Literature DB >> 24500090

Intravoxel incoherent motion diffusion-weighted imaging of pancreatic neuroendocrine tumors: prediction of the histologic grade using pure diffusion coefficient and tumor size.

Eui Jin Hwang1, Jeong Min Lee, Jeong Hee Yoon, Jung Hoon Kim, Joon Koo Han, Byung Ihn Choi, Kyoung-Bun Lee, Jin-Young Jang, Sun-Whe Kim, Marcel Dominik Nickel, Berthold Kiefer.   

Abstract

PURPOSE: The purpose of this study was to assess the value of intravoxel incoherent motion and diffusion-weighted imaging for predicting the histologic grade of pancreatic neuroendocrine tumors (PNETs).
MATERIALS AND METHODS: Forty patients with surgically diagnosed PNETs who underwent preoperative magnetic resonance imaging, including diffusion-weighted imaging with a series of 10 b values (0-1000 s/mm(2), were included in this institutional review board-approved retrospective study. The apparent diffusion coefficient (ADC(total)), the intravoxel incoherent motion parameters (pure diffusion coefficient [D], pseudodiffusion coefficient [D(*)], and perfusion fraction [f]) were measured on the tumors. Histologic grading was performed on the basis of the World Health Organization 2010 classification system. Logistic regression analysis and receiver operating curve analysis were performed to identify the significant factors predicting the histologic grades.
RESULTS: Grades 2 and 3 tumors were significantly larger than grade 1 tumors (average 3.62 cm vs 2.17 cm in diameter; P=0.001). Grades 2 and 3 tumors showed significantly lower D values than did grade 1 tumors (0.95 vs 1.21×10(-3) mm(2)/s; P=0.009), although the ADC(total) showed no significant difference. When any of the following 2 criteria was used, (a) tumor size smaller than 2.0 cm in diameter and (b) D value greater than 1.2×10(-3) mm(2)/s, the sensitivity, specificity, and positive predictive value for diagnosing grade 1 PNETs were 76.92%, 100%, and 100%, respectively.
CONCLUSIONS: Pure diffusion coefficient (D) is possibly a better marker than ADC(total) is for differentiating grade 1 from grade 2 or 3 PNET and, combined with tumor size, can predict grade 1 PNET with a high specificity.

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Year:  2014        PMID: 24500090     DOI: 10.1097/RLI.0000000000000028

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  20 in total

1.  CT radiomics may predict the grade of pancreatic neuroendocrine tumors: a multicenter study.

Authors:  Dongsheng Gu; Yabin Hu; Hui Ding; Jingwei Wei; Ke Chen; Hao Liu; Mengsu Zeng; Jie Tian
Journal:  Eur Radiol       Date:  2019-06-21       Impact factor: 5.315

2.  MR imaging of primary hepatic neuroendocrine neoplasm and metastatic hepatic neuroendocrine neoplasm: a comparative study.

Authors:  RuoFan Sheng; YanHong Xie; MengSu Zeng; Yuan Ji; ShengXiang Rao; CaiZhong Chen
Journal:  Radiol Med       Date:  2015-04-24       Impact factor: 3.469

3.  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

4.  Is the combination of MR and CT findings useful in determining the tumor grade of pancreatic neuroendocrine tumors?

Authors:  Fumihito Toshima; Dai Inoue; Takahiro Komori; Kotaro Yoshida; Norihide Yoneda; Tetsuya Minami; Osamu Matsui; Hiroko Ikeda; Toshifumi Gabata
Journal:  Jpn J Radiol       Date:  2017-03-03       Impact factor: 2.374

Review 5.  Various diffusion magnetic resonance imaging techniques for pancreatic cancer.

Authors:  Meng-Yue Tang; Xiao-Ming Zhang; Tian-Wu Chen; Xiao-Hua Huang
Journal:  World J Radiol       Date:  2015-12-28

6.  Use of intravoxel incoherent motion diffusion-weighted MR imaging for assessment of treatment response to invasive fungal infection in the lung.

Authors:  Chenggong Yan; Jun Xu; Wei Xiong; Qi Wei; Ru Feng; Yuankui Wu; Qifa Liu; Caixia Li; Queenie Chan; Yikai Xu
Journal:  Eur Radiol       Date:  2016-05-14       Impact factor: 5.315

7.  Intravoxel incoherent motion: application in differentiation of hepatocellular carcinoma and focal nodular hyperplasia.

Authors:  Ma Luo; Ling Zhang; Xin Hua Jiang; Wei Dong Zhang
Journal:  Diagn Interv Radiol       Date:  2017 Jul-Aug       Impact factor: 2.630

Review 8.  State-of-the-art Imaging of Pancreatic Neuroendocrine Tumors.

Authors:  Eric P Tamm; Priya Bhosale; Jeffrey H Lee; Eric M Rohren
Journal:  Surg Oncol Clin N Am       Date:  2016-04       Impact factor: 3.495

Review 9.  Prognostication and response assessment in liver and pancreatic tumors: The new imaging.

Authors:  Riccardo De Robertis; Paolo Tinazzi Martini; Emanuele Demozzi; Gino Puntel; Silvia Ortolani; Sara Cingarlini; Andrea Ruzzenente; Alfredo Guglielmi; Giampaolo Tortora; Claudio Bassi; Paolo Pederzoli; Mirko D'Onofrio
Journal:  World J Gastroenterol       Date:  2015-06-14       Impact factor: 5.742

10.  Can MDCT or EUS features predict the histopathological grading scheme of pancreatic neuroendocrine neoplasms?

Authors:  Hui Zhu; Lang Ying; Wei Tang; Xiujiang Yang; Bo Sun
Journal:  Radiol Med       Date:  2017-02-07       Impact factor: 3.469

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