Dr. Essel on Quantitative Computed Tomography Image Feature Analysis in Gynecologic Cancers | OncLive

Dr. Essel on Quantitative Computed Tomography Image Feature Analysis in Gynecologic Cancers

January 19, 2019

Kathleen G. Essel, MD, gynecologic oncology fellow at the University of Oklahoma Health Science Center with the Stephenson Cancer Center, discusses the benefits of using quantitative computed tomography image feature analysis to predict response to immune checkpoint inhibitors in patients with gynecologic cancers.

Kathleen G. Essel, MD, fellow at the University of Oklahoma Health Science Center with the Stephenson Cancer Center, discusses the benefits of using quantitative computed tomography (CT) image feature analysis to predict response to immune checkpoint inhibitors in patients with gynecologic cancers.

In a recent trial, Essel and colleagues set out to prove the hypothesis that quantitative image feature analysis computed from CT images prior to and following the start of therapy with an immune checkpoint inhibitor would better predict patient response to treatment than conventional RECIST and immune RECIST criteria and they were successful. The analysis was found to accurately predict response to these inhibitors in patients with recurrent gynecologic cancer.

Essel says that not only is it a very useful tool, it is a cost-effective one compared with other imaging tools that have been explored, such as MRIs or PET CTs, which are also very hard to access in rural areas without many academic health centers. CTs are much more universal, she adds; they’re a quick, viable option that will help providers figure out whether a patient is responsive to treatment. Prospective clinical trials incorporating this tool into immunotherapy studies are needed, Essel concludes.

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