Literature DB >> 28480609

Pancreatic neuroendocrine tumor: Correlations between MRI features, tumor biology, and clinical outcome after surgery.

Rodrigo Canellas1, Grace Lo1, Sreejita Bhowmik1, Cristina Ferrone2, Dushyant Sahani1.   

Abstract

PURPOSE: To assess which magnetic resonance imaging (MRI) features are associated with pNETs (pancreatic neuroendocrine tumors) grade based on the WHO classification, as well as identify MRI features related to disease progression after surgery.
MATERIALS AND METHODS: In this Institutional Review Board (IRB)-approved study, 1.5T and 3.0T MRI scans of 80 patients with surgically verified pNETs were assessed. The images were evaluated for tumor location; size; pattern; predominant signal intensity on precontrast T1 - and T2 -weighted images, as well as on postcontrast arterial and portal venous phase T1 -weighted sequences; presence of pancreatic duct dilatation; pancreatic atrophy; restricted diffusion; vascular involvement by the tumor; extrapancreatic tumor spread; and synchronous liver metastases. Tumors were graded based on the WHO classification and patients were followed-up with computed tomography (CT) or MRI after surgical resection. Data were analyzed with Student's t and chi-square tests, logistic regression, and Kaplan-Meier curves.
RESULTS: The MRI features that were associated with aggressive tumors were: size >2.0 cm (odds ratio [OR] = 4.8, P = 0.002), "T2 nonbright lesions" on T2 -weighted images (OR = 4.6, P = 0.008), presence of pancreatic ductal dilatation (OR = 4.9, P = 0.024), and restricted diffusion within the lesion (OR = 4.9, P = 0.013). Differences in progression-free survival distribution were found for patients whose pNETs were associated with the following MRI features: size >2.0 cm (χ2 (1) = 6.0, P = 0.014), "nonbright lesions" on T2 -weighted images (χ2 (1) = 6.8, P = 0.009), and presence of pancreatic duct dilatation (χ2 (1) = 10.9, P = 0.001).
CONCLUSION: MRI features can be used to assess pNETs aggressiveness and identify patients at risk for early disease progression after surgical resection. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:425-432.
© 2017 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  MRI; WHO classification; pancreatic NET grade; pancreatic neuroendocrine tumors

Mesh:

Year:  2017        PMID: 28480609     DOI: 10.1002/jmri.25756

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  10 in total

1.  Serotonin immunoreactive pancreatic neuroendocrine neoplasm associated with main pancreatic duct dilation: a recognizable entity with excellent long-term outcome.

Authors:  Marco Dioguardi Burgio; Jérome Cros; Nicola Panvini; Thomas Depoilly; Anne Couvelard; Philippe Ruszniewski; Louis de Mestier; Olivia Hentic; Alain Sauvanet; Safi Dokmak; Alex Faccinetto; Maxime Ronot; Valérie Vilgrain
Journal:  Eur Radiol       Date:  2021-05-11       Impact factor: 5.315

Review 2.  Imaging of pancreatic neuroendocrine tumors: recent advances, current status, and controversies.

Authors:  Lingaku Lee; Tetsuhide Ito; Robert T Jensen
Journal:  Expert Rev Anticancer Ther       Date:  2018-07-17       Impact factor: 4.512

3.  Can histogram analysis of MR images predict aggressiveness in pancreatic neuroendocrine tumors?

Authors:  Riccardo De Robertis; Bogdan Maris; Nicolò Cardobi; Paolo Tinazzi Martini; Stefano Gobbo; Paola Capelli; Silvia Ortolani; Sara Cingarlini; Salvatore Paiella; Luca Landoni; Giovanni Butturini; Paolo Regi; Aldo Scarpa; Giampaolo Tortora; Mirko D'Onofrio
Journal:  Eur Radiol       Date:  2018-01-19       Impact factor: 5.315

4.  Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study.

Authors:  Hai-Bin Zhu; Pei Nie; Liu Jiang; Juan Hu; Xiao-Yan Zhang; Xiao-Ting Li; Ming Lu; Ying-Shi Sun
Journal:  Insights Imaging       Date:  2022-10-08

5.  Pancreatic neuroendocrine tumor: prediction of the tumor grade using magnetic resonance imaging findings and texture analysis with 3-T magnetic resonance.

Authors:  Chuan-Gen Guo; Shuai Ren; Xiao Chen; Qi-Dong Wang; Wen-Bo Xiao; Jing-Feng Zhang; Shao-Feng Duan; Zhong-Qiu Wang
Journal:  Cancer Manag Res       Date:  2019-03-04       Impact factor: 3.989

6.  Usefulness of selective arterial calcium injection tests for functional pancreatic neuroendocrine tumors.

Authors:  Yutaka Nakano; Minoru Kitago; Masahiro Shinoda; Seishi Nakatsuka; Isao Kurihara; Hiroshi Yagi; Yuta Abe; Go Oshima; Shutaro Hori; Takahiro Yokose; Yuko Kitagawa
Journal:  Sci Rep       Date:  2021-01-08       Impact factor: 4.379

7.  A [68Ga]Ga-DOTANOC PET/CT Radiomic Model for Non-Invasive Prediction of Tumour Grade in Pancreatic Neuroendocrine Tumours.

Authors:  Alessandro Bevilacqua; Diletta Calabrò; Silvia Malavasi; Claudio Ricci; Riccardo Casadei; Davide Campana; Serena Baiocco; Stefano Fanti; Valentina Ambrosini
Journal:  Diagnostics (Basel)       Date:  2021-05-12

8.  Quantitative Computed Tomography Image Analysis to Predict Pancreatic Neuroendocrine Tumor Grade.

Authors:  Alessandra Pulvirenti; Rikiya Yamashita; Jayasree Chakraborty; Natally Horvat; Kenneth Seier; Caitlin A McIntyre; Sharon A Lawrence; Abhishek Midya; Maura A Koszalka; Mithat Gonen; David S Klimstra; Diane L Reidy; Peter J Allen; Richard K G Do; Amber L Simpson
Journal:  JCO Clin Cancer Inform       Date:  2021-06

9.  The latest exploration of staging and prognostic classification for pancreatic neuroendocrine tumors: a large population-based study.

Authors:  Shanshan Gao; Ning Pu; Lingxiao Liu; Changyu Li; Xuefeng Xu; Xiaolin Wang; Wenhui Lou
Journal:  J Cancer       Date:  2018-04-19       Impact factor: 4.207

10.  Updated Trends in Imaging Practices for Pancreatic Neuroendocrine Tumors (PNETs): A Systematic Review and Meta-Analysis to Pave the Way for Standardization in the New Era of Big Data and Artificial Intelligence.

Authors:  Ephraïm Partouche; Randy Yeh; Thomas Eche; Laura Rozenblum; Nicolas Carrere; Rosine Guimbaud; Lawrence O Dierickx; Hervé Rousseau; Laurent Dercle; Fatima-Zohra Mokrane
Journal:  Front Oncol       Date:  2021-07-14       Impact factor: 6.244

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.