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Visualization and Quantification of Brown and Beige Adipose Tissues in Mice using [18F]FDG Micro-PET/MR Imaging
Published on: July 1, 2021
Rapid Contour-based Segmentation for 18F-FDG PET Imaging of Lung Tumors by Using ITK-SNAP: Comparison to Expert-based
Florent L Besson1, Théophraste Henry1, Céline Meyer1
1From the Department of Biophysics and Nuclear Medicine, Bicêtre University Hospital, Assistance Publique-Hôpitaux de Paris, 78 rue du Général Leclerc, 94275 Le Kremlin-Bicêtre, France (F.L.B., T.H., C.M., V.C., V.R., G.G., M.C., P.C.R., E.D.); IR4M-UMR 8081, Université Paris Saclay, Université Paris Sud, CNRS, Orsay, France (F.L.B., E.D.); Service Hospitalier Frédéric Joliot, CEA, Université Paris-Sud, Orsay, France (E.B., V.A., V.L.); Department of Nuclear Medicine, Hôpital Marie Lannelongue, Le Plessis Robinson, France (L.M.); Université Paris-Sud, Faculté de Médecine, Université Paris-Saclay, Le Kremlin-Bicêtre, France (F.P., A.S., S.B., D.M., M.H.); Service de Pneumologie, Hôpital Bicêtre, AP-HP, Le Kremlin-Bicêtre, France (F.P., A.S., S.B., D.M., M.H.); and INSERM UMR_S 999, Hôpital Marie Lannelongue, Le Plessis Robinson, France (F.P., A.S., S.B., D.M., M.H.).
Abstract:
Purpose To assess the performance of the ITK-SNAP software for fluorodeoxyglucose (FDG) positron emission tomography (PET) segmentation of complex-shaped lung tumors compared with an optimized, expert-based manual reference standard. Materials and Methods Seventy-six FDG PET images of thoracic lesions were retrospectively segmented by using ITK-SNAP software. Each tumor was manually segmented by six raters to generate an optimized reference standard by using the simultaneous truth and performance level estimate algorithm. Four raters segmented 76 FDG PET images of lung tumors twice by using ITK-SNAP active contour algorithm. Accuracy of ITK-SNAP procedure was assessed by using Dice coefficient and Hausdorff metric. Interrater and intrarater reliability were estimated by using intraclass correlation coefficients of output volumes. Finally, the ITK-SNAP procedure was compared with currently recommended PET tumor delineation methods on the basis of thresholding at 41% volume of interest (VOI; VOI41) and 50% VOI (VOI50) of the tumor's maximal metabolism intensity. Results Accuracy estimates for the ITK-SNAP procedure indicated a Dice coefficient of 0.83 (95% confidence interval: 0.77, 0.89) and a Hausdorff distance of 12.6 mm (95% confidence interval: 9.82, 15.32). Interrater reliability was an intraclass correlation coefficient of 0.94 (95% confidence interval: 0.91, 0.96). The intrarater reliabilities were intraclass correlation coefficients above 0.97. Finally, VOI41 and VOI50 accuracy metrics were as follows: Dice coefficient, 0.48 (95% confidence interval: 0.44, 0.51) and 0.34 (95% confidence interval: 0.30, 0.38), respectively, and Hausdorff distance, 25.6 mm (95% confidence interval: 21.7, 31.4) and 31.3 mm (95% confidence interval: 26.8, 38.4), respectively. Conclusion ITK-SNAP is accurate and reliable for active-contour-based segmentation of heterogeneous thoracic PET tumors. ITK-SNAP surpassed the recommended PET methods compared with ground truth manual segmentation.
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