Exploratory radiomic features from integrated


Journal

European journal of nuclear medicine and molecular imaging
ISSN: 1619-7089
Titre abrégé: Eur J Nucl Med Mol Imaging
Pays: Germany
ID NLM: 101140988

Informations de publication

Date de publication:
Jul 2019
Historique:
received: 29 08 2018
accepted: 04 03 2019
pubmed: 29 3 2019
medline: 15 7 2020
entrez: 29 3 2019
Statut: ppublish

Résumé

The purpose of this study was to determine if Following IRB approval and informed consent, patients underwent a staging PET/MRI following Twenty patients (18 males, 2 female; median 67 years, range 52-86) comprised the final study cohort; ten patients had metastases. Lower second-order SUV entropy combined with higher second-order ADC entropy were the best feature-pair for discriminating metastatic patients, MANOVA p value <0.001 (SN = 80%, SP = 80%, PPV = 80%, NPV = 80%, ACC = 80%). SUV High ADC entropy combined with low SUV entropy is associated with a higher prevalence of metastases and a promising initial signature for future study.

Identifiants

pubmed: 30919055
doi: 10.1007/s00259-019-04306-7
pii: 10.1007/s00259-019-04306-7
pmc: PMC6533412
doi:

Substances chimiques

Radiopharmaceuticals 0
Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1478-1484

Subventions

Organisme : Cancer Research UK
ID : C1519/A16463
Pays : United Kingdom
Organisme : Wellcome Trust
ID : WT203148/Z/16/Z
Pays : United Kingdom

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Auteurs

Serena Baiocco (S)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Advanced Research Center for Electronic Systems (ARCES), University of Bologna, Bologna, Italy.
Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi" (DEI), University of Bologna, Bologna, Italy.

Bert-Ram Sah (BR)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Andrew Mallia (A)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK.

Christian Kelly-Morland (C)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK.

Radhouene Neji (R)

MR Research Collaborations, Siemens Healthcare, Frimley, UK.

J James Stirling (JJ)

King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK.

Sami Jeljeli (S)

King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK.

Alessandro Bevilacqua (A)

Advanced Research Center for Electronic Systems (ARCES), University of Bologna, Bologna, Italy.
Department of Computer Science and Engineering (DISI), University of Bologna, Bologna, Italy.

Gary J R Cook (GJR)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK.

Vicky Goh (V)

Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK. vicky.goh@kcl.ac.uk.
King's College London & Guy's and St Thomas' PET Centre, St Thomas' Hospital, London, UK. vicky.goh@kcl.ac.uk.
Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, Lambeth Wing, St Thomas Hospital, Westminster Bridge Road, London, SE1 7EH, UK. vicky.goh@kcl.ac.uk.

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Classifications MeSH