THE INCIDENCE OF BREAST CANCER patients with brain metastases is increasing (1
). This is due in part to the pharmaceutical focus on development of therapeutic agents that successfully treat systemic, but not brain metastases. Still, the median survival time with aggressive treatment is extended by only 4–12 months.
To study the mechanisms of breast cancer metastasis to the brain, mouse models have been developed using human breast cancer cell lines (3
). Histology, immunohistochemistry, and microscopy are typically used to estimate the numbers and the cross-sectional area of metastases, and for analysis of cellular markers (5
). The limitations of these methods are the need to sacrifice the animal, allowing only an endpoint analysis, and the small subset of tissue volume assessed.
Microimaging technologies, including high-resolution magnetic resonance imaging (MRI), micro-computed tomography, and positron emission tomography have shown great utility for characterizing small-animal models of disease. MRI is particularly well suited for studies of brain metastasis because it is noninvasive, three-dimensional, has excellent soft-tissue contrast, and no limitation in depth of penetration at clinical magnetic field strengths.
Cellular MRI combines the use of high-resolution MRI with cell labels to track cells of interest. The most commonly used labels are iron-based nanoparticles including superparamagnetic, ultrasmall, and micron-sized iron oxide particles (MPIO). Stem cells (8
), macrophages (9
), dendritic cells (10
), cancer cells (11
), and lymphocytes (12
) have been tracked in vivo with MRI using this approach. The presence of the label causes a distortion in the magnetic field and leads to abnormal signal hypointensities in iron-sensitive images.
Most studies have employed T2
w) spin echo, and T2
*-weighted gradient echo sequences to detect iron-labeled cells. The balanced steady-state free precession (b-SSFP) imaging sequence has been used to detect single iron-labeled macrophages and cancer cells in vivo as signal voids in the mouse brain (11
). The major advantage of the b-SSFP sequence is its high signal-to-noise ratio (SNR) efficiency, allowing for imaging at high spatial resolution in reasonable scan times (14
). Another important feature of b-SSFP is its high sensitivity to magnetic field inhomogeneities (15
Miraux et al (17
) also investigated the b-SSFP sequence on mouse brains at 4.7 and 9.4 T. They compared b-SSFP images of implanted gliomas with T2
w SE images, the most commonly employed contrast for the visualization of brain tumors in mice. At 4.7 T the SNR and brain-to-tumor contrast-to-noise ratio (CNR) were comparable in b-SSFP and T2
w images, but the scan time was ≈4 times shorter with b-SSFP. At 9.4 T, the CNR was attenuated and tumors were barely visible.
Bernas et al (18
) developed a b-SSFP protocol at 3 T to optimally visualize iron-loaded glioma in the mouse brain. This protocol consists of a set of two b-SSFP image acquisitions with complementary contrasts, allowing delineation of tumors, which appear as regions of signal hyperintensity due to longer T2
of tumor tissue compared to brain parenchyma, and providing high sensitivity to iron-labeled cells, which are detected as regions of signal void.
The purpose of this study was to optimize b-SSFP at 1.5 T with the goal of generating image contrast for the simultaneous detection of single iron-labeled cancer cells and brain tumors in vivo in one scan. A single scan would reduce the acquisition time and allow for monitoring of both nonproliferative cancer cells and developing metastases. For this purpose, MPIO-labeled cancer cells were injected into the left ventricle of the heart in nude mice. After intracardiac injection, cells become trapped in the brain microvasculature. With time, some cancer cells proliferate into metastases that appear as regions of signal hyperintensity in b-SSFP images, primarily due to increased T2
relaxation, while other cells remain dormant (nonproliferative) and are detected as persistent signal voids (11