Department of Computer Science, University of Verona, Str. le Grazie 15, Verona, Italy.
INRIA, Strasbourg, France.
Int J Comput Assist Radiol Surg. 2019 Aug;14(8):1329-1339. doi: 10.1007/s11548-019-01997-z. Epub 2019 Jun 3.
Although ultrasound (US) images represent the most popular modality for guiding breast biopsy, malignant regions are often missed by sonography, thus preventing accurate lesion localization which is essential for a successful procedure. Biomechanical models can support the localization of suspicious areas identified on a preoperative image during US scanning since they are able to account for anatomical deformations resulting from US probe pressure. We propose a deformation model which relies on position-based dynamics (PBD) approach to predict the displacement of internal targets induced by probe interaction during US acquisition.
The PBD implementation available in NVIDIA FleX is exploited to create an anatomical model capable of deforming online. Simulation parameters are initialized on a calibration phantom under different levels of probe-induced deformations; then, they are fine-tuned by minimizing the localization error of a US-visible landmark of a realistic breast phantom. The updated model is used to estimate the displacement of other internal lesions due to probe-tissue interaction.
The localization error obtained when applying the PBD model remains below 11 mm for all the tumors even for input displacements in the order of 30 mm. This proposed method obtains results aligned with FE models with faster computational performance, suitable for real-time applications. In addition, it outperforms rigid model used to track lesion position in US-guided breast biopsies, at least halving the localization error for all the displacement ranges considered.
Position-based dynamics approach has proved to be successful in modeling breast tissue deformations during US acquisition. Its stability, accuracy and real-time performance make such model suitable for tracking lesions displacement during US-guided breast biopsy.
尽管超声(US)图像是引导乳房活检最常用的方式,但超声往往会错过恶性区域,从而无法准确定位病变,这对于手术的成功至关重要。生物力学模型可以支持在 US 扫描期间对术前图像上识别出的可疑区域进行定位,因为它们能够解释由于 US 探头压力引起的解剖变形。我们提出了一种依赖于基于位置的动力学(PBD)方法的变形模型,以预测 US 采集期间探头相互作用引起的内部目标的位移。
利用 NVIDIA FleX 中提供的 PBD 实现来创建能够在线变形的解剖模型。在不同的探头变形水平下,对校准体模进行仿真参数初始化;然后,通过最小化真实乳房体模的 US 可见标志的定位误差来对其进行微调。使用更新后的模型来估计由于探头-组织相互作用而导致的其他内部病变的位移。
当应用 PBD 模型时,即使在输入位移达到 30mm 左右的情况下,所有肿瘤的定位误差仍保持在 11mm 以下。与具有更快计算性能的 FE 模型相比,该方法获得的结果更准确,适用于实时应用。此外,它优于用于在 US 引导下进行乳房活检中跟踪病变位置的刚性模型,在考虑的所有位移范围内,至少将定位误差减半。
基于位置的动力学方法已被证明可成功地模拟 US 采集期间乳房组织的变形。其稳定性、准确性和实时性能使该模型适用于跟踪 US 引导下乳房活检中病变的位移。