Use artificial intelligence to prevent the harm caused by immunotherapy

Researchers at Case Western Reserve University use artificial intelligence (AI) to analyze simple tissue scans and discover biomarkers that can tell doctors about lung cancer patients that may actually get worse with immunotherapy. It states that it did.

Use artificial intelligence to prevent the harm caused by immunotherapy

Until recently, researchers and oncologists have categorized these lung cancer patients into two major categories: those who benefit from immunotherapy and those who do not.

However, a third category, the emergence of patients called hyperprogressors who are actually harmed by immunotherapy, such as shortening lifespan after treatment, is a doctoral student in biomedical engineering and a university student. Prajal Vaidya, a researcher at the Computational Center, said. Imaging and personalized diagnosis (CCIPD).

“This is an important subset of patients who may completely avoid immunotherapy,” said Vaidya, the lead author of a 2020 paper that published the findings of the Journal for Immunotherapy of Cancer.

“Ultimately, we need to integrate this into the clinical setting so that doctors have all the information they need to call individual patients,” Vaidya added.

According to National Cancer, immunotherapy currently uses drugs to help the immune system fight cancer, whereas chemotherapy uses drugs to kill cancer cells directly. Is a different treatment. Laboratory.

Leaded by Anant Madabhushi, a professor of biomedical engineering at the Donnell Institute, CCIPD has become a world leader in the detection, diagnosis and characterization of a variety of cancers and other diseases by combining medical imaging, machine learning and AI.

This new study follows other recent studies by CCIPD scientists who have demonstrated that AI and machine learning can be used to predict which lung cancer patients will benefit from immunotherapy.

In this and previous studies, Case Western Reserve and Cleveland Clinic scientists were basically looking for and identifying patterns of CT scans performed when lung cancer was first diagnosed and known before treatment. I’m teaching my computer to reveal information that might have been useful.

And while many cancer patients are benefiting from immunotherapy, researchers are looking for better ways to identify who is most likely to respond to those treatments.

“This is an important finding because the radioactive patterns from routine CT scans can identify three types of reactions in lung cancer patients receiving immunotherapy treatment: responders, non-responders, and hyperadvancers. “Because it shows,” said senior author Madabushi. Of research.

“Currently, there are no validated biomarkers to distinguish this subset of high-risk patients who not only benefit from immunotherapy but can actually cause a rapid acceleration of the disease during treatment.” , Pradnya Patil, MD, FACP, associate staff member of Taussig Cancer. Institute, Cleveland Clinic, and research author.

“Analysis of radioactivity in routine scans prior to treatment may provide a non-invasive means of identifying these patients,” Patil said.

“This can be an invaluable tool for treating clinicians while determining the optimal systemic therapy for patients with advanced non-small cell lung cancer,” Patil added.

As with other previous cancer studies at CCIPD, scientists have rediscovered some of the most important clues that patients will be harmed by immunotherapy outside the tumor.

“We found that the radiation characteristics outside the tumor were more predictive than those inside the tumor, and that changes in the blood vessels surrounding the nodules were also more predictive,” Vaidya said.

She said the latest study was conducted using data collected from 109 patients with non-small cell lung cancer being treated with immunotherapy.

This story was published from the Wire Agency Feed without changing the text.