Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial.
Gastroenterology
; 159(2): 512-520.e7, 2020 08.
Article
em En
| MEDLINE
| ID: mdl-32371116
ABSTRACT
BACKGROUND & AIMS:
One-fourth of colorectal neoplasias are missed during screening colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems allow for real-time computer-aided detection (CADe) of polyps with high accuracy. We performed a multicenter, randomized trial to assess the safety and efficacy of a CADe system in detection of colorectal neoplasias during real-time colonoscopy.METHODS:
We analyzed data from 685 subjects (61.32 ± 10.2 years old; 337 men) undergoing screening colonoscopies for CRC, post-polypectomy surveillance, or workup due to positive results from a fecal immunochemical test or signs or symptoms of CRC, at 3 centers in Italy from September through November 2019. Patients were randomly assigned (11) to groups who underwent high-definition colonoscopies with the CADe system or without (controls). The CADe system included an artificial intelligence-based medical device (GI-Genius, Medtronic) trained to process colonoscopy images and superimpose them, in real time, on the endoscopy display a green box over suspected lesions. A minimum withdrawal time of 6 minutes was required. Lesions were collected and histopathology findings were used as the reference standard. The primary outcome was adenoma detection rate (ADR, the percentage of patients with at least 1 histologically proven adenoma or carcinoma). Secondary outcomes were adenomas detected per colonoscopy, non-neoplastic resection rate, and withdrawal time.RESULTS:
The ADR was significantly higher in the CADe group (54.8%) than in the control group (40.4%) (relative risk [RR], 1.30; 95% confidence interval [CI], 1.14-1.45). Adenomas detected per colonoscopy were significantly higher in the CADe group (mean, 1.07 ±1.54) than in the control group (mean 0.71 ± 1.20) (incidence rate ratio, 1.46; 95% CI, 1.15-1.86). Adenomas 5 mm or smaller were detected in a significantly higher proportion of subjects in the CADe group (33.7%) than in the control group (26.5%; RR, 1.26; 95% CI, 1.01-1.52), as were adenomas of 6 to 9 mm (detected in 10.6% of subjects in the CADe group vs 5.8% in the control group; RR, 1.78; 95% CI, 1.09-2.86), regardless of morphology or location. There was no significant difference between groups in withdrawal time (417 ± 101 seconds for the CADe group vs 435 ± 149 for controls; P = .1) or proportion of subjects with resection of non-neoplastic lesions (26.0% in the CADe group vs 28.7% of controls; RR, 1.00; 95% CI, 0.90-1.12).CONCLUSIONS:
In a multicenter, randomized trial, we found that including CADe in real-time colonoscopy significantly increases ADR and adenomas detected per colonoscopy without increasing withdrawal time. ClinicalTrials.gov no 04079478.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Interpretação de Imagem Assistida por Computador
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Neoplasias Colorretais
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Adenoma
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Programas de Rastreamento
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Colonoscopia
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Aprendizado Profundo
Tipo de estudo:
Clinical_trials
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Diagnostic_studies
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Etiology_studies
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Prognostic_studies
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Screening_studies
Limite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article