NDLI: Accurate functional volume definition in PET for radiotherapy treatment planning

Content Provider	IEEE Xplore Digital Library
Author	Hatt, M. Dekker, A. De Ruysscher, D. Oellers, M. Lambin, P. Roux, C. Visvikis, D.
Copyright Year	2008
Description	Author affiliation: INSERM U650, LaTIM, Brest, 29200, France (Hatt, M.; Roux, C.; Visvikis, D.) \|\| Department of Radiation Oncology (MAASTRO Clinic), Maastricht University Medical Centre, The Netherlands (Dekker, A.; De Ruysscher, D.; Oellers, M.; Lambin, P.)
Abstract	Accurate volume contouring in PET is now considered crucial in radiotherapy as the use of functional imaging allows improved gross tumour volume (GTV) definition. On the other hand, an accurate delineation of the GTV as well as the definition of variable activity accumulation regions inside the tumour itself may facilitate the applications of “dose painting” for optimization of dosimetry. The objectives of such optimization include lower doses delivered to healthy surrounding tissues and higher doses delivered to malignant ones. Current state of the art algorithms for functional volume segmentation consist of adaptive threshold approaches. We have developed a segmentation approach for inhomogeneous tumours in PET, namely the FLAB (Fuzzy Locally Adaptive Bayesian), that was previously validated on simulated images. In this study, we investigated the accuracy of this algorithm in comparison to threshold-based approaches, applied to images of lung cancer patients scanned with FDG PET/CT. Simulated tumours were generated based on the activity distribution and shapes of the real lesions imaged on these patients in order to establish a “ground truth” as far as functional tumour volume is concerned. In addition, some of the patients were subsequently operated with the tumours removed and a subsequent macroscopic investigation performed to determine the true tumour sizes. These were compared to those from the segmented volumes obtained using the different algorithms under investigation. The FLAB algorithm is able to accurately extract the overall tumour from the healthy background tissues, as well as precisely delineate variable activity concentration regions of interest inside the tumours, whereas the other methodologies fail to do so. In addition, the FLAB results were systematically closer to the histology results than the other methodologies considered. Future studies will investigate the impact of the use of FLAB in radiotherapy treatment planning.
Starting Page	5567
Ending Page	5571
File Size	2452282
Page Count	5
File Format	PDF
ISBN	9781424427147
ISSN	10957863
DOI	10.1109/NSSMIC.2008.4774509
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-19
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Positron emission tomography Tumors Cancer Image segmentation Dosimetry Bayesian methods Lungs Computed tomography Shape Lesions
Content Type	Text
Resource Type	Article

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