The effect of a novel Bayesian penalised likelihood PET reconstruction algorithm on the assessment of malignancy risk in solitary pulmonary nodules according to the British Thoracic Society guidelines.


Journal

European journal of radiology
ISSN: 1872-7727
Titre abrégé: Eur J Radiol
Pays: Ireland
ID NLM: 8106411

Informations de publication

Date de publication:
Aug 2019
Historique:
received: 14 01 2019
revised: 21 05 2019
accepted: 09 06 2019
entrez: 17 7 2019
pubmed: 17 7 2019
medline: 26 11 2019
Statut: ppublish

Résumé

British Thoracic Society (BTS) guidelines advocate using FDG PET-CT with the Herder model to estimate malignancy risk in solitary pulmonary nodules (SPNs). Qualitative and semi-quantitative assessment of SPN uptake is based upon analysis of Ordered Subset Expected Maximisation (OSEM) PET images. Our aim was to assess the effect of a Bayesian Penalised Likelihood (BPL) PET reconstruction on the assessment of SPN FDG uptake and estimation of malignancy risk (Herder score). Subjects with SPNs who underwent FDG PET-CT between 2014-2017, with histological confirmation of malignancy or histological/imaging follow-up confirmation of benignity were included. Two blinded readers independently classified SPN uptake on both OSEM and BPL (BTS score; 1 = none; 2 = ≤ mediastinal blood pool (MBP); 3 = >MBP but ≤ 2x liver; 4 = >2x liver), with resultant calculation of the Herder score (%) for both reconstructions. 97 subjects with 75 (77%) malignant SPNs were included. BPL increased the BTS score in 25 (26%) SPNs; 9 SPNs (7 malignant) increased from BTS score 2 to 3, 16 (13 malignant) from BTS score 3 to 4, with a mean Herder score increase of 18 ± 22%. The mean Herder score for all SPNs with BPL was higher than OSEM (73 ± 29 vs 68 ± 32%, p = 0.001). There was no difference in Herder model diagnostic performance between BPL and OSEM, with similar areas under the curve (0.84 vs 0.83, p = 0.39). BPL increases the Herder score in 26% of SPNs compared to OSEM but does not alter the diagnostic performance of the Herder model.

Identifiants

pubmed: 31307640
pii: S0720-048X(19)30209-8
doi: 10.1016/j.ejrad.2019.06.005
pii:
doi:

Substances chimiques

Fluorodeoxyglucose F18 0Z5B2CJX4D

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

149-155

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

D J Murphy (DJ)

King's College London & Guy's and St. Thomas' PET Centre, St. Thomas' Hospital, London, UK; Department of Cancer Imaging, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK. Electronic address: david.murphy@st-vincents.ie.

L Royle (L)

Department of Radiology, Guy's and St. Thomas' NHS Foundation Trust, London, UK.

Z Chalampalakis (Z)

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

L Alves (L)

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

N Martins (N)

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

P Bassett (P)

Statsconsultancy Ltd., London, UK.

R Breen (R)

Department of Respiratory Medicine, Guy's and St. Thomas' NHS Foundation Trust, London, UK.

A Nair (A)

Department of Radiology, Guy's and St. Thomas' NHS Foundation Trust, London, UK.

A Bille (A)

Department of Cardiothoracic Surgery, Guy's and St. Thomas' NHS Foundation Trust, London, UK.

S Chicklore (S)

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

G J Cook (GJ)

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

M Subesinghe (M)

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

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Classifications MeSH