Label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters by linear-array-based photoacoustic tomography

Pengfei Hai, Yong Zhou, Ruiying Zhang, Jun Ma, Yang Li, Jin Yu Shao, Lihong V. Wang

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Circulating tumor cell (CTC) clusters, arising from multicellular groupings in a primary tumor, greatly elevate the metastatic potential of cancer compared with single CTCs. High-throughput detection and quantification of CTC clusters are important for understanding the tumor metastatic process and improving cancer therapy. Here, we applied a linear-array-based photoacoustic tomography (LA-PAT) system and improved the image reconstruction for label-free high-throughput CTC cluster detection and quantification in vivo. The feasibility was first demonstrated by imaging CTC cluster ex vivo. The relationship between the contrast-to-noise ratios (CNRs) and the number of cells in melanoma tumor cell clusters was investigated and verified. Melanoma CTC clusters with a minimum of four cells could be detected, and the number of cells could be computed from the CNR. Finally, we demonstrated imaging of injected melanoma CTC clusters in rats in vivo. Similarly, the number of cells in the melanoma CTC clusters could be quantified. The data showed that larger CTC clusters had faster clearance rates in the bloodstream, which agreed with the literature. The results demonstrated the capability of LA-PAT to detect and quantify melanoma CTC clusters in vivo and showed its potential for tumor metastasis study and cancer therapy.

Original languageEnglish
Article number041004
JournalJournal of biomedical optics
Volume22
Issue number4
DOIs
StatePublished - Apr 1 2017

Keywords

  • Photoacoustic tomography
  • cancer metastasis
  • cancer therapy
  • circulating tumor cell clusters

Fingerprint

Dive into the research topics of 'Label-free high-throughput detection and quantification of circulating melanoma tumor cell clusters by linear-array-based photoacoustic tomography'. Together they form a unique fingerprint.

Cite this