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 cel...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°ow 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°uorescent 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 identied 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.展开更多
基金the National Science Fund for Distinguished Young Scholars(Grant No.61425006)Program of Shanghai Technology Research Leader(Grant No.17XD1402200).
文摘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°ow 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°uorescent 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 identied 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.
