癌细胞机械特性快速自动检测方法和系统研究

Bladder cancer is among the top ten most common malignancies globally. In China, bladder cancer inflicts more patients than prostate cancer, having over 60,000 new cases annually. Because of its high recurrence rate, patients require continuous surveillance. The associated healthcare costs are greater than other malignancies. Hence, early and accurate bladder cancer detection is of critical significance since it improves prognosis and simplifies treatment...The gold standard for diagnosing bladder cancer is invasive cystoscopy with biopsy of lesions that are then categorized by the histopathologist. Anesthesia is administered and a cystoscope (flexible fiberoptic scope or rigid tube with light source) is inserted into the bladder through the urethra to allow the urologist to visualize abnormalities. On the cellular level, voided urine cytology (visually examining the morphology of cells that exfoliate or “fall off” the bladder lining during urination) has been a valuable approach for non-invasive detection of bladder cancer. However, its overall usefulness is limited by the fact that it is insensitive for low-grade superficial lesions, and its accuracy is highly dependent on the experience of the cytopathologist. Intensive efforts in the development of biochemical and genetic markers for bladder cancer detection have been only partially successful, largely due to their low detection specificity and high complexity and cost of these tests...This project will explore the novel concept of using ‘biomechanical’ markers for mechanical characterization of cells in voided urine. This project will develop new methodologies, micro devices, and automated measurement techniques that will, for the first time, allow parallel multi-parameter mechanical measurement of exfoliated cells in voided urine. Biomechanical models will be established to process raw measurement data to assign each cell with two quantities unique to the cell as unique signatures. These cell-size independent quantities will include Young’s modulus and viscosity, which reflect cell stiffness and the fluidity of cytoplasm inside the cell. ..In collaboration with RenJi Hospital, data will be obtained on both bladder cancer cells and normal cells present in voided urine from patients. Models will be established for classifying cancer and normal cells. Testing accuracy and sensitivity are both anticipated to be higher than 90%. The project will reveal the efficacy of biomechanical markers for bladder cancer detection. These novel, non-invasive, relatively inexpensive diagnostic techniques will provide a stand-alone or bolstering method for non-invasive, low-cost, high-performance bladder cancer diagnosis and surveillance.

本项目针对膀胱癌发病率高、进展快、复发率高，对研究发展准确度高、灵敏性强的无损检测技术的迫切需求，突破癌细胞机械特性（包括细胞杨氏模量、细胞浆粘稠度）快速自动检测方法和系统的研究，探明癌细胞机械性能指标与发病进程的关系，建立预测模型。从而形成一种基于尿脱落细胞机械特性的膀胱癌无创检测诊断新方法，预期达到细胞机械特性检测速度高于5细胞/秒、检测灵敏度和准确性均高于90%，帮助临床医生对膀胱癌进行诊断监测，避免目前常用的膀胱镜诊断方法给病人造成的痛苦，甚至伤害，克服尿脱落细胞形态检查技术的模糊性以及尚未找到灵敏且准确的肿瘤标记物等技术难题，为膀胱癌的预防、诊断、预后随访监测提供一种新的技术途径，具有重要的临床和社会意义。

本项目针对膀胱癌发病率高、进展快、复发率高，对研究发展准确度高、灵敏性强的无损检测技术的迫切需求，重点研究了膀胱癌细胞多维机械特性（包括细胞杨氏模量、细胞浆粘稠度）的快速自动检测方法和系统，并深入探讨了癌细胞机械性能指标与发病进程的关系，建立了预测模型，最终形成了一套基于细胞机械特性的膀胱癌无创检测诊断新方法。项目研制了基于细胞多维机械特性检测的膀胱癌体外自动诊断系统样机，系统达到了项目任务书中提出的技术指标：检测速度：>5个细胞/每秒；压力闭环自动控制系统的控制精度为±1Pa；对膀胱癌样本的检测灵敏度和准确性均≥90%；发表了学术论文21篇，获授权发明专利10项；培养了青年教师和博士硕士生14人，并获得了上海市技术发明一等奖1项。本项目形成的理论、技术和实验成果，有望帮助临床医生对膀胱癌进行诊断监测，为膀胱癌的预防、诊断、预后随访监测提供一种新的技术途径，具有重要的临床和社会意义。