified tissues in small animals nondestructively. It has been especially useful for the characterization of skeletal mutations but limited in its utility for the analysis of soft tissue such as the cardiovascular system. Visualization of the cardiovascular system has been largely restricted to structures that can be filled with radiopaque intravascular contrast agents in adult animals. Recent ex vivo studies using osmium tetroxide, iodinated contrast agents, inorganic iodine, and phosphotungstic acid have demonstrated the ability to stain soft tissues differentially, allowing for high intertissue contrast in micro-CT images. In the present study, we demonstrate the application of this technology for visualization of cardiovascular structures in developing mouse embryos using Lugol solution (aqueous potassium iodide plus iodine). Methods and Results-We show the optimization of this method to obtain ex vivo micro-CT images of embryonic and neonatal mice with excellent soft-tissue contrast. We demonstrate the utility of this method to visualize key structures during cardiovascular development at various stages of embryogenesis. Our method benefits from the ease of sample preparation, low toxicity, and low cost. Furthermore, we show how multiple cardiac defects can be demonstrated by micro-CT in a single specimen with a known genetic lesion. Indeed, a previously undescribed cardiac venous abnormality is revealed in a PlexinD1 mutant mouse. Conclusions-Micro-CT of iodine-stained tissue is a valuable technique for the characterization of cardiovascular development and defects in mouse models of congenital heart disease. (Circ Cardiovasc Imaging. 2010;3:314-322.)Key Words: micro-CT Ⅲ iodine Ⅲ mouse Ⅲ development Ⅲ PlexinD1 Ⅲ congenital heart disease T he ability to genetically manipulate the mouse has resulted in a powerful model system for the investigation of many disease processes. In particular, genetic studies in the mouse have enhanced our understanding of embryonic development, and by extension, of congenital defects. In humans, cardiac defects are the most common serious anomalies among live births with an estimated frequency of 0.6%. 1 Numerous mouse models of congenital heart disease have been generated and characterized, adding greater insight into the molecular and cellular origins of these defects. 2 In addition, current research in the area of targeted gene deletions holds great promise to further elucidate mechanisms of cardiac development. Editorial see p 228 Clinical Perspective on p 322Although structurally similar to the human, the significantly reduced size of the murine cardiovascular system presents a number of technical challenges when attempting to stage anatomic features such as vascular structures. Identification and characterization of the phenotype of cardiovascular defects in mice traditionally has relied on histological analysis of sectioned specimens. Histology,...

Purpose The purpose of this work was to develop and demonstrate feasibility and initial clinical validation of quantitative susceptibility mapping (QSM) in the abdomen as an imaging biomarker of hepatic iron overload. Theory In general, QSM is faced with the challenges of background field removal and dipole inversion. Respiratory motion, the presence of fat, and severe iron overload further complicate QSM in the abdomen. We propose a technique for QSM in the abdomen that addresses these challenges. Methods Data were acquired from 10 subjects without hepatic iron overload and 33 subjects with known or suspected iron overload. The proposed technique was used to estimate the susceptibility map in the abdomen, from which hepatic iron overload was measured. As a reference, spin-echo data were acquired for R2-based LIC estimation. Liver R2* was measured for correlation with liver susceptibility estimates. Results Correlation between susceptibility and R2-based LIC estimation was R2 = 0.76 at 1.5T and R2 = 0.83 at 3T. Further, high correlation between liver susceptibility and liver R2* (R2 = 0.94 at 1.5T; R2 = 0.93 at 3T) was observed. Conclusion We have developed and demonstrated initial validation of QSM in the abdomen as an imaging biomarker of hepatic iron overload.

Purpose To compare the performance of fat fraction quantification using single-R2* and dual-R2* correction methods in patients with fatty liver, using MR spectroscopy (MRS) as the reference standard. Materials and Methods From a group of 97 patients, 32 patients with hepatic fat fraction greater than 5%, as measured by MRS, were identified. In these patients, chemical shift encoded fat-water imaging was performed, covering the entire liver in a single breath-hold. Fat fraction was measured from the imaging data by post-processing using 6 different models: single- and dual-R2* correction, each performed with complex fitting, magnitude fitting and mixed magnitude/complex fitting to compare the effects of phase error correction. Fat fraction measurements were compared to co-registered spectroscopy measurements using linear regression. Results Linear regression demonstrated higher agreement with MRS using single-R2* correction compared with dual-R2* correction. Among single-R2* models, all 3 fittings methods performed similarly well (slope = 1.0 ± 0.06, r2=0.89–0.91). Conclusion Single-R2* modeling is more accurate than dual-R2* modeling for hepatic fat quantification in patients, even in those with high hepatic fat concentrations.

Purpose To evaluate the accuracy of R2* models (1/T2* = R2*) for chemical shift-encoded magnetic resonance imaging (CSE-MRI)-based proton density fat-fraction (PDFF) quantification in patients with fatty liver and iron overload, using MR spectroscopy (MRS) as the reference standard. Materials and Methods Two Monte Carlo simulations were implemented to compare the root-mean-squared-error (RMSE) performance of single-R2* and dual-R2* correction in a theoretical liver environment with high iron. Fatty liver was defined as hepatic PDFF >5.6% based on MRS; only subjects with fatty liver were considered for analyses involving fat. From a group of 40 patients with known/suspected iron overload, nine patients were identified at 1.5T, and 13 at 3.0T with fatty liver. MRS linewidth measurements were used to estimate R2* values for water and fat peaks. PDFF was measured from CSE-MRI data using single-R2* and dual-R2* correction with magnitude and complex fitting. Results Spectroscopy-based R2* analysis demonstrated that the R2* of water and fat remain close in value, both increasing as iron overload increases: linear regression between R2*W and R2*F resulted in slope = 0.95 [0.79–1.12] (95% limits of agreement) at 1.5T and slope = 0.76 [0.49–1.03] at 3.0T. MRI-PDFF using dual-R2* correction had severe artifacts. MRI-PDFF using single-R2* correction had good agreement with MRS-PDFF: Bland–Altman analysis resulted in −0.7% (bias) ± 2.9% (95% limits of agreement) for magnitude-fit and −1.3% ± 4.3% for complex-fit at 1.5T, and −1.5% ± 8.4% for magnitude-fit and −2.2% ± 9.6% for complex-fit at 3.0T. Conclusion Single-R2* modeling enables accurate PDFF quantification, even in patients with iron overload.