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Prognostic 18F-FDG Radiomic Features in Advanced High-Grade Serous Ovarian Cancer.

Daniela Travaglio Morales1,2, Carlos Huerga Cabrerizo3, Itsaso Losantos García4

  • 1Nuclear Medicine Department, La Paz University Hospital, 28046 Madrid, Spain.

Diagnostics (Basel, Switzerland)
|November 24, 2023
PubMed
Summary
This summary is machine-generated.

Radiomic features from 18F-FDG PET scans can predict outcomes in high-grade serous ovarian cancer (HGSOC). Specific features like GLRLM_RLNU and Kurtosis show prognostic value for disease-free and overall survival, respectively.

Keywords:
PETheterogeneityovarian cancerprognosisradiomicstexture features

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging

Background:

  • High-grade serous ovarian cancer (HGSOC) is aggressive with variable outcomes, potentially due to tumor heterogeneity.
  • 18F-FDG PET radiomics offer a way to analyze tumor heterogeneity, but its prognostic role in HGSOC requires further study.

Purpose of the Study:

  • To evaluate the prognostic significance of pretreatment 18F-FDG PET radiomic features in patients with advanced HGSOC.

Main Methods:

  • Retrospective analysis of 36 advanced HGSOC patients (2016-2020).
  • Extraction of radiomic features from pretreatment 18F-FDG PET scans.
  • Correlation of radiomic features with disease-free survival (DFS) and overall survival (OS) using ROC/median cutoffs.

Main Results:

  • GLRLM_RLNU, GLSZM_ZSNU, and Total Lesion Glycolysis (TLG) were significantly associated with DFS.
  • GLRLM_RLNU demonstrated a significant difference in DFS (p=0.035), maintaining significance in multivariate analysis (p=0.048).
  • Intensity-based Kurtosis showed a significant association with OS (p=0.027).

Conclusions:

  • Pretreatment 18F-FDG PET radiomic features, including GLRLM_RLNU, GLSZM_ZSNU, and Kurtosis, hold prognostic value for patients with advanced HGSOC.
  • These radiomic parameters may aid in predicting disease-free and overall survival, offering insights into tumor behavior.