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Prognostic Value of Pseudotime from Texture Parameters of [18F]fluorodeoxyglucose PET/CT in Resectable Pancreatic Ductal Adenocarcinoma

Research output: Contribution to journalArticlepeer-review

Abstract

Rationale and Objectives This study evaluates the prognostic value of pseudotime derived from radiomics texture parameters on [18F]fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) images of resectable pancreatic ductal adenocarcinoma (PDAC) patients. Materials and Methods We retrospectively analyzed data from 711 patients who underwent FDG PET/CT before surgery. We extracted 56 radiomics features and calculated the pseudotime, a continuous metric estimating disease progression, using the Phenopath algorithm. Clinicopathologic features and other conventional PET parameters were also obtained. Correlation analyses were performed between the conventional PET parameters and pseudotime, and survival analysis was performed according to the clinicopathologic variables. Results Correlation analysis revealed that pseudotime correlates weakly with SUVmax and SUVmean and strongly with the metabolic tumor volume (MTV) and total lesion glycolysis (TLG). A multivariate survival analysis revealed that pseudotime is an independent predictor of disease-free survival (hazard ratio [HR] = 1.67, p < 0.001, c-index = 0.59), showing stronger prognostic performance than MTV (HR = 1.48, p = 0.009, c = 0.57) and TLG (HR = 1.39, p = 0.03, c = 0.56). When pseudotime was combined with TLG for risk stratification, the integrated model demonstrated the strongest prognostic separation among subgroups. Texture parameters related to homogeneity correlated positively with pseudotime, and those representing heterogeneity showed mixed correlations, highlighting the complexity of tumor biology. Conclusion Our findings indicate that pseudotime is a meaningful prognostic biomarker in resectable PDAC patients undergoing surgery, with stronger predictive power than established metabolic parameters. Stratification performance improved when it was combined with conventional markers.

Original languageEnglish
Pages (from-to)189-200
Number of pages12
JournalAcademic Radiology
Volume33
Issue number1
DOIs
StatePublished - Jan 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Pancreatic cancer
  • Prognosis
  • Pseudotime analysis
  • Radiomics
  • [F]fluorodeoxyglucose

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