18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction

Teoh, Eugene J., McGowan, Daniel R., Bradley, Kevin M. ORCID: https://orcid.org/0000-0003-1911-3382, Belcher, Elizabeth, Black, Edward, Moore, Alastair, Sykes, Annemarie and Gleeson, Fergus V. 2016. 18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction. European Radiology 26 (11) , pp. 4098-4106. 10.1007/s00330-016-4253-2

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Abstract

Purpose To investigate whether using a Bayesian penalised likelihood reconstruction (BPL) improves signal-to-background (SBR), signal-to-noise (SNR) and SUVmax when evaluating mediastinal nodal disease in non-small cell lung cancer (NSCLC) compared to ordered subset expectation maximum (OSEM) reconstruction. Materials and methods 18F-FDG PET/CT scans for NSCLC staging in 47 patients (112 nodal stations with histopathological confirmation) were reconstructed using BPL and compared to OSEM. Node and multiple background SUV parameters were analysed semi-quantitatively and visually. Results Comparing BPL to OSEM, there were significant increases in SUVmax (mean 3.2–4.0, p<0.0001), SBR (mean 2.2–2.6, p<0.0001) and SNR (mean 27.7–40.9, p<0.0001). Mean background SNR on OSEM was 10.4 (range 7.6–14.0), increasing to 12.4 (range 8.2–16.7, p<0.0001). Changes in background SUVs were minimal (largest mean difference 0.17 for liver SUVmean, p<0.001). There was no significant difference between either algorithm on receiver operating characteristic analysis (p=0.26), although on visual analysis, there was an increase in sensitivity and small decrease in specificity and accuracy on BPL. Conclusion BPL increases SBR, SNR and SUVmax of mediastinal nodes in NSCLC compared to OSEM, but did not improve the accuracy for determining nodal involvement.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Publisher:	Springer Verlag (Germany)
ISSN:	0938-7994
Date of First Compliant Deposit:	4 June 2020
Date of Acceptance:	26 January 2016
Last Modified:	05 May 2023 13:09
URI:	https://orca.cardiff.ac.uk/id/eprint/132175

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