New Delhi, December 27 (IANS). For patients suffering from head and neck cancer, a new tool based on Artificial Intelligence (AI) is proving to be helpful in better prognosis i.e. more accurately assessing the further outcomes of the disease. This technology helps doctors understand how effective cancer treatment may be in a patient and what the future risk is.
Dana-Farber & Mace General Brigham’s AI tool (ENE Predictor) is designed specifically for oropharyngeal cancer (a type of head and neck cancer). It tells patients how likely the cancer is to spread beyond the lymph nodes (nodes), called extranodal extension (ENE). Knowing the number of ENE is very important for prognosis (future condition).
“This tool enables us to identify which patients might benefit most from which treatment or who might be given immunotherapy or additional chemotherapy,” said senior author Benjamin Kahn of the Artificial Intelligence in Medicine (AIM) program at Mass General Brigham.
“Our tool is also able to identify which patients only need surgery,” Kahn said.
It was published in the Journal of Clinical Oncology.
Treatment of oropharyngeal cancer is fraught with complications. This includes methods like surgery, radiation therapy or chemotherapy. Preventing its negative effects can be quite painful. This AI tool lets patients know whether they need more aggressive treatment (such as chemotherapy or immunotherapy) or less (such as surgery only). This reduces side effects, such as difficulty in swallowing, speech problems or fatigue. Prognosis is available even before treatment, so that doctors can make better plans. It accurately predicts the spread and survival rate of cancer.
It analyzes the images of CT scan (computed tomography). The AI model estimates the number of lymph nodes with ENE from these images. In the past, diagnosing ENE required surgical removal of nodes and testing, but this tool is non-invasive—meaning it can be done without surgery. It can provide better results by taking into account clinical risk factors (such as age, tumor size).
Tests were conducted on 1,733 patients. The tool correctly identified patients who had a higher risk of cancer spreading and shorter survival. It was better than traditional models, especially in predicting survival and progression.
“The AI tool helps predict the number of lymph nodes with ENE. This has never been done before, and shows that this is a powerful, new prognostic biomarker for oropharyngeal cancer that can be used to improve existing staging schemes and treatment planning,” Kahn said.
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