胃肠胰神经内分泌肿瘤CT影像组学研究进展
Advances in CT Radiomics Research on Gastroenteropancreatic Neuroendocrine Neoplasms
摘要: 胃肠胰神经内分泌肿瘤(gastroenteropancreatic neuroendocrine neoplasms, GEP-NENs)是一类具有高度多样性和复杂性的罕见肿瘤，其发病率逐年增加。CT检查是诊断、评估、随访GEP-NENs的重要影像学方法，而影像组学作为一种新兴的无创分析方法，可从诊断图像中提取定量且具有可重复性的特征参数，已被广泛运用于各类肿瘤的诊断、疗效评估、预后预测等多个方面。本文就CT影像组学在GEP-NENs鉴别诊断、病理分级预测、生物学行为预测、疗效评估及预后预测的研究进展进行综述，以期为后续研究方向提供思路。
Abstract: Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) represent a rare tumor category characterized by high diversity and complexity, with an escalating annual incidence. Computed tomography (CT) serves as a crucial imaging modality for diagnosing, evaluating, and monitoring GEP-NENs. As an emerging non-invasive analytical approach, radiomics enables the extraction of quantitative and reproducible feature parameters from diagnostic images. It has been widely applied in various aspects of tumor diagnosis, treatment efficacy assessment, and prognosis prediction. This review summarizes the research progress of CT radiomics in the differential diagnosis, pathological grading prediction, biological behavior prediction, treatment efficacy assessment, and prognosis prediction of GEP-NENs, aiming to provide insights for future research directions.
文章引用：王欣, 汤丽平. 胃肠胰神经内分泌肿瘤CT影像组学研究进展[J]. 临床医学进展, 2026, 16(3): 2100-2108. https://doi.org/10.12677/acm.2026.1631001

参考文献

[1] Zhang, X., Fan, Y., Jing, R., Getu, M.A., Chen, W., Zhang, W., et al. (2024) Gastroenteropancreatic Neuroendocrine Neoplasms: Current Development, Challenges, and Clinical Perspectives. Military Medical Research, 11, Article No. 35. [Google Scholar] [CrossRef] [PubMed]
[2] Xu, Z., Wang, L., Dai, S., Chen, M., Li, F., Sun, J., et al. (2021) Epidemiologic Trends of and Factors Associated with Overall Survival for Patients with Gastroenteropancreatic Neuroendocrine Tumors in the United States. JAMA Network Open, 4, e2124750. [Google Scholar] [CrossRef] [PubMed]
[3] Shi, M., Fan, Z., Xu, J., Yang, J., Li, Y., Gao, C., et al. (2021) Gastroenteropancreatic Neuroendocrine Neoplasms G3: Novel Insights and Unmet Needs. Biochimica et Biophysica Acta (BBA)—Reviews on Cancer, 1876, Article ID: 188637. [Google Scholar] [CrossRef] [PubMed]
[4] Fernandez, C.J., Agarwal, M., Pottakkat, B., Haroon, N.N., George, A.S. and Pappachan, J.M. (2021) Gastroenteropancreatic Neuroendocrine Neoplasms: A Clinical Snapshot. World Journal of Gastrointestinal Surgery, 13, 231-255. [Google Scholar] [CrossRef] [PubMed]
[5] Dasari, A., Shen, C., Halperin, D., Zhao, B., Zhou, S., Xu, Y., et al. (2017) Trends in the Incidence, Prevalence, and Survival Outcomes in Patients with Neuroendocrine Tumors in the United States. JAMA Oncology, 3, Article No. 1335. [Google Scholar] [CrossRef] [PubMed]
[6] Das, S. and Dasari, A. (2021) Epidemiology, Incidence, and Prevalence of Neuroendocrine Neoplasms: Are There Global Differences? Current Oncology Reports, 23, Article No. 43. [Google Scholar] [CrossRef] [PubMed]
[7] Zheng, R., Zhao, H., An, L., Zhang, S., Chen, R., Wang, S., et al. (2023) Incidence and Survival of Neuroendocrine Neoplasms in China with Comparison to the United States. Chinese Medical Journal, 136, 1216-1224. [Google Scholar] [CrossRef] [PubMed]
[8] Chang, J.S., Chen, L., Shan, Y., Chu, P., Tsai, C. and Tsai, H. (2021) Scientific Reports, 11, Article No. 7881. [Google Scholar] [CrossRef] 
[9] Tobias, J. and Keutgen, X.M. (2024) Diagnostics and Imaging for Pancreatic Neuroendocrine Tumors. Surgical Clinics of North America, 104, 883-890. [Google Scholar] [CrossRef] [PubMed]
[10] 牟玮, 田捷. PET/CT、SPECT/CT影像组学: 沟通宏观影像和微观分子的桥梁[J]. 中华核医学与分子影像杂志, 2024, 44(2): 65-67.
[11] Mayerhoefer, M.E., Materka, A., Langs, G., Häggström, I., Szczypiński, P., Gibbs, P., et al. (2020) Introduction to Radiomics. Journal of Nuclear Medicine, 61, 488-495. [Google Scholar] [CrossRef] [PubMed]
[12] De Muzio, F., Pellegrino, F., Fusco, R., Tafuto, S., Scaglione, M., Ottaiano, A., et al. (2023) Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics. Diagnostics, 13, Article No. 2877. [Google Scholar] [CrossRef] [PubMed]
[13] Chen, M., Copley, S.J., Viola, P., Lu, H. and Aboagye, E.O. (2023) Radiomics and Artificial Intelligence for Precision Medicine in Lung Cancer Treatment. Seminars in Cancer Biology, 93, 97-113. [Google Scholar] [CrossRef] [PubMed]
[14] Staal, F.C.R., Aalbersberg, E.A., van der Velden, D., Wilthagen, E.A., Tesselaar, M.E.T., Beets-Tan, R.G.H., et al. (2022) GEP-NET Radiomics: A Systematic Review and Radiomics Quality Score Assessment. European Radiology, 32, 7278-7294. [Google Scholar] [CrossRef] [PubMed]
[15] Berbís, M.Á., Godino, F.P., Rodríguez-Comas, J., Nava, E., García-Figueiras, R., Baleato-González, S., et al. (2023) Radiomics in CT and MR Imaging of the Liver and Pancreas: Tools with Potential for Clinical Application. Abdominal Radiology, 49, 322-340. [Google Scholar] [CrossRef] [PubMed]
[16] Becker, A.E. (2014) Pancreatic Ductal Adenocarcinoma: Risk Factors, Screening, and Early Detection. World Journal of Gastroenterology, 20, Article No. 11182. [Google Scholar] [CrossRef] [PubMed]
[17] Kimura, T., Miyamoto, H., Fukuya, A., Kitamura, S., Okamoto, K., Kimura, M., et al. (2016) Neuroendocrine Carcinoma of the Pancreas with Similar Genetic Alterations to Invasive Ductal Adenocarcinoma. Clinical Journal of Gastroenterology, 9, 261-265. [Google Scholar] [CrossRef] [PubMed]
[18] He, M., Liu, Z., Lin, Y., Wan, J., Li, J., Xu, K., et al. (2019) Differentiation of Atypical Non-Functional Pancreatic Neuroendocrine Tumor and Pancreatic Ductal Adenocarcinoma Using CT Based Radiomics. European Journal of Radiology, 117, 102-111. [Google Scholar] [CrossRef] [PubMed]
[19] Zhang, T., Xiang, Y., Wang, H., Yun, H., Liu, Y., Wang, X., et al. (2022) Radiomics Combined with Multiple Machine Learning Algorithms in Differentiating Pancreatic Ductal Adenocarcinoma from Pancreatic Neuroendocrine Tumor: More Hands Produce a Stronger Flame. Journal of Clinical Medicine, 11, Article No. 6789. [Google Scholar] [CrossRef] [PubMed]
[20] De Robertis, R., Mascarin, B., Bardhi, E., Spoto, F., Cardobi, N. and D’Onofrio, M. (2025) Radiomics in Differential Diagnosis of Pancreatic Tumors. European Journal of Radiology Open, 14, Article ID: 100651. [Google Scholar] [CrossRef] [PubMed]
[21] Wang, R., Liu, H., Liang, P., Zhao, H., Li, L. and Gao, J. (2021) Radiomics Analysis of CT Imaging for Differentiating Gastric Neuroendocrine Carcinomas from Gastric Adenocarcinomas. European Journal of Radiology, 138, Article ID: 109662. [Google Scholar] [CrossRef] [PubMed]
[22] He, X., Yang, S., Ren, J., Wang, N., Li, M., You, Y., et al. (2024) Synergizing Traditional CT Imaging with Radiomics: A Novel Model for Preoperative Diagnosis of Gastric Neuroendocrine and Mixed Adenoneuroendocrine Carcinoma. Frontiers in Oncology, 14, Article ID: 1480466. [Google Scholar] [CrossRef] [PubMed]
[23] 赵金莉. 基于CT图像的放射组学对直肠神经内分泌肿瘤和直肠腺癌的鉴别诊断价值[D]: [硕士学位论文]. 沈阳: 中国医科大学, 2021.
[24] Rindi, G., Mete, O., Uccella, S., Basturk, O., La Rosa, S., Brosens, L.A.A., et al. (2022) Overview of the 2022 WHO Classification of Neuroendocrine Neoplasms. Endocrine Pathology, 33, 115-154. [Google Scholar] [CrossRef] [PubMed]
[25] 中国临床肿瘤学会指南工作委员会. 中国临床肿瘤学会(CSCO)神经内分泌肿瘤诊疗指南2024 [M]. 北京: 人民卫生出版社, 2024.
[26] Sorbye, H., Grande, E., Pavel, M., Tesselaar, M., Fazio, N., Reed, N.S., et al. (2023) European Neuroendocrine Tumor Society (ENETS) 2023 Guidance Paper for Digestive Neuroendocrine Carcinoma. Journal of Neuroendocrinology, 35, e13249. [Google Scholar] [CrossRef] [PubMed]
[27] Ricci, C., Mosconi, C., Ingaldi, C., Vara, G., Verna, M., Pettinari, I., et al. (2021) The 3-Dimensional-Computed Tomography Texture Is Useful to Predict Pancreatic Neuroendocrine Tumor Grading. Pancreas, 50, 1392-1399. [Google Scholar] [CrossRef] [PubMed]
[28] Liu, C., Bian, Y., Meng, Y., Liu, F., Cao, K., Zhang, H., et al. (2022) Preoperative Prediction of G1 and G2/3 Grades in Patients with Nonfunctional Pancreatic Neuroendocrine Tumors Using Multimodality Imaging. Academic Radiology, 29, e49-e60. [Google Scholar] [CrossRef] [PubMed]
[29] Wang, X., Qiu, J., Tan, C., Chen, Y., Tan, Q., Ren, S., et al. (2022) Development and Validation of a Novel Radiomics-Based Nomogram with Machine Learning to Preoperatively Predict Histologic Grade in Pancreatic Neuroendocrine Tumors. Frontiers in Oncology, 12, Article ID: 843376. [Google Scholar] [CrossRef] [PubMed]
[30] Ye, J., Fang, P., Peng, Z., Huang, X., Xie, J. and Yin, X. (2023) A Radiomics-Based Interpretable Model to Predict the Pathological Grade of Pancreatic Neuroendocrine Tumors. European Radiology, 34, 1994-2005. [Google Scholar] [CrossRef] [PubMed]
[31] Javed, A.A., Zhu, Z., Kinny-Köster, B., Habib, J.R., Kawamoto, S., Hruban, R.H., et al. (2024) Accurate Non-Invasive Grading of Nonfunctional Pancreatic Neuroendocrine Tumors with a CT Derived Radiomics Signature. Diagnostic and Interventional Imaging, 105, 33-39. [Google Scholar] [CrossRef] [PubMed]
[32] Bian, Y., Jiang, H., Ma, C., Wang, L., Zheng, J., Jin, G., et al. (2020) Ct-based Radiomics Score for Distinguishing between Grade 1 and Grade 2 Nonfunctioning Pancreatic Neuroendocrine Tumors. American Journal of Roentgenology, 215, 852-863. [Google Scholar] [CrossRef] [PubMed]
[33] Zhao, Z., Bian, Y., Jiang, H., Fang, X., Li, J., Cao, K., et al. (2020) CT-Radiomic Approach to Predict G1/2 Nonfunctional Pancreatic Neuroendocrine Tumor. Academic Radiology, 27, e272-e281. [Google Scholar] [CrossRef] [PubMed]
[34] Pulvirenti, A., Yamashita, R., Chakraborty, J., Horvat, N., Seier, K., McIntyre, C.A., et al. (2021) Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade. JCO Clinical Cancer Informatics, 5, 679-694. [Google Scholar] [CrossRef] [PubMed]
[35] Chiti, G., Grazzini, G., Flammia, F., Matteuzzi, B., Tortoli, P., Bettarini, S., et al. (2022) Gastroenteropancreatic Neuroendocrine Neoplasms (GEP-NENs): A Radiomic Model to Predict Tumor Grade. La Radiologia Medica, 127, 928-938. [Google Scholar] [CrossRef] [PubMed]
[36] 王睿, 梁盼, 余娟, 等. 基于极端梯度上升算法的联合诊断模型对胃神经内分泌肿瘤病理分级的诊断效能[J]. 中华医学杂志, 2021, 101(34): 2717-2722.
[37] Liang, P., Xu, C., Tan, F., Li, S., Chen, M., Hu, D., et al. (2020) Prediction of the World Health Organization Grade of Rectal Neuroendocrine Tumors Based on CT Histogram Analysis. Cancer Medicine, 10, 595-604. [Google Scholar] [CrossRef] [PubMed]
[38] 陈洛海, 梁赟, 陈洁. 2023年度神经内分泌肿瘤治疗研究进展[J]. 肿瘤综合治疗电子杂志, 2024, 10(2): 14-19.
[39] Gillies, R.J., Kinahan, P.E. and Hricak, H. (2016) Radiomics: Images Are More than Pictures, They Are Data. Radiology, 278, 563-577. [Google Scholar] [CrossRef] [PubMed]
[40] Gu, W., Chen, Y., Zhu, H., Chen, H., Yang, Z., Mo, S., et al. (2023) Development and Validation of CT-Based Radiomics Deep Learning Signatures to Predict Lymph Node Metastasis in Non-Functional Pancreatic Neuroendocrine Tumors: A Multicohort Study. eClinicalMedicine, 65, Article ID: 102269. [Google Scholar] [CrossRef] [PubMed]
[41] Ahmed, T.M., Zhu, Z., Yasrab, M., Blanco, A., Kawamoto, S., He, J., et al. (2024) Preoperative Prediction of Lymph Node Metastases in Nonfunctional Pancreatic Neuroendocrine Tumors Using a Combined CT Radiomics-Clinical Model. Annals of Surgical Oncology, 31, 8136-8145. [Google Scholar] [CrossRef] [PubMed]
[42] Wang, Y., Gu, W., Huang, D., Zhang, W., Chen, Y., Xu, J., et al. (2025) Evaluation of Tumor Pseudocapsule Using Computed Tomography-Based Radiomics in Pancreatic Neuroendocrine Tumors to Predict Prognosis and Guide Surgical Strategy: A Cohort Study. International Journal of Surgery, 111, 4454-4463. [Google Scholar] [CrossRef] [PubMed]
[43] Ma, M., Gu, W., Liang, Y., Han, X., Zhang, M., Xu, M., et al. (2024) A Novel Model for Predicting Postoperative Liver Metastasis in R0 Resected Pancreatic Neuroendocrine Tumors: Integrating Computational Pathology and Deep Learning-radiomics. Journal of Translational Medicine, 22, Article No. 768. [Google Scholar] [CrossRef] [PubMed]
[44] Mori, M., Palumbo, D., Muffatti, F., Partelli, S., Mushtaq, J., Andreasi, V., et al. (2022) Prediction of the Characteristics of Aggressiveness of Pancreatic Neuroendocrine Neoplasms (PanNENs) Based on CT Radiomic Features. European Radiology, 33, 4412-4421. [Google Scholar] [CrossRef] [PubMed]
[45] Blazevic, A., Starmans, M.P.A., Brabander, T., Dwarkasing, R.S., van Gils, R.A.H., Hofland, J., et al. (2021) Predicting Symptomatic Mesenteric Mass in Small Intestinal Neuroendocrine Tumors Using Radiomics. Endocrine-Related Cancer, 28, 529-539. [Google Scholar] [CrossRef] [PubMed]
[46] Rinke, A., Müller, H., Schade-Brittinger, C., Klose, K., Barth, P., Wied, M., et al. (2009) Placebo-Controlled, Double-Blind, Prospective, Randomized Study on the Effect of Octreotide LAR in the Control of Tumor Growth in Patients with Metastatic Neuroendocrine Midgut Tumors: A Report from the PROMID Study Group. Journal of Clinical Oncology, 27, 4656-4663. [Google Scholar] [CrossRef] [PubMed]
[47] Caplin, M.E., Pavel, M., Ćwikła, J.B., Phan, A.T., Raderer, M., Sedláčková, E., et al. (2014) Lanreotide in Metastatic Enteropancreatic Neuroendocrine Tumors. New England Journal of Medicine, 371, 224-233. [Google Scholar] [CrossRef] [PubMed]
[48] 中国抗癌协会神经内分泌肿瘤整合诊治指南(精简版) [J].中国肿瘤临床, 2023, 50(8): 385-397.
[49] Polici, M., Caruso, D., Masci, B., Marasco, M., Valanzuolo, D., Dell’Unto, E., et al. (2024) Radiomics in Advanced Gastroenteropancreatic Neuroendocrine Neoplasms: Identifying Responders to Somatostatin Analogs. Journal of Neuroendocrinology, 37, e13472. [Google Scholar] [CrossRef] [PubMed]
[50] Lee, L., Ito, T. and Jensen, R.T. (2018) Everolimus in the Treatment of Neuroendocrine Tumors: Efficacy, Side-Effects, Resistance, and Factors Affecting Its Place in the Treatment Sequence. Expert Opinion on Pharmacotherapy, 19, 909-928. [Google Scholar] [CrossRef] [PubMed]
[51] Caruso, D., Polici, M., Rinzivillo, M., Zerunian, M., Nacci, I., Marasco, M., et al. (2022) CT-Based Radiomics for Prediction of Therapeutic Response to Everolimus in Metastatic Neuroendocrine Tumors. La Radiologia Medica, 127, 691-701. [Google Scholar] [CrossRef] [PubMed]
[52] Chen, L., Wang, W., Jin, K., Yuan, B., Tan, H., Sun, J., et al. (2022) Special Issue “the Advance of Solid Tumor Research in China”: Prediction of Sunitinib Efficacy Using Computed Tomography in Patients with Pancreatic Neuroendocrine Tumors. International Journal of Cancer, 152, 90-99. [Google Scholar] [CrossRef] [PubMed]
[53] Alevroudis, E., Spei, M., Chatziioannou, S.N., Tsoli, M., Wallin, G., Kaltsas, G., et al. (2021) Clinical Utility of 18F-FDG PET in Neuroendocrine Tumors Prior to Peptide Receptor Radionuclide Therapy: A Systematic Review and Meta-Analysis. Cancers, 13, Article No. 1813. [Google Scholar] [CrossRef] [PubMed]
[54] Shaheen, S., Moradi, F., Gamino, G. and Kunz, P.L. (2020) Patient Selection and Toxicities of PRRT for Metastatic Neuroendocrine Tumors and Research Opportunities. Current Treatment Options in Oncology, 21, Article No. 25. [Google Scholar] [CrossRef] [PubMed]
[55] Strosberg, J., El-Haddad, G., Wolin, E., Hendifar, A., Yao, J., Chasen, B., et al. (2017) Phase 3 Trial of 177Lu-Dotatate for Midgut Neuroendocrine Tumors. New England Journal of Medicine, 376, 125-135. [Google Scholar] [CrossRef] [PubMed]
[56] Behmanesh, B., Saray, A.A., Deevband, R.M., et al. (2024) Radiomics Analysis for Clinical Decision Support in 177Lu-Dotatate Therapy of Metastatic Neuroendocrine Tumors Using CT Images. Journal of Biomedical Physics & Engineering, 14, 423-434.
[57] Manfredi, S., Walter, T., Baudin, E., Coriat, R., Ruszniewski, P., Lecomte, T., et al. (2017) Management of Gastric Neuro-Endocrine Tumours in a Large French National Cohort (GTE). Endocrine, 57, 504-511. [Google Scholar] [CrossRef] [PubMed]
[58] Homps, M., Soyer, P., Coriat, R., Dermine, S., Pellat, A., Fuks, D., et al. (2023) A Preoperative Computed Tomography Radiomics Model to Predict Disease-Free Survival in Patients with Pancreatic Neuroendocrine Tumors. European Journal of Endocrinology, 189, 476-484. [Google Scholar] [CrossRef] [PubMed]
[59] Heo, S., Park, H.J., Kim, H.J., Kim, J.H., Park, S.Y., Kim, K.W., et al. (2024) Prognostic Value of CT-Based Radiomics in Grade 1-2 Pancreatic Neuroendocrine Tumors. Cancer Imaging, 24, Article No. 28. [Google Scholar] [CrossRef] [PubMed]
[60] Yang, Z., Han, Y., Cheng, M., Wang, R., Li, J., Zhao, H., et al. (2023) Prognostic Value of Computed Tomography Radiomics Features in Patients with Gastric Neuroendocrine Neoplasm. Frontiers in Oncology, 13, Article ID: 1143291. [Google Scholar] [CrossRef] [PubMed]
[61] Yang, Z., Han, Y., Li, F., Zhang, A., Cheng, M. and Gao, J. (2023) Deep Learning Radiomics Analysis Based on Computed Tomography for Survival Prediction in Gastric Neuroendocrine Neoplasm: A Multicenter Study. Quantitative Imaging in Medicine and Surgery, 13, 8190-8203. [Google Scholar] [CrossRef] [PubMed]
[62] An, P., Zhang, J., Li, M., Duan, P., He, Z., Wang, Z., et al. (2022) Clinical Data-CT Radiomics-Based Model for Predicting Prognosis of Patients with Gastrointestinal Pancreatic Neuroendocrine Neoplasms (GP-NENs). Computational and Mathematical Methods in Medicine, 2022, Article ID: 4186305. [Google Scholar] [CrossRef] [PubMed]

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