Student builds algorithm to help improve the results of radiotherapy for pancreatic cancer patients

Rishab Jain, born in 2005, in the USA, was a middle school student when he invented a tool to help doctors improve the results of radiotherapy for pancreatic cancer patients using artificial intelligence. He created this tool after a family friend died of pancreatic cancer.

Rishab was interested in science from an early age, having to program when he was seven years old. He got interested in treatments for pancreatic cancer after a family friend died of that condition.

“Radiotherapy is the treatment that’s used in some stages of pancreatic cancer to help shrink a tumour down to a point at which can be surgically removed,” the boy explained.

The student created an algorithm that uses images of the human digestive system and found it could correctly detect the pancreas with a 98.9 percent success rate. The student’s solution makes the radiotherapy treatment more efficient by honing in on the exact location of the pancreas. “Currently, when patients are in a CT or MRI-guided radiotherapy machine, doctors have to manually adjust for any errors of the pancreas moving due to breathing or anatomical changes and size of the body. Currently, when patients are in a CT or MRI-guided radiotherapy machine, doctors have to manually adjust for any errors of the pancreas moving due to breathing or anatomical changes and size of the body. Sometimes the radiation can hit healthy cells and end up killing them. It can cause side effects and other serious issues. What my tool does, in real-time — meaning instantaneously whenever the scans from CT or MRI machine are outputted — is takes those scans in and locate exactly where the pancreas is so the radiotherapy can be applied effectively to that spot”, he detailed.

The innovation aims to improve accuracy, reduce invasiveness and increase efficiency during treatment, resulting in a better quality of life and chance for survival among patients.

The inventor had the help of Dr. Döne Demirgöz, a 3M corporate supply chain black belt and product development and research expert, who guaranteed this tool has an accuracy rate of more than 80 percent.

He won the Discovery Education 3M Young Scientist Challenge in 2018.

RIshab hopes to become a surgeon.

Adapted from: https://bit.ly/2pczklS