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Post-neoadjuvant treatment pancreatic cancer resectability and outcome prediction using CT, 18F-FDG PET/MRI and CA 19–9

Authors :
Jeongin Yoo
Jeong Min Lee
Ijin Joo
Dong Ho Lee
Jeong Hee Yoon
Mi Hye Yu
Jin-Young Jang
Sang Hyub Lee
Source :
Cancer Imaging, Vol 23, Iss 1, Pp 1-13 (2023)
Publication Year :
2023
Publisher :
BMC, 2023.

Abstract

Abstract Background CT prediction of resectability and prognosis following neoadjuvant treatment (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aims to determine whether addition of 18F-fluorodeoxyglucose (FDG) postiron emission tomography (PET)/MRI and carbohydrate antigen (CA) 19–9 to contrast-enhanced CT (CECT) can improve accuracy of predicting resectability compared to CECT alone and predict prognosis in PDAC patients after NAT. Methods In this retrospective study, 120 PDAC patients (65 women; mean age, 66.7 years [standard deviation, 8.4]) underwent CECT, PET/MRI, and CA 19–9 examinations after NAT between January 2013 and June 2021. Three board-certified radiologists independently rated the overall resectability on a 5-point scale (score 5, definitely resectable) in three sessions (session 1, CECT; 2, CECT plus PET/MRI─no FDG avidity and no diffusion restriction at tumor-vessel contact indicated modification of CECT scores to ≥ 3; 3, CECT plus PET plus CA 19–9─no FDG avidity at tumor-vessel contact and normalized CA 19–9 indicated modification of CECT scores to ≥ 3). Jackknife free-response receiver operating characteristic method and generalized estimating equations were used to compare pooled area under the curve (AUC), sensitivity, and specificity of three sessions. Predictors for recurrence-free survival (RFS) were assessed using Cox regression analyses. Results Each session showed different pooled AUC (session 1 vs. 2 vs. 3, 0.853 vs. 0.873 vs. 0.874, p = 0.026), sensitivity (66.2% [137/207] vs. 86.0% [178/207] vs. 84.5% [175/207], p

Details

Language :
English
ISSN :
14707330
Volume :
23
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Cancer Imaging
Publication Type :
Academic Journal
Accession number :
edsdoj.7c0dd0f3e2b4915a1a4f893e127b72d
Document Type :
article
Full Text :
https://doi.org/10.1186/s40644-023-00565-8