影像组学在宫颈癌中的研究及应用进展

ISSN:2705-098X(P)

EISSN:2705-0505(O)

语言:中文

作者
刘文淼,尹桂秀
文章摘要
本文通过整合、分析近5年宫颈癌及影像组学相关的文献,发现影像组学在宫颈癌中的应用十分广泛,涵盖诊断、治疗反应评估、预后预测等多个方面,可实现对宫颈癌的诊断、治疗决策、治疗效果的早期评估和个体化预测,影像组学在宫颈癌中的应用潜力显著。本文系统地回顾和分析近五年来影像组学在宫颈癌中的研究现状、技术进展及未解决的问题,为该领域的进一步研究提供参考。
文章关键词
宫颈癌;影像组学;研究进展
参考文献
[1] Yao H,Yan C,Qiumin H,et al.Epidemiological Trends and Attributable Risk Burden of Cervical Cancer:An Observational Study from 1990 to 2019.Int J Clin Pract,2022,2022:3356431. [2] Li D,Huang S,Liu K,et al.Clinicopathological characteristics and survival outcomes in human papillomavirus independent cervical cancer:a propensity score matched analysis.Int J Gynecol Cancer,2022,32(5):599-605. [3] Lévi-Strauss T,Tortorici B,Lopez O,et al.Radiomics,a Promising New Discipline:Example of Hepatocellular Carcinoma.Diagnostics (Basel),2023,13(7):1303. [4] Huang W,Tao Z,Younis MH,et al.Nuclear medicine radiomics in digestive system tumors:Concept,applications,challenges,and future perspectives.View(Beijing),2023,4(6):20230032[pii]. [5] Liu X,Elbanan MG,Luna A,et al.Radiomics in Abdominopelvic Solid-Organ Oncologic Imaging:Current Status.AJR Am J Roentgenol, 2022,219(6):985-995. [6] Huang X,Wang X,Lan X,et al.The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer:A mini review.Front Oncol,2022,12:990176. [7] Han X,Guan J,Guo L,et al.A CT-based interpretable deep learning signature for predicting PD-L1 expression in bladder cancer:a two- center study.Cancer Imaging,2025,25(1):27. [8] Fang Y,Zhang Q,Yan J,et al.Application of radiomics in acute and severe non-neoplastic diseases:A literature review.J Crit Care, 2025,87:155027. [9] Chen X,Liu W,Thai TC,et al.Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients.Comput Methods Programs Biomed,2020,197:105759. [10] Pei J,Yu J,Ge P,et al.Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.Technol Cancer Res Treat,2024,23:15330338241298554. [11] Wu F,Zhang R,Li F,et al.Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer.Front Med(Lausanne),2024,11:1336640. [12] Xia X,Li D,Du W,et al.Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer. Diagnostics(Basel),2022,12(10):2446. [13] Wang W,Jiao Y,Zhang L,et al.Multiparametric MRI-based radiomics analysis:differentiation of subtypes of cervical cancer in the early stage.Acta Radiol,2022,63(6):847-856. [14] Liu Y,Song T,Dong TF,et al.MRI-based radiomics analysis to evaluate the clinicopathological characteristics of cervical carcinoma:a multicenter study.Acta Radiol,2023,64(1):395-403. [15] Tang S,Yen A,Wang K,et al.Progression-Free Survival Prediction for Locally Advanced Cervical Cancer After Chemoradiotherapy With MRI-based Radiomics.Clin Oncol(R Coll Radiol),2025,38:103702. [16] Cepero A,Yang Y,Young L,et al.Longitudinal FDG-PET Radiomics for Early Prediction of Treatment Response to Chemoradiation in Locally Advanced Cervical Cancer:A Pilot Study.Cancers(Basel),2024,16(22):3813. [17] Xue J,Wu M,Zhang J,et al.Delta-radiomics analysis based on magnetic resonance imaging to identify radiation proctitis in patients with cervical cancer after radiotherapy.Front Oncol,2025,15:1523567. [18] Zhang Y,Liu L,Zhang K,et al.Nomograms Combining Clinical and Imaging Parameters to Predict Recurrence and Disease-free Survival After Concurrent Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer.Acad Radiol,2023,30(3):499-508. [19] Kawahara D,Nishibuchi I,Kawamura M,et al.Radiomic Analysis for Pretreatment Prediction of Recurrence Post-Radiotherapy in Cervical Squamous Cell Carcinoma Cancer.Diagnostics(Basel),2022,12(10):2346. [20] Bseiso A,Saqib M,Saigol MS,et al.Patient survival prediction in locally advanced cervical squamous cell carcinoma using MRI-based radiomics:retrospective cohort study.Ann Med Surg(Lond),2023,85(11):5328-5336. [21] Sun Z,Wang W,Huang W,et al.Noninvasive imaging evaluation of peritoneal recurrence and chemotherapy benefit in gastric cancer after gastrectomy:a multicenter study.Int J Surg,2023,109(7):2010-2024. [22] Cai Z,Li S,Xiong Z,et al.Multimodal MRI-based deep-radiomics model predicts response in cervical cancer treated with neoadjuvant chemoradiotherapy.Sci Rep,2024,14(1):19090. [23] Xin W,Rixin S,Linrui L,et al.Machine learning-based radiomics for predicting outcomes in cervical cancer patients undergoing concurrent chemoradiotherapy.Comput Biol Med,2024,177:108593. [24] Yu Z,Zhihui Q,Linrui L,et al.Machine Learning-Based Models for Assessing Postoperative Risk Factors in Patients with Cervical Cancer.Acad Radiol,2024,31(4):1410-1418.
Full Text:
DOI