Literature DB >> 27543074

Prediction of pancreatic neuroendocrine tumour grade with MR imaging features: added value of diffusion-weighted imaging.

Emad Lotfalizadeh1, Maxime Ronot2,3,4, Mathilde Wagner1,5, Jérôme Cros6,7, Anne Couvelard6,7, Marie-Pierre Vullierme1, Wassim Allaham1, Olivia Hentic8, Philippe Ruzniewski8, Valérie Vilgrain1,6,5.   

Abstract

OBJECTIVES: To evaluate the value of MR imaging including diffusion-weighted imaging (DWI) for the grading of pancreatic neuroendocrine tumours (pNET).
MATERIAL AND METHODS: Between 2006 and 2014, all resected pNETs with preoperative MR imaging including DWI were included. Tumour grading was based on the 2010 WHO classification. MR imaging features included size, T1-w, and T2-w signal intensity, enhancement pattern, apparent (ADC) and true diffusion (D) coefficients.
RESULTS: One hundred and eight pNETs (mean 40 ± 33 mm) were evaluated in 94 patients (48 women, 51 %, mean age 52 ± 12). Fifty-five (51 %), 42 (39 %), and 11 (10 %) tumours were given the following grades (G): G1, G2, and G3. Mean ADC and D values were significantly lower as grade increased (ADC: 2.13 ± 0.70, 1.78 ± 0.72, and 0.86 ± 0.22 10-3 mm2/s, and D: 1.92 ± 0.70, 1.75 ± 0.74, and 0.82 ± 0.19 10-3 mm2/s G1, G2, and G3, all p < 0.001). A higher grade was associated with larger sized tumours (p < 0.001). The AUROC of ADC and D to differentiate G3 and G1-2 were 0.96 ± 0.02 and 0.95 ± 0.02. Optimal cut-off values for the identification of G3 were 1.19 10-3 mm2/s for ADC (sensitivity 100 %, specificity 92 %) and 1.04 10-3 mm2/s for D (sensitivity 82 %, specificity 92 %).
CONCLUSION: Morphological/functional MRI features of pNETS depend on tumour grade. DWI is useful for the identification of high-grade tumours. KEY POINTS: • Morphological and functional MRI features of pNETs depend on tumour grade. • Their combination has a high predictive value for grade. • All pNETs should be explored by MR imaging including DWI. • DWI is helpful for identification of high-grade and poorly-differentiated tumours.

Entities:  

Keywords:  Carcinoma; Grading; Ki-67; Neoplasm; Pancreas

Mesh:

Year:  2016        PMID: 27543074     DOI: 10.1007/s00330-016-4539-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  27 in total

1.  Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

Authors:  Xuan Gao; Xiaolin Wang
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-09-26       Impact factor: 2.924

2.  The North American Neuroendocrine Tumor Society Consensus Paper on the Surgical Management of Pancreatic Neuroendocrine Tumors.

Authors:  James R Howe; Nipun B Merchant; Claudius Conrad; Xavier M Keutgen; Julie Hallet; Jeffrey A Drebin; Rebecca M Minter; Terry C Lairmore; Jennifer F Tseng; Herbert J Zeh; Steven K Libutti; Gagandeep Singh; Jeffrey E Lee; Thomas A Hope; Michelle K Kim; Yusuf Menda; Thorvardur R Halfdanarson; Jennifer A Chan; Rodney F Pommier
Journal:  Pancreas       Date:  2020-01       Impact factor: 3.327

3.  Accuracy of apparent diffusion coefficient in differentiating pancreatic neuroendocrine tumour from intrapancreatic accessory spleen.

Authors:  Ankur Pandey; Pallavi Pandey; Mounes Aliyari Ghasabeh; Farnaz Najmi Varzaneh; Pegah Khoshpouri; Nannan Shao; Manijeh Zargham Pour; Daniel Fadaei Fouladi; Ralph H Hruban; Anne Marie O'Broin-Lennon; Ihab R Kamel
Journal:  Eur Radiol       Date:  2017-11-13       Impact factor: 5.315

Review 4.  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

5.  Simple Vascular Architecture Classification in Predicting Pancreatic Neuroendocrine Tumor Grade and Prognosis.

Authors:  Ke Chen; Wenming Zhang; Zhaozhen Zhang; Yiping He; Yuan Liu; Xiujiang Yang
Journal:  Dig Dis Sci       Date:  2018-08-18       Impact factor: 3.199

6.  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

7.  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

8.  Wireless amplified NMR detector for improved visibility of image contrast in heterogeneous lesions.

Authors:  Xianchun Zeng; Shengqiang Xu; Changyong Cao; Jian Wang; Chunqi Qian
Journal:  NMR Biomed       Date:  2018-07-16       Impact factor: 4.044

9.  Efficacy of apparent diffusion coefficient in predicting aggressive histological features of papillary thyroid carcinoma.

Authors:  Bin Song; Hao Wang; Yongqi Chen; Weiyan Liu; Ran Wei; Yi Ding
Journal:  Diagn Interv Radiol       Date:  2018-11       Impact factor: 2.630

10.  Ferumoxytol-enhanced MR imaging for differentiating intrapancreatic splenules from other tumors.

Authors:  M R Muehler; V R Rendell; L L Bergmann; E R Winslow; S B Reeder
Journal:  Abdom Radiol (NY)       Date:  2020-12-30
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.