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Evaluation of endometrial cancer subtypes with metabolic, volumetric, and tumor heterogeneity parameters obtained from F-18 FDG PET/CT imaging

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2024
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Abstract (EN)

The aim of the study is to examine the relationship between endometrial cancer subtypes and lymph node metastasis status and texture parameters reflecting metabolic, volumetric, and tumor heterogeneity of the primary tumor obtained from F-18 FDG PET/CT images. 159 patients who underwent F-18 FDG PET/CT imaging for staging purposes with the diagnosis of endometrial cancer were included in the study. Age, body mass index, primary tumor subtypes, grades, and lymph node metastasis status of the cases were determined. The cases were grouped in two seperate ways, first according to the primary tumor subtypes and then to lymph node metastasis status. Images were evaluated in the LIFEx program. By getting the primary tumor segmented, texture features reflecting metabolic, volumetric, and tumor heterogeneity were obtained. The relationships between these parameters and the groups were examined. MTV, TLG, SUVmax, SUVmean, and SUVmin values were found to be higher in type 2 endometrial cancer patients. When these parameters are examined with logistic regression analysis; it is seen that the most effective parameter on type 2 endometrial cancer was SUVmin. SUVmin and TLG values were higher in patients with lymph node metastases. Considering the texture parameters, while the parameters reflecting heterogeneity are observed to be high in high-risk endometrial cancers and patients with lymph node metastases, the parameters reflecting homogeneity are found to be high in low-grade endometrial cancers and patients without lymph node metastases. In our study, we showed that metabolic and volumetric parameters of the primary tumor obtained from F-18 FDG PET/CT imaging and radiomics data reflecting tumor heterogeneity can contribute to distinguishing endometrial cancer types and predicting lymph node metastasis.

Author

Samet Yağcı

How to Cite

Samet Yağcı (Medical Specialty Thesis). Evaluation of endometrial cancer subtypes with metabolic, volumetric, and tumor heterogeneity parameters obtained from F-18 FDG PET/CT imaging, 2024, Süleyman Demirel University.

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