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Prognostic Value of [

Lieke C E Pullen1, Wyanne A Noortman1,2, Lianne Triemstra3

  • 1Biomedical Photonic Imaging Group, University of Twente, 7522 NB Enschede, The Netherlands.

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Summary
This summary is machine-generated.

[18F]FDG-PET radiomics did not improve the identification of metastases in locally advanced gastric cancer. While a slight improvement was seen in intestinal and mixed-type tumors, the added benefit did not justify the complex analysis.

Keywords:
[18F]FDG-PET/CTgastric cancermachine learningradiomics

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging

Background:

  • Locally advanced gastric cancer presents challenges in identifying peritoneal and distant metastases.
  • Accurate preoperative staging is crucial for treatment planning and patient outcomes.

Purpose of the Study:

  • To evaluate the effectiveness of [18F]FDG-PET radiomics in improving the detection of peritoneal and distant metastases in locally advanced gastric cancer.
  • To compare the performance of clinical, radiomic, and clinicoradiomic models for metastasis identification.

Main Methods:

  • Analysis of [18F]FDG-PET scans from 206 patients in the prospective multicentre PLASTIC-study.
  • Extraction of 105 radiomic features and development of three classification models (clinical, radiomic, clinicoradiomic).
  • Model evaluation using Area Under the Curve (AUC) with repeated random splits and subgroup analysis based on Lauren classification.

Main Results:

  • All models demonstrated low performance in identifying metastases (AUCs 0.51-0.59).
  • Subgroup analysis for intestinal and mixed-type tumors showed a moderate AUC of 0.71 for the clinicoradiomic model, but no significant improvement for diffuse-type tumors.
  • The addition of radiomic features to the clinical model offered only a slight improvement in classification performance for intestinal and mixed-type tumors.

Conclusions:

  • [18F]FDG-PET-based radiomics did not significantly enhance preoperative identification of metastases in locally advanced gastric cancer.
  • The marginal improvement observed in specific tumor subtypes does not justify the extensive radiomic analysis due to its complexity and laboriousness.