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

前列腺癌 医学 无线电技术 磁共振成像 接收机工作特性 生化复发 代谢组学 断点群集区域 碳离子放射治疗 放射治疗 核医学 肿瘤科 癌症 内科学 放射科 生物信息学 生物 受体 前列腺切除术
作者
Guangyuan Zhang,Zhenshan Zhang,Yulei Pei,Wei Hu,Yushan Xue,Renli Ning,Xiaomao Guo,Yun Sun,Qing Zhang
出处
期刊:Frontiers in Endocrinology [Frontiers Media]
卷期号:14 被引量:1
标识
DOI:10.3389/fendo.2023.1272806
摘要

Introduction We 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. Methods Metabolomic 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. Results Correlation 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. Discussion These 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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