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Automated cytological detection of Barrett’s neoplasia with infrared spectroscopy

  • Original Article—Alimentary Tract
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Abstract

Background

Development of a nonendoscopic test for Barrett’s esophagus would revolutionize population screening and surveillance for patients with Barrett’s esophagus. Swallowed cell collection devices have recently been developed to obtain cytology brushings from the esophagus: automated detection of neoplasia in such samples would enable large-scale screening and surveillance.

Methods

Fourier transform infrared (FTIR) spectroscopy was used to develop an automated tool for detection of Barrett’s esophagus and Barrett’s neoplasia in esophageal cell samples. Cytology brushings were collected at endoscopy, cytospun onto slides and FTIR images were measured. An automated cell recognition program was developed to identify individual cells on the slide.

Results

Cytology review and contemporaneous histology was used to inform a training dataset containing 141 cells from 17 patients. A classification model was constructed by principal component analysis fed linear discriminant analysis, then tested by leave-one-sample-out cross validation. With application of this training model to whole slide samples, a threshold voting system was used to classify samples according to their constituent cells. Across the entire dataset of 115 FTIR maps from 66 patients, whole samples were classified with sensitivity and specificity respectively as follows: normal squamous cells 79.0% and 81.1%, nondysplastic Barrett’s esophagus cells 31.3% and 100%, and neoplastic Barrett’s esophagus cells 83.3% and 62.7%.

Conclusions

Analysis of esophageal cell samples can be performed with FTIR spectroscopy with reasonable sensitivity for Barrett’s neoplasia, but with poor specificity with the current technique.

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Acknowledgements

The authors thank Doug Townsend and Max Diem from Northeastern University, Boston, for all their advice on many technical aspects of spectral cytopathology. Oliver Old was in receipt of a Royal College of Surgeons of England Surgical Research Fellowship during this study.

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Authors and Affiliations

  1. Biophotonics Research Unit, Gloucestershire Hospitals NHS Foundation Trust, Great Western Road, Gloucester, GL1 3NN, UK

    Oliver Old, Gavin Lloyd, Martin Isabelle, L. Max Almond, Catherine Kendall & Hugh Barr

  2. University of Exeter Medical School, Royal Devon and Exeter NHS Foundation Trust, Exeter, EX2 5DW, UK

    Oliver Old

  3. School of Physics and Astronomy, University of Exeter, Exeter, EX4 4QL, UK

    Gavin Lloyd, Catherine Kendall & Nick Stone

  4. Heartlands Hospital, Bordesley Green East, Birmingham, B9 5SS, UK

    L. Max Almond

  5. Gloucestershire Hospitals NHS Foundation Trust, Great Western Road, Gloucester, GL1 3NN, UK

    Karol Baxter, Neil Shepherd & Hugh Barr

  6. NIHR Exeter Clinical Research Facility, University of Exeter Medical School, Royal Devon and Exeter NHS Foundation Trust, Exeter, EX2 5DW, UK

    Angela Shore

Authors
  1. Oliver Old
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  2. Gavin Lloyd
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  3. Martin Isabelle
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  8. Angela Shore
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  9. Nick Stone
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  10. Hugh Barr
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Corresponding author

Correspondence to Oliver Old.

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The authors declare that they have no conflict of interest.

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Old, O., Lloyd, G., Isabelle, M. et al. Automated cytological detection of Barrett’s neoplasia with infrared spectroscopy. J Gastroenterol 53, 227–235 (2018). https://doi.org/10.1007/s00535-017-1344-z

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  • DOI: https://doi.org/10.1007/s00535-017-1344-z

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