Literature DB >> 25836686

Optimising delineation accuracy of tumours in PET for radiotherapy planning using blind deconvolution.

A Guvenis1, A Koc2.   

Abstract

Positron emission tomography (PET) imaging has been proven to be useful in radiotherapy planning for the determination of the metabolically active regions of tumours. Delineation of tumours, however, is a difficult task in part due to high noise levels and the partial volume effects originating mainly from the low camera resolution. The goal of this work is to study the effect of blind deconvolution on tumour volume estimation accuracy for different computer-aided contouring methods. The blind deconvolution estimates the point spread function (PSF) of the imaging system in an iterative manner in a way that the likelihood of the given image being the convolution output is maximised. In this way, the PSF of the imaging system does not need to be known. Data were obtained from a NEMA NU-2 IQ-based phantom with a GE DSTE-16 PET/CT scanner. The artificial tumour diameters were 13, 17, 22, 28 and 37 mm with a target/background ratio of 4:1. The tumours were delineated before and after blind deconvolution. Student's two-tailed paired t-test showed a significant decrease in volume estimation error (p < 0.001) when blind deconvolution was used in conjunction with computer-aided delineation methods. A manual delineation confirmation demonstrated an improvement from 26 to 16 % for the artificial tumour of size 37 mm while an improvement from 57 to 15 % was noted for the small tumour of 13 mm. Therefore, it can be concluded that blind deconvolution of reconstructed PET images may be used to increase tumour delineation accuracy.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2015        PMID: 25836686      PMCID: PMC4501345          DOI: 10.1093/rpd/ncv110

Source DB:  PubMed          Journal:  Radiat Prot Dosimetry        ISSN: 0144-8420            Impact factor:   0.972


  15 in total

1.  Impact of partial-volume effect correction on the predictive and prognostic value of baseline 18F-FDG PET images in esophageal cancer.

Authors:  Mathieu Hatt; Adrien Le Pogam; Dimitris Visvikis; Olivier Pradier; Catherine Cheze Le Rest
Journal:  J Nucl Med       Date:  2012-01       Impact factor: 10.057

2.  Gradient-based delineation of the primary GTV on FDG-PET in non-small cell lung cancer: a comparison with threshold-based approaches, CT and surgical specimens.

Authors:  Marie Wanet; John Aldo Lee; Birgit Weynand; Marc De Bast; Alain Poncelet; Valérie Lacroix; Emmanuel Coche; Vincent Grégoire; Xavier Geets
Journal:  Radiother Oncol       Date:  2010-11-11       Impact factor: 6.280

3.  FDG-PET-CT reduces the interobserver variability in rectal tumor delineation.

Authors:  Jeroen Buijsen; Jørgen van den Bogaard; Hiska van der Weide; Stephanie Engelsman; Ruud van Stiphout; Marco Janssen; Geerard Beets; Regina Beets-Tan; Philippe Lambin; Guido Lammering
Journal:  Radiother Oncol       Date:  2012-01-24       Impact factor: 6.280

4.  Understanding Blind Deconvolution Algorithms.

Authors:  Anat Levin; Yair Weiss; Fredo Durand; William T Freeman
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2011-07-28       Impact factor: 6.226

Review 5.  The use of FDG-PET to target tumors by radiotherapy.

Authors:  Guido Lammering; Dirk De Ruysscher; Angela van Baardwijk; Brigitta G Baumert; Jacques Borger; Ludy Lutgens; Piet van den Ende; Michel Ollers; Philippe Lambin
Journal:  Strahlenther Onkol       Date:  2010-08-30       Impact factor: 3.621

6.  The Cancer Imaging Archive (TCIA): maintaining and operating a public information repository.

Authors:  Kenneth Clark; Bruce Vendt; Kirk Smith; John Freymann; Justin Kirby; Paul Koppel; Stephen Moore; Stanley Phillips; David Maffitt; Michael Pringle; Lawrence Tarbox; Fred Prior
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

7.  Effects of image characteristics on performance of tumor delineation methods: a test-retest assessment.

Authors:  Patsuree Cheebsumon; Floris H P van Velden; Maqsood Yaqub; Virginie Frings; Adrianus J de Langen; Otto S Hoekstra; Adriaan A Lammertsma; Ronald Boellaard
Journal:  J Nucl Med       Date:  2011-08-17       Impact factor: 10.057

8.  Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.

Authors:  Mathieu Hatt; Catherine Cheze-le Rest; Angela van Baardwijk; Philippe Lambin; Olivier Pradier; Dimitris Visvikis
Journal:  J Nucl Med       Date:  2011-10-11       Impact factor: 10.057

9.  Comparative assessment of methods for estimating tumor volume and standardized uptake value in (18)F-FDG PET.

Authors:  Perrine Tylski; Simon Stute; Nicolas Grotus; Kaya Doyeux; Sébastien Hapdey; Isabelle Gardin; Bruno Vanderlinden; Irène Buvat
Journal:  J Nucl Med       Date:  2010-01-15       Impact factor: 10.057

10.  Automated tumour boundary delineation on (18)F-FDG PET images using active contour coupled with shifted-optimal thresholding method.

Authors:  Kitiwat Khamwan; Anchali Krisanachinda; Charnchai Pluempitiwiriyawej
Journal:  Phys Med Biol       Date:  2012-09-11       Impact factor: 3.609

View more
  2 in total

1.  Design and evaluation of an accurate CNR-guided small region iterative restoration-based tumor segmentation scheme for PET using both simulated and real heterogeneous tumors.

Authors:  Alpaslan Koç; Albert Güveniş
Journal:  Med Biol Eng Comput       Date:  2019-12-17       Impact factor: 2.602

Review 2.  Impact of partial-volume correction in oncological PET studies: a systematic review and meta-analysis.

Authors:  Matthijs C F Cysouw; Gerbrand M Kramer; Linda J Schoonmade; Ronald Boellaard; Henrica C W de Vet; Otto S Hoekstra
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-08-04       Impact factor: 9.236

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.