Evaluating the cancer detection and grading potential of prostatic-zinc imaging: a simulation study
Evaluating the cancer detection and grading potential of prostatic-zinc imaging: a simulation study
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DOI：
10.1088/0031-9155/54/3/020
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发表时间：
2009-02-07
影响因子：
3.5
通讯作者：
Fridman, E.
中科院分区：
文献类型：
--
作者：
Cortesi, M.;Chechik, R.;Fridman, E.
本文对前列腺锌浓度图像进行了分析。目标是评估可以从这些图像中提取的潜在临床相关信息。在没有实验图像的情况下，合成图像是根据临床测量的良性和癌症组织样本中的锌浓度分布产生的，按病变级别进行分类。我们描述了图像的产生方法，并对计数统计噪声的影响进行了建模。我们详细介绍了图像分析，它基于标准图像处理和分割工具的组合，针对这一特定应用进行了优化。从图像分析中获得的关于最低锌值的信息被转化为临床数据，例如肿瘤的存在、位置、大小和分级。他们的可信度是借助标准的统计工具，如接收器工作特性分析。目前的工作预测有可能检测(4+3)级以上的前列腺癌微小病变，具有非常好的特异性和敏感性。本分析进一步提供了经直肠探头要求的像素大小和图像计数统计数据，该探头将记录患者体内的前列腺锌图谱。
The present work deals with the analysis of prostatic-zinc-concentration images. The goal is to evaluate potential clinically relevant information that can be extracted from such images. In the absence of experimental images, synthetic ones are produced from clinically measured zinc-concentration distributions in certified benign and cancerous tissue samples, classified by the lesion grade. We describe the method for producing the images and model the effect of counting statistics noise. We present in detail the image analysis, which is based on a combination of standard image processing and segmentation tools, optimized for this particular application. The information on lowest zinc value obtained from the image analysis is translated to clinical data such as tumour presence, location, size and grade. Their confidence is evaluated with the help of standard statistical tools such as receiver operating characteristic analysis. The present work predicts a potential for detecting small prostate-cancer lesions, of grade (4+3) and above, with very good specificity and sensitivity. The present analysis further provides data on the pixel size and image counting statistics requested from the trans-rectal probe that will record in vivo prostatic-zinc maps in patients.