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Assessment of fiberoptic near-infrared raman spectroscopy for diagnosis of bladder and prostate cancer.

机译:评估光纤近红外拉曼光谱对膀胱癌和前列腺癌的诊断。

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OBJECTIVES: To determine whether a fiberoptic Raman system, suitable for in vivo use, is able to differentiate between benign and malignant bladder and prostate pathologic findings in vitro. Raman spectroscopy is an optical technique that provides a measure of the molecular composition of tissue by analyzing the way that tissue scatters laser light. Laboratory studies have shown that the technique can be used to identify and characterize transitional cell carcinoma and prostate adenocarcinoma in vitro. METHODS: A total of 220 Raman spectra were recorded from 29 snap-frozen bladder samples collected at cystoscopic procedures, and 197 Raman spectra were recorded from 38 snap-frozen prostate samples collected at transurethral resection of the prostate. The spectra were correlated with the histologic features and used to construct separate diagnostic algorithms for the bladder and prostate. These algorithms were tested as to their ability to determine the pathologic finding of a sample from its Raman spectrum. RESULTS: The bladder algorithm was able to differentiate benign samples (normal and cystitis) from malignant samples (transitional cell carcinoma), with an overall accuracy of 84%. The prostate algorithm was able to differentiate benign samples (benign prostatic hyperplasia and prostatitis) from malignant samples (prostate cancer), with an overall accuracy of 86%. CONCLUSIONS: The results of this study have demonstrated that the clinical Raman system can provide an accurate and objective method to diagnose prostate and bladder cancer in vitro. Because the Raman probe is suitable for use during endoscopic, laparoscopic, or open procedures, this work paves the way for in vivo studies.
机译:目的:确定适合体内使用的光纤拉曼系统是否能够在体外区分良性和恶性膀胱及前列腺病理结果。拉曼光谱法是一种光学技术,通过分析组织散射激光的方式来提供对组织分子组成的测量。实验室研究表明,该技术可用于体外鉴定和表征移行细胞癌和前列腺腺癌。方法:在膀胱镜下收集的29份速冻膀胱样本中共记录了220个拉曼光谱,并从经尿道前列腺电切术收集的38份速冻前列腺样本中记录了197个拉曼光谱。光谱与组织学特征相关,并用于构建膀胱和前列腺的独立诊断算法。对这些算法从拉曼光谱确定样本病理发现的能力进行了测试。结果:膀胱算法能够区分良性样本(正常和膀胱炎)与恶性样本(过渡细胞癌),总准确度为84%。前列腺算法能够区分良性样本(良性前列腺增生和前列腺炎)与恶性样本(前列腺癌),总准确度为86%。结论:本研究结果表明,临床拉曼系统可为体外诊断前列腺癌和膀胱癌提供准确,客观的方法。由于拉曼探针适用于内窥镜,腹腔镜或开放手术,因此这项工作为体内研究铺平了道路。

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