3D microwave tomography of the breast using prior anatomical information.
3D microwave tomography of the breast using prior anatomical information.
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使用先前的解剖信息对乳房进行 3D 微波断层扫描。
DOI：
10.1118/1.4944592
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发表时间：
2016
期刊：
影响因子：
3.8
通讯作者：
Paulsen,KeithD
中科院分区：
文献类型：
--
作者：
Golnabi,AmirH;Meaney,PaulM;Paulsen,KeithD
作者开发了一种新的乳房三维图像重建技术，该技术利用磁共振成像（MRI）的软组织空间分辨率，并结合微波成像的介电特性区分，产生双模态方法，目的是提高磁共振成像的特异性，可能不需要非特异性造影剂。集成是通过应用软先验正则化来完成的，该正则化导入从MR检查中生成的分割几何网格，并使用它来约束微波层析成像算法，以恢复这些内部子区域之间清晰描绘的分割区域内几乎均匀的属性分布。方法以往的研究表明，该方法在二维模拟和幻像实验以及临床检查中都是有效的。本研究将该算法扩展到三维空间，并对空间先验信息与实际数据在大小和位置上的不对准误差的敏感性和鲁棒性进行了深入分析。结果三维图像结果对重建网格密度的依赖性不强，目标区域大小变化大于125%，恢复属性值变化小于30%，这一结果比二维图像结果更具鲁棒性。同样，在3D图像中发生的小于13%的变化是由于近90%的包含物大小的目标位置变化造成的。在实际幻影实验中，采用三维空间先验算法的介电常数和电导率误差分别比不使用先验算法的误差小约5倍和2倍。本研究证实，以软约束的形式结合结构信息可以大大提高预定义感兴趣区域的属性估计的准确性。这些发现令人鼓舞，并为在临床研究中使用软先验技术奠定了坚实的基础，在临床研究中，他们的微波成像系统和MRI可以同时收集患者的乳房检查数据。
PurposeThe authors have developed a new 3D breast image reconstruction technique that utilizes the soft tissue spatial resolution of magnetic resonance imaging (MRI) and integrates the dielectric property differentiation from microwave imaging to produce a dual modality approach with the goal of augmenting the specificity of MR imaging, possibly without the need for nonspecific contrast agents. The integration is performed through the application of a soft prior regularization which imports segmented geometric meshes generated from MR exams and uses it to constrain the microwave tomography algorithm to recover nearly uniform property distributions within segmented regions with sharp delineation between these internal subzones.MethodsPrevious investigations have demonstrated that this approach is effective in 2D simulation and phantom experiments and also in clinical exams. The current study extends the algorithm to 3D and provides a thorough analysis of the sensitivity and robustness to misalignment errors in size and location between the spatial prior information and the actual data.ResultsImage results in 3D were not strongly dependent on reconstruction mesh density, and the changes of less than 30% in recovered property values arose from variations of more than 125% in target region size—an outcome which was more robust than in 2D. Similarly, changes of less than 13% occurred in the 3D image results from variations in target location of nearly 90% of the inclusion size. Permittivity and conductivity errors were about 5 times and 2 times smaller, respectively, with the 3D spatial prior algorithm in actual phantom experiments than those which occurred without priors.ConclusionsThe presented study confirms that the incorporation of structural information in the form of a soft constraint can considerably improve the accuracy of the property estimates in predefined regions of interest. These findings are encouraging and establish a strong foundation for using the soft prior technique in clinical studies, where their microwave imaging system and MRI can simultaneously collect breast exam data in patients.