Frontiers in Endocrinology (Oct 2023)

Biological and clinical significance of radiomics features obtained from magnetic resonance imaging preceding pre-carbon ion radiotherapy in prostate cancer based on radiometabolomics

  • Guangyuan Zhang,
  • Guangyuan Zhang,
  • Guangyuan Zhang,
  • Zhenshan Zhang,
  • Zhenshan Zhang,
  • Zhenshan Zhang,
  • Yulei Pei,
  • Yulei Pei,
  • Yulei Pei,
  • Wei Hu,
  • Wei Hu,
  • Wei Hu,
  • Yushan Xue,
  • Yushan Xue,
  • Yushan Xue,
  • Renli Ning,
  • Renli Ning,
  • Renli Ning,
  • Xiaomao Guo,
  • Xiaomao Guo,
  • Xiaomao Guo,
  • Yun Sun,
  • Yun Sun,
  • Yun Sun,
  • Qing Zhang,
  • Qing Zhang,
  • Qing Zhang

DOI
https://doi.org/10.3389/fendo.2023.1272806
Journal volume & issue
Vol. 14

Abstract

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IntroductionWe aimed to investigate the feasibility of metabolomics to explain the underlying biological implications of radiomics features obtained from magnetic resonance imaging (MRI) preceding carbon ion radiotherapy (CIRT) in patients with prostate cancer and to further explore the clinical significance of radiomics features on the prognosis of patients, based on their biochemical recurrence (BCR) status.MethodsMetabolomic results obtained using high-performance liquid chromatography coupled with tandem mass spectrometry of urine samples, combined with pre-RT radiomic features extracted from MRI images, were evaluated to investigate their biological significance. Receiver operating characteristic (ROC) curve analysis was subsequently conducted to examine the correlation between these biological implications and clinical BCR status. Statistical and metabolic pathway analyses were performed using MetaboAnalyst and R software.ResultsCorrelation analysis revealed that methionine alteration extent was significantly related to four radiomic features (Contrast, Difference Variance, Small Dependence High Gray Level Emphasis, and Mean Absolute Deviation), which were significantly correlated with BCR status. The area under the curve (AUC) for BCR prediction of these four radiomic features ranged from 0.704 to 0.769, suggesting that the higher the value of these four radiomic features, the greater the decrease in methionine levels after CIRT and the lower the probability of BCR. Pre-CIRT MRI radiomic features were associated with CIRT-suppressed metabolites.DiscussionThese radiomic features can be used to predict the alteration in the amplitude of methionine after CIRT and the BCR status, which may contribute to the optimization of the CIRT strategy and deepen the understanding of PCa.

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