影像组学在肝占位性病变诊疗中的研究进展

Journal: Basic Medical Theory Research DOI: 10.12238/bmtr.v6i5.10103

沈正民, 王海久

青海大学附属医院肝胆胰外科 ; 青海省包虫病研究重点实验室

Abstract

肝占位性病变是一类拥有共同特征的疾病,会对周围组织器官产生压迫。包括多种良性或恶性病变。肝占位性病变具有异质性和复杂性,使用传统的影像学方法进行诊断有一定的局限性,在诊疗过程中难以做到早期准确诊断。而影像组学作为一种新兴的技术手段,可为肝占位性病变识别、诊断、治疗及预后提供新的可能性。本文旨在对影像组学在肝占位性病变研究领域中的最新应用进展进行综述。

Keywords

肝细胞癌;肝包虫病;泡状棘球蚴;肝脏储备功能;影像组学

References

[1] 李文东.16排螺旋CT在原发性腹膜后占位性病变鉴别诊断中的价值[J].山西医药杂志,2020,49(14):1813-1815.
[2] Saini T,Tom JP, Saikia UN, Dey P. Fine needle aspiration cytology of a space-occupying lesion in the liver. Cytopath ology.2022;33(5):647-649.
[3] Marrero JA, Ahn J, Rajender Reddy K; Americal College of Gastroenterology. ACG clinical guideline: the diagnosis and management of focal liver lesions. Am J Gastroenterol. 2014; 109(9):1328-1348.
[4] 李永强.双排螺旋CT平扫与增强扫描在肝脏占位性病变早期诊断中的应用分析[J].临床医学研究与实践,2017,2(25):139-140.
[5] Sawicka K, Hassan N, Dumaine C, et al. Direction of the Biopsy Needle in Ultrasound-Guided Renal Biopsy Impacts Spe cimen Adequacy and Risk of Bleeding. Can Assoc Radiol J. 2019;70(4):361-366.
[6] Bera K, Braman N, Gupta A, Velcheti V, Madabhushi A. Predicting cancer outcomes with radiomics and artificial inte lligence in radiology. Nat Rev Clin Oncol.2022;19(2):132-146.
[7] Lambin P,Rios-Velazquez E,Leijenaar R,et al. Radiomics: extracting more information from medical images using advan ced feature analysis.Eur J Cancer.2012;48(4):441-446.
[8] 宋兰,朱振宸,姜蕾,等.CT影像组学在预测肺腺癌ALK融合基因表达中的价值初探[J].中华放射学杂志,2019,(11):963-964 -965-966-967.
[9] Yin J, Qiu JJ, Qian W, et al. A radiomics signature to identify malignant and benign liver tumors on plain CT images. J Xray Sci Technol.2020;28(4):683-694.
[10] 冯忠园,叶靖.基于T_2WI影像组学鉴别肝细胞癌与肝内胆管细胞癌的研究[J].临床医学研究与实践,2020,5(22):1-4.
[11] Liu X,Khalvati F,Namdar K, et al. Can machine learning radiomics provide pre-operative differentiation of combined hepatocellular cholangiocarcinoma from hepatocellular carci noma and cholangiocarcinoma to inform optimal treatment planning?.Eur Radiol.2021;31(1):244-255.
[12] Mao B, Zhang L, Ning P, et al. Preoperative prediction for pathological grade of hepatocellular carcinoma via machi ne learning-based radiomics. Eur Radiol. 2020;30(12):6924-6932.
[13] Ma X,Wei J,Gu D,etal. Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcin oma using contrast-enhanced CT.Eur Radiol. 2019;29(7):3595 -3605.
[14] Simpson AL, Adams LB, Allen PJ,et al. Texture analysis of preoperative CT images for prediction of postoperative hep atic insufficiency: a preliminary study. J Am Coll Surg. 2015; 220(3):339-346.
[15] Zhang Z,Jiang H,Chen J,etal. Hepatocellular carcinoma: radiomics nomogram on gadoxetic acid-enhanced MR imaging for early postoperative recurrence prediction. Cancer Imagi ng.2019;19(1):22.Published2019May14.
[16] Ji GW, Zhu FP, Xu Q, et al. Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutio nal study.EBioMedicine.2019;50:156-165.
[17] Wen H,Vuitton L,Tuxun T,etal.Echinococcosis: Advances in the 21st Century. Clin Microbiol Rev.2019;32(2):e00075-18.Published2019 Feb13.
[18] Agudelo Higuita NI, Brunetti E, McCloskey C. Cystic Echinococcosis.J Clin Microbiol.2016;54(3):518-523.
[19] Stojkovic M,Junghanss T.Cystic and alveolar echinoco ccosis.Handb Clin Neurol.2013;114:327-334.
[20] 王健.CT影像组学在肝泡状棘球蚴病临床评估中的应用[D].新疆医科大学,2022.
[21] Tuxun T, Apaer S, Ma HZ, et al. Plasma IL-23 and IL-5 as surrogate markers of lesion metabolic activity in patients with hepatic alveolar echinococcosis. Sci Rep. 2018;8(1):4417.Published2018 Mar13.
[22] 张烈,李延茂,丛山.泡型肝包虫病患者肝切除术后肝衰竭风险的预测因素研究[J].肝脏,2021,26(03):302-304+308.
[23] 周才明,吕明德,殷晓煜.肝纤维化定量评估肝癌病人肝功能储备力的临床研究[J].中华肝胆外科杂志,2004,(9):10-12.
[24] 周玮,胡红杰,沈博,等.基于钆塞酸二钠增强磁共振成像影像组学定量评估肝硬化患者肝脏储备功能的应用价值[J].中国医学科学院学报,2020,42(04):459-467.

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