Recent studies in oncology have addressed the importance of detecting circulating tumor cell clusters because circulating tumor cell clusters might survive and metastasize more easily than single circulating tumor cells. Signals with larger peak widths detected by in vivo flow cytometer (IVFC) have been used to identify cell clusters in previous studies. However, the accuracy of this criterion might be greatly degraded by variance in blood flow and the rolling behaviors of circulating tumor cells. Here, we propose a criterion and algorithm to distinguish cell clusters from single cells. In this work, we first used area-based and volume-based models for single fluorescent cells. Simulating each model, we analyzed the corresponding morphology of IVFC signals from cell clusters. According to the Rayleigh criterion, the valley between two adjacent peak signals from two distinguishable cells should be lower than 73.5% of the peak values. A novel signal processing algorithm for IVFC was developed based on this criterion. The results showed that cell clusters can be reliably identified using our proposed algorithm. Intravital imaging was also performed to further support our algorithm. With enhanced accuracy, IVFC is a powerful tool to study circulating cell clusters.

肿瘤一直威胁着人类的健康, 大多数肿瘤患者死于转移性瘤而非原发性瘤。循环肿瘤细胞(CTC)是肿瘤转移的重要标志, CTC的检测可以用来监控肿瘤的转移情况及预后评估。在体光声流式细胞术(PAFC)利用CTC与血液背景的光吸收差异可以实现CTC的在体检测。相比于传统的CTC检测方法, PAFC可以无创、高灵敏地检测循环系统中的CTC数目。总结了PAFC无标记检测黑色素瘤CTC信号及纳米颗粒靶向标记乳腺癌CTC信号的方法, 以及这些方法在肿瘤转移、治疗效果评估中的应用。