Prostate Cancer Detection Using Composite Impedance Metric.
Prostate Cancer Detection Using Composite Impedance Metric.
复制标题
DOI：
10.1109/tmi.2016.2578939
复制
发表时间：
2016-12
影响因子：
10.6
通讯作者：
Halter RJ
中科院分区：
文献类型：
--
作者：
Khan S;Mahara A;Hyams ES;Schned AR;Halter RJ
前列腺癌（PCa）复发通常通过评估手术切缘（SM）的状态来预测-阳性手术切缘（PSM）使生化复发的机会增加2-4倍，这可能导致PCa复发。为此，在人前列腺的离体研究中采用具有显微内窥镜探针的电阻抗采集系统。该系统测量频率范围（1 kHz至1 MHz）内的组织生物阻抗，并计算复合阻抗（CIM）的数量。使用CIM数据训练的分类器可以用于将组织分类为良性或癌性。该系统被用来收集阻抗谱从14个切除的前列腺，这是从男性接受根治性前列腺切除术，共23癌和53良性测量。数据显示，良性和肿瘤组织的阻抗特性以及前列腺顶面、底面和侧面的测量值之间存在统计学显著差异（p<0.05）。此外，在留一患者交叉验证中，通过结合高频CIM相位数据来训练具有径向基函数核的支持向量机分类器，实现了90.79%的最大预测准确度。观察结果与良性和恶性前列腺组织的生理学和形态学一致。发现CIM是区分良性组织和癌性组织的有效工具。
Prostate cancer (PCa) recurrences are often predicted by assessing the status of surgical margins (SM) – positive surgical margins (PSM) increase the chances of biochemical recurrence by 2–4 times which may lead to PCa recurrence. To this end, an electrical impedance acquisition system with a microendoscopic probe was employed in an ex-vivo study of human prostates. This system measures the tissue bioimpedance over a range of frequencies (1 kHz to 1MHz), and computes a number of Composite Impedance Metrics (CIM). A classifier trained using CIM data can be used to classify tissue as benign or cancerous. The system was used to collect the impedance spectra from 14 excised prostates, which were obtained from men undergoing radical prostatectomy, for a total of 23 cancerous and 53 benign measurements. The data revealed statistically significant (p<0.05) differences in the impedance properties of the benign and tumorous tissues, and among the measurements taken on the apical, base, and lateral surface of the prostate. Further, in the leave-one-patient-out cross validation, a maximum predictive accuracy of 90.79% was achieved by combining high frequency CIM phase data to train a support vector machine classifier with a radial basis function kernel. The observations are consistent with the physiology and morphology of benign and malignant prostate tissue. CIMs were found to be an effective tool in distinguishing benign from cancerous tissues.