Background and Aims
High-resolution microendoscopy (HRME) is an optical biopsy technology that provides
subcellular imaging of esophageal mucosa but requires expert interpretation of these
histopathology-like images. We compared endoscopists with an automated software algorithm
for detection of esophageal squamous cell neoplasia (ESCN) and evaluated the endoscopists’
accuracy with and without input from the software algorithm.
Methods
Thirteen endoscopists (6 experts, 7 novices) were trained and tested on 218 post-hoc
HRME images from 130 consecutive patients undergoing ESCN screening/surveillance.
The automated software algorithm interpreted all images as neoplastic (high-grade
dysplasia, ESCN) or non-neoplastic. All endoscopists provided their interpretation
(neoplastic or non-neoplastic) and confidence level (high or low) without and with
knowledge of the software overlay highlighting abnormal nuclei and software interpretation.
The criterion standard was histopathology consensus diagnosis by 2 pathologists.
Results
The endoscopists had a higher mean sensitivity (84.3%, standard deviation [SD] 8.0%
vs 76.3%, P = .004), lower specificity (75.0%, SD 5.2% vs 85.3%, P < .001) but no significant difference in accuracy (81.1%, SD 5.2% vs 79.4%, P = .26) of ESCN detection compared with the automated software algorithm. With knowledge
of the software algorithm, the specificity of the endoscopists increased significantly
(75.0% to 80.1%, P = .002) but not the sensitivity (84.3% to 84.8%, P = .75) or accuracy (81.1% to 83.1%, P = .13). The increase in specificity was among novices (P = .008) but not experts (P = .11).
Conclusions
The software algorithm had lower sensitivity but higher specificity for ESCN detection
than endoscopists. Using computer-assisted diagnosis, the endoscopists maintained
high sensitivity while increasing their specificity and accuracy compared with their
initial diagnosis. Automated HRME interpretation would facilitate widespread usage
in resource-poor areas where this portable, low-cost technology is needed.
Abbreviations:
ESCN (esophageal squamous cell neoplasia), HRME (high-resolution microendoscopy), LCE (Lugol’s iodine chromoendoscopy), PIVI (Preservation and Incorporation of Valuable Endoscopic Innovations), SD (standard deviation)To read this article in full you will need to make a payment
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References
- Global time trends in the incidence of esophageal squamous cell carcinoma.Clin Epidemiol. 2018; 10: 717-728
- Cancer of the esophagus and stomach.Mayo Clin Proc. 2008; 83: 712-722
- Esophageal cancer: cases and causes (part I).Endoscopy. 2007; 39: 550-555
- Epidemiology and pathogenesis of esophageal cancer.Semin Radiat Oncol. 2007; 17: 2-9
- Lugol chromoendoscopy for esophageal squamous cell cancer.Endoscopy. 2001; 33: 75-79
- Assessment of novel endoscopic techniques for visualizing superficial esophageal squamous cell carcinoma: autofluorescence and narrow-band imaging.Dis Esophagus. 2009; 22: 439-446
- Narrow band imaging versus lugol chromoendoscopy to diagnose squamous cell carcinoma of the esophagus: a systematic review and meta-analysis.BMC Cancer. 2017; 17: 54
- Low-cost high-resolution microendoscopy for the detection of esophageal squamous cell neoplasia: an international trial.Gastroenterology. 2015; 149: 321-329
- Applications and advancements in the use of high-resolution microendoscopy for detection of gastrointestinal neoplasia.Clin Gastroenterol Hepatol. 2014; 12: 1789-1792
- High-resolution microendoscopy for the detection of cervical neoplasia in low-resource settings.PLoS One. 2012; 7e44924
- Accuracy and interrater reliability for the diagnosis of Barrett's neoplasia among users of a novel, portable high-resolution microendoscope.Dis Esophagus. 2014; 27: 55-62
- Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy.Gastroenterology. 2018; 155: 1069-1078.e8
- Application of convolutional neural network in the diagnosis of the invasion depth of gastric cancer based on conventional endoscopy.Gastrointest Endosc. 2019; 89: 806-815.e1
- Impact of deep learning assistance on the histopathologic review of lymph nodes for metastatic breast cancer.Am J Surg Pathol. 2018; 42: 1636-1646
- A tablet-interfaced high-resolution microendoscope with automated image interpretation for real-time evaluation of esophageal squamous cell neoplasia.Gastrointest Endosc. 2016; 84: 834-841
- Automated frame selection process for high-resolution microendoscopy.J Biomed Opt. 2015; 20: 46014
- Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts.Int J Comput Assist Radiol Surg. 2017; 12: 757-766
- Software for automated classification of probe-based confocal laser endomicroscopy videos of colorectal polyps.World J Gastroenterol. 2012; 18: 5560-5569
- High-resolution microendoscopy: a point-of-care diagnostic for cervical dysplasia in low-resource settings.Eur J Cancer Prev. 2017; 26: 63-70
- Quantitative analysis of high-resolution microendoscopic images for diagnosis of esophageal squamous cell carcinoma.Clin Gastroenterol Hepatol. 2015; 13: 272-279.e2
- Tests for equivalence or non-inferiority for paired binary data.Stat Med. 2002; 21: 231-245
- Computer-aided detection (CAD) in mammography: does it help the junior or the senior radiologist?.Eur J Radiol. 2005; 54: 90-96
- The American Society for Gastrointestinal Endoscopy PIVI (Preservation and Incorporation of Valuable Endoscopic Innovations) on imaging in Barrett's esophagus.Gastrointest Endosc. 2012; 76: 252-254
- Computer-based classification of small colorectal polyps by using narrow-band imaging with optical magnification.Gastrointest Endosc. 2011; 74: 1354-1359
- Computer-aided diagnosis of dysplasia in Barrett's esophagus using endoscopic optical coherence tomography.J Biomed Opt. 2006; 11044010
- Computer-aided detection of early Barrett's neoplasia using volumetric laser endomicroscopy.Gastrointest Endosc. 2017; 86: 839-846
Article Info
Publication History
Published online: July 16, 2020
Accepted:
July 2,
2020
Received:
February 17,
2020
Footnotes
DISCLOSURE: R. Richards-Kortum is an inventor on patents related to optical technologies owned by the University of Texas licensed to Remicalm LLC. All other authors disclosed no financial relationships.
Identification
Copyright
© 2021 by the American Society for Gastrointestinal Endoscopy
