UNLABELLED: The role of quantitative (18)F-FDG PET studies for the differentiation of benign and malignant bone lesions is still an open question. METHODS: Our evaluation included 83 patients with 37 histologically proven malignancies and 46 benign lesions. Thirty-five of the 46 benign lesions were histologically confirmed. The (18)F-FDG studies were accomplished as a dynamic series for 60 min. Evaluation of the (18)F-FDG kinetics was performed using the following parameters: standardized uptake value (SUV), global influx (Ki), computation of the transport constants K1-k4 with consideration of the distribution volume (VB) according to a 2-tissue-compartment model, fractal dimension based on the box-counting procedure (parameter for the inhomogeneity of the tumors). RESULTS: The mean SUV, the vascular fraction VB, K1, and k3 were higher in malignant tumors compared with benign lesions (t test; P < 0.05). Although the (18)F-FDG SUV was helpful to differentiate benign and malignant tumors, there was some overlap, which limited the diagnostic accuracy. On the basis of the discriminant analysis, the SUV alone showed a sensitivity of only 54.05%, a specificity of 91.30%, and a diagnostic accuracy of 74.70%. The fractal dimension was superior and showed a sensitivity of 71.88%, a specificity of 81.58%, and an accuracy of 77.14%. The combination of SUV, fractal dimension, VB, K1-k4, and Ki revealed the best results with a sensitivity of 75.86%, a specificity of 97.22%, and an accuracy of 87.69%. Bayesian analysis showed true-positive results at the level of 0.8 for a low prevalence of disease (0.235) if the full kinetic data were used in the evaluation. CONCLUSION: (18)F-FDG PET has a high specificity for the exclusion of a malignant bone tumor. Evaluation of the full (18)F-FDG kinetics and the application of discriminant analysis are required and can be used prospectively to classify a bone lesion as malignant or benign.
UNLABELLED: The role of quantitative (18)F-FDG PET studies for the differentiation of benign and malignant bone lesions is still an open question. METHODS: Our evaluation included 83 patients with 37 histologically proven malignancies and 46 benign lesions. Thirty-five of the 46 benign lesions were histologically confirmed. The (18)F-FDG studies were accomplished as a dynamic series for 60 min. Evaluation of the (18)F-FDG kinetics was performed using the following parameters: standardized uptake value (SUV), global influx (Ki), computation of the transport constants K1-k4 with consideration of the distribution volume (VB) according to a 2-tissue-compartment model, fractal dimension based on the box-counting procedure (parameter for the inhomogeneity of the tumors). RESULTS: The mean SUV, the vascular fraction VB, K1, and k3 were higher in malignant tumors compared with benign lesions (t test; P < 0.05). Although the (18)F-FDG SUV was helpful to differentiate benign and malignant tumors, there was some overlap, which limited the diagnostic accuracy. On the basis of the discriminant analysis, the SUV alone showed a sensitivity of only 54.05%, a specificity of 91.30%, and a diagnostic accuracy of 74.70%. The fractal dimension was superior and showed a sensitivity of 71.88%, a specificity of 81.58%, and an accuracy of 77.14%. The combination of SUV, fractal dimension, VB, K1-k4, and Ki revealed the best results with a sensitivity of 75.86%, a specificity of 97.22%, and an accuracy of 87.69%. Bayesian analysis showed true-positive results at the level of 0.8 for a low prevalence of disease (0.235) if the full kinetic data were used in the evaluation. CONCLUSION: (18)F-FDG PET has a high specificity for the exclusion of a malignant bone tumor. Evaluation of the full (18)F-FDG kinetics and the application of discriminant analysis are required and can be used prospectively to classify a bone lesion as malignant or benign.
Authors: Nanda C Krak; R Boellaard; Otto S Hoekstra; Jos W R Twisk; Corneline J Hoekstra; Adriaan A Lammertsma Journal: Eur J Nucl Med Mol Imaging Date: 2004-10-15 Impact factor: 9.236
Authors: Arman Rahmim; Martin A Lodge; Nicolas A Karakatsanis; Vladimir Y Panin; Yun Zhou; Alan McMillan; Steve Cho; Habib Zaidi; Michael E Casey; Richard L Wahl Journal: Eur J Nucl Med Mol Imaging Date: 2018-09-29 Impact factor: 9.236
Authors: Ludwig G Strauss; Dirk Koczan; Sven Klippel; Leyun Pan; Stefan Willis; Christos Sachpekidis; Antonia Dimitrakopoulou-Strauss Journal: Am J Nucl Med Mol Imaging Date: 2013-09-19