Clinicopathologic Characteristics of Neuroendocrine Tumors with Assessment by Digital Image Analysis for Ki-67 Index with a Focus on the Gastroenteropancreatic Tract: a Single-center Study

Overview

Journal Int J Clin Exp Pathol

Specialty Pathology

Date 2023 Oct 11

PMID 37818384

Authors

Ji Hyun Park

Su-Jin Shin

Nara Jeon

Beom Jin Lim

Affiliations

Soon will be listed here.

Abstract

Objectives: Neuroendocrine tumors (NETs) are a heterogeneous group of tumors that arise at various sites throughout the body. The gastroenteropancreatic (GEP) tract is the most common site of NETs. We investigated the clinicopathologic features of patients with GEP-NETs and the utility of digital image analysis, which was compared to eyeball estimation, a conventional method used to determine the Ki-67 labeling index.

Methods: The clinicopathologic data of GEP-NET patients at Gangnam Severance Hospital from January 2008 to October 2019 were retrospectively analyzed. Each case was reclassified according to the 2019 World Health Organization classification system, to which the classification of grade 3 was added. Comparisons between eyeball estimation and the digital image analysis method for Ki-67 index assessment were performed by calculating Cohen's kappa (k) coefficient.

Results: In total, 345 patients with GEP-NETs were enrolled. The mean age was 49.3 (range 13-79) years, with more male (61.1%) than female patients. The primary tumor sites were the rectum (70.1%), pancreas (12.5%), stomach (6.7%), and duodenum (5.8%). Overall, 298 (86.4%), 35 (10.1%), 2 (0.6%), and 10 (2.9%) patients exhibited grade 1, 2, and 3 and neuroendocrine carcinoma, respectively. Statistical analysis revealed that age > 50 years, tumor size > 2 cm, and presence of lymphovascular invasion, nodal metastasis, and distant metastasis were significantly associated with short overall survival. Additionally, 283 patients underwent digital image analysis of the Ki-67 index, and substantial agreement was found between the two methods (κ value: 0.765).

Conclusions: Eyeball estimation revealed non-inferior results compared with digital image analysis. Further research is needed to evaluate the possibility of using digital image analysis as an alternative analysis method.

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References

Yao J, Hassan M, Phan A, Dagohoy C, Leary C, Mares J . One hundred years after "carcinoid": epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol. 2008; 26(18):3063-72. DOI: 10.1200/JCO.2007.15.4377. View

Strosberg J, Cheema A, Weber J, Han G, Coppola D, Kvols L . Prognostic validity of a novel American Joint Committee on Cancer Staging Classification for pancreatic neuroendocrine tumors. J Clin Oncol. 2011; 29(22):3044-9. DOI: 10.1200/JCO.2011.35.1817. View

Tang L, Gonen M, Hedvat C, Modlin I, Klimstra D . Objective quantification of the Ki67 proliferative index in neuroendocrine tumors of the gastroenteropancreatic system: a comparison of digital image analysis with manual methods. Am J Surg Pathol. 2012; 36(12):1761-70. DOI: 10.1097/PAS.0b013e318263207c. View

Kloppel G, Couvelard A, Perren A, Komminoth P, McNicol A, Nilsson O . ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: towards a standardized approach to the diagnosis of gastroenteropancreatic neuroendocrine tumors and their prognostic stratification. Neuroendocrinology. 2008; 90(2):162-6. DOI: 10.1159/000182196. View

Zhong F, Bi R, Yu B, Yang F, Yang W, Shui R . A Comparison of Visual Assessment and Automated Digital Image Analysis of Ki67 Labeling Index in Breast Cancer. PLoS One. 2016; 11(2):e0150505. PMC: 4771161. DOI: 10.1371/journal.pone.0150505. View

Bellizzi A . Pathologic Considerations in Gastroenteropancreatic Neuroendocrine Tumors. Surg Oncol Clin N Am. 2020; 29(2):185-208. PMC: 7212902. DOI: 10.1016/j.soc.2019.11.003. View

Williams E, Sandler M . The classification of carcinoid tum ours. Lancet. 1963; 1(7275):238-9. DOI: 10.1016/s0140-6736(63)90951-6. View

Song L, Zhai X, Yu S, Ma Y, Wang F, Yu X . Clinical analysis of 547 patients with neuroendocrine tumors in a Chinese population: A single-center study. Cancer Med. 2019; 8(8):3729-3737. PMC: 6639184. DOI: 10.1002/cam4.2259. View

Cai W, Tan Y, Ge W, Ding K, Hu H . Pattern and risk factors for distant metastases in gastrointestinal neuroendocrine neoplasms: a population-based study. Cancer Med. 2018; 7(6):2699-2709. PMC: 6010810. DOI: 10.1002/cam4.1507. View

10.

Reid M, Bagci P, Ohike N, Saka B, Erbarut Seven I, Dursun N . Calculation of the Ki67 index in pancreatic neuroendocrine tumors: a comparative analysis of four counting methodologies. Mod Pathol. 2015; 29(1):93. DOI: 10.1038/modpathol.2015.124. View

11.

Erickson L, Lloyd R . Practical markers used in the diagnosis of endocrine tumors. Adv Anat Pathol. 2004; 11(4):175-89. DOI: 10.1097/01.pap.0000131824.77317.a7. View

12.

Dasari A, Shen C, Halperin D, Zhao B, Zhou S, Xu Y . Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States. JAMA Oncol. 2017; 3(10):1335-1342. PMC: 5824320. DOI: 10.1001/jamaoncol.2017.0589. View

13.

Coriat R, Walter T, Terris B, Couvelard A, Ruszniewski P . Gastroenteropancreatic Well-Differentiated Grade 3 Neuroendocrine Tumors: Review and Position Statement. Oncologist. 2016; 21(10):1191-1199. PMC: 5061528. DOI: 10.1634/theoncologist.2015-0476. View

14.

Kim J, Hong S, Ro J . Recent updates on grading and classification of neuroendocrine tumors. Ann Diagn Pathol. 2017; 29:11-16. DOI: 10.1016/j.anndiagpath.2017.04.005. View

15.

Klimstra D, Modlin I, Coppola D, Lloyd R, Suster S . The pathologic classification of neuroendocrine tumors: a review of nomenclature, grading, and staging systems. Pancreas. 2010; 39(6):707-12. DOI: 10.1097/MPA.0b013e3181ec124e. View

16.

Tsai H, Wu C, Tsai C, Lin S, Chen L, Chang J . The epidemiology of neuroendocrine tumors in Taiwan: a nation-wide cancer registry-based study. PLoS One. 2013; 8(4):e62487. PMC: 3632554. DOI: 10.1371/journal.pone.0062487. View

17.

Kloppel G, Perren A, Heitz P . The gastroenteropancreatic neuroendocrine cell system and its tumors: the WHO classification. Ann N Y Acad Sci. 2004; 1014:13-27. DOI: 10.1196/annals.1294.002. View

18.

Fulawka L, Blaszczyk J, Tabakov M, Halon A . Assessment of Ki-67 proliferation index with deep learning in DCIS (ductal carcinoma in situ). Sci Rep. 2022; 12(1):3166. PMC: 8873444. DOI: 10.1038/s41598-022-06555-3. View

19.

Chi Y, Jiang W, Du F, Sun Y, Song Y, Yang L . [Neuroendocrine tumors: analysis of 252 cases]. Zhonghua Zhong Liu Za Zhi. 2013; 35(1):67-70. DOI: 10.3760/cma.j.issn.0253-3766.2013.01.015. View

20.

Boukhar S, Gosse M, Bellizzi A, Rajan K D A . Ki-67 Proliferation Index Assessment in Gastroenteropancreatic Neuroendocrine Tumors by Digital Image Analysis With Stringent Case and Hotspot Level Concordance Requirements. Am J Clin Pathol. 2021; 156(4):607-619. PMC: 8427716. DOI: 10.1093/ajcp/aqaa275. View