The Potential of Digital Image Analysis to Determine Tumor Cell Content in Biobanked Formalin-Fixed, Paraffin-Embedded Tissue Samples

Christine Greene, Edwina O'Doherty, Fatima Abdullahi Sidi, Victoria Bingham, Natalie Fisher, Matt Humphries, Stephanie Craig, Louise Harewood, Stephen McQuaid, Claire Lewis, Jacqueline James

Research output: Contribution to journalArticlepeer-review

Abstract

Best practices dictate that biobanks ensure accurate determination of tumor content before supplying formalin-fixed, paraffin-embedded (FFPE) tissue samples to researchers for nucleic acid extraction and downstream molecular testing. It is advisable that trained and competent individuals, who understand the requirements of the downstream molecular tests, perform the microscopic morphological examination. However, the special skills, time, and costs associated with these assessments can be prohibitive, especially in large case cohorts requiring extensive pathological review. Determination of tumor content reliably by digital image analysis (DIA) could represent a significant advantage if validated, utilized, and deployed by biobanks. Whole slide digital scanned images of colorectal, lung, and breast cancer specimens were created. The scanned images were imported into the DIA software QuPath and digital annotations were completed by biobank technicians, under the direction of trained histopathology senior scientists. Automated cell detection was conducted and tumor epithelial cells were classified and quantified. DIA scores were highly concordant with the manual assessment for 376 of 435 samples (86%). A detailed review of discordant cases indicated digital scores had a higher accuracy than the manual estimation. Automated digital quantification has the potential to replace visual estimations with reduced subjectivity and increased reliability compared with manual tumor estimations. We recommend the use of DIA by biobanks involved in provision of FFPE tissue samples, especially in large research studies requiring high volumes of cases to be analyzed.
Original languageEnglish
JournalBiopreservation and Biobanking
Early online date29 Mar 2021
DOIs
Publication statusPublished - 29 Mar 2021

Keywords

  • image analysis
  • molecular testing
  • tumor annotation

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