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直肠癌中的放射组学:应用现状与研究进展

Radiomics in rectal cancer: current status of use and advances in research.

作者信息

Huang Wei-Qin, Lin Ruo-Xuan, Ke Xiao-Hui, Deng Xiao-Hong, Ni Shi-Xiong, Tang Lina

机构信息

Department of Ultrasonography, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fudan University Shanghai Cancer Center, Fuzhou, China.

出版信息

Front Oncol. 2025 Jan 17;14:1470824. doi: 10.3389/fonc.2024.1470824. eCollection 2024.

DOI:10.3389/fonc.2024.1470824
PMID:39896183
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11782148/
Abstract

Rectal cancer is a leading cause of morbidity and mortality among patients with malignant tumors in China. In light of the advances made in therapeutic approaches such as neoadjuvant therapy and total mesorectal excision, precise preoperative assessment has become crucial for developing a personalized treatment plan. As an emerging technology, radiomics has gained widespread application in the diagnosis, assessment of treatment response, and analysis of prognosis for rectal cancer by extracting high-throughput quantitative features from medical images. Radiomics thus demonstrates considerable potential for optimizing clinical decision-making. In this paper, we reviewed recent research focusing on advances in the use of radiomics for managing rectal cancer. The review covers TNM staging of tumors, assessment of neoadjuvant therapy outcomes, and survival prediction. We also discuss the challenges and prospects for future developments in translational medicine, particularly the need for data standardization, consistent feature extraction methodologies, and rigorous model validation.

摘要

直肠癌是中国恶性肿瘤患者发病和死亡的主要原因之一。鉴于新辅助治疗和全直肠系膜切除术等治疗方法的进展,精确的术前评估对于制定个性化治疗方案至关重要。作为一种新兴技术,放射组学通过从医学图像中提取高通量定量特征,在直肠癌的诊断、治疗反应评估和预后分析中得到了广泛应用。因此,放射组学在优化临床决策方面显示出巨大潜力。在本文中,我们回顾了近期关于放射组学在直肠癌管理中应用进展的研究。该综述涵盖了肿瘤的TNM分期、新辅助治疗结果评估和生存预测。我们还讨论了转化医学未来发展面临的挑战和前景,特别是数据标准化、一致的特征提取方法和严格的模型验证的必要性。

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本文引用的文献

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Development and Validation of a Radiomics Model Based on Lymph-Node Regression Grading After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.基于新辅助放化疗后局部晚期直肠癌淋巴结消退分级的影像组学模型的开发与验证
Int J Radiat Oncol Biol Phys. 2023 Nov 15;117(4):821-833. doi: 10.1016/j.ijrobp.2023.05.027. Epub 2023 May 24.
2
MRI-Based Radiomic Models Outperform Radiologists in Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer.MRI 基放射组学模型在预测局部晚期直肠癌新辅助放化疗病理完全缓解方面优于放射科医生。
Acad Radiol. 2023 Sep;30 Suppl 1:S176-S184. doi: 10.1016/j.acra.2022.12.037. Epub 2023 Feb 2.
3
Radiomics Approaches for the Prediction of Pathological Complete Response after Neoadjuvant Treatment in Locally Advanced Rectal Cancer: Ready for Prime Time?基于影像组学方法预测局部晚期直肠癌新辅助治疗后的病理完全缓解:已准备好进入黄金时代了吗?
Cancers (Basel). 2023 Jan 9;15(2):432. doi: 10.3390/cancers15020432.
4
Whole-liver enhanced CT radiomics analysis to predict metachronous liver metastases after rectal cancer surgery.全肝增强 CT 放射组学分析预测直肠癌术后肝转移的发生。
Cancer Imaging. 2022 Sep 11;22(1):50. doi: 10.1186/s40644-022-00485-z.
5
Endorectal ultrasound radiomics in locally advanced rectal cancer patients: despeckling and radiotherapy response prediction using machine learning.直肠内超声放射组学在局部进展期直肠癌患者中的应用:使用机器学习进行去斑处理和放疗反应预测。
Abdom Radiol (NY). 2022 Nov;47(11):3645-3659. doi: 10.1007/s00261-022-03625-y. Epub 2022 Aug 11.
6
Development and External Validation of a Preoperative Nomogram for Predicting Lateral Pelvic Lymph Node Metastasis in Patients With Advanced Lower Rectal Cancer.预测晚期低位直肠癌患者侧方盆腔淋巴结转移的术前列线图的开发与外部验证
Front Oncol. 2022 Jul 8;12:930942. doi: 10.3389/fonc.2022.930942. eCollection 2022.
7
Pre-Treatment Computed Tomography Radiomics for Predicting the Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Retrospective Study.治疗前计算机断层扫描影像组学预测局部晚期直肠癌新辅助放化疗疗效的回顾性研究
Front Oncol. 2022 May 10;12:850774. doi: 10.3389/fonc.2022.850774. eCollection 2022.
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MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy.MRI影像组学模型预测直肠癌放化疗后的病理完全缓解情况。
Radiology. 2022 May;303(2):351-358. doi: 10.1148/radiol.211986. Epub 2022 Feb 8.
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Radiomics Features at Multiparametric MRI Predict Disease-Free Survival in Patients With Locally Advanced Rectal Cancer.多参数 MRI 放射组学特征预测局部进展期直肠癌患者无病生存。
Acad Radiol. 2022 Aug;29(8):e128-e138. doi: 10.1016/j.acra.2021.11.024. Epub 2021 Dec 24.
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Lancet Digit Health. 2022 Jan;4(1):e8-e17. doi: 10.1016/S2589-7500(21)00215-6.