Literature DB >> 32709455

Morphological imaging and CT histogram analysis to differentiate pancreatic neuroendocrine tumor grade 3 from neuroendocrine carcinoma.

A Azoulay1, J Cros2, M-P Vullierme1, L de Mestier3, A Couvelard2, O Hentic4, P Ruszniewski3, A Sauvanet5, V Vilgrain6, M Ronot7.   

Abstract

PURPOSE: To compare morphological imaging features and CT texture histogram parameters between grade 3 pancreatic neuroendocrine tumors (G3-NET) and neuroendocrine carcinomas (NEC).
MATERIALS AND METHODS: Patients with pathologically proven G3-NET and NEC, according to the 2017 World Health Organization classification who had CT and MRI examinations between 2006-2017 were retrospectively included. CT and MRI examinations were reviewed by two radiologists in consensus and analyzed with respect to tumor size, enhancement patterns, hemorrhagic content, liver metastases and lymphadenopathies. Texture histogram analysis of tumors was performed on arterial and portal phase CT images. images. Morphological imaging features and CT texture histogram parameters of G3-NETs and NECs were compared.
RESULTS: Thirty-seven patients (21 men, 16 women; mean age, 56±13 [SD] years [range: 28-82 years]) with 37 tumors (mean diameter, 60±46 [SD] mm) were included (CT available for all, MRI for 16/37, 43%). Twenty-three patients (23/37; 62%) had NEC and 14 patients (14/37; 38%) had G3-NET. NECs were larger than G3-NETs (mean, 70±51 [SD] mm [range: 18 - 196mm] vs. 42±24 [SD] mm [range: 8 - 94mm], respectively; P=0.039), with more tumor necrosis (75% vs. 33%, respectively; P=0.030) and lower attenuation on precontrast (30±4 [SD] HU [range: 25-39 HU] vs. 37±6 [SD] [range: 25-45 HU], respectively; P=0.002) and on portal venous phase CT images (75±18 [SD] HU [range: 43 - 108 HU] vs. 92±19 [SD] HU [range: 46 - 117 HU], respectively; P=0.014). Hemorrhagic content on MRI was only observed in NEC (P=0.007). The mean ADC value was lower in NEC ([1.1±0.1 (SD)]×10-3 mm2/s [range: (0.91 - 1.3)×10-3 mm2/s] vs. [1.4±0.2 (SD)]×10-3 mm2/s [range: (1.1 - 1.6)×10-3 mm2/s]; P=0.005). CT histogram analysis showed that NEC were more heterogeneous on portal venous phase images (Entropy-0: 4.7±0.2 [SD] [range: 4.2-5.1] vs. 4.5±0.4 [SD] [range: 3.7-4.9]; P=0.023).
CONCLUSION: Pancreatic NECs are larger, more frequently hypoattenuating and more heterogeneous with hemorrhagic content than G3-NET on CT and MRI.
Copyright © 2020 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Entities:  

Keywords:  Magnetic resonance imaging; Neuroendocrine tumors; OMS 2017; Texture analysis; Tomography, X-ray computed

Mesh:

Year:  2020        PMID: 32709455     DOI: 10.1016/j.diii.2020.06.006

Source DB:  PubMed          Journal:  Diagn Interv Imaging        ISSN: 2211-5684            Impact factor:   4.026


  8 in total

Review 1.  Artificial intelligence: a critical review of current applications in pancreatic imaging.

Authors:  Maxime Barat; Guillaume Chassagnon; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2021-02-06       Impact factor: 2.374

Review 2.  CT and MRI of pancreatic tumors: an update in the era of radiomics.

Authors:  Marion Bartoli; Maxime Barat; Anthony Dohan; Sébastien Gaujoux; Romain Coriat; Christine Hoeffel; Christophe Cassinotto; Guillaume Chassagnon; Philippe Soyer
Journal:  Jpn J Radiol       Date:  2020-10-21       Impact factor: 2.374

Review 3.  GEP-NET radiomics: a systematic review and radiomics quality score assessment.

Authors:  Femke C R Staal; Else A Aalbersberg; Daphne van der Velden; Erica A Wilthagen; Margot E T Tesselaar; Regina G H Beets-Tan; Monique Maas
Journal:  Eur Radiol       Date:  2022-07-26       Impact factor: 7.034

4.  Clinicopathological features of esophageal schwannomas in mainland China: systematic review of the literature.

Authors:  Zi-Ye Gao; Xiao-Bo Liu; Sandeep Pandey; Bo Gao; Ping Liu; Qing-Hui Zhang; Yuan-Jun Gao; Sheng-Bao Li
Journal:  Int J Clin Oncol       Date:  2020-11-20       Impact factor: 3.402

5.  Prediction of the World Health Organization Grade of rectal neuroendocrine tumors based on CT histogram analysis.

Authors:  Ping Liang; Chuou Xu; Fangqin Tan; Shichao Li; Mingzhen Chen; Daoyu Hu; Ihab Kamel; Yaqi Duan; Zhen Li
Journal:  Cancer Med       Date:  2020-12-01       Impact factor: 4.452

Review 6.  Artificial Intelligence Applied to Pancreatic Imaging: A Narrative Review.

Authors:  Maria Elena Laino; Angela Ammirabile; Ludovica Lofino; Lorenzo Mannelli; Francesco Fiz; Marco Francone; Arturo Chiti; Luca Saba; Matteo Agostino Orlandi; Victor Savevski
Journal:  Healthcare (Basel)       Date:  2022-08-11

Review 7.  Digestive Well-Differentiated Grade 3 Neuroendocrine Tumors: Current Management and Future Directions.

Authors:  Anna Pellat; Anne Ségolène Cottereau; Lola-Jade Palmieri; Philippe Soyer; Ugo Marchese; Catherine Brezault; Romain Coriat
Journal:  Cancers (Basel)       Date:  2021-05-18       Impact factor: 6.639

Review 8.  Multimodal Management of Grade 1 and 2 Pancreatic Neuroendocrine Tumors.

Authors:  Ugo Marchese; Martin Gaillard; Anna Pellat; Stylianos Tzedakis; Einas Abou Ali; Anthony Dohan; Maxime Barat; Philippe Soyer; David Fuks; Romain Coriat
Journal:  Cancers (Basel)       Date:  2022-01-15       Impact factor: 6.639

  8 in total

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