The composition of cell tissue in a colorectal polyp, as seen by NBI, can be divided into three types called NICE classification:
NICE 1: The polyp’s cell tissue still has a normal composition. In this case, the doctor will order follow-up checks to monitor the development of the polyp. However, he/she will not need to remove the polyp because the chances of it being cancerous are still very slim.
NICE 2: The composition of the cell tissue looks similar to a net, which indicates that the cells could eventually become cancerous. The doctor will therefore remove the polyp immediately using a coil or a special type of electric knife.
NICE 3: The cell tissue appears wild and disorderly, much like cancer cells. In this case, the doctor may not remove the whole polyp using a colonoscope, but may use tissue acquisition instead. The patient will need a consultation with an oncologist to assess which method of removing the polyp is most suitable.
The use of the NBI technique gives a more precise diagnosis. It also makes it easier for the doctor to devise a treatment plan. NBI can identify even the smallest polyps, as little as 5mm in diameter. This, thus, allows the doctor to calculate as accurately as possible whether the polyps pose a risk to the rest of the body. With a white-light colonoscopy, however, such small polyps might go unnoticed.
Still, the effectiveness of any colonoscopy using NBI largely depends on the expertise of the doctor and his/her mastery of the technique. It depends specifically on his/her adeptness at reading the results of the epithelium screening. Moreover, since there are only a small number of doctors who are experts in this technique, hospitals often overlook NBI as a screening option. This should not be the case, however. Infact, NBI offers a safe alternative to chromoendoscopy, as doctors just need to inject the patient with a dye or stain.
Artificial Intelligence (AI) Technology from Japan
Artificial intelligence (AI) can be used to assist in colonoscopy procedures as a way of developing higher quality detection through increased accuracy when identifying polyps, which are the most common cause of colon cancer. Some polyps are so tiny or hidden away that a traditional colonoscopy makes them difficult to spot. However, doctors using AI technology are now more likely to detect such polyps. Additionally, AI can also help to reduce colonoscopy procedure times, giving doctors the feeling of having an extra pair of hands and eyes when trying to spot polyps located in the patient’s colon. This allows for the polyps to be removed immediately during the colonoscopy, avoiding unnecessary hospital stays and surgeries for patients.