Li Dan, Makeev Andrey, Glick Stephen J
Food and Drug Administration, Silver Spring, Maryland, United States.
J Med Imaging (Bellingham). 2023 Feb;10(Suppl 2):S22403. doi: 10.1117/1.JMI.10.S2.S22403. Epub 2023 Mar 10.
Differentiating between benign and malignant masses is one of the biggest challenges in breast imaging. The challenge is ingrained in the similarity of the attenuation coefficients between different types of lesion tissues and fibroglandular tissues. Contrast-enhanced imaging techniques can take advantage of the differing metabolism in different tissues, therefore, potentially allowing better differentiation of malignant and benign lesions. To facilitate the development and optimization of such technologies, we propose a fully digital 4D phantom that features time-varying enhancement patterns for different tissue types.
The 4D model is based on a static, anthropomorphic 3D digital breast phantom. Masses inserted into the 3D phantom are based on a previously published model. Physiological parameters that capture the key characteristics of masses, e.g., wash-in and wash-out rates indicating metabolic level, are employed in the model to simulate fundamental features for categorizing mass types. The two-compartmental model, a well-known model in the field of pharmacokinetics, is used to depict the diffusion process of the contrast agent. Two methods are proposed to allow for the simulations of lesions with necrotic cores of varying shapes and sizes.
The fourth dimension of the phantom models different time-varying enhancement patterns for different materials including fibroglandular tissue and lesion tissue. Metabolic characteristics of mass models can be adjusted to provide different enhancement patterns. The parameters of the 4D phantom can also be adjusted to fit different scenarios. The usage of the phantom is demonstrated by simulating mammograms at different time frames.
A 4D digital anthropomorphic breast phantom that models different time-varying contrast enhancement patterns is presented. This phantom could be an integral tool for use in trials to assess image quality of iodinated contrast-enhanced mammography, digital breast tomosynthesis, and breast computed tomography systems.
鉴别乳腺影像中良性和恶性肿块是最大的挑战之一。这一挑战源于不同类型病变组织与纤维腺组织之间衰减系数的相似性。因此，对比增强成像技术可利用不同组织中代谢差异，从而有可能更好地区分恶性和良性病变。为促进此类技术的开发与优化，我们提出一种全数字4D体模，其具有不同组织类型随时间变化的增强模式。
4D模型基于静态、拟人化的3D数字乳腺体模。插入3D体模的肿块基于先前发表的模型。模型采用捕捉肿块关键特征的生理参数，例如指示代谢水平的流入和流出率，来模拟用于分类肿块类型的基本特征。采用药代动力学领域知名的双室模型来描述造影剂的扩散过程。提出了两种方法来模拟具有不同形状和大小坏死核心的病变。
体模的第四维模拟了包括纤维腺组织和病变组织在内的不同材料随时间变化的增强模式。可调整肿块模型的代谢特征以提供不同的增强模式。还可调整4D体模的参数以适应不同场景。通过模拟不同时间帧的乳腺X线照片展示了体模的使用方法。
提出了一种模拟不同时间变化对比增强模式的4D数字拟人化乳腺体模。该体模可成为用于评估碘化对比增强乳腺X线摄影、数字乳腺断层合成和乳腺计算机断层扫描系统图像质量试验的重要工具。
