Literature DB >> 23927348

An automatic method for accurate volume delineation of heterogeneous tumors in PET.

F Hofheinz1, J Langner, J Petr, B Beuthien-Baumann, J Steinbach, J Kotzerke, J van den Hoff.   

Abstract

PURPOSE: Accurate volumetric tumor delineation is of increasing importance in radiation treatment planning. Many tumors exhibit only moderate tracer uptake heterogeneity and delineation methods using an adaptive threshold lead to robust results. These methods use a tumor reference value R (e.g., ROI maximum) and the tumor background Bg to compute the volume reproducing threshold. This threshold corresponds to an isocontour which defines the tumor boundary. However, the boundaries of strongly heterogeneous tumors can not be described by an isocontour anymore and therefore conventional threshold methods are not suitable for accurate delineation. The aim of this work is the development and validation of a delineation method for heterogeneous tumors.
METHODS: The new method (voxel-specific threshold method, VTM) can be considered as an extension of an adaptive threshold method (lesion-specific threshold method, LTM), where instead of a lesion-specific threshold for the whole ROI, a voxel-specific threshold is computed by determining for each voxel Bg and R in the close vicinity of the voxel. The absolute threshold for the considered voxel is then given by Tabs=T×(R-Bg)+Bg, where T=0.39 was determined with phantom measurements. VALIDATION: 30 clinical datasets from patients with non-small-cell lung cancer were used to generate 30 realistic anthropomorphic software phantoms of tumors with different heterogeneities and well-known volumes and boundaries. Volume delineation was performed with VTM and LTM and compared with the known lesion volumes and boundaries.
RESULTS: In contrast to LTM, VTM was able to reproduce the true tumor boundaries accurately, independent of the heterogeneity. The deviation of the determined volume from the true volume was (0.8±4.2)% for VTM and (11.0±16.4)% for LTM.
CONCLUSIONS: In anthropomorphic software phantoms, the new method leads to promising results and to a clear improvement of volume delineation in comparison to conventional background-corrected thresholding. In the next step, the suitability for clinical routine will be further investigated.

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Year:  2013        PMID: 23927348     DOI: 10.1118/1.4812892

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  31 in total

1.  On the assessment of spatial resolution of PET systems with iterative image reconstruction.

Authors:  Kuang Gong; Simon R Cherry; Jinyi Qi
Journal:  Phys Med Biol       Date:  2016-02-11       Impact factor: 3.609

2.  Classification and evaluation strategies of auto-segmentation approaches for PET: Report of AAPM task group No. 211.

Authors:  Mathieu Hatt; John A Lee; Charles R Schmidtlein; Issam El Naqa; Curtis Caldwell; Elisabetta De Bernardi; Wei Lu; Shiva Das; Xavier Geets; Vincent Gregoire; Robert Jeraj; Michael P MacManus; Osama R Mawlawi; Ursula Nestle; Andrei B Pugachev; Heiko Schöder; Tony Shepherd; Emiliano Spezi; Dimitris Visvikis; Habib Zaidi; Assen S Kirov
Journal:  Med Phys       Date:  2017-05-18       Impact factor: 4.071

3.  Hybrid positron emission tomography segmentation of heterogeneous lung tumors using 3D Slicer: improved GrowCut algorithm with threshold initialization.

Authors:  Hannah Mary T Thomas; Devadhas Devakumar; Balukrishna Sasidharan; Stephen R Bowen; Danie Kingslin Heck; E James Jebaseelan Samuel
Journal:  J Med Imaging (Bellingham)       Date:  2017-01-23

4.  Confirmation of the prognostic value of pretherapeutic tumor SUR and MTV in patients with esophageal squamous cell carcinoma.

Authors:  Frank Hofheinz; Yimin Li; Ingo G Steffen; Qin Lin; Chen Lili; Wu Hua; Jörg van den Hoff; Sebastian Zschaeck
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-04-04       Impact factor: 9.236

Review 5.  A review on segmentation of positron emission tomography images.

Authors:  Brent Foster; Ulas Bagci; Awais Mansoor; Ziyue Xu; Daniel J Mollura
Journal:  Comput Biol Med       Date:  2014-04-28       Impact factor: 4.589

Review 6.  Characterization of PET/CT images using texture analysis: the past, the present… any future?

Authors:  Mathieu Hatt; Florent Tixier; Larry Pierce; Paul E Kinahan; Catherine Cheze Le Rest; Dimitris Visvikis
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-06-06       Impact factor: 9.236

7.  Predictive Value of Asphericity in Pretherapeutic [111In]DTPA-Octreotide SPECT/CT for Response to Peptide Receptor Radionuclide Therapy with [177Lu]DOTATATE.

Authors:  Christoph Wetz; I Apostolova; I G Steffen; F Hofheinz; C Furth; D Kupitz; J Ruf; M Venerito; S Klose; Holger Amthauer
Journal:  Mol Imaging Biol       Date:  2017-06       Impact factor: 3.488

8.  The asphericity of the metabolic tumour volume in NSCLC: correlation with histopathology and molecular markers.

Authors:  Ivayla Apostolova; Kilian Ego; Ingo G Steffen; Ralph Buchert; Heinz Wertzel; H Jost Achenbach; Sandra Riedel; Jens Schreiber; Meinald Schultz; Christian Furth; Thorsten Derlin; Holger Amthauer; Frank Hofheinz; Thomas Kalinski
Journal:  Eur J Nucl Med Mol Imaging       Date:  2016-07-28       Impact factor: 9.236

9.  Attenuation correction in 4D-PET using a single-phase attenuation map and rigidity-adaptive deformable registration.

Authors:  Faraz Kalantari; Jing Wang
Journal:  Med Phys       Date:  2017-02-03       Impact factor: 4.071

10.  Asphericity of pretherapeutic tumour FDG uptake provides independent prognostic value in head-and-neck cancer.

Authors:  Ivayla Apostolova; Ingo G Steffen; Florian Wedel; Alexandr Lougovski; Simone Marnitz; Thorsten Derlin; Holger Amthauer; Ralph Buchert; Frank Hofheinz; Winfried Brenner
Journal:  Eur Radiol       Date:  2014-06-26       Impact factor: 5.315

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