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      Effects of rigid and non-rigid image registration on test-retest variability of quantitative [ 18F]FDG PET/CT studies

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          [ 18F]fluoro-2-deoxy-D-glucose ([ 18F]FDG) positron emission tomography (PET) is a valuable tool for monitoring response to therapy in oncology. In longitudinal studies, however, patients are not scanned in exactly the same position. Rigid and non-rigid image registration can be applied in order to reuse baseline volumes of interest (VOI) on consecutive studies of the same patient. The purpose of this study was to investigate the impact of various image registration strategies on standardized uptake value (SUV) and metabolic volume test-retest variability (TRT).


          Test-retest whole-body [ 18F]FDG PET/CT scans were collected retrospectively for 11 subjects with advanced gastrointestinal malignancies (colorectal carcinoma). Rigid and non-rigid image registration techniques with various degrees of locality were applied to PET, CT, and non-attenuation corrected PET (NAC) data. VOI were drawn independently on both test and retest scans. VOI drawn on test scans were projected onto retest scans and the overlap between projected VOI and manually drawn retest VOI was quantified using the Dice similarity coefficient (DSC). In addition, absolute (unsigned) differences in TRT of SUV max, SUV mean, metabolic volume and total lesion glycolysis (TLG) were calculated in on one hand the test VOI and on the other hand the retest VOI and projected VOI. Reference values were obtained by delineating VOIs on both scans separately.


          Non-rigid PET registration showed the best performance (median DSC: 0.82, other methods: 0.71-0.81). Compared with the reference, none of the registration types showed significant absolute differences in TRT of SUV max, SUV mean and TLG (p > 0.05). Only for absolute TRT of metabolic volume, significant lower values (p < 0.05) were observed for all registration strategies when compared to delineating VOIs separately, except for non-rigid PET registrations (p = 0.1). Non-rigid PET registration provided good volume TRT (7.7%) that was smaller than the reference (16%).


          In particular, non-rigid PET image registration showed good performance similar to delineating VOI on both scans separately, and with smaller TRT in metabolic volume estimates.

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          Most cited references 18

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          elastix: a toolbox for intensity-based medical image registration.

          Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.
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            FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0

            The aim of this guideline is to provide a minimum standard for the acquisition and interpretation of PET and PET/CT scans with [18F]-fluorodeoxyglucose (FDG). This guideline will therefore address general information about [18F]-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET/CT) and is provided to help the physician and physicist to assist to carrying out, interpret, and document quantitative FDG PET/CT examinations, but will concentrate on the optimisation of diagnostic quality and quantitative information.
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              Standards for PET image acquisition and quantitative data analysis.

              Quantitative (18)F-FDG PET is increasingly being recognized as an important tool for diagnosis, determination of prognosis, and response monitoring in oncology. However, PET quantification with, for example, standardized uptake values (SUVs) is affected by many technical and physiologic factors. As a result, some of the variations in the literature on SUV-based patient outcomes are explained by differences in (18)F-FDG PET study methods. Various technical and clinical studies have been performed to understand the factors affecting PET quantification. On the basis of the results of those studies, several recommendations and guidelines have been proposed with the aims of improving the image quality and the quantitative accuracy of (18)F-FDG PET studies. In this contribution, an overview of recommendations and guidelines for quantitative (18)F-FDG PET studies in oncology is provided. Special attention is given to the rationale underlying certain recommendations and to some of the differences in various guidelines.

                Author and article information

                EJNMMI Res
                EJNMMI Res
                EJNMMI Research
                10 March 2012
                : 2
                : 10
                [1 ]Department of Nuclear Medicine & PET Research, VU University Medical Center, Amsterdam, The Netherlands
                [2 ]Division of Nuclear Medicine and Medical Imaging Center, University Hospital Leuven, Leuven, Belgium
                [3 ]Discovery Medicine and Clinical Pharmacology, Bristol-Myers Squibb Co., Princeton, NJ, USA
                [4 ]Center for Processing Speech and Images, Department of Electrical Engineering, KU Leuven, Leuven, Belgium
                Copyright ©2012 van Velden et al; licensee Springer.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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