Prashant Shekhar

Prashant Shekhar

Data Scientist and Professor

In vivo detection of Circulating Tumor Cell Clusters (CTCCs)

In this project, we introduced a non-invasive Deep Learning based AI approach for effective identification of Circulating Tumor Cells (CTCs) and Circulating Tumor Cell Clusters (CTCCs) in whole blood using label-free flow cytometry. These CTCs and CTCCs are widely regarded as important biomarkers of metastatic growth. Particularly, our approach provided a high purity classification model establishing superiority over previously introduced approaches.

Relevant publications for this project

  1. Vora, N., Shekhar, P., Esmail, M., Patra, A., & Georgakoudi, I. Deep Learning-Enabled, Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry. bioRxiv, 2023 August Link..

  2. Vora, N., Shekhar, P., Kwan, J., Esmail, M., Patra, A., and Georgakoudi, I. Meet the clusters: a deep learning approach for label-free detection of circulating tumor cell clusters using flow cytometry. In Multiscale Imaging and Spectroscopy IV (p. PC123630A). SPIE. 2023 March Link.

  3. Vora, N., Shekhar, P., Esmail, M., Patra, A., and Georgakoudi, I. Label-free flow cytometry of rare circulating tumor cell clusters in whole blood. Nature Scientific Reports. 2022 ;12(1): 1-14 Link.

  4. Georgakoudi, I., Vora, N., Shekhar, P., and Patra, A. Label-free flow cytometric detection of circulating tumor cell clusters is enabled in whole blood samples by machine learning-based signal analysis. In Unconventional Optical Imaging III (p. PC121360U). SPIE. 2022 May Link.

  5. Vora, N., Shekhar, P., Esmail, M., Patra, A., and Georgakoudi, I. Detection of Rare Circulating Tumor Cell Clusters in Whole Blood Using Label-free, Flow Cytometry. In Microscopy Histopathology and Analytics (pp. MW3A-3). Optica Publishing Group. 2022 April Link.