Schalk Stefan G, Demi Libertario, Bouhouch Nabil, Kuenen Maarten P J, Postema Arnoud W, de la Rosette Jean J M C H, Wijkstra Hessel, Tjalkens Tjalling J, Mischi Massimo
IEEE Trans Biomed Eng. 2017 Mar;64(3):661-670. doi: 10.1109/TBME.2016.2571624. Epub 2016 May 20.
The role of angiogenesis in cancer growth has stimulated research aimed at noninvasive cancer detection by blood perfusion imaging. Recently, contrast ultrasound dispersion imaging was proposed as an alternative method for angiogenesis imaging. After the intravenous injection of an ultrasound-contrast-agent bolus, dispersion can be indirectly estimated from the local similarity between neighboring time-intensity curves (TICs) measured by ultrasound imaging. Up until now, only linear similarity measures have been investigated. Motivated by the promising results of this approach in prostate cancer (PCa), we developed a novel dispersion estimation method based on mutual information, thus including nonlinear similarity, to further improve its ability to localize PCa.
First, a simulation study was performed to establish the theoretical link between dispersion and mutual information. Next, the method's ability to localize PCa was validated in vivo in 23 patients (58 datasets) referred for radical prostatectomy by comparison with histology.
A monotonic relationship between dispersion and mutual information was demonstrated. The in vivo study resulted in a receiver operating characteristic (ROC) curve area equal to 0.77, which was superior (p = 0.21-0.24) to that obtained by linear similarity measures (0.74-0.75) and (p <; 0.05) to that by conventional perfusion parameters (≤0.70).
Mutual information between neighboring time-intensity curves can be used to indirectly estimate contrast dispersion and can lead to more accurate PCa localization.
An improved PCa localization method can possibly lead to better grading and staging of tumors, and support focal-treatment guidance. Moreover, future employment of the method in other types of angiogenic cancer can be considered.
血管生成在癌症生长中的作用激发了旨在通过血液灌注成像进行无创癌症检测的研究。最近，对比超声散斑成像被提出作为血管生成成像的一种替代方法。静脉注射超声造影剂团注后，可通过超声成像测量的相邻时间 - 强度曲线（TIC）之间的局部相似性间接估计散斑。到目前为止，仅研究了线性相似性度量。受该方法在前列腺癌（PCa）中取得的有前景结果的启发，我们开发了一种基于互信息的新型散斑估计方法，从而纳入非线性相似性，以进一步提高其定位PCa的能力。
首先，进行了一项模拟研究以建立散斑与互信息之间的理论联系。接下来，通过与组织学比较，在23例接受根治性前列腺切除术的患者（58个数据集）中对该方法定位PCa的能力进行了体内验证。
证明了散斑与互信息之间存在单调关系。体内研究得出的受试者操作特征（ROC）曲线面积等于0.77，优于（p = 0.21 - 0.24）通过线性相似性度量获得的结果（0.74 - 0.75），且（p < 0.05）优于传统灌注参数的结果（≤0.70）。
相邻时间 - 强度曲线之间的互信息可用于间接估计对比散斑，并可导致更准确的PCa定位。
一种改进的PCa定位方法可能会带来更好的肿瘤分级和分期，并支持局部治疗指导。此外，可以考虑该方法未来在其他类型血管生成性癌症中的应用。
