Evidence map›Paper›PMID 33761089›Full record

ArticleDigestive diseases and sciences2022

Artificial Intelligence-Based Assessment of Colorectal Polyp Histology by Elastic-Scattering Spectroscopy.

Eladio Rodriguez-Diaz, Lisa I Jepeal, György Baffy, Wai-Kit Lo, Hiroshi MashimoMD, Ousama A'amar, Irving J Bigio, Satish K Singh

Abstract read
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In one paragraph

Article in Digestive diseases and sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 43% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Eladio Rodriguez-DiazResearch Service, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA.
Lisa I JepealResearch Service, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA.
György BaffyDepartment of Medicine, Section of Gastroenterology, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA.
Wai-Kit LoDepartment of Medicine, Section of Gastroenterology, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA.
Hiroshi MashimoMDDepartment of Medicine, Section of Gastroenterology, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA.
Ousama A'amarDepartment of Biomedical Engineering, College of Engineering, Boston University, 44 Cummington Mall, Boston, MA, 02215, USA.
Irving J BigioDepartment of Biomedical Engineering, College of Engineering, Boston University, 44 Cummington Mall, Boston, MA, 02215, USA.
Satish K SinghResearch Service, VA Boston Healthcare System, 150 South Huntington Ave., Boston, MA, 02130, USA. satish.singh@va.gov.ORCID 0000-0002-7664-3155
Boston University · USVA Boston Healthcare System · US

Funding

CMA: Marker-assisted prevention and risk stratification (MAPRS): Artificial Intelligence Endoscopy for Colorectal Cancer Prevention (CMA1)I01BX004455 · VA · VA BOSTON HEALTH CARE SYSTEM · PI SINGH, SATISH K · 2019 to 2022
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Optical Spectroscopy in the Management of Colorectal NeoplasiaI01CX001146 · VA · VA BOSTON HEALTH CARE SYSTEM · PI SINGH, SATISH K · 2015 to 2023
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BLRD VA I01 BX004455CSRD VA I01 CX001146
6 · The paper itself

Abstract

backgroundColonoscopic screening and surveillance for colorectal cancer could be made safer and more efficient if endoscopists could predict histology without the need to biopsy and perform histopathology on every polyp. Elastic-scattering spectroscopy (ESS), using fiberoptic probes integrated into standard biopsy tools, can assess, both in vivo and in real time, the scattering and absorption properties of tissue related to its underlying pathology.

aimsThe objective of this study was to evaluate prospectively the potential of ESS to predict polyp pathology accurately.

methodsWe obtained ESS measurements from patients undergoing screening/surveillance colonoscopy using an ESS fiberoptic probe integrated into biopsy forceps. The integrated forceps were used for tissue acquisition, following current standards of care, and optical measurement. All measurements were correlated to the index pathology. A machine learning model was then applied to measurements from 367 polyps in 169 patients to prospectively evaluate its predictive performance.

resultsThe model achieved sensitivity of 0.92, specificity of 0.87, negative predictive value (NPV) of 0.87, and high-confidence rate (HCR) of 0.84 for distinguishing 220 neoplastic polyps from 147 non-neoplastic polyps of all sizes. Among 138 neoplastic and 131 non-neoplastic polyps ≤ 5 mm, the model achieved sensitivity of 0.91, specificity of 0.88, NPV of 0.89, and HCR of 0.83.

conclusionsResults show that ESS is a viable endoscopic platform for real-time polyp histology, particularly for polyps ≤ 5 mm. ESS is a simple, low-cost, clinically friendly, optical biopsy modality that, when interfaced with minimally obtrusive endoscopic tools, offers an attractive platform for in situ polyp assessment.

Indexed as

AdenocarcinomaAdenomatous PolypsArtificial IntelligenceColonic PolypsColonoscopyColorectal NeoplasmsDiagnosis, Computer-AssistedHumansSensitivity and SpecificitySpectrum AnalysisArtificial intelligenceColonic polypsColonoscopyColorectal neoplasmMachine learningSpectroscopy

Identifiers

PMID33761089
OpenAlexW3137341730

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.