Radiation therapy


Avasopasem Shields Normal Cells from Radiation, Helps Kill Cancer Cells

What is the aim of Cancer treatments? Cancer treatments aim to kill cancer cells. Other treatments often used to help people with cancer, called supportive therapies, protect normal tissues or make the side effects from cancer treatments more bearable. What if one drug could play both of these roles at the same time? In new studies in mice, researchers found that a drug called avasopasem manganese (AVA), which has been found to protect normal tissues from radiation therapy, can also make cancer cells more vulnerable to radiation treatment. AVA provides this dual effect by exploiting the differences in the way normal and tumour cells produce hydrogen peroxide, explained Douglas Spitz, PhD, professor of radiation oncology at the University of Iowa, who helped lead the study. With any cancer treatment, “you try to find this sweet spot where you’re balanced between an effective therapeutic dose for killing cancer cells, but not causing excessive harm to normal tissues,” said Michael Espey, PhD, of NCI’s Division of Cancer Treatment and Diagnosis, who was not involved in the study. “If you can [have a single drug that] lowers the toxicity in normal tissues while increasing the toxicity in cancer cells, then you really have sort of a game-changer.” More work is needed to see if the effects observed in mice can be replicated in people. But in April, Galera Therapeutics, which manufactures AVA, reported positive findings from a small clinical trial of AVA added to a targeted form of radiation therapy in people with pancreatic cancer. Two other ongoing clinical trials are also testing AVA in combination with radiation therapy in lung and pancreatic cancer. Building on Cells’ Natural Defense Mechanisms In radiation therapy, high doses of x-rays or other charged particles are aimed at a tumour. The radiation can damage cancer cells’ DNA to the point where the cells stop dividing or die. While a single radiation dose is administered in minutes, many of the resulting changes in cells that cause them to die take days to occur. When a dose of radiation hits a cell, its high energy creates compounds called free…

Research News

Artificial intelligenc can jump-start radiation therapy for cancer patients

instantly generates dosage plan, avoids potentially crucial delay DALLAS – Jan. 27, 2020 – Artificial intelligence can help cancer patients start their radiation therapy sooner – and thereby decrease the odds of the cancer spreading – by instantly translating complex clinical data into an optimal plan of attack. Patients typically must wait several days to a week to begin therapy while doctors manually develop treatment plans. But new research from UT Southwestern shows how enhanced deep-learning models streamlined this process down to a fraction of a second. “Some of these patients need radiation therapy immediately, but doctors often have to tell them to go home and wait,” says Steve Jiang, Ph.D., who directs UT Southwestern’s Medical Artificial Intelligence and Automation (MAIA) Lab. “Achieving optimal treatment plans in near real time is important and part of our broader mission to use AI to improve all aspects of cancer care.” Radiation therapy : A common form of cancer treatment Radiation therapy is a common form of cancer treatment that utilizes high radiation beams to destroy cancer cells and shrink tumors. Previous research shows that delaying this therapy by even a week can increase the chance of some cancers either recurring or spreading by 12-14 percent. Such statistics motivated Jiang’s team to explore methods of using AI to improve multiple facets of radiation therapy – from the initial dosage plans required before the treatment can begin to the dose recalculations that occur as the plan progresses. Jiang says developing a sophisticated treatment plan can be a time-consuming and tedious process that involves careful review of the patient’s imaging data and several phases of feedback within the medical team. Study published in Medical Physics A new study from the MAIA Lab on dose prediction, published in Medical Physics, demonstrated AI’s ability to produce optimal treatment plans within five-hundredths of a second after receiving clinical data for patients. Researchers achieved this by feeding the data for 70 prostate cancer patients into four deep-learning models. Through repetition, the AI learned to develop 3D renderings of how best to distribute the radiation in each patient. Each model…