Halter Ryan J, Schned Alan, Heaney John, Hartov Alex, Paulsen Keith D
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA.
J Urol. 2009 Oct;182(4):1608-13. doi: 10.1016/j.juro.2009.06.013. Epub 2009 Aug 15.
The electrical properties of prostate tissues gauged at discrete frequencies provide sufficient contrast to discriminate malignant from benign prostatic tissues. The frequency dependence of these properties is also a function of tissue morphology. We evaluated the potential of this spectral dependence to provide additional diagnostic information for prostate cancer detection.
Electrical conductivity and permittivity were recorded from 50 ex vivo prostates at 31 logarithmically spaced frequencies of 100 Hz to 100 kHz. We used a well established, 4 parameter (sigma(infinity), Delta sigma, f(c) and alpha) model to describe individual spectra with each model parameter influenced by tissue morphology. We evaluated these parameters in terms of discriminatory power using ROC curves.
Of the 4 spectral parameters sigma(infinity) and f(c) were significantly greater in cancer than in benign tissues and Delta sigma was significantly more negative in cancer than in benign tissues (each p <0.0001). f(c) provided the maximum discriminating power with an ROC AUC of 0.821 and 81.5% specificity at 70% sensitivity. Also, sigma(infinity) and Delta sigma provided high levels of discrimination with an AUC of 0.770 and 0.782, respectively.
Spectral electrical admittivity properties provide sufficient levels of ex vivo cancer discrimination that may potentially enhance disease localization when prostate cancer is suspected. The development of novel technologies gauging these properties in vivo has the potential to provide new tissue characterizing tools for prostate cancer detection and identification.
在离散频率下测量的前列腺组织电特性提供了足够的对比度,以区分恶性前列腺组织和良性前列腺组织。这些特性的频率依赖性也是组织形态的函数。我们评估了这种光谱依赖性为前列腺癌检测提供额外诊断信息的潜力。
在100 Hz至100 kHz的31个对数间隔频率下,记录了50个离体前列腺的电导率和介电常数。我们使用一个成熟的四参数(σ(∞)、Δσ、fc和α)模型来描述个体光谱,每个模型参数都受组织形态的影响。我们使用ROC曲线评估这些参数的鉴别能力。
在这4个光谱参数中,癌症组织中的σ(∞)和fc显著高于良性组织,癌症组织中的Δσ显著低于良性组织(均p<0.0001)。fc提供了最大的鉴别能力,ROC曲线下面积(AUC)为0.821,在70%灵敏度下特异性为81.5%。此外,σ(∞)和Δσ也提供了较高的鉴别水平,AUC分别为0.770和0.782。
光谱电导率特性提供了足够的离体癌症鉴别水平,当怀疑有前列腺癌时,可能会增强疾病定位。开发在体内测量这些特性的新技术有可能为前列腺癌的检测和识别提供新的组织表征工具。