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首页> 外文期刊>Contrast media & molecular imaging >Quantification of Nanoparticle Enhancement in Polarized Breast Tumor Macrophage Deposits by Spatial Analysis of MRI and Histological Iron Contrast Using Computer Vision
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Quantification of Nanoparticle Enhancement in Polarized Breast Tumor Macrophage Deposits by Spatial Analysis of MRI and Histological Iron Contrast Using Computer Vision

机译：通过使用计算机视觉的MRI和组织学铁对比的空间分析，对极化的乳腺肿瘤巨噬细胞沉积物中的纳米颗粒增强进行定量

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Magnetic resonance imaging applications utilizing nanoparticle agents for polarized macrophage detection are conventionally analyzed according to iron-dependent parameters averaged over large regions of interest (ROI). However, contributions from macrophage iron deposits are usually obscured in these analyses due to their lower spatial frequency and smaller population size compared with the bulk of the tumor tissue. We hypothesized that, by addressing MRI and histological pixel contrast heterogeneity using computer vision image analysis approaches rather than statistical ROI distribution averages, we could enhance our ability to characterize deposits of polarized tumor-associated macrophages (TAMs). We tested this approach using in vivo iron MRI (FeMRI) and histological detection of macrophage iron in control and ultrasmall superparamagnetic iron oxide (USPIO) enhanced mouse models of breast cancer. Automated spatial profiling of the number and size of iron-containing macrophage deposits according to localized high-iron FeMRI or Prussian blue pixel clustering performed better than using distribution averages to evaluate the effects of contrast agent injections. This analysis was extended to characterize subpixel contributions to the localized FeMRI measurements with histology that confirmed the association of endogenous and nanoparticle-enhanced iron deposits with macrophages in vascular regions and further allowed us to define the polarization status of the macrophage iron deposits detected by MRI. These imaging studies demonstrate that characterization of TAMs in breast cancer models can be improved by focusing on spatial distributions of iron deposits rather than ROI averages and indicate that nanoparticle uptake is dependent on the polarization status of the macrophage populations. These findings have broad implications for nanoparticle-enhanced biomedical imaging especially in cancer.
机译：常规地，根据在大的感兴趣区域（ROI）上平均的铁依赖性参数来分析利用纳米粒子试剂用于极化巨噬细胞检测的磁共振成像应用。但是，由于巨噬细胞铁沉积物的空间频率较低且与肿瘤组织的体积相比较小，因此通常在这些分析中无法确定其贡献。我们假设，通过使用计算机视觉图像分析方法而非统计ROI分布平均值来解决MRI和组织学像素对比度的异质性，我们可以增强表征极化肿瘤相关巨噬细胞（TAM）沉积的能力。我们在体内对照和超小型超顺磁性氧化铁（USPIO）增强的乳腺癌小鼠模型中使用体内铁MRI（FeMRI）和组织学检测巨噬细胞铁测试了该方法。根据局部高铁FeMRI或普鲁士蓝像素聚类对含铁巨噬细胞沉积物的数量和大小进行自动空间分布分析，其效果要好于使用平均分布来评估造影剂注射的效果。扩展了该分析以通过组织学表征亚像素对局部FeMRI测量的贡献，该组织学证实了内源性和纳米颗粒增强的铁沉积物与血管区域巨噬细胞的关联，并且进一步使我们能够定义MRI检测到的巨噬细胞铁沉积物的极化状态。这些影像学研究表明，通过关注铁沉积物的空间分布而不是ROI平均值，可以改善乳腺癌模型中TAM的表征，并表明纳米颗粒的摄取取决于巨噬细胞群体的极化状态。这些发现对纳米颗粒增强的生物医学成像尤其是在癌症中具有广泛的意义。

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