Chen Shuo, Zhu Shanshan, Cui Xiaoyu, Xu Wenbin, Kong Chuize, Zhang Zhe, Qian Wei
Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110169, China.
Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, China.
Biomed Opt Express. 2019 Jun 24;10(7):3533-3544. doi: 10.1364/BOE.10.003533. eCollection 2019 Jul 1.
The assessment of the muscle invasion of bladder cancer typically plays a crucial role in therapeutic decision-making and has significant impacts on the recurrence rate and survival rate. Although histopathology is sufficiently accurate and usually served as the gold standard for bladder cancer diagnosis, it is invasive, time-consuming, and requires intensive sample preparation by a well-trained pathologist to achieve an optimal diagnosis. Therefore, a fast and noninvasive method to accurately identify non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is in demand. In this study, the SERS technique combined with the PLS-LDA method based on a small amount of blood serum samples is employed to distinguish healthy volunteers, NMIBC, and MIBC patients. According to the results, the overall diagnostic accuracy is 93.3%. The diagnostic accuracies are 97.8% and 93.2% for healthy versus bladder cancer groups and NMIBC versus MIBC groups, respectively. Therefore, the proposed method has demonstrated excellent performance on accurately identifying muscle invasion of bladder cancer, which can assist timely diagnosis and proper treatment for bladder cancer patients.
膀胱癌肌肉浸润情况的评估通常在治疗决策中起着关键作用，并且对复发率和生存率有重大影响。尽管组织病理学足够准确，通常作为膀胱癌诊断的金标准，但它具有侵入性、耗时，并且需要训练有素的病理学家进行密集的样本制备才能实现最佳诊断。因此，需要一种快速且无创的方法来准确识别非肌肉浸润性膀胱癌（NMIBC）和肌肉浸润性膀胱癌（MIBC）。在本研究中，基于少量血清样本，采用表面增强拉曼光谱（SERS）技术结合偏最小二乘判别分析（PLS-LDA）方法来区分健康志愿者、NMIBC患者和MIBC患者。结果显示，总体诊断准确率为93.3%。健康组与膀胱癌组、NMIBC组与MIBC组的诊断准确率分别为97.8%和93.2%。因此，所提出的方法在准确识别膀胱癌肌肉浸润方面表现出优异的性能，可为膀胱癌患者的及时诊断和恰当治疗提供帮助。
