Li Ya, Li Yu, Wang Xu, Wang Kang, Li Haoliang, Wang Pengfei, Xue Qi, Xu Feng, Zhang Wenchang, Yang Xiaonan, Chen Bing
Department of Gastroenterology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450001, China.
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
Anal Bioanal Chem. 2025 Jan;417(1):95-107. doi: 10.1007/s00216-024-05624-y. Epub 2024 Oct 30.
The detection of extremely rare circulating tumor cells (CTCs) in peripheral blood and simultaneously identifying their viabilities are significant for cancer diagnosis and prognosis as well as monitoring the efficacy of personalized treatment. A lens-free imaging system features high-resolution images taken over a large field of view (FOV), which has great potential for CTC detection and viability determination. But current still lens-free systems restrict the application for CTC detection in real samples due to the inherent limitations of lens-free technology: (1) the location of cells in the FOV will affect the imaging; (2) the extremely rare CTCs probably did not exist in one observation. In this paper, we realized the detection of CTCs in whole blood and the simultaneous determination of their viabilities by lens-free imaging cytometry. Our in-flow system plus a large FOV range of lens-free imaging highly increased the detection rate of rare CTCs with a high throughput of 150,000 cells per minute and improved the recognition efficiency for blood cells, living/dead CTCs by using a cell tracing-assisted deep learning algorithm. With this method, the average precision of blood cells, living/dead lung cancer cells A549, and living/dead colon cancer cells SW620 reached 98.80%, 97.88%, 97.93%, 97.72%, and 98.60%, respectively. Our system got a highly consistent result with the manual counting method using fluorescent staining (Pearson's r 99.93% for SW620) and can easily detect as few as 10 dead or living CTCs from 100,000 white blood cells (WBCs). Finally, real clinical samples were detected in our system. Both dead and living CTCs were found in all six advanced-stage cancer patients, and the number of living CTCs per million WBCs ranged from 13 to 39, more than that of the dead CTCs (5 to 25), while none of the CTCs were detected in six healthy control subjects. Moreover, we also found that CTCs died very quickly after leaving the human body, indicating that CTCs should be studied as soon as possible after sampling. Although this method is implemented for CTCs, it can also be used for the detection of other rare cells.
在外周血中检测极其罕见的循环肿瘤细胞（CTC）并同时确定其活力，对于癌症诊断、预后评估以及监测个性化治疗效果具有重要意义。无透镜成像系统具有在大视野（FOV）下拍摄高分辨率图像的特点，在CTC检测和活力测定方面具有巨大潜力。但目前的无透镜系统由于无透镜技术的固有局限性，限制了其在实际样本中进行CTC检测的应用：（1）细胞在FOV中的位置会影响成像；（2）极其罕见的CTC可能在一次观察中并不存在。在本文中，我们通过无透镜成像流式细胞术实现了全血中CTC的检测及其活力的同时测定。我们的流入系统加上大FOV范围的无透镜成像，以每分钟150,000个细胞的高通量显著提高了罕见CTC的检测率，并通过使用细胞追踪辅助深度学习算法提高了对血细胞、活/死CTC的识别效率。通过这种方法，血细胞、活/死肺癌细胞A549以及活/死结肠癌细胞SW620的平均精度分别达到了98.80%、97.88%、97.93%、97.72%和98.60%。我们的系统与使用荧光染色的手动计数方法得到了高度一致的结果（SW620的皮尔逊相关系数r为99.93%），并且能够轻松地从100,000个白细胞（WBC）中检测到低至10个死的或活的CTC。最后，我们的系统对实际临床样本进行了检测。在所有六名晚期癌症患者中均发现了死的和活的CTC，每百万WBC中活的CTC数量在13至39之间，多于死的CTC数量（5至25），而在六名健康对照受试者中未检测到任何CTC。此外，我们还发现CTC离开人体后很快就会死亡，这表明在采样后应尽快对CTC进行研究。尽管该方法是针对CTC实施的，但它也可用于检测其他罕见细胞。
