Dr. Essel on Rationale to Explore Quantitative CT Image Feature Analysis in Gynecologic Cancers

Kathleen G. Essel, MD
Published: Saturday, Nov 09, 2019



Kathleen G. Essel, MD, gynecologic oncology fellow, Stephenson Cancer Center, University of Oklahoma, discusses the rationale to explore quantitative computed tomography (CT) image feature analysis in gynecologic cancers.

Immunotherapy is used in several gynecologic cancers; however, it is unknown which patients within each indication are the most likely to benefit from the approach. Notably, investigators in melanoma have been able to identify 4 distinct types of response to immunotherapy. The first 2 types of responses were reflective of how responses are typically evaluated after chemotherapy in gynecologic cancers, says Essel. In the latter types, investigators noted that the tumor grows before it gets smaller, or that the primary tumor shrinks and new lesions develop, even though the overall tumor burden is reduced.

These data suggest that traditional RECIST criteria are not sufficient to evaluate response to immune checkpoint inhibitors, explains Essel. As such, Essel and colleagues sought to evaluate the use of quantitative CT image feature analysis as an alternative to RECIST criteria in predicting response to immunotherapy.
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Kathleen G. Essel, MD, gynecologic oncology fellow, Stephenson Cancer Center, University of Oklahoma, discusses the rationale to explore quantitative computed tomography (CT) image feature analysis in gynecologic cancers.

Immunotherapy is used in several gynecologic cancers; however, it is unknown which patients within each indication are the most likely to benefit from the approach. Notably, investigators in melanoma have been able to identify 4 distinct types of response to immunotherapy. The first 2 types of responses were reflective of how responses are typically evaluated after chemotherapy in gynecologic cancers, says Essel. In the latter types, investigators noted that the tumor grows before it gets smaller, or that the primary tumor shrinks and new lesions develop, even though the overall tumor burden is reduced.

These data suggest that traditional RECIST criteria are not sufficient to evaluate response to immune checkpoint inhibitors, explains Essel. As such, Essel and colleagues sought to evaluate the use of quantitative CT image feature analysis as an alternative to RECIST criteria in predicting response to immunotherapy.



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