International Journal of Molecular Sciences (Feb 2023)

Quantification and Characterization of CTCs and Clusters in Pancreatic Cancer by Means of the Hough Transform Algorithm

  • Francisco José Calero-Castro,
  • Sheila Pereira,
  • Imán Laga,
  • Paula Villanueva,
  • Gonzalo Suárez-Artacho,
  • Carmen Cepeda-Franco,
  • Patricia de la Cruz-Ojeda,
  • Elena Navarro-Villarán,
  • Sandra Dios-Barbeito,
  • María José Serrano,
  • Cristóbal Fresno,
  • Javier Padillo-Ruiz

DOI
https://doi.org/10.3390/ijms24054278
Journal volume & issue
Vol. 24, no. 5
p. 4278

Abstract

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Circulating Tumor Cells (CTCs) are considered a prognostic marker in pancreatic cancer. In this study we present a new approach for counting CTCs and CTC clusters in patients with pancreatic cancer using the IsofluxTM System with the Hough transform algorithm (Hough-IsofluxTM). The Hough-IsofluxTM approach is based on the counting of an array of pixels with a nucleus and cytokeratin expression excluding the CD45 signal. Total CTCs including free and CTC clusters were evaluated in healthy donor samples mixed with pancreatic cancer cells (PCCs) and in samples from patients with pancreatic ductal adenocarcinoma (PDAC). The IsofluxTM System with manual counting was used in a blinded manner by three technicians who used Manual-IsofluxTM as a reference. The accuracy of the Hough-IsofluxTM approach for detecting PCC based on counted events was 91.00% [84.50, 93.50] with a PCC recovery rate of 80.75 ± 16.41%. A high correlation between the Hough-IsofluxTM and Manual-IsofluxTM was observed for both free CTCs and for clusters in experimental PCC (R2 = 0.993 and R2 = 0.902 respectively). However, the correlation rate was better for free CTCs than for clusters in PDAC patient samples (R2 = 0.974 and R2 = 0.790 respectively). In conclusion, the Hough-IsofluxTM approach showed high accuracy for the detection of circulating pancreatic cancer cells. A better correlation rate was observed between Hough-IsofluxTM approach and with the Manual-IsofluxTM for isolated CTCs than for clusters in PDAC patient samples.

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