A gel tumour phantom for assessment of the accuracy of manual and automatic delineation of gross tumour volume from FDG-PET/CT.

Skretting, Arne; Evensen, Jan F.; Løndalen, Ayca M.; Bogsrud, Trond V.; Glomset, Otto K.; Eilertsen, Karsten

Introduction. Our primary aim was to make a phantom for PET that could mimic a highly irregular tumour and provide true tumour contours. The secondary aim was to use the phantom to assess the accuracy of different methods for delineation of tumour volume from the PET images. Material and methods. An empty mould was produced on the basis of a contrast enhanced computed tomography (CT) study of a patient with a squamous cell carcinoma in the head and neck region. The mould was filled with a homogeneous fast-settling gel that contained both 18F for positron emission tomography (PET) and an iodine contrast agent. This phantom (mould and gel) was scanned on a PET/CT scanner. A series of reference tumour contours were obtained from the CT images in the PET/CT. Tumour delineation based on the PET images was achieved manually, by isoSUV thresholding, and by a recently developed three-dimensional (3D) Difference of Gaussians algorithm (DoG). Average distances between the PET-derived and reference contours were assessed by a 3D distance transform. Results. The manual, thresholding and DoG delineation methods resulted in volumes that were 146%, 86% and 100% of the reference volume, respectively, and average distance deviations from the reference surface were 1.57 mm, 1.48 mm and 1.0, mm, respectively. Discussion. Manual drawing as well as isoSUV determination of tumour contours in geometrically irregular tumours may be unreliable. The DoG method may contribute to more correct delineation of the tumour. Although the present phantom had a homogeneous distribution of activity, it may also provide useful knowledge in the case of inhomogeneous activity distributions. Conclusion. The geometric irregular tumour phantom with its inherent reference contours was an important tool for testing of different delineation methods and for teaching delineation.

ALGORITHMS; IMAGING phantoms; STRUCTURAL frame models; TOMOGRAPHY; POSITRON emission tomography

Acta Oncologica, 2013, Vol 52, Issue 3, p636

0284-186X

Academic Journal

10.3109/0284186X.2012.718095