Introduction
Non-invasive in vivo cellular imaging with MRI has greatly broadened our understanding in many cellular and molecular processes, as well as in monitoring stem cell therapy. The target cells can be made MRI-detectable by labeling them with iron-oxide contrast agents, such as micrometer-sized-iron-oxide (MPIO) particles. With sufficient iron loading per cell, it is possible to detect single cells in vivo with MRI. However, motion artifacts and the need for gated acquisition have made imaging cells in the heart more challenging and time-consuming. The goal of this study is to develop a strategy to enable real-time imaging of individual labeled cells without the need for a gated or breath-hold protocol. To this end, we have implemented a new model-based imaging scheme for high-resolution free-breathing imaging, using the Partially Separable Function (PSF) model.
Methods
1. Model system
We use a rodent abdominal heterotopic working heart and lung transplantation model with DA to BN rat pair, using BN-to-BN transplantation as isograft controls.
2. Iron oxide particle labeling
Immune cells, mostly macrophages, were labeled in vivo by direct intravenous injection of 3 mg micrometer-sized-iron-oxide (MPIO) particles 1 day prior to MRI scans.
3. MRI protocols
Real-time free-breathing imaging, and ECG and respiration gated T2* and cine imaging were performed using a Bruker AVANCE 4.7-T system with a home-built 5.5 cm surface coil and an in-plane resolution of 195 μm.
4. Partially Separable Function (PSF) method and theory
The PSF model approximates the hypersurface, d(k, t), formed by the time varying data as a summation of M simpler functions that are each the product of one-dimensional functions αm(k) and ϕm(t), and recent results have shown that cardiac imaging with breathing exists in a low rank space where M = 16. Data collection consists of interleaving two scans: (i) a high temporal resolution data set for estimating {ϕm(t)}Mm = 1 and (ii) a high spatial resolution scan used to estimate {αm(k)}Mm = 1. The low rank of the model allows for temporal interpolation over time intervals failing the Nyquist criterion thereby avoiding the need to time data collection with the cardiac and respiratory motions.
Results
We have used a rodent heterotopic transplantation model for tracking labeled immune cells in vivo. In this model, immune cells, mostly macrophages, can be labeled in vivo by direct intravenous administration of MPIO particles; labeled immune cells then migrate to the rejecting transplanted hearts and are detected by T2*-weighted imaging. Low-dosage MPIO particles are used in this study for sparse labeling of macrophages to promote the visualization of single cells, even though the images lack the necessary spatial resolution by at least a factor of 4.
Without gating, real-time free-breathing MRI results in blurring due to motion artifacts (Fig. 1A). The model-based data collection and reconstruction scheme (Fig. 1B) yields a high-quality image comparable to ECG-and-respiration-gated cine imaging (Fig 1C), however in a much shorter acquisition time. The model-based method enables identification of MPIO-labeled cells in vivo (Fig. 1D) in real-time data acquisition. The model-based method acquires data continuously whereas the gated scheme collects data intermittently, depending upon the relationship of the ECG and respiratory signals. In addition to a shorter acquisition time, the continuous model-based scheme preserves all information in the k-t space, which is especially important in functional evaluation of the diseased conditions with arrhythmia or compromised breath-holding.
Figure 1. (A) Fourier reconstruction of free-breathing MRI. (B) Model-based reconstruction of the same free-breathing MRI. (C) ECG-and-respiration-gated
cine imaging for comparison. (D) Enlarged view of the heart showing the infiltrated
MPIO-labeled cells.
Conclusion
The model-based imaging scheme allows real-time free-breathing imaging with resolution and image quality sufficient for tracking labeled cells in vivo in beating hearts.
References
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Magn Reson Med. 2006, 55:242-9. PubMed Abstract | Publisher Full Text
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Proc Natl Acad Sci. 2006, 103:1852-7. PubMed Abstract | Publisher Full Text | PubMed Central Full Text




