» Articles » PMID: 32498099

Endoscopic Ultrasound-guided Fine-needle Aspiration for the Diagnosis and Grading of Pancreatic Neuroendocrine Tumors: a Retrospective Analysis of 110 Cases

Abstract

Background: Data on the reliability of the Ki-67 index and grading calculations from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) of pancreatic neuroendocrine tumors (PanNETs) are controversial. We aimed to assess the accuracy of these data compared with histology.

Methods: Cytological analysis from EUS-FNA in patients with suspected PanNETs (n = 110) were compared with resection samples at a single institution. A minimum of 2000 cells were considered to be adequate for grading. Correlation and agreement between cytology and histology in grading and Ki-67 values, respectively, were investigated. Secondary outcomes included the diagnostic performance of EUS-FNA.

Results: EUS-FNA samples were adequate for PanNET diagnosis and PanNET grading in 98/110 (89.1 %) and 77/110 (70.0 %) patients, respectively; thus, 77 samples were adequate for comparing cytology vs. histology. There were 67 (62.0 %), 40 (36.4 %), and 1 (0.9 %) patients with a final diagnosis of G1, G2, and G3 tumors, respectively. EUS-FNA grading was concordant with surgical pathology in 81.8 % of patients; under- and overgrading occurred in 15.6 % and 2.6 %, respectively. The overall level of agreement for grading was moderate (Cohen's κ = 0.59, 95 % confidence interval [CI] 0.34 - 0.78). Spearman's rho for Ki-67 in tumors ≤ 20 mm and > 20 mm was strong and moderate, respectively (rho = 0.68, 95 %CI 0.47 - 0.83; rho = 0.59, 95 %CI 0.35 - 0.75). The Bland - Altman plot showed that the Ki-67 values were comparable and reproducible between the two measurements.

Conclusions: Although they were not available for a significant number of patients, grading and Ki-67 values from cytology correlated with histology moderately to strongly.

Citing Articles

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.

Mo S, Huang C, Wang Y, Qin S BMC Med Imaging. 2025; 25(1):22.

PMID: 39827128 PMC: 11743008. DOI: 10.1186/s12880-025-01555-x.


The diagnostic value of endoscopic ultrasound for esophageal subepithelial lesions: A review.

Li W, Shao M, Hu S, Xie S, He B Medicine (Baltimore). 2024; 103(46):e40419.

PMID: 39560558 PMC: 11576025. DOI: 10.1097/MD.0000000000040419.


A novel endoscopic ultrasomics-based machine learning model and nomogram to predict the pathological grading of pancreatic neuroendocrine tumors.

Mo S, Wang Y, Huang C, Wu W, Qin S Heliyon. 2024; 10(14):e34344.

PMID: 39130461 PMC: 11315146. DOI: 10.1016/j.heliyon.2024.e34344.


Surgery for pancreatic neuroendocrine tumors during the COVID-19 pandemic: a retrospective cohort from a high-volume center.

Paiella S, Landoni L, De Pastena M, Elio G, Casciani F, Cingarlini S Updates Surg. 2024; 76(5):1827-1832.

PMID: 39033485 PMC: 11455720. DOI: 10.1007/s13304-024-01942-z.


Pancreatic Neuroendocrine Tumor (Pan-NET) Presented by Abdominal Pain: A Case Report and Literature Review.

Regolo M, Cardaci N, Salmeri C, Laudani A, Colaci M, Ippolito M J Clin Med. 2023; 12(20).

PMID: 37892755 PMC: 10607714. DOI: 10.3390/jcm12206617.