Thursday, November 30 | 3:10 p.m.-3:20 p.m. | R1-SSRO04-6 | Room S502
In this presentation, researchers will demonstrate how diffusion-weighted imaging MRI (DWI-MRI) may enhance chemoradiotherapy response prediction of early treatment timepoints for cervical cancer.
In her talk, Megan Jacobsen, PhD, from University of Texas MD Anderson Cancer Center, will talk about her team’s research, which found that apparent diffusion coefficient data from DWI-MRI showed slightly less restricted diffusion during the first two weeks of chemoradiotherapy in women with favorable human papillomavirus (HPV) circulating tumor DNA response, a fluid-based biomarker.
Previous reports indicate that chemoradiotherapy response in HPV-related cervical cancers corresponds with decreases in tumor volume on T2-weighted MRI and increases in apparent diffusion coefficient from diffusion-weighted imaging. However, the researchers pointed out that imaging throughout radiotherapy can be poor at predicting recurrence.
They hypothesized that HPV-specific circulating tumor DNA, along with MRI, could better predict long-term patient outcomes based on immunologic response to HPV. The team included data from nine women with locally advanced cervical cancer. The women also had T2-weighted MRI and DWI-MRI at baseline.
The researchers found that the average apparent diffusion coefficient increased in both HPV circulating tumor DNA responders and nonresponders. They reported that the largest differences happened at baseline and week two.
They also found that all women showed volume decreases of at least 53% between baseline and completion of external beam radiotherapy. However, the team also reported no significant difference in normalized tumor volume between patients who did or did not clear HPV circulating tumor DNA.
The group suggested that HPV circulating tumor DNA adds complementary data for immunologic response that is not fully seen MRI metrics alone. The team added that its results validate prospective correlative studies and outcomes modeling in predicting chemoradiotherapy response in cervical cancer.
Find out all of the details in this session.