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 Review


Authors: Partouche, E.; Yeh, R.; Eche, T.; Rozenblum, L.; Carrere, N.; Guimbaud, R.; Dierickx, L. O.; Rousseau, H.; Dercle, L.; Mokrane, F. Z.
Review Title: 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
Abstract: Purpose: Medical imaging plays a central and decisive role in guiding the management of patients with pancreatic neuroendocrine tumors (PNETs). Our aim was to synthesize all recent literature of PNETs, enabling a comparison of all imaging practices. Methods: based on a systematic review and meta-analysis approach, we collected; using MEDLINE, EMBASE, and Cochrane Library databases; all recent imaging-based studies, published from December 2014 to December 2019. Study quality assessment was performed by QUADAS-2 and MINORS tools. Results: 161 studies consisting of 19852 patients were included. There were 63 ‘imaging’ studies evaluating the accuracy of medical imaging, and 98 ‘clinical’ studies using medical imaging as a tool for response assessment. A wide heterogeneity of practices was demonstrated: imaging modalities were: CT (57.1%, n=92), MR (42.9%, n=69), PET/CT (13.3%, n=31), and SPECT/CT (9.3%, n=15). International imaging guidelines were mentioned in 2.5% (n=4/161) of studies. In clinical studies, imaging protocol was not mentioned in 30.6% (n=30/98) of cases and only mentioned imaging modality without further information in 63.3% (n=62/98), as compared to imaging studies (1.6% (n=1/63) of (p<0.001)). QUADAS-2 and MINORS tools deciphered existing biases in the current literature. Conclusion: We provide an overview of the updated current trends in use of medical imaging for diagnosis and response assessment in PNETs. The most commonly used imaging modalities are anatomical (CT and MRI), followed by PET/CT and SPECT/CT. Therefore, standardization and homogenization of PNETs imaging practices is needed to aggregate data and leverage a big data approach for Artificial Intelligence purposes. © Copyright © 2021 Partouche, Yeh, Eche, Rozenblum, Carrere, Guimbaud, Dierickx, Rousseau, Dercle and Mokrane.
Keywords: treatment response; histopathology; review; nuclear magnetic resonance imaging; sensitivity and specificity; quality control; computer assisted tomography; practice guideline; diagnostic imaging; standardization; systematic review; artificial intelligence; intermethod comparison; meta analysis; mri; predictive value; pancreas islet cell tumor; meta-analysis; single photon emission computed tomography; fine needle aspiration biopsy; pet - positron emission tomography; human; x-ray computed tomography; big data; computed tomogaphy; imaging practices; pancreatic neuroendocrine tumors (pnets); quality assessment of diagnostic accuracy studies
Journal Title: Frontiers in Oncology
Volume: 11
ISSN: 2234-943X
Publisher: Frontiers Media S.A.  
Date Published: 2021-07-14
Start Page: 628408
Language: English
DOI: 10.3389/fonc.2021.628408
PROVIDER: scopus
PMCID: PMC8316992
PUBMED: 34336643
DOI/URL:
Notes: Review -- Export Date: 1 September 2021 -- Source: Scopus
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  1. Randy Yeh
    68 Yeh