New CT Scan Technique to Improve Prognosis and Treatments for Head and Neck Cancers

By MedImaging International staff writers
Posted on 27 Feb 2025

Image: Data collected in pre-treatment CT-scans may provide important imaging biomarkers to better predict patient prognosis (Photo courtesy of Shutterstock)

Cancers of the mouth, nose, and throat are becoming increasingly common in the U.S., particularly among younger individuals. Approximately 60,000 new cases are diagnosed annually, with 20% of these cases occurring in individuals under the age of 55. Despite improvements in surgical methods and other treatments, the five-year survival rate for head and neck squamous cell carcinoma (HNSCC) remains around 50%. Risk factors for HNSCC include tobacco use, alcohol consumption, and certain strains of Human Papillomavirus (HPV). The typical treatment for these cancers involves surgical tumor removal, radiation therapy to the affected area, and chemotherapy, immunotherapy, or a combination of these treatments. However, these therapies can lead to severe and sometimes permanent side effects that impact a patient’s ability to see, swallow, or speak. A new study now offers new insights that could ultimately help oncologists predict how the disease will respond to various treatments, leading to better survival outcomes for patients.

Researchers from the University of Maryland (Baltimore, MD, USA) conducted a study analyzing pre-treatment CT scans from patients with head and neck squamous cell carcinoma (HNSCC) to identify radiomic biomarkers that could predict the aggressiveness of the disease and its response to treatment. CT scans are routinely used as a pre-treatment diagnostic tool for HNSCC patients and help oncologists formulate personalized treatment plans. In this study, published in Scientific Reports, the researchers examined data from 203 patients at the University of Maryland Greenebaum Comprehensive Cancer Center (UMGCCC) and 77 patients from the MD Anderson Cancer Center, dating back to 2003. Using advanced radiomics, which applies complex mathematical and statistical algorithms, the team identified tumor characteristics that are not visible to the naked eye. These biomarkers were then used to create predictive models that focused on the likelihood of progression-free survival following treatment.

The findings indicated that these radiomic biomarkers could provide valuable insights into which patients are most likely to benefit from specific treatments. The researchers discovered that incorporating radiomic biomarkers into treatment planning may enable oncologists to recommend less invasive therapies, thereby reducing the risk of long-term side effects. In future studies, the team hopes to deepen their understanding of these imaging biomarkers, validating their findings with data from other institutions. This research will need to be completed before a prospective clinical trial can be conducted, where treatment interventions could be guided by imaging biomarkers and predictive models. For example, patients with biomarkers indicative of less aggressive disease might be given a reduced radiation protocol.

“Integrating prognostic and predictive biomarkers into clinical care could help to provide more targeted therapies, leading to improved survival outcomes for patients,” said the study’s senior author, Lei Ren, PhD. “The findings from this study pave the way for future investigations through larger clinical trials to further evaluate the clinical efficacy of radiomics biomarkers for progression-free survival prediction in HNSCC patients.”