Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA.
Prostate. 2011 Dec;71(16):1759-67. doi: 10.1002/pros.21393. Epub 2011 Apr 25.
The electrical properties of prostate tissues are dependent on cellular morphology and have been demonstrated to distinguish between benign and malignant formations. Because Gleason grading is also based on tissue architecture we explored the hypothesis that the electrical properties might also provide discriminating power between high- and low-Gleason grade cancers.
Electrical properties (σ, ε, Δσ, σ(∞) , f(c) , and α) were gauged from 546 prostate tissue samples and correlated with histopathological assessment. Primary and secondary Gleason grades and a Gleason score were assigned to the tissues identified as cancer. We evaluated how well differently graded cancers were separable from benign tissues and from each other on the basis of these properties using ROC curves.
Of the 546 prostate tissue samples, 71 were identified as cancer and 465 as benign. ε, Δσ, σ(∞) , and f(c) provided the most discriminatory power with area under the curves (AUCs) ranging from 0.77-0.82 for detecting any cancer, 0.72-0.8 for low-grade cancer, and increasing to 0.87-0.9 for detecting high-grade cancer. Further, ε, Δσ, and σ(∞) , provided AUCs ranging from 0.74 to 0.75 for discriminating between low- and high-grade cancers.
Using the electrical properties to identify prostate cancer is improved when high-grade cancers are sought. These electrical properties can also discriminate between different grades of tumors. These findings suggest that technologies being developed to sense and image these properties in vivo may discriminate between aggressive and indolent lesions.
前列腺组织的电学特性取决于细胞形态,并且已经证明可以区分良性和恶性病变。由于 Gleason 分级也是基于组织结构,我们探讨了这样一个假设,即电学特性也可能为高低级 Gleason 分级癌症之间提供区分能力。
从 546 个前列腺组织样本中测量电学特性(σ、ε、Δσ、σ(∞)、f(c)和α),并与组织病理学评估相关联。将原发性和继发性 Gleason 分级以及 Gleason 评分分配给被识别为癌症的组织。我们评估了这些特性如何在不同分级的癌症与良性组织以及彼此之间的区分能力,使用 ROC 曲线。
在 546 个前列腺组织样本中,71 个被确定为癌症,465 个为良性。ε、Δσ、σ(∞)和 f(c)提供了最高的区分能力,曲线下面积(AUC)范围从 0.77-0.82 用于检测任何癌症,0.72-0.8 用于检测低级别癌症,并且增加到 0.87-0.9 用于检测高级别癌症。此外,ε、Δσ和 σ(∞)用于区分低级别和高级别癌症的 AUC 范围从 0.74 到 0.75。
当寻找高级别癌症时,使用电学特性来识别前列腺癌会得到改善。这些电学特性还可以区分不同级别的肿瘤。这些发现表明,正在开发用于在体内感测和成像这些特性的技术可能能够区分侵袭性和惰性病变。