Radiomics in pancreatic neuroendocrine tumors: methodological issues and clinical significance

Purpose To present the state-of-art of radiomics in the context of pancreatic neuroendocrine tumors (PanNETs), with a focus on the methodological and technical approaches used, to support the search of guidelines for optimal applications. Furthermore, an up-to-date overview of the current clinical a...

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Veröffentlicht in:European journal of nuclear medicine and molecular imaging 2021-11, Vol.48 (12), p.4002-4015
Hauptverfasser: Bezzi, C., Mapelli, P., Presotto, L., Neri, I., Scifo, P., Savi, A., Bettinardi, V., Partelli, S., Gianolli, L., Falconi, M., Picchio, M.
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container_issue 12
container_start_page 4002
container_title European journal of nuclear medicine and molecular imaging
container_volume 48
creator Bezzi, C.
Mapelli, P.
Presotto, L.
Neri, I.
Scifo, P.
Savi, A.
Bettinardi, V.
Partelli, S.
Gianolli, L.
Falconi, M.
Picchio, M.
description Purpose To present the state-of-art of radiomics in the context of pancreatic neuroendocrine tumors (PanNETs), with a focus on the methodological and technical approaches used, to support the search of guidelines for optimal applications. Furthermore, an up-to-date overview of the current clinical applications of radiomics in the field of PanNETs is provided. Methods Original articles were searched on PubMed and Science Direct with specific keywords. Evaluations of the selected studies have been focused mainly on (i) the general radiomic workflow and the assessment of radiomic features robustness/reproducibility, as well as on the major clinical applications and investigations accomplished so far with radiomics in the field of PanNETs: (ii) grade prediction, (iii) differential diagnosis from other neoplasms, (iv) assessment of tumor behavior and aggressiveness, and (v) treatment response prediction. Results Thirty-one articles involving PanNETs radiomic-related objectives were selected. In regard to the grade differentiation task, yielded AUCs are currently in the range of 0.7–0.9. For differential diagnosis, the majority of studies are still focused on the preliminary identification of discriminative radiomic features. Limited information is known on the prediction of tumors aggressiveness and of treatment response. Conclusions Radiomics is recently expanding in the setting of PanNETs. From the analysis of the published data, it is emerging how, prior to clinical application, further validations are necessary and methodological implementations require optimization. Nevertheless, this new discipline might have the potential in assisting the current urgent need of improving the management strategies in PanNETs patients.
doi_str_mv 10.1007/s00259-021-05338-8
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For differential diagnosis, the majority of studies are still focused on the preliminary identification of discriminative radiomic features. Limited information is known on the prediction of tumors aggressiveness and of treatment response. Conclusions Radiomics is recently expanding in the setting of PanNETs. From the analysis of the published data, it is emerging how, prior to clinical application, further validations are necessary and methodological implementations require optimization. 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For differential diagnosis, the majority of studies are still focused on the preliminary identification of discriminative radiomic features. Limited information is known on the prediction of tumors aggressiveness and of treatment response. Conclusions Radiomics is recently expanding in the setting of PanNETs. From the analysis of the published data, it is emerging how, prior to clinical application, further validations are necessary and methodological implementations require optimization. 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Furthermore, an up-to-date overview of the current clinical applications of radiomics in the field of PanNETs is provided. Methods Original articles were searched on PubMed and Science Direct with specific keywords. Evaluations of the selected studies have been focused mainly on (i) the general radiomic workflow and the assessment of radiomic features robustness/reproducibility, as well as on the major clinical applications and investigations accomplished so far with radiomics in the field of PanNETs: (ii) grade prediction, (iii) differential diagnosis from other neoplasms, (iv) assessment of tumor behavior and aggressiveness, and (v) treatment response prediction. Results Thirty-one articles involving PanNETs radiomic-related objectives were selected. In regard to the grade differentiation task, yielded AUCs are currently in the range of 0.7–0.9. For differential diagnosis, the majority of studies are still focused on the preliminary identification of discriminative radiomic features. Limited information is known on the prediction of tumors aggressiveness and of treatment response. Conclusions Radiomics is recently expanding in the setting of PanNETs. From the analysis of the published data, it is emerging how, prior to clinical application, further validations are necessary and methodological implementations require optimization. Nevertheless, this new discipline might have the potential in assisting the current urgent need of improving the management strategies in PanNETs patients.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>33835220</pmid><doi>10.1007/s00259-021-05338-8</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-7532-6211</orcidid></addata></record>
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subjects Advanced Image Analyses (Radiomics and Artificial Intelligence)
Cardiology
Clinical significance
Diagnosis
Diagnosis, Differential
Differential diagnosis
Humans
Imaging
Medicine
Medicine & Public Health
Neoplasms
Neuroendocrine tumors
Neuroendocrine Tumors - diagnostic imaging
Nuclear Medicine
Oncology
Optimization
Orthopedics
Pancreas
Pancreatic cancer
Pancreatic Neoplasms - diagnostic imaging
Predictions
Radiology
Radiomics
Reproducibility of Results
Review Article
Therapeutic applications
Tumors
Workflow
title Radiomics in pancreatic neuroendocrine tumors: methodological issues and clinical significance
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