Literature DB >> 27178141

Performance of automatic image segmentation algorithms for calculating total lesion glycolysis for early response monitoring in non-small cell lung cancer patients during concomitant chemoradiotherapy.

Willem Grootjans1, Edwin A Usmanij2, Wim J G Oyen3, Erik H F M van der Heijden4, Eric P Visser2, Dimitris Visvikis5, Mathieu Hatt5, Johan Bussink6, Lioe-Fee de Geus-Oei7.   

Abstract

BACKGROUND AND
PURPOSE: This study evaluated the use of total lesion glycolysis (TLG) determined by different automatic segmentation algorithms, for early response monitoring in non-small cell lung cancer (NSCLC) patients during concomitant chemoradiotherapy.
MATERIALS AND METHODS: Twenty-seven patients with locally advanced NSCLC treated with concomitant chemoradiotherapy underwent (18)F-fluorodeoxyglucose (FDG) PET/CT imaging before and in the second week of treatment. Segmentation of the primary tumours and lymph nodes was performed using fixed threshold segmentation at (i) 40% SUVmax (T40), (ii) 50% SUVmax (T50), (iii) relative-threshold-level (RTL), (iv) signal-to-background ratio (SBR), and (v) fuzzy locally adaptive Bayesian (FLAB) segmentation. Association of primary tumour TLG (TLGT), lymph node TLG (TLGLN), summed TLG (TLGS=TLGT+TLGLN), and relative TLG decrease (ΔTLG) with overall-survival (OS) and progression-free survival (PFS) was determined using univariate Cox regression models.
RESULTS: Pretreatment TLGT was predictive for PFS and OS, irrespective of the segmentation method used. Inclusion of TLGLN improved disease and early response assessment, with pretreatment TLGS more strongly associated with PFS and OS than TLGT for all segmentation algorithms. This was also the case for ΔTLGS, which was significantly associated with PFS and OS, with the exception of RTL and T40.
CONCLUSIONS: ΔTLGS was significantly associated with PFS and OS, except for RTL and T40. Inclusion of TLGLN improves early treatment response monitoring during concomitant chemoradiotherapy with FDG-PET.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  (18)F-FDG PET/CT; Automatic image segmentation; Concomitant chemoradiochemotherapy; Early response monitoring; Non-small cell lung cancer; Total lesion glycolysis

Mesh:

Substances:

Year:  2016        PMID: 27178141     DOI: 10.1016/j.radonc.2016.04.039

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  3 in total

1.  Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography.

Authors:  Abhinav K Jha; Esther Mena; Brian Caffo; Saeed Ashrafinia; Arman Rahmim; Eric Frey; Rathan M Subramaniam
Journal:  J Med Imaging (Bellingham)       Date:  2017-03-03

Review 2.  Role of interim 18F-FDG-PET/CT for the early prediction of clinical outcomes of Non-Small Cell Lung Cancer (NSCLC) during radiotherapy or chemo-radiotherapy. A systematic review.

Authors:  Marta Cremonesi; Laura Gilardi; Mahila Esmeralda Ferrari; Gaia Piperno; Laura Lavinia Travaini; Robert Timmerman; Francesca Botta; Guido Baroni; Chiara Maria Grana; Sara Ronchi; Delia Ciardo; Barbara Alicja Jereczek-Fossa; Cristina Garibaldi; Roberto Orecchia
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-07-05       Impact factor: 9.236

3.  Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting.

Authors:  Andrei Iantsen; Marta Ferreira; Francois Lucia; Vincent Jaouen; Caroline Reinhold; Pietro Bonaffini; Joanne Alfieri; Ramon Rovira; Ingrid Masson; Philippe Robin; Augustin Mervoyer; Caroline Rousseau; Frédéric Kridelka; Marjolein Decuypere; Pierre Lovinfosse; Olivier Pradier; Roland Hustinx; Ulrike Schick; Dimitris Visvikis; Mathieu Hatt
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-03-27       Impact factor: 9.236

  3 in total

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