Literature DB >> 31564038

Prospective comparison of whole-body MRI with diffusion-weighted and conventional imaging for the follow-up of neuroendocrine tumors.

Maximilien Minon1, Clothilde Soriano2, David Morland3,4, Thomas Walter5, Côme Lepage6, Antoine Tabarin7, Mathilde Deblock8, Pascal Rousset9, Coralie Barbe10, Christine Hoeffel11,4, Guillaume Cadiot2.   

Abstract

AIM: To determine whether whole-body magnetic resonance imaging is valuable in staging of neuroendocrine tumors by comparison with the conventional imaging defined by the combination of computed tomography and somatostatin receptor scintigraphy.
METHODS: This study concerned the patients included in the multicenter prospective study NCT02786303 with the following inclusion criteria: well-differentiated gastroenteropancreatic neuroendocrine tumors or of unknown primary, and computed tomography, whole-body magnetic resonance imaging and somatostatin receptor scintigraphy performed within 6 weeks. Results of the conventional imaging were compared with those of magnetic resonance imaging. Discrepancies between the conventional imaging and magnetic resonance imaging were evaluated by reviewing medical records.
RESULTS: Thirty-one patients (17 men and 14 women) were prospectively included. Complete concordance between the magnetic resonance imaging and the conventional imaging results was observed in 25 patients and discrepancies in 6. Whole-body magnetic resonance imaging detected more liver lesions than the conventional imaging did but standard imaging set was more effective in the detection of bone and peritoneum lesions than magnetic resonance imaging. Detecting more lesions had no impact on therapeutic management.
CONCLUSIONS: Whole-body magnetic resonance imaging including diffusion weighted may be a valuable alternative to computed tomography and somatostatin receptor scintigraphy. Further studies should compare whole-body MRI to the 68Ga PET/CT.

Entities:  

Keywords:  Computed tomography; Diffusion-weighted; Magnetic resonance imaging; Neuroendocrine tumor; Positron-emission tomography; Somatostatin receptor scintigraphy

Mesh:

Year:  2019        PMID: 31564038     DOI: 10.1007/s12020-019-02095-5

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.633


  19 in total

1.  ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: towards a standardized approach to the diagnosis of gastroenteropancreatic neuroendocrine tumors and their prognostic stratification.

Authors:  Günter Klöppel; Anne Couvelard; Aurel Perren; Paul Komminoth; Anne-Marie McNicol; Ola Nilsson; Aldo Scarpa; Jean-Yves Scoazec; Bertram Wiedenmann; Mauro Papotti; Guido Rindi; Ursula Plöckinger
Journal:  Neuroendocrinology       Date:  2009-08-28       Impact factor: 4.914

2.  ENETS Consensus Guidelines for the Standards of Care in Neuroendocrine Tumors: follow-up and documentation.

Authors:  Rudolf Arnold; Yuan-Jia Chen; Frederico Costa; Massimo Falconi; David Gross; Ashley B Grossman; Rudolf Hyrdel; Beata Kos-Kudła; Ramon Salazar; Ursula Plöckinger
Journal:  Neuroendocrinology       Date:  2009-08-28       Impact factor: 4.914

3.  Appropriate Use Criteria for Somatostatin Receptor PET Imaging in Neuroendocrine Tumors.

Authors:  Thomas A Hope; Emily K Bergsland; Murat Fani Bozkurt; Michael Graham; Anthony P Heaney; Ken Herrmann; James R Howe; Matthew H Kulke; Pamela L Kunz; Josh Mailman; Lawrence May; David C Metz; Corina Millo; Sue O'Dorisio; Diane L Reidy-Lagunes; Michael C Soulen; Jonathan R Strosberg
Journal:  J Nucl Med       Date:  2017-10-12       Impact factor: 10.057

4.  Detection of liver metastases from endocrine tumors: a prospective comparison of somatostatin receptor scintigraphy, computed tomography, and magnetic resonance imaging.

Authors:  Clarisse Dromain; Thierry de Baere; Jean Lumbroso; Hubert Caillet; Agnès Laplanche; Valerie Boige; Michel Ducreux; Pierre Duvillard; Dominique Elias; Martin Schlumberger; Robert Sigal; Eric Baudin
Journal:  J Clin Oncol       Date:  2005-01-01       Impact factor: 44.544

5.  High sensitivity of diffusion-weighted MR imaging for the detection of liver metastases from neuroendocrine tumors: comparison with T2-weighted and dynamic gadolinium-enhanced MR imaging.

Authors:  Gaspard d'Assignies; Priscilla Fina; Onorina Bruno; Marie-Pierre Vullierme; Florence Tubach; Valérie Paradis; Alain Sauvanet; Philippe Ruszniewski; Valérie Vilgrain
Journal:  Radiology       Date:  2013-03-26       Impact factor: 11.105

6.  Impact of Liver and Whole-Body Diffusion-Weighted MRI for Neuroendocrine Tumors on Patient Management: A Pilot Study.

Authors:  Frederick Moryoussef; Louis de Mestier; Mohamed Belkebir; Sophie Deguelte-Lardière; Hedia Brixi; Reza Kianmanesh; Christine Hoeffel; Guillaume Cadiot
Journal:  Neuroendocrinology       Date:  2016-04-28       Impact factor: 4.914

7.  Whole-body MRI, including diffusion-weighted imaging, for the initial staging of malignant lymphoma: comparison to computed tomography.

Authors:  Thomas C Kwee; Henriette M E Quarles van Ufford; Frederik J Beek; Taro Takahara; Cuno S Uiterwaal; Marc B Bierings; Inge Ludwig; Rob Fijnheer; Rutger A J Nievelstein
Journal:  Invest Radiol       Date:  2009-10       Impact factor: 6.016

8.  Trends in the Incidence, Prevalence, and Survival Outcomes in Patients With Neuroendocrine Tumors in the United States.

Authors:  Arvind Dasari; Chan Shen; Daniel Halperin; Bo Zhao; Shouhao Zhou; Ying Xu; Tina Shih; James C Yao
Journal:  JAMA Oncol       Date:  2017-10-01       Impact factor: 31.777

9.  TNM staging of foregut (neuro)endocrine tumors: a consensus proposal including a grading system.

Authors:  G Rindi; G Klöppel; H Alhman; M Caplin; A Couvelard; W W de Herder; B Erikssson; A Falchetti; M Falconi; P Komminoth; M Körner; J M Lopes; A-M McNicol; O Nilsson; A Perren; A Scarpa; J-Y Scoazec; B Wiedenmann
Journal:  Virchows Arch       Date:  2006-09-12       Impact factor: 4.064

10.  Whole-body MRI including diffusion-weighted MRI compared with 5-HTP PET/CT in the detection of neuroendocrine tumors.

Authors:  Lina Carlbom; José Caballero-Corbalán; Dan Granberg; Jens Sörensen; Barbro Eriksson; Håkan Ahlström
Journal:  Ups J Med Sci       Date:  2016-11-29       Impact factor: 2.384

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  1 in total

1.  Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI-A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making.

Authors:  Uli Fehrenbach; Siyi Xin; Alexander Hartenstein; Timo Alexander Auer; Franziska Dräger; Konrad Froböse; Henning Jann; Martina Mogl; Holger Amthauer; Dominik Geisel; Timm Denecke; Bertram Wiedenmann; Tobias Penzkofer
Journal:  Cancers (Basel)       Date:  2021-05-31       Impact factor: 6.639

  1 in total

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