Literature DB >> 20570382

Implementation of hypoxia imaging into treatment planning and delivery.

Daniela Thorwarth1, Markus Alber.   

Abstract

PURPOSE: To review the current status of implementation of functional hypoxia imaging in radiotherapy (RT) planning and treatment delivery.
METHODS: Before biological imaging techniques such as positron emission tomography (PET) or magnetic resonance (MR) can be used for individual RT adaptation, three main requirements have to be fulfilled. First, tissue parameters have to be derived from the imaging data that correlate with individual therapy outcome. Then, the spatial and temporal stability of hypoxia PET images needs to be established. Finally, the dose painting (DP) concepts have to be practically feasible to be used as a basis for clinical trials.
RESULTS: A number of recent clinical studies could show the correlation of hypoxia PET imaging with different tracers and RT outcome. Most of the studies revealed a correlation between mean or maximum values and parameters assessed from the PET avid volume and treatment success, only few investigations used quantitative imaging. Multiparametric imaging seems to be very valuable. Recently, the spatial and temporal stability of hypoxia PET attracted attention. Temporal changes in the distribution of functional tumour properties were reported. Furthermore, technical feasibility of DP by contours (DPC) as well as DP by numbers (DPBN) was shown by several investigators. The challenge is now to design clinical studies in order to prove the impact of DP treatments on individual therapy success.
CONCLUSION: A patient-specific adaptation of RT based on functional hypoxia imaging with PET is possible and promising. Conceptual feasibility could be shown for DPBN whereas to date, only DPC seems to be plausible and feasible in a clinical context.
Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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Mesh:

Year:  2010        PMID: 20570382     DOI: 10.1016/j.radonc.2010.05.012

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


  22 in total

1.  [Image-guided radiation therapy. Paradigm change in radiation therapy].

Authors:  F Wenz; C Belka; M Reiser; S O Schönberg
Journal:  Radiologe       Date:  2012-03       Impact factor: 0.635

2.  Spatiotemporal stability of Cu-ATSM and FLT positron emission tomography distributions during radiation therapy.

Authors:  Tyler J Bradshaw; Stephen Yip; Ngoneh Jallow; Lisa J Forrest; Robert Jeraj
Journal:  Int J Radiat Oncol Biol Phys       Date:  2014-03-28       Impact factor: 7.038

Review 3.  Imaging techniques for tumour delineation and heterogeneity quantification of lung cancer: overview of current possibilities.

Authors:  Wouter van Elmpt; Catharina M L Zegers; Marco Das; Dirk De Ruysscher
Journal:  J Thorac Dis       Date:  2014-04       Impact factor: 2.895

Review 4.  Personalized radiotherapy treatment planning based on functional imaging.

Authors:  Malgorzata Skórska; Tomasz Piotrowski
Journal:  Rep Pract Oncol Radiother       Date:  2017-05-15

Review 5.  Molecular imaging of tumor hypoxia with positron emission tomography.

Authors:  Olivia J Kelada; David J Carlson
Journal:  Radiat Res       Date:  2014-03-27       Impact factor: 2.841

Review 6.  PET radiopharmaceuticals for imaging of tumor hypoxia: a review of the evidence.

Authors:  Egesta Lopci; Ilaria Grassi; Arturo Chiti; Cristina Nanni; Gianfranco Cicoria; Luca Toschi; Cristina Fonti; Filippo Lodi; Sandro Mattioli; Stefano Fanti
Journal:  Am J Nucl Med Mol Imaging       Date:  2014-06-07

Review 7.  Image-derived biomarkers and multimodal imaging strategies for lung cancer management.

Authors:  Alexander W Sauter; Nina Schwenzer; Mathew R Divine; Bernd J Pichler; Christina Pfannenberg
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-01-09       Impact factor: 9.236

Review 8.  The future of personalised radiotherapy for head and neck cancer.

Authors:  Jimmy J Caudell; Javier F Torres-Roca; Robert J Gillies; Heiko Enderling; Sungjune Kim; Anupam Rishi; Eduardo G Moros; Louis B Harrison
Journal:  Lancet Oncol       Date:  2017-04-26       Impact factor: 41.316

9.  EPR oxygen images predict tumor control by a 50% tumor control radiation dose.

Authors:  Martyna Elas; Jessica M Magwood; Brandi Butler; Chanel Li; Rona Wardak; Rebekah DeVries; Eugene D Barth; Boris Epel; Samuel Rubinstein; Charles A Pelizzari; Ralph R Weichselbaum; Howard J Halpern
Journal:  Cancer Res       Date:  2013-07-16       Impact factor: 12.701

10.  Benefits of a clinical data warehouse with data mining tools to collect data for a radiotherapy trial.

Authors:  Erik Roelofs; Lucas Persoon; Sebastiaan Nijsten; Wolfgang Wiessler; André Dekker; Philippe Lambin
Journal:  Radiother Oncol       Date:  2013-02-05       Impact factor: 6.280

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