Comparaison de six méthodes de segmentation du volume tumoral sur la 18F-FDG TEP-TDM avec le volume de référence anatomopathologique dans les cancers bronchopulmonaires non à petites cellules

PET-guided delineation of radiation therapy treatment volumes: a survey of image segmentation techniques

Historically, anatomical CT and MR images were used to delineate the gross tumour volumes (GTVs) for radiotherapy treatment planning. The capabilities offered by modern radiation therapy units and the widespread availability of combined PET/CT scanners stimulated the development of biological PET imaging-guided radiation therapy treatment planning with the aim to produce highly conformal radiation dose distribution to the tumour. One of the most difficult issues facing PET-based treatment planning is the accurate delineation of target regions from typical blurred and noisy functional images. The major problems encountered are image segmentation and imperfect system response function. Image segmentation is defined as the process of classifying the voxels of an image into a set of distinct classes. The difficulty in PET image segmentation is compounded by the low spatial resolution and high noise characteristics of PET images. Despite the difficulties and known limitations, several image segmentation approaches have been proposed and used in the clinical setting including thresholding, edge detection, region growing, clustering, stochastic models, deformable models, classifiers and several other approaches. A detailed description of the various approaches proposed in the literature is reviewed. Moreover, we also briefly discuss some important considerations and limitations of the widely used techniques to guide practitioners in the field of radiation oncology. The strategies followed for validation and comparative assessment of various PET segmentation approaches are described. Future opportunities and the current challenges facing the adoption of PET-guided delineation of target volumes and its role in basic and clinical research are also addressed.

Molecular PET/CT imaging-guided radiation therapy treatment planning

The role of positron emission tomography (PET) during the past decade has evolved rapidly from that of a pure research tool to a methodology of enormous clinical potential. (18)F-fluorodeoxyglucose (FDG)-PET is currently the most widely used probe in the diagnosis, staging, assessment of tumor response to treatment, and radiation therapy planning because metabolic changes generally precede the more conventionally measured parameter of change in tumor size. Data accumulated rapidly during the last decade, thus validating the efficacy of FDG imaging and many other tracers in a wide variety of malignant tumors with sensitivities and specificities often in the high 90 percentile range. As a result, PET/computed tomography (CT) had a significant impact on the management of patients because it obviated the need for further evaluation, guided further diagnostic procedures, and assisted in planning therapy for a considerable number of patients. On the other hand, the progress in radiation therapy technology has been enormous during the last two decades, now offering the possibility to plan highly conformal radiation dose distributions through the use of sophisticated beam targeting techniques such as intensity-modulated radiation therapy (IMRT) using tomotherapy, volumetric modulated arc therapy, and many other promising technologies for sculpted three-dimensional (3D) dose distribution. The foundation of molecular imaging-guided radiation therapy lies in the use of advanced imaging technology for improved definition of tumor target volumes, thus relating the absorbed dose information to image-based patient representations. This review documents technological advancements in the field concentrating on the conceptual role of molecular PET/CT imaging in radiation therapy treatment planning and related image processing issues with special emphasis on segmentation of medical images for the purpose of defining target volumes. There is still much more work to be done and many of the techniques reviewed are themselves not yet widely implemented in clinical settings.