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直肠癌肿瘤及瘤周区域在MRI中的多模态放射组学研究进展

Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI.

作者信息

Gong Tingting, Gao Ying, Li He, Wang Jianqiu, Li Zili, Yuan Qinghai

机构信息

The Second Affiliated Hospital of Jilin University, Jilin Province, China.

Jilin Province Cancer Hospital, Jilin Province, China.

出版信息

Abdom Radiol (NY). 2025 May 31. doi: 10.1007/s00261-025-04965-1.

Abstract

Rectal cancer (RC) is one of the most common malignant tumors of the digestive system and has an alarmingly high incidence and mortality rate globally. Compared to conventional imaging examinations, radiomics can extract quantitative features that reflect tumor heterogeneity and mine data from medical images. In this review, we discuss the potential value of multimodal MRI-based radiomics in the diagnosis and treatment of RC, with a special emphasis on the role of peritumoral tissue characteristics in clinical decision-making. Existing studies have shown that a radiomics model integrating intratumoral and peritumoral characteristics has good application prospects in RC staging evaluation, efficacy prediction, metastasis monitoring, recurrence early warning, and prognosis judgment. At the same time, this paper also objectively analyzes the existing methodological limitations in this field, including insufficient data standardization, inadequate model validation, limited sample size and poor reproducibility of results. By combining existing evidence, this review aimed to enhance the attention of clinicians and radiologists on the characteristics of peritumoral tissues and promote the translational application of radiomics technology in the individualized treatment of RC.

摘要

直肠癌(RC)是消化系统最常见的恶性肿瘤之一,在全球范围内其发病率和死亡率高得惊人。与传统成像检查相比,放射组学可以从医学图像中提取反映肿瘤异质性的定量特征并挖掘数据。在本综述中,我们讨论基于多模态磁共振成像(MRI)的放射组学在直肠癌诊断和治疗中的潜在价值,特别强调肿瘤周围组织特征在临床决策中的作用。现有研究表明,整合肿瘤内和肿瘤周围特征的放射组学模型在直肠癌分期评估、疗效预测、转移监测、复发预警和预后判断方面具有良好的应用前景。同时,本文也客观分析了该领域现有方法学的局限性,包括数据标准化不足、模型验证不充分、样本量有限以及结果可重复性差等问题。通过结合现有证据,本综述旨在提高临床医生和放射科医生对肿瘤周围组织特征的关注,并促进放射组学技术在直肠癌个体化治疗中的转化应用。

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