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Peer-reviewedCC BY 4.0DEN Open

Enhanced Esophageal Cancer Detection Using Spectrum‐Aided Vision Enhancer: A Comparative Study of White Light Imaging, Narrow‐Band Imaging, and Algorithmic Narrow‐Band Imaging‐Like Imaging

  • Jer‐Wei Wu1
  • Yao‐Kuang Wang2,3,4
  • Arvind Mukundan5,6,7
  • Riya Karmakar5,8
  • Nguyen Ngoc Quynh Nhu9
  • Yaswanth Nagisetti5
  • Wei‐Chih Liao10
  • Ming‐Lun Han1,10
  • I‐Chen Wu3,4
  • Hsiang‐Chen Wang5,11
11 affiliations
  1. 1Division of Endoscopy Department of Integrated Diagnostics & Therapeutics National Taiwan University Hospital Taipei Taiwan
  2. 2Graduate Institute of Clinical Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan
  3. 3Division of Gastroenterology Department of Internal Medicine Kaohsiung Medical University Hospital Kaohsiung Taiwan
  4. 4Department of Medicine Faculty of Medicine College of Medicine Kaohsiung Medical University Kaohsiung Taiwan
  5. 5Department of Mechanical Engineering National Chung Cheng University Chia Yi Taiwan
  6. 6Department of Biomedical Imaging Chennai Institute of Technology Chennai India
  7. 7Department of Computer Science Engineering School of Engineering and Technology Sanjivani University Kopargaon India
  8. 8Department of Integrated Bachelor of Technology School of Engineering and Technology Sanjivani University Kopargaon India
  9. 9Department of Biomedical Engineering International University ‐ Vietnam National University Ho Chi Minh City Vietnam
  10. 10Division of Gastroenterology and Hepatology Department of Internal Medicine National Taiwan University Hospital National Taiwan University College of Medicine Taipei Taiwan
  11. 11Department of Medical Research Dalin Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Chia Yi Taiwan
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Abstract

Background and Aims: Esophageal squamous cell carcinoma (ESCC) detection is crucial for improving survival. While narrow‐band imaging (NBI) improves mucosal visualization, limitations remain. We evaluated the diagnostic performance of the Spectrum‐Aided Vision Enhancer (SAVE), an algorithmic NBI‐like technology reconstructed from white light imaging (WLI).

Methods: We conducted a retrospective, image‐based exploratory feasibility study to descriptively evaluate the diagnostic performance of WLI, NBI, and SAVE. A dataset of 1350 still endoscopic images (450 each for WLI, NBI, and SAVE) across normal mucosa, dysplasia, and ESCC stages from 158 patients was blindly reviewed by three endoscopists with different experience levels (3, 5, and 15 years). Diagnostic metrics included sensitivity, specificity, accuracy, and reading time.

Results: For ESCC, SAVE demonstrated diagnostic performance metrics (sensitivity: 0.81–0.97, specificity: 0.85–0.96) that were numerically similar to WLI and NBI. For dysplasia detection, SAVE had lower observed sensitivity (0.39–0.62) compared to NBI (0.55–0.85) across all observers, representing a clinical limitation for precancerous screening in its current format. Mean per‐image reading times were similar across WLI, NBI, and SAVE.

Conclusions: In this retrospective study, SAVE showed diagnostic potential for ESCC, with observed diagnostic performance metrics numerically similar to those of WLI and NBI in this exploratory dataset, but lacked sensitivity for dysplasia. These findings are hypothesis‐generating and warrant further prospective, multicenter validation to refine the algorithm for early cancer detection.

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Cite

BibTeXRIS
BibTeX
@article{wu2026enhanced,
  title = {{Enhanced Esophageal Cancer Detection Using Spectrum‐Aided Vision Enhancer: A Comparative Study of White Light Imaging, Narrow‐Band Imaging, and Algorithmic Narrow‐Band Imaging‐Like Imaging}},
  author = {Jer‐Wei Wu and Yao‐Kuang Wang and Arvind Mukundan and Riya Karmakar and Nguyen Ngoc Quynh Nhu and Yaswanth Nagisetti and Wei‐Chih Liao and Ming‐Lun Han and I‐Chen Wu and Hsiang‐Chen Wang},
  journal = {DEN Open},
  year = {2026},
  month = nov,
  doi = {10.1002/deo2.70467},
  url = {https://doi.org/10.1002/deo2.70467},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Enhanced Esophageal Cancer Detection Using Spectrum‐Aided Vision Enhancer: A Comparative Study of White Light Imaging, Narrow‐Band Imaging, and Algorithmic Narrow‐Band Imaging‐Like Imaging
AU  - Jer‐Wei Wu
AU  - Yao‐Kuang Wang
AU  - Arvind Mukundan
AU  - Riya Karmakar
AU  - Nguyen Ngoc Quynh Nhu
AU  - Yaswanth Nagisetti
AU  - Wei‐Chih Liao
AU  - Ming‐Lun Han
AU  - I‐Chen Wu
AU  - Hsiang‐Chen Wang
PY  - 2026
DA  - 2026/11/04
JO  - DEN Open
DO  - 10.1002/deo2.70467
UR  - https://doi.org/10.1002/deo2.70467
AB  - Background and Aims: Esophageal squamous cell carcinoma (ESCC) detection is crucial for improving survival. While narrow‐band imaging (NBI) improves mucosal visualization, limitations remain. We evaluated the diagnostic performance of the Spectrum‐Aided Vision Enhancer (SAVE), an algorithmic NBI‐like technology reconstructed from white light imaging (WLI).  Methods: We conducted a retrospective, image‐based exploratory feasibility study to descriptively evaluate the diagnostic performance of WLI, NBI, and SAVE. A dataset of 1350 still endoscopic images (450 each for WLI, NBI, and SAVE) across normal mucosa, dysplasia, and ESCC stages from 158 patients was blindly reviewed by three endoscopists with different experience levels (3, 5, and 15 years). Diagnostic metrics included sensitivity, specificity, accuracy, and reading time.  Results: For ESCC, SAVE demonstrated diagnostic performance metrics (sensitivity: 0.81–0.97, specificity: 0.85–0.96) that were numerically similar to WLI and NBI. For dysplasia detection, SAVE had lower observed sensitivity (0.39–0.62) compared to NBI (0.55–0.85) across all observers, representing a clinical limitation for precancerous screening in its current format. Mean per‐image reading times were similar across WLI, NBI, and SAVE.  Conclusions: In this retrospective study, SAVE showed diagnostic potential for ESCC, with observed diagnostic performance metrics numerically similar to those of WLI and NBI in this exploratory dataset, but lacked sensitivity for dysplasia. These findings are hypothesis‐generating and warrant further prospective, multicenter validation to refine the algorithm for early cancer detection.
SN  - 2692-4609
ER  -