SNFGE SNFGE
 
Thématique :
- Endoscopie/Imagerie
Originalité :
Très original
Solidité :
A confirmer
Doit faire évoluer notre pratique :
Pas encore
 
 
Nom du veilleur :
Professeur Emmanuel CORON
Coup de coeur :
 
 
Gastrointestinal Endoscopy
  2016/04  
 
  2016 Mar;83(3):643-9  
  doi: 10.1016/j.gie.2015.08.004  
 
  Computer-aided diagnosis of colorectal polyp histology by using a real-time image recognition system and narrow-band imaging magnifying colonoscopy  
 
  Kominami Y, Yoshida S, Tanaka S, Sanomura Y, Hirakawa T, Raytchev B, Tamaki T, Koide T, Kaneda K, Chayama K  
  http://www.ncbi.nlm.nih.gov/pubmed/?term=Computer-aided+diagnosis+of+colorectal+polyp+histology+by+using+a+real-time+image+recognition+system+and+narrow-band+imaging+magnifying+colonoscopy  
 
 

BACKGROUND AND AIMS:

It is necessary to establish cost-effective examinations and treatments for diminutive colorectal tumors that consider the treatment risk and surveillance interval after treatment. The Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) committee of the American Society for Gastrointestinal Endoscopy published a statement recommending the establishment of endoscopic techniques that practice the resect and discard strategy. The aims of this study were to evaluate whether our newly developed real-time image recognition system can predict histologic diagnoses of colorectal lesions depicted on narrow-band imaging and to satisfy some problems with the PIVI recommendations.

METHODS:

We enrolled 41 patients who had undergone endoscopic resection of 118 colorectal lesions (45 nonneoplastic lesions and 73 neoplastic lesions). We compared the results of real-time image recognition system analysis with that of narrow-band imaging diagnosis and evaluated the correlation between image analysis and the pathological results.

RESULTS:

Concordance between the endoscopic diagnosis and diagnosis by a real-time image recognition system with a support vector machine output value was 97.5% (115/118). Accuracy between the histologic findings of diminutive colorectal lesions (polyps) and diagnosis by a real-time image recognition system with a support vector machine output value was 93.2% (sensitivity, 93.0%; specificity, 93.3%; positive predictive value (PPV), 93.0%; and negative predictive value, 93.3%).

CONCLUSIONS:

Although further investigation is necessary to establish our computer-aided diagnosis system, this real-time image recognition system may satisfy the PIVI recommendations and be useful for predicting the histology of colorectal tumors.

 
Question posée
 
Est-il possible d’automatiser l’interprétation endoscopique des polypes diminutifs ?
 
Question posée
 
Il s’agit d’une étude de preuve de concept mais dont les résultats sont intéressants puisque la concordance entre l’interprétation automatique et en temps réel de la nature de polypes colorectaux diminutifs avait une sensibilité et une spécificité >90%, donc compatible avec les recommandations PIVI pour l’intégration en pratique clinique.
 
Commentaires

A confirmer mais constitue une première étape intéressante vers la caractérisation automatique des polypes colorectaux.

 
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