| [1] |
Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA A Cancer J Clin, 2021, 71(3): 209-49. doi: 10.3322/caac.21660
|
| [2] |
Tripathi P, Guo WF, Rao SX, et al. Additional value of MRI-detected EMVI scoring system in rectal cancer: applicability in predicting synchronous metastasis[J]. Tumori J, 2020, 106: 286-94. doi: 10.1177/0300891620901745
|
| [3] |
Guiot J, Vaidyanathan A, Deprez L, et al. A review in radiomics: making personalized medicine a reality via routine imaging[J]. Med Res Rev, 2022, 42(1): 426-40. doi: 10.1002/med.21846
|
| [4] |
Riley RD, Ensor J, Snell KIE, et al. Calculating the sample size required for developing a clinical prediction model[J]. BMJ, 2020, 368: m441.
|
| [5] |
Horvat N, Carlos Tavares Rocha C, Clemente Oliveira B, et al. MRI of rectal cancer: tumor staging, imaging techniques, and management[J]. Radiographics, 2019, 39(2): 367-87. doi: 10.1148/rg.2019180114
|
| [6] |
Tang C, Lu GX, Xu JM, et al. Diffusion kurtosis imaging and MRIdetected extramural venous invasion in rectal cancer: correlation with clinicopathological prognostic factors[J]. Abdom Radiol, 2023, 48(3): 844-54.
|
| [7] |
Paul S, Arya S, Mokul S, et al. Extramural vascular invasion as an independent prognostic marker in locally advanced rectal cancer: propensity score match pair analysis[J]. Abdom Radiol, 2022, 47 (11): 3671-8. doi: 10.1007/s00261-022-03608-z
|
| [8] |
龚娇, 孙恒昌, 胡波. 列线图在肿瘤风险预测和预后评估中的应用[J]. 中华检验医学杂志, 2020, 43(6): 614-8.
|
| [9] |
Balachandran VP, Gonen M, Smith JJ, et al. Nomograms in oncology: more than meets the eye[J]. Lancet Oncol, 2015, 16(4): e173-80. doi: 10.1016/S1470-2045(14)71116-7
|
| [10] |
Scapicchio C, Gabelloni M, Barucci A, et al. A deep look into radiomics[J]. Radiol med, 2021, 126(10): 1296-311. doi: 10.1007/s11547-021-01389-x
|
| [11] |
Liu ZY, Wang S, Dong D, et al. The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges[J]. Theranostics, 2019, 9(5): 1303-22. doi: 10.7150/thno.30309
|
| [12] |
Khan T, Usman Y, Abdo T, et al. Diagnosis and management of peripheral lung nodule[J]. Ann Transl Med, 2019, 7(15): 348. doi: 10.21037/atm.2019.03.59
|
| [13] |
Guiot J, Vaidyanathan A, Deprez L, et al. A review in radiomics: making personalized medicine a reality via routine imaging[J]. Med Res Rev, 2022, 42(1): 426-40. doi: 10.1002/med.21846
|
| [14] |
庄奥博, 朱德祥, 许平平, 等. T1期结直肠癌淋巴结转移的危险因素分析及其列线图预测模型的应用价值[J]. 中华消化外科杂志, 2021, 20 (3): 323-30. https://cdmd.cnki.com.cn/Article/CDMD-10161-1022709494.htm
|
| [15] |
马骤, 谭令, 刘紫麟, 等. 50岁以下结直肠癌远处转移风险的列线图模型构建与验证[J]. 中国现代普通外科进展, 2023, 26(1): 59-63. https://www.cnki.com.cn/Article/CJFDTOTAL-PWJZ202301014.htm
|
| [16] |
李明东, 谢红强, 陶涛, 等. 结直肠癌患者术后肠梗阻发生风险列线图预测模型的构建及评估[J]. 中华消化病与影像杂志: 电子版, 2021, 11(4): 158-63. https://www.cnki.com.cn/Article/CJFDTOTAL-ZHYE202104006.htm
|
| [17] |
Weiser MR, Hsu M, Bauer PS, et al. Clinical calculator based on molecular and clinicopathologic characteristics predicts recurrence following resection of stage Ⅰ-Ⅲ colon cancer[J]. J Clin Oncol, 2021, 39(8): 911-9. doi: 10.1200/JCO.20.02553
|
| [18] |
Xu JS, Dai SQ, Yuan Y, et al. A prognostic model for colon cancer patients based on eight signature autophagy genes[J]. Front Cell Dev Biol, 2020, 8: 602174. doi: 10.3389/fcell.2020.602174
|
| [19] |
Liu S, Yu X, Yang S, et al. Machine learning- based radiomics nomogram for detecting extramural venous invasion in rectal cancer [J]. Front Oncol, 2021, 11: 610338. doi: 10.3389/fonc.2021.610338
|
| [20] |
王可欣, 余静, 徐青. 基于RESOLVE ADC的影像组学列线图在预测直肠癌壁外血管侵犯中的应用价值[J]. 肿瘤影像学, 2023, 32(2): 138-47. https://www.cnki.com.cn/Article/CJFDTOTAL-YXYX202302006.htm
|
| [21] |
Yu XL, Song WL, Guo D, et al. Preoperative prediction of extramural venous invasion in rectal cancer: comparison of the diagnostic efficacy of radiomics models and quantitative dynamic contrast- enhanced magnetic resonance imaging[J]. Front Oncol, 2020, 10: 459 doi: 10.3389/fonc.2020.00459
|
| [22] |
Fang JJ, Sun W, Wu D, et al. Value of texture analysis based on dynamic contrast- enhanced magnetic resonance imaging in preoperative assessment of extramural venous invasion in rectal cancer[J]. Insights Imaging, 2022, 13(1): 179.
|
| [23] |
赵丽. 定量磁共振技术在直肠癌术前评估中的应用[D]. 北京: 北京协和医学院, 2022.
|
| [24] |
Shu ZY, Mao DW, Song QW, et al. Multiparameter MRI-based radiomics for preoperative prediction of extramural venous invasion in rectal cancer[J]. Eur Radiol, 2022, 32(2): 1002-13.
|
| [25] |
李鹏, 梁浩然, 杨旭, 等. 分段读出平面回波成像序列对宫颈癌扩散加权成像质量的影响[J]. 中国医学物理学杂志, 2019, 36(6): 705-9. https://www.cnki.com.cn/Article/CJFDTOTAL-YXWZ201906017.htm
|
| [26] |
Zhao M, Liu Z, Sha Y, et al. Readout-segmented echo-planar imaging in the evaluation of sinonasal lesions: a comprehensive comparison of image quality in single-shot echo-planar imaging[J]. Magn Reson Imaging, 2016, 34(2): 166-72.
|
| [27] |
Schaap DP, Voogt ELK, Burger JWA, et al. Prognostic implications of MRI-detected EMVI and tumor deposits and their response to neoadjuvant therapy in cT3 and cT4 rectal cancer[J]. Int J Radiat Oncol, 2021, 111(3): 816-25.
|
| [28] |
Yang XY, Chen Y, Wen ZQ, et al. Role of quantitative dynamic contrast-enhanced MRI in evaluating regional lymph nodes with a short- axis diameter of less than 5 mm in rectal cancer[J]. Am J Roentgenol, 2019, 212(1): 77-83.
|
| [29] |
Chen Y, Yang XY, Wen ZQ, et al. Association between highresolution MRI-detected extramural vascular invasion and tumour microcirculation estimated by dynamic contrast- enhanced MRI in rectal cancer: preliminary results[J]. BMC Cancer, 2019, 19(1): 1-11.
|
| [30] |
Li ZH, Huang HS, Wang CC, et al. DCE- MRI radiomics models predicting the expression of radioresistant-related factors of LRP-1 and survivin in locally advanced rectal cancer[J]. Front Oncol, 2022, 12: 881341.
|
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