title: 18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction.
abstract: OBJECTIVE
  To investigate whether using a Bayesian penalised likelihood reconstruction (BPL) improves signal-to-background (SBR), signal-to-noise (SNR) and SUVmaxwhen evaluating mediastinal nodal disease in non-small cell lung cancer (NSCLC) compared to ordered subset expectation maximum (OSEM) reconstruction.
  
  
  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.
  
  
  CONCLUSIONS
  BPL increases SBR, SNR and SUVmaxof mediastinal nodes in NSCLC compared to OSEM, but did not improve the accuracy for determining nodal involvement.
  
  
  CONCLUSIONS
  • Penalised likelihood PET reconstruction was applied for assessing mediastinal nodes in NSCLC. • The new reconstruction generated significant increases in signal-to-background, signal-to-noise and SUVmax. • This led to an improvement in visual sensitivity using the new algorithm. • Higher SUVmaxthresholds may be appropriate for semi-quantitative analyses with penalised likelihood.
authors.affiliation: Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK.|Department of Oncology, University of Oxford, Oxford, OX3 7DQ, UK.
authors.forename: Eugene J
authors.initials: EJ
authors.lastname: Teoh
authors.affiliation: Department of Oncology, University of Oxford, Oxford, OX3 7DQ, UK. daniel.mcgowan@oncology.ox.ac.uk.|Radiation Physics and Protection, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK. daniel.mcgowan@oncology.ox.ac.uk.
authors.forename: Daniel R
authors.initials: DR
authors.lastname: McGowan
authors.affiliation: Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK.
authors.forename: Kevin M
authors.initials: KM
authors.lastname: Bradley
authors.affiliation: Department of Thoracic Surgery, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Belcher
authors.affiliation: Department of Thoracic Surgery, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.
authors.forename: Edward
authors.initials: E
authors.lastname: Black
authors.affiliation: Department of Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK.
authors.forename: Alastair
authors.initials: A
authors.lastname: Moore
authors.affiliation: Department of Respiratory Medicine, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK.
authors.forename: Annemarie
authors.initials: A
authors.lastname: Sykes
authors.affiliation: Department of Radiology, Churchill Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK.|Department of Oncology, University of Oxford, Oxford, OX3 7DQ, UK.
authors.forename: Fergus V
authors.initials: FV
authors.lastname: Gleeson
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000473:pathology; D004812:Epidemiologic Methods; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D008198:Lymph Nodes / Q000000981:diagnostic imaging / Q000473:pathology; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D064847:Multimodal Imaging; D009367:Neoplasm Staging; D000072078:Positron Emission Tomography Computed Tomography / Q000379:methods*; D019275:Radiopharmaceuticals
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: Bayesian; Lung cancer staging; Mediastinal nodes; PET reconstruction; PET-CT; Signal-to-noise