Radiation therapy, also known as radiotherapy, refers to a therapy that uses ionizing radiation often as part of treatment against cancer. It works towards controlling or killing malignant cells and is generally delivered through a linear accelerator. This sort of therapy has efficacious for a number of cancer forms in cases where the disease is localized to a certain part of the body. Further, radiation therapy might also work as part of adjuvant therapy that prevents recurrence of tumors after an individual undergoes surgery for removal of a primary malignant tumor, such as the initial stages of breast cancer.
Now a research team is working towards developing an AI (Artificial Intelligence) aimed towards personalizing the treatment of patients through improvements within the quality of imaging during the treatment. This would help in predicting and accounting for all changes that occur in the anatomy of an individual over time so that a radiation delivery could be automatically adopted. The newly developed AI algorithm would be a huge advancement for Radiotherapy Market as it is likely to improve the precision and accuracy, and overall treatment of a patient undergoing radiation.
The team’s objective was to use state-of-the-art AI techniques for the optimization of online adaptive radiotherapy. The new therapy would work towards changes that may occur in a patient during the process of treatment. Thereafter the technique can ‘adapt’ the original prescription day-after-day as per the necessities to ensure the right dose is given at the right time to the correct body part with less to no damages to the patient’s healthy tissues. This aspect is one of the substantial challenges of all cancer treatment sessions as tumors evolve continuously and their shape changes over time. Till now, it was impossible to work around this problem because of the computational and workflow complexities; however, AI might provide a reasonable solution in the near future.
The team stated that deep learning approaches would be used to address all challenges present within modern radiation oncology, such as speed, precision, and personalization. The researchers involved looking forward to identifying the elements of the radiotherapy process, including strategies to detect and adapt towards changes in any patient’s anatomy, quality of treatment images, and methods that help personalize the treatment plans.
The primary goal for the present study is not only to create extraordinarily novel AI algorithms but also they can potentially be applied to clinical practices so that patients have the opportunity to receive better treatments.
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