Preoperative 18F-FDG PET/CT tumor markers outperform MRI-based markers for the prediction of lymph node metastases in primary endometrial cancer.


Journal

European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774

Informations de publication

Date de publication:
May 2020
Historique:
received: 14 08 2019
accepted: 12 12 2019
revised: 15 11 2019
pubmed: 9 2 2020
medline: 21 10 2020
entrez: 9 2 2020
Statut: ppublish

Résumé

To compare the diagnostic accuracy of preoperative 18F-FDG PET/CT and MRI tumor markers for prediction of lymph node metastases (LNM) and aggressive disease in endometrial cancer (EC). Preoperative whole-body 18F-FDG PET/CT and pelvic MRI were performed in 215 consecutive patients with histologically confirmed EC. PET/CT-based tumor standardized uptake value (SUV For prediction of LNM, MTV yielded the largest area under the ROC curve (AUC) (AUC = 0.80), whereas V Tumor markers from 18F-FDG PET/CT outperform MRI markers for the prediction of LNM. MTV > 27 ml yields a high diagnostic performance for predicting aggressive disease and represents a promising supplement to conventional PET/CT reading in EC. • Metabolic tumor volume (MTV) outperforms other 18F-FDG PET/CT and MRI markers for preoperative prediction of lymph node metastases (LNM) in endometrial cancer patients. • Using cutoff values for tumor volume for prediction of LNM, MTV > 27 ml yielded higher specificity and accuracy than V

Identifiants

pubmed: 32034487
doi: 10.1007/s00330-019-06622-w
pii: 10.1007/s00330-019-06622-w
pmc: PMC7160067
doi:

Substances chimiques

Radiopharmaceuticals 0
Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2443-2453

Subventions

Organisme : Helse Vest
ID : 912060
Organisme : Bergens Forskningsstiftelse
ID : BFS2018TMT06

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Auteurs

Kristine E Fasmer (KE)

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway. kristine.fasmer@helse-bergen.no.
Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway. kristine.fasmer@helse-bergen.no.

Ankush Gulati (A)

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway.

Julie A Dybvik (JA)

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway.

Sigmund Ytre-Hauge (S)

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway.
Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.

Øyvind Salvesen (Ø)

Unit for Applied Clinical Research, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway.

Jone Trovik (J)

Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway.
Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.

Camilla Krakstad (C)

Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway.
Centre for Cancer Biomarkers, Department of Clinical Science, University of Bergen, Bergen, Norway.

Ingfrid S Haldorsen (IS)

Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Jonas Liesvei 65, 5021, Bergen, Norway.
Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.

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Classifications MeSH