Automated software-assisted diagnosis of esophageal squamous cell neoplasia using high-resolution microendoscopy.
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...
| Publicado en: | Gastrointestinal Endoscopy Vol. 93; no. 4; pp. 831 - 832 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Apr2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149312588&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149312588 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00165107 4A9 jtl: Gastrointestinal Endoscopy issn: 00165107 maglogo: N pubinfo: dt: Apr2021 vid: 93 iid: 4 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 149312588 149312588 149312588 10.1016/j.gie.2020.07.007 149312588 ppf: 831 ppct: 1 formats: tig: atl: Automated software-assisted diagnosis of esophageal squamous cell neoplasia using high-resolution microendoscopy. aug: au: Tan, Mimi C. Bhushan, Sheena Quang, Timothy Schwarz, Richard Patel, Kalpesh H. Yu, Xinying Li, Zhengqi Wang, Guiqi Zhang, Fan Wang, Xueshan Xu, Hong Richards-Kortum, Rebecca R. Anandasabapathy, Sharmila affil: Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, Texas sug: subj: Esophageal Neoplasms Diagnosis Neoplasms, Squamous Cell Diagnosis Endoscopy Methods Optical Imaging Methods Image Processing, Computer Assisted Methods Human Algorithms Sensitivity and Specificity Descriptive Statistics ab: 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. 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. 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). 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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