Advances in imaging for assessment of biological behavior and prognosis in pancreatic neuroendocrine tumors_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

XIAO Rong ¹ ,  LU Tao ²

1. School of Medicine and Life Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu 610000, P. R. China;
2. Department of Radiology, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, Chengdu 610032, P. R. China;

Corresponding?author：

LU Tao, Email: 345248302@qq.com

Keywords：

pancreatic neuroendocrine tumor; imaging; radiomics; prognosis; review

DOI：

10.7507/1007-9424.202508052

Video：

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Objective To review the application of imaging in evaluating tumor biological behavior and predicting prognosis of pancreatic neuroendocrine tumors (pNETs), and to assess its clinical value. Methods A literature review was performed on recent domestic and foreign researches focusing on imaging methods and radiomics models of pNETs. Results Recent studies have received preliminary achievement in applying imaging to assess the biological behavior and prognosis of pNETs. Existing imaging-based predictive models can serve as effective biomarkers in predicting liver metastasis, lymph node metastasis, and vascular invasion in pNETs, as well as in estimating patients’ survival and treatment response. Conclusion Imaging plays a important role in individualized management of pNETs, enabling more accurate diagnosis, treatment planning, and prognostic evaluation.

Citation： XIAO Rong, LU Tao. Advances in imaging for assessment of biological behavior and prognosis in pancreatic neuroendocrine tumors. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2026, 33(2): 190-198. doi: 10.7507/1007-9424.202508052 Copy

1.	Dasari A, Shen C, Halperin D, et al. Trends in the incidence, prevalence, and survival outcomes in patients with neuroendocrine tumors in the United States. JAMA Oncol, 2017, 3(10): 1335-1342.
2.	Milanetto AC, Armellin C, Gasparini D, et al. Quality of life after pancreatic surgery for neuroendocrine tumors of the pancreas: observational study of long-term outcomes. Cancers (Basel), 2025, 17(19): 3205. doi: 10.3390/cancers17193205.
3.	Fang JM, Li J, Shi J. An update on the diagnosis of gastroenteropancreatic neuroendocrine neoplasms. World J Gastroenterol, 2022, 28(10): 1009-1023.
4.	Fang JM, Shi J. A clinicopathologic and molecular update of pancreatic neuroendocrine neoplasms with a focus on the New World Health Organization classification. Arch Pathol Lab Med, 2019, 143(11): 1317-1326.
5.	Yang M, Zeng L, Ke NW, et al. World Health Organization grading classification for pancreatic neuroendocrine neoplasms: a comprehensive analysis from a large Chinese institution. BMC Cancer, 2020, 20(1): 906. doi: 10.1186/s12885-020-07356-5.
6.	Genc CG, Klümpen HJ, van Oijen MGH, et al. A nationwide population-based study on the survival of patients with pancreatic neuroendocrine tumors in the netherlands. World J Surg, 2018, 42(2): 490-497.
7.	Shyr BS, Shyr BU, Chen SC, et al. Impact of tumor grade on pancreatic neuroendocrine tumors. Asian J Surg, 2022, 45(12): 2659-2663.
8.	Homps M, Soyer P, Coriat R, et al. A preoperative computed tomography radiomics model to predict disease-free survival in patients with pancreatic neuroendocrine tumors. Eur J Endocrinol, 2023, 189(4): 476-484.
9.	Lee NJ, Hruban RH, Fishman EK. Pancreatic neuroendocrine tumor: review of heterogeneous spectrum of CT appearance. Abdom Radiol (NY), 2018, 43(11): 3025-3034.
10.	陳麗娟, 趙蕾, 杜雪菲. 多層螺旋CT與磁共振擴散加權成像在胰腺神經內分泌腫瘤中的應用價值. 中國CT和MRI雜志, 2024, 22(2): 114-117.
11.	Segaran N, Devine C, Wang M, et al. Current update on imaging for pancreatic neuroendocrine neoplasms. World J Clin Oncol, 2021, 12(10): 897-911.
12.	Katsuta E, Kudo A, Akashi T, et al. Macroscopic morphology for estimation of malignant potential in pancreatic neuroendocrine neoplasm. J Cancer Res Clin Oncol, 2016, 142(6): 1299-1306.
13.	Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology, 2016, 278(2): 563-577.
14.	Halfdanarson TR, Rabe KG, Rubin J, et al. Pancreatic neuroendocrine tumors (PNETs): incidence, prognosis and recent trend toward improved survival. Ann Oncol, 2008, 19(10): 1727-1733.
15.	Kubo H, Ohgi K, Ohike N, et al. Tumor vascularity on contrast-enhanced computed tomography as a predictive marker of metastatic potential for small nonfunctioning pancreatic neuroendocrine tumors. Surgery, 2024, 175(2): 484-490.
16.	Williams JK, Schwarz JL, Keutgen XM. Surgery for metastatic pancreatic neuroendocrine tumors: a narrative review. Hepatobiliary Surg Nutr, 2023, 12(1): 69-83.
17.	Battistella A, Partelli S, Andreasi V, et al. Preoperative assessment of microvessel density in nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs). Surgery, 2022, 172(4): 1236-1244.
18.	Frilling A, Modlin IM, Kidd M, et al. Recommendations for management of patients with neuroendocrine liver metastases. Lancet Oncol, 2014, 15(1): e8-e21.
19.	Chu QD, Hill HC, Douglass HO, et al. Predictive factors associated with long-term survival in patients with neuroendocrine tumors of the pancreas. Ann Surg Oncol, 2002, 9(9): 855-862.
20.	Pavel M, O'Toole D, Costa F, et al. ENETS consensus guidelines update for the management of distant metastatic disease of intestinal, pancreatic, bronchial neuroendocrine neoplasms (NEN) and NEN of unknown primary site. Neuroendocrinology, 2016, 103(2): 172-185.
21.	Pan M, Yang Y, Teng T, et al. Development and validation of a simple-to-use nomogram to predict liver metastasis in patients with pancreatic neuroendocrine neoplasms: a large cohort study. BMC Gastroenterol, 2021, 21(1): 101. doi: 10.1186/s12876-021-01685-w.
22.	Pan Y, Chen HY, Chen JY, et al. Clinical and CT quantitative features for predicting liver metastases in patients with pancreatic neuroendocrine tumors: a study with prospective/external validation. Acad Radiol, 2024, 31(9): 3612-3619.
23.	Ma M, Gu W, Liang Y, et al. A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics. J Transl Med, 2024, 22(1): 768. doi: 10.1186/s12967-024-05449-4.
24.	Ahmed TM, Zhu Z, Yasrab M, et al. Preoperative prediction of lymph node metastases in nonfunctional pancreatic neuroendocrine tumors using a combined CT radiomics-clinical model. Ann Surg Oncol, 2024, 31(12): 8136-8145.
25.	Zhang N, He J, Maithel SK, et al. Accuracy and prognostic impact of nodal status on preoperative imaging for management of pancreatic neuroendocrine tumors: a multi-institutional study. Ann Surg Oncol, 2024, 31(5): 2882-2891.
26.	Han S, Kim JH, Yoo J, et al. Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors. Eur Radiol, 2022, 32(4): 2506-2517.
27.	Sun HT, Zhang SL, Liu K, et al. MRI-based nomogram estimates the risk of recurrence of primary nonmetastatic pancreatic neuroendocrine tumors after curative resection. J Magn Reson Imaging, 2019, 50(2): 397-409.
28.	Zhu HB, Nie P, Jiang L, et al. Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study. Insights Imaging, 2022, 13(1): 162. doi: 10.1186/s13244-022-01301-9.
29.	Harimoto N, Araki K, Hoshino K, et al. Diffusion-weighted MRI predicts lymph node metastasis and tumor aggressiveness in resectable pancreatic neuroendocrine tumors. World J Surg, 2020, 44(12): 4136-4141.
30.	Gu W, Chen Y, Zhu H, et al. 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, 2023, 65: 102269. doi: 10.1016/j.eclinm.2023.102269.
31.	Mori M, Palumbo D, Muffatti F, et al. Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features. Eur Radiol, 2023, 33(6): 4412-4421.
32.	Mapelli P, Bezzi C, Muffatti F, et al. Somatostatin receptor activity assessed by ⁶⁸Ga-DOTATOC PET can preoperatively predict DAXX/ATRX loss of expression in well-differentiated pancreatic neuroendocrine tumors. Eur J Nucl Med Mol Imaging, 2023, 50(9): 2818-2829.
33.	Mapelli P, Bezzi C, Palumbo D, et al. ⁶⁸Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine well-differentiated tumours. Eur J Nucl Med Mol Imaging, 2022, 49(7): 2352-2363.
34.	Mapelli P, Bezzi C, Muffatti F, et al. Preoperative assessment of lymph nodal metastases with [⁶⁸Ga]Ga-DOTATOC PET radiomics for improved surgical planning in well-differentiated pancreatic neuroendocrine tumours. Eur J Nucl Med Mol Imaging, 2024, 51(9): 2774-2783.
35.	Khanna L, Prasad SR, Sunnapwar A, et al. Pancreatic neuroendocrine neoplasms: 2020 update on pathologic and imaging findings and classification. Radiographics, 2020, 40(5): 1240-1262.
36.	何達, 宋彬. 胰腺神經內分泌腫瘤診療現狀. 中國普通外科雜志, 2024, 33(3): 311-320.
37.	趙燕, 胡世康, 王利, 等. 不同病理級別胰腺神經內分泌腫瘤的鑒別: 基于CT影像特征. 中國普外基礎與臨床雜志, 2025, 32(5): 590-595.
38.	Yamamoto Y, Okamura Y, Uemura S, et al. Vascularity and tumor size are significant predictors for recurrence after resection of a pancreatic neuroendocrine tumor. Ann Surg Oncol, 2017, 24(8): 2363-2370.
39.	Takahashi Y, Akishima-Fukasawa Y, Kobayashi N, et al. Prognostic value of tumor architecture, tumor-associated vascular characteristics, and expression of angiogenic molecules in pancreatic endocrine tumors. Clin Cancer Res, 2007, 13(1): 187-196.
40.	Liu YL, Zhu HB, Chen ML, et al. Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging. World J Gastrointest Surg, 2023, 15(12): 2809-2819.
41.	Jeon SK, Lee JM, Joo I, et al. Nonhypervascular pancreatic neuroendocrine tumors: differential diagnosis from pancreatic ductal adenocarcinomas at MR imaging-retrospective cross-sectional study. Radiology, 2017, 284(1): 77-87.
42.	Ahn B, Park HJ, Kim HJ, et al. Radiologic tumor border can further stratify prognosis in patients with pancreatic neuroendocrine tumor. Pancreatology, 2024, 24(5): 753-763.
43.	陳小勇, 徐敬慈, 李芹芹, 等. CT征象對胰腺神經內分泌腫瘤侵襲性行為的預測價值. CT理論與應用研究, 2022, 31(3): 399-407.
44.	Nanno Y, Toyama H, Matsumoto I, et al. Reappraisal of malignant risk assessment for small (≤20 mm) non-functioning pancreatic neuroendocrine tumors. Ann Surg Oncol, 2023, 30(6): 3493-3500.
45.	Makris EA, Cannon JGD, Norton JA, et al. Calcifications and cystic morphology on preoperative imaging predict survival after resection of pancreatic neuroendocrine tumors. Ann Surg Oncol, 2023, 30(4): 2424-2430.
46.	Shen X, Yang F, Jiang T, et al. A nomogram to preoperatively predict the aggressiveness of non-functional pancreatic neuroendocrine tumors based on CT features. Eur J Radiol, 2024, 171: 111284. doi: 10.1016/j.ejrad.2023.111284.
47.	Abdulrezzak U, Kurt YK, Kula M, et al. Combined imaging with ⁶⁸Ga-DOTA-TATE and ¹⁸F-FDG PET/CT on the basis of volumetric parameters in neuroendocrine tumors. Nucl Med Commun, 2016, 37(8): 874-881.
48.	Sato A, Masui T, Yogo A, et al. Usefulness of ¹⁸F-FDG-PET/CT in the diagnosis and prediction of recurrence of pancreatic neuroendocrine neoplasms. J Hepatobiliary Pancreat Sci, 2020, 27(7): 414-420.
49.	Heo S, Park HJ, Kim HJ, et al. Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors. Cancer Imaging, 2024, 24(1): 28. doi: 10.1186/s40644-024-00673-z.
50.	Park YJ, Park YS, Kim ST, et al. A machine learning approach using [¹⁸F]FDG PET-based radiomics for prediction of tumor grade and prognosis in pancreatic neuroendocrine tumor. Mol Imaging Biol, 2023, 25(5): 897-910.
51.	Mizumoto T, Toyama H, Terai S, et al. Prediction of lymph node metastasis in pancreatic neuroendocrine tumors by contrast enhancement characteristics. Pancreatology, 2017, 17(6): 956-961.
52.	Singh S, Chan DL, Moody L, et al. Recurrence in resected gastroenteropancreatic neuroendocrine tumors. JAMA Oncol, 2018, 4(4): 583-585.
53.	Chen H, Li Z, Hu Y, et al. Maximum value on arterial phase computed tomography predicts prognosis and treatment efficacy of sunitinib for pancreatic neuroendocrine tumours. Ann Surg Oncol, 2023, 30(5): 2988-2998.
54.	Chen L, Wang W, Jin K, et al. Special issue “The advance of solid tumor research in China”: prediction of sunitinib efficacy using computed tomography in patients with pancreatic neuroendocrine tumors. Int J Cancer, 2023, 152(1): 90-99.
55.	Ingenerf M, Kiesl S, Winkelmann M, et al. Treatment assessment of pNET and NELM after everolimus by quantitative MRI parameters. Biomedicines, 2022, 10(10): 2618. doi: 10.3390/biomedicines10102618.
56.	Ingenerf M, Karim H, Auernhammer C, et al. Quantitative SSTR-PET/CT for predicting response and survival outcomes in patients with pancreatic neuroendocrine tumors receiving CAPTEM. Radiol Oncol, 2023, 57(4): 436-445.
57.	?nner H, Abdülrezzak ü, Tutu? A. Could the skewness and kurtosis texture parameters of lesions obtained from pretreatment Ga-⁶⁸DOTA-TATE PET/CT images predict receptor radionuclide therapy response in patients with gastroenteropancreatic neuroendocrine tumors? Nucl Med Commun, 2020, 41(10): 1034-1039.
58.	Pettersson OJ, Fr?ss-Baron K, Crona J, et al. Tumor growth rate in pancreatic neuroendocrine tumor patients undergoing PRRT with ¹⁷⁷Lu-DOTATATE. Endocr Connect, 2021, 10(4): 422-431.

1. Dasari A, Shen C, Halperin D, et al. Trends in the incidence, prevalence, and survival outcomes in patients with neuroendocrine tumors in the United States. JAMA Oncol, 2017, 3(10): 1335-1342.
2. Milanetto AC, Armellin C, Gasparini D, et al. Quality of life after pancreatic surgery for neuroendocrine tumors of the pancreas: observational study of long-term outcomes. Cancers (Basel), 2025, 17(19): 3205. doi: 10.3390/cancers17193205.
3. Fang JM, Li J, Shi J. An update on the diagnosis of gastroenteropancreatic neuroendocrine neoplasms. World J Gastroenterol, 2022, 28(10): 1009-1023.
4. Fang JM, Shi J. A clinicopathologic and molecular update of pancreatic neuroendocrine neoplasms with a focus on the New World Health Organization classification. Arch Pathol Lab Med, 2019, 143(11): 1317-1326.
5. Yang M, Zeng L, Ke NW, et al. World Health Organization grading classification for pancreatic neuroendocrine neoplasms: a comprehensive analysis from a large Chinese institution. BMC Cancer, 2020, 20(1): 906. doi: 10.1186/s12885-020-07356-5.
6. Genc CG, Klümpen HJ, van Oijen MGH, et al. A nationwide population-based study on the survival of patients with pancreatic neuroendocrine tumors in the netherlands. World J Surg, 2018, 42(2): 490-497.
7. Shyr BS, Shyr BU, Chen SC, et al. Impact of tumor grade on pancreatic neuroendocrine tumors. Asian J Surg, 2022, 45(12): 2659-2663.
8. Homps M, Soyer P, Coriat R, et al. A preoperative computed tomography radiomics model to predict disease-free survival in patients with pancreatic neuroendocrine tumors. Eur J Endocrinol, 2023, 189(4): 476-484.
9. Lee NJ, Hruban RH, Fishman EK. Pancreatic neuroendocrine tumor: review of heterogeneous spectrum of CT appearance. Abdom Radiol (NY), 2018, 43(11): 3025-3034.
10. 陳麗娟, 趙蕾, 杜雪菲. 多層螺旋CT與磁共振擴散加權成像在胰腺神經內分泌腫瘤中的應用價值. 中國CT和MRI雜志, 2024, 22(2): 114-117.
11. Segaran N, Devine C, Wang M, et al. Current update on imaging for pancreatic neuroendocrine neoplasms. World J Clin Oncol, 2021, 12(10): 897-911.
12. Katsuta E, Kudo A, Akashi T, et al. Macroscopic morphology for estimation of malignant potential in pancreatic neuroendocrine neoplasm. J Cancer Res Clin Oncol, 2016, 142(6): 1299-1306.
13. Gillies RJ, Kinahan PE, Hricak H. Radiomics: images are more than pictures, they are data. Radiology, 2016, 278(2): 563-577.
14. Halfdanarson TR, Rabe KG, Rubin J, et al. Pancreatic neuroendocrine tumors (PNETs): incidence, prognosis and recent trend toward improved survival. Ann Oncol, 2008, 19(10): 1727-1733.
15. Kubo H, Ohgi K, Ohike N, et al. Tumor vascularity on contrast-enhanced computed tomography as a predictive marker of metastatic potential for small nonfunctioning pancreatic neuroendocrine tumors. Surgery, 2024, 175(2): 484-490.
16. Williams JK, Schwarz JL, Keutgen XM. Surgery for metastatic pancreatic neuroendocrine tumors: a narrative review. Hepatobiliary Surg Nutr, 2023, 12(1): 69-83.
17. Battistella A, Partelli S, Andreasi V, et al. Preoperative assessment of microvessel density in nonfunctioning pancreatic neuroendocrine tumors (NF-PanNETs). Surgery, 2022, 172(4): 1236-1244.
18. Frilling A, Modlin IM, Kidd M, et al. Recommendations for management of patients with neuroendocrine liver metastases. Lancet Oncol, 2014, 15(1): e8-e21.
19. Chu QD, Hill HC, Douglass HO, et al. Predictive factors associated with long-term survival in patients with neuroendocrine tumors of the pancreas. Ann Surg Oncol, 2002, 9(9): 855-862.
20. Pavel M, O'Toole D, Costa F, et al. ENETS consensus guidelines update for the management of distant metastatic disease of intestinal, pancreatic, bronchial neuroendocrine neoplasms (NEN) and NEN of unknown primary site. Neuroendocrinology, 2016, 103(2): 172-185.
21. Pan M, Yang Y, Teng T, et al. Development and validation of a simple-to-use nomogram to predict liver metastasis in patients with pancreatic neuroendocrine neoplasms: a large cohort study. BMC Gastroenterol, 2021, 21(1): 101. doi: 10.1186/s12876-021-01685-w.
22. Pan Y, Chen HY, Chen JY, et al. Clinical and CT quantitative features for predicting liver metastases in patients with pancreatic neuroendocrine tumors: a study with prospective/external validation. Acad Radiol, 2024, 31(9): 3612-3619.
23. Ma M, Gu W, Liang Y, et al. A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics. J Transl Med, 2024, 22(1): 768. doi: 10.1186/s12967-024-05449-4.
24. Ahmed TM, Zhu Z, Yasrab M, et al. Preoperative prediction of lymph node metastases in nonfunctional pancreatic neuroendocrine tumors using a combined CT radiomics-clinical model. Ann Surg Oncol, 2024, 31(12): 8136-8145.
25. Zhang N, He J, Maithel SK, et al. Accuracy and prognostic impact of nodal status on preoperative imaging for management of pancreatic neuroendocrine tumors: a multi-institutional study. Ann Surg Oncol, 2024, 31(5): 2882-2891.
26. Han S, Kim JH, Yoo J, et al. Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors. Eur Radiol, 2022, 32(4): 2506-2517.
27. Sun HT, Zhang SL, Liu K, et al. MRI-based nomogram estimates the risk of recurrence of primary nonmetastatic pancreatic neuroendocrine tumors after curative resection. J Magn Reson Imaging, 2019, 50(2): 397-409.
28. Zhu HB, Nie P, Jiang L, et al. Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study. Insights Imaging, 2022, 13(1): 162. doi: 10.1186/s13244-022-01301-9.
29. Harimoto N, Araki K, Hoshino K, et al. Diffusion-weighted MRI predicts lymph node metastasis and tumor aggressiveness in resectable pancreatic neuroendocrine tumors. World J Surg, 2020, 44(12): 4136-4141.
30. Gu W, Chen Y, Zhu H, et al. 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, 2023, 65: 102269. doi: 10.1016/j.eclinm.2023.102269.
31. Mori M, Palumbo D, Muffatti F, et al. Prediction of the characteristics of aggressiveness of pancreatic neuroendocrine neoplasms (PanNENs) based on CT radiomic features. Eur Radiol, 2023, 33(6): 4412-4421.
32. Mapelli P, Bezzi C, Muffatti F, et al. Somatostatin receptor activity assessed by ⁶⁸Ga-DOTATOC PET can preoperatively predict DAXX/ATRX loss of expression in well-differentiated pancreatic neuroendocrine tumors. Eur J Nucl Med Mol Imaging, 2023, 50(9): 2818-2829.
33. Mapelli P, Bezzi C, Palumbo D, et al. ⁶⁸Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine well-differentiated tumours. Eur J Nucl Med Mol Imaging, 2022, 49(7): 2352-2363.
34. Mapelli P, Bezzi C, Muffatti F, et al. Preoperative assessment of lymph nodal metastases with [⁶⁸Ga]Ga-DOTATOC PET radiomics for improved surgical planning in well-differentiated pancreatic neuroendocrine tumours. Eur J Nucl Med Mol Imaging, 2024, 51(9): 2774-2783.
35. Khanna L, Prasad SR, Sunnapwar A, et al. Pancreatic neuroendocrine neoplasms: 2020 update on pathologic and imaging findings and classification. Radiographics, 2020, 40(5): 1240-1262.
36. 何達, 宋彬. 胰腺神經內分泌腫瘤診療現狀. 中國普通外科雜志, 2024, 33(3): 311-320.
37. 趙燕, 胡世康, 王利, 等. 不同病理級別胰腺神經內分泌腫瘤的鑒別: 基于CT影像特征. 中國普外基礎與臨床雜志, 2025, 32(5): 590-595.
38. Yamamoto Y, Okamura Y, Uemura S, et al. Vascularity and tumor size are significant predictors for recurrence after resection of a pancreatic neuroendocrine tumor. Ann Surg Oncol, 2017, 24(8): 2363-2370.
39. Takahashi Y, Akishima-Fukasawa Y, Kobayashi N, et al. Prognostic value of tumor architecture, tumor-associated vascular characteristics, and expression of angiogenic molecules in pancreatic endocrine tumors. Clin Cancer Res, 2007, 13(1): 187-196.
40. Liu YL, Zhu HB, Chen ML, et al. Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging. World J Gastrointest Surg, 2023, 15(12): 2809-2819.
41. Jeon SK, Lee JM, Joo I, et al. Nonhypervascular pancreatic neuroendocrine tumors: differential diagnosis from pancreatic ductal adenocarcinomas at MR imaging-retrospective cross-sectional study. Radiology, 2017, 284(1): 77-87.
42. Ahn B, Park HJ, Kim HJ, et al. Radiologic tumor border can further stratify prognosis in patients with pancreatic neuroendocrine tumor. Pancreatology, 2024, 24(5): 753-763.
43. 陳小勇, 徐敬慈, 李芹芹, 等. CT征象對胰腺神經內分泌腫瘤侵襲性行為的預測價值. CT理論與應用研究, 2022, 31(3): 399-407.
44. Nanno Y, Toyama H, Matsumoto I, et al. Reappraisal of malignant risk assessment for small (≤20 mm) non-functioning pancreatic neuroendocrine tumors. Ann Surg Oncol, 2023, 30(6): 3493-3500.
45. Makris EA, Cannon JGD, Norton JA, et al. Calcifications and cystic morphology on preoperative imaging predict survival after resection of pancreatic neuroendocrine tumors. Ann Surg Oncol, 2023, 30(4): 2424-2430.
46. Shen X, Yang F, Jiang T, et al. A nomogram to preoperatively predict the aggressiveness of non-functional pancreatic neuroendocrine tumors based on CT features. Eur J Radiol, 2024, 171: 111284. doi: 10.1016/j.ejrad.2023.111284.
47. Abdulrezzak U, Kurt YK, Kula M, et al. Combined imaging with ⁶⁸Ga-DOTA-TATE and ¹⁸F-FDG PET/CT on the basis of volumetric parameters in neuroendocrine tumors. Nucl Med Commun, 2016, 37(8): 874-881.
48. Sato A, Masui T, Yogo A, et al. Usefulness of ¹⁸F-FDG-PET/CT in the diagnosis and prediction of recurrence of pancreatic neuroendocrine neoplasms. J Hepatobiliary Pancreat Sci, 2020, 27(7): 414-420.
49. Heo S, Park HJ, Kim HJ, et al. Prognostic value of CT-based radiomics in grade 1-2 pancreatic neuroendocrine tumors. Cancer Imaging, 2024, 24(1): 28. doi: 10.1186/s40644-024-00673-z.
50. Park YJ, Park YS, Kim ST, et al. A machine learning approach using [¹⁸F]FDG PET-based radiomics for prediction of tumor grade and prognosis in pancreatic neuroendocrine tumor. Mol Imaging Biol, 2023, 25(5): 897-910.
51. Mizumoto T, Toyama H, Terai S, et al. Prediction of lymph node metastasis in pancreatic neuroendocrine tumors by contrast enhancement characteristics. Pancreatology, 2017, 17(6): 956-961.
52. Singh S, Chan DL, Moody L, et al. Recurrence in resected gastroenteropancreatic neuroendocrine tumors. JAMA Oncol, 2018, 4(4): 583-585.
53. Chen H, Li Z, Hu Y, et al. Maximum value on arterial phase computed tomography predicts prognosis and treatment efficacy of sunitinib for pancreatic neuroendocrine tumours. Ann Surg Oncol, 2023, 30(5): 2988-2998.
54. Chen L, Wang W, Jin K, et al. Special issue “The advance of solid tumor research in China”: prediction of sunitinib efficacy using computed tomography in patients with pancreatic neuroendocrine tumors. Int J Cancer, 2023, 152(1): 90-99.
55. Ingenerf M, Kiesl S, Winkelmann M, et al. Treatment assessment of pNET and NELM after everolimus by quantitative MRI parameters. Biomedicines, 2022, 10(10): 2618. doi: 10.3390/biomedicines10102618.
56. Ingenerf M, Karim H, Auernhammer C, et al. Quantitative SSTR-PET/CT for predicting response and survival outcomes in patients with pancreatic neuroendocrine tumors receiving CAPTEM. Radiol Oncol, 2023, 57(4): 436-445.
57. ?nner H, Abdülrezzak ü, Tutu? A. Could the skewness and kurtosis texture parameters of lesions obtained from pretreatment Ga-⁶⁸DOTA-TATE PET/CT images predict receptor radionuclide therapy response in patients with gastroenteropancreatic neuroendocrine tumors? Nucl Med Commun, 2020, 41(10): 1034-1039.
58. Pettersson OJ, Fr?ss-Baron K, Crona J, et al. Tumor growth rate in pancreatic neuroendocrine tumor patients undergoing PRRT with ¹⁷⁷Lu-DOTATATE. Endocr Connect, 2021, 10(4): 422-431.

CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Advances in imaging for assessment of biological behavior and prognosis in pancreatic neuroendocrine tumors

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