基于超声的前列腺癌特征分析：一项体内临床可行性研究。
Ultrasound-based characterization of prostate cancer: an in vivo clinical feasibility study.
作者信息
Imani Farhad, Abolmaesumi Purang, Gibson Eli, Galesh-Khale Amir Khojaste, Gaed Mena, Moussa Madeleine, Gomez Jose A, Romagnoli Cesare, Siemens D Robert, Leviridge Michael, Chang Silvia, Fenster Aaron, Ward Aaron D, Mousavi Parvin
机构信息
Queen's University, Kingston, Ontario, Canada.
The University of British Columbia, Vancouver, British Columbia, Canada.
出版信息
Med Image Comput Comput Assist Interv. 2013;16(Pt 2):279-86. doi: 10.1007/978-3-642-40763-5_35.
UNLABELLED
This paper presents the results of an in vivo clinical study to accurately characterize prostate cancer using new features of ultrasound RF time series.
METHODS
The mean central frequency and wavelet features of ultrasound RF time series from seven patients are used along with an elaborate framework of ultrasound to histology registration to identify and verify cancer in prostate tissue regions as small as 1.7 mm x 1.7 mm.
RESULTS
In a leave-one-patient-out cross-validation strategy, an average classification accuracy of 76% and the area under ROC curve of 0.83 are achieved using two proposed RF time series features. The results statistically significantly outperform those achieved by previously reported features in the literature. The proposed features show the clinical relevance of RF time series for in vivo characterization of cancer.
未标注
本文展示了一项体内临床研究的结果，该研究旨在利用超声射频时间序列的新特征准确表征前列腺癌。
方法
使用了来自7名患者的超声射频时间序列的平均中心频率和小波特征，并结合一个精心构建的超声与组织学配准框架，以识别和验证前列腺组织区域中低至1.7毫米×1.7毫米的癌症。
结果
在留一患者交叉验证策略中，使用两个提出的射频时间序列特征实现了平均分类准确率为76%，ROC曲线下面积为0.83。结果在统计学上显著优于文献中先前报道的特征所取得的结果。所提出的特征显示了射频时间序列在体内癌症表征方面的临床相关性。
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