A Novel Observational Strategy for Nonfunctional Pancreatic Neuroendocrine Neoplasms With Texture Analysis: A Multicenter Retrospective Study.

Background/aim: Surgical resection is recommended for nonfunctional pancreatic neuroendocrine neoplasms (NF-pNENs). However, metastasis is rare in patients with small lesions with histological grade 1 (G1); thus, observation is an optional treatment approach for small NF-pNENs. Texture analysis (TA) is an imaging analysis mode for quantification of heterogeneity by extracting quantitative parameters from images. We retrospectively evaluated the utility of TA in predicting histological grade of resected NF-pNENs in a multicenter retrospective study.

Patients And Methods: The utility of TA in preoperative prediction of grade were evaluated with 29 patients treated by pancreatectomy for NF-pNEN who underwent preoperative dynamic computed tomography scan between January 1, 2013 and December 31, 2020 at three hospitals affiliated with the Jikei University School of Medicine. TA was performed with dedicated software for medical imaging processing for determining histological tumor grade using dynamic computed tomography images.

Results: Histological tumor grades based on the 2017 World Health Organization Classification for Pancreatic Neuroendocrine Neoplasms were grade 1, 2 and 3 in 18, 10 and one patient, respectively. Preoperative grades by TA were 1 and 2/3 in 15 and 14 patients, respectively. The sensitivity, specificity and area under the curve for TA-oriented grade 1 lesions were 1.00, 0.889 and 0.965 (95% confidence interval=0.901-1.000), respectively.

Conclusion: TA is useful for predicting grade 2/3 NF-pNEN and can provide a safe option for observation for patients with small grade 1 lesions.