Computer-Aided

Detection. Analysis. Prediction.

The GI Genius™ intelligent endoscopy module offers a transformative solution — powered by AI — to address the challenges of detecting potential signs of colorectal cancer, early.3

Ground Truth of rectosigmoid polyps:

Endoscopy or Histophatology?

A presentation by Prof. James East, Translational Gastroenterology Unit, Oxford, United Kingdom.

Artificial intelligence for leaving-in-situ colorectal polyps:

Results from the first prospective study with GI GeniusTM CADx module

A presentation by Dr. Giulio Antonelli, Castelli Hospital, Rome, Italy.

Support optical diagnosis

By harnessing deep learning algorithms and real-time data, GI Genius™ supports physicians to detect and estimate possible histology of colorectal polyps through enhanced visualization in white light colonoscopy.9,10

Detect more.
Miss less.

  • Colonoscopy can be preventative against the development of colorectal cancer by early detection and resection of neoplastic lesions. However, the procedure is highly operator dependent and detection rates can vary greatly.1
  • A second observer during colonoscopy may improve adenoma detection rate (ADR).2 Endoscopists with higher ADR during screening colonoscopy, more effectively reduce the risk of colorectal cancer.1


Each 1.0% increase in the adenoma detection rate was associated with
a 3.0% decrease in the risk of interval cancer1

Real results.

Demonstrated value.

RCT studies have demonstrated that GI Genius™ intelligent endoscopy module may contribute to a two-fold reduction in miss rate of colorectal neoplasia6 and potentially enhance Adenoma Detection Rate.

Nearly
50% reduction in AMR6

Discussed in:
Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

Authors:
Repici, A., Badalamenti, M., Maselli, R.,  et al.

Published in:
Gastroenterology, 2020

Nearly
14% increase in ADR3

Discussed in:
Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia

Authors:
Wallace M. B., Sharma P., Bhandari P., et al.

Published in:
Gastroenterology, 2022

Advanced precision.
Demonstrated performance.

100%

sensitivity per lesion4,*

87.6%

faster polyp recognition than the endoscopist (RT)4,*

Detect the undetected

The GI Genius™ intelligent endoscopy module offers a transformative solution — powered by artificial intelligence — to address the challenges of detecting colorectal cancer, early.

Indications

GI Genius™ is an artificial intelligence based medical device that has been trained to process colonoscopy images containing regions consistent with colorectal lesions like polyps, including those with flat (non-polypoid) morphology.

GI Genius™ is intended to be used by trained clinicians as an adjunct to white light colonoscopy for the purposes of highlighting regions suspected to have visual characteristics consistent with different types of mucosal abnormalities (e.g. colorectal polyps).

If characterization support is enabled, a polyp detected and highlighted by GI Genius™ is consistently framed in white light video colonoscopy, based on the visual characteristics of the detected polyp, GI Genius™ provides an estimate of the possible polyp histology.

GI Genius™ is intended to be used as an adjunct to colonoscopy procedures and is not intended to replace endoscopist assessment or histopathological sampling.

The whole colonoscopy video and the regions highlighted by GI Genius™  system must be independently assessed by the endoscopist, with all the available and obtainable information, without primarily relying on GI Genius™  system output.

GI Genius™  system does not prescribe any clinical management action regarding the detected and highlighted polyps.  The endoscopist must take appropriate actions according to the standard clinical practice.

GI Genius™  system does not make any elaboration or alteration of the colonoscopy video streaming, it only overlays graphical markers.

Risks

If the device is used outside of Instructions For Use it could potentially lead to inappropriate diagnostic information being displayed to the user (e.g. to analyze images from an unintended patient population, on images acquired with incompatible imaging hardware or incompatible image acquisition parameters).

Incorrect detection or characterization of lesion(s) may lead to false positive or false negative which may result in incorrect patients management with possible adverse effects: Unnecessary treatment, unnecessary additional medical imaging and/ or unnecessary additional diagnostic workup such as biopsy, complications, including incorrect diagnosis and delay in disease management. 

Device failure could lead to the absence of results, delay of results or incorrect results, which could likewise lead to inaccurate patient assessment.  

In the event of unrecoverable failure please switch off and revert to Non AI enhanced colonoscopy.

References

  1. Corley DA, Jenson CD, Marks AR JR, et al. Adenoma Detection Rate and Risk of Colorectal Cancer and Death. NEJM 2014;370:1298-306.
  2. Aslanian HR, Shieh FK, Chan FW, et al. Nurse observation during colonoscopy increases polyp detection: a randomized prospective study. Am J Gastroenterol. 2013;108(2):166–172.
  3. Repici, A., Badalamenti, M., Maselli, R., Correale, L., Radaelli, F., Rondonotti, E., ... & Anderloni, A. (2020). Efficacy of Real‑Time Computer‑Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology
  4. Clinical Evaluation Report. CB-17-08 System. LQ20052607.
  5. Hassan C, Wallace MB, Sharma P, et al. New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection. Gut. 2020; 69:799–800.
  6. Wallace MB, Sharma P, Bhandari P, et al. Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia, Gastroenterology, 2022, ISSN 0016-5085, https://doi.org/10.1053/j.gastro.2022.03.007.
  7. V & V data on file/usability engineering file.
  8. GI Genius™ instructions for use. Version 3.3
  9. Cesare Hassan, Giuseppina Balsamo, Roberto Lorenzetti, Angelo Zullo, Giulio Antonelli, ARTIFICIAL INTELLIGENCE FOR LEAVING IN SITU COLORECTAL POLYPS RESULTS OF A REALTIME CLINICAL TRIAL, , Clinical Gastroenterology and Hepatology (2022), doi: https://doi.org/10.1016/j.cgh.2022.04.045.
  10. Houwen B., Hassan C., Definition of competence standards for optical diagnosis of diminutive colorectal polyps: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement, Endoscopy 2022; 54: 88–99

* Information is from a Clinical Evaluation Report. CB-17-08 System. LQ20052607.