Literature DB >> 11337565

Dynamic PET 18F-FDG studies in patients with primary and recurrent soft-tissue sarcomas: impact on diagnosis and correlation with grading.

A Dimitrakopoulou-Strauss1, L G Strauss, M Schwarzbach, C Burger, T Heichel, F Willeke, G Mechtersheimer, T Lehnert.   

Abstract

UNLABELLED: The purpose of this study was to evaluate (18)F-FDG PET studies of primary and recurrent sarcomas for diagnosis and correlation with grading.
METHODS: The evaluation included 56 patients, 43 with histologically proven malignancies and 13 with benign lesions. Seventeen patients were referred with suspicion on a primary tumor, and the remaining 39 were referred with suspicion on a recurrent tumor. The FDG studies were accomplished as a dynamic series for 60 min. The evaluation of the FDG kinetics was performed using the following parameters: standardized uptake value (SUV), global influx, computation of the transport constants K1-k4 with consideration of the distribution volume (VB) according to a two-tissue-compartment model, and fractal dimension based on the box-counting procedure (parameter for the inhomogeneity of the tumors).
RESULTS: Visual evaluation revealed a sensitivity of 76.2%, a specificity of 42.9%, and an accuracy of 67.9%. The vascular fraction VB and the SUV were higher in malignant tumors compared with benign lesions (t test, P < 0.05). Although the FDG SUV helped to distinguish benign and malignant tumors, there was some overlap, which limited the diagnostic accuracy. The SUV and fractal dimension accounted for significant differences in six of the nine diagnostic pairs. Whereas grade (G) II and G III tumors were differentiated from lipomas on the basis of the fractal dimension and some other kinetic parameters, no differences were found between G I tumors and lipomas. On the basis of the discriminant analysis, the differentiation of soft-tissue tumors was best for the use of six parameters of the FDG kinetics (SUV, VB, K1, k3, influx, and fractal dimension). Eighty-four percent of G III tumors, 37.5% of G II tumors, 80% of G I tumors, 50% of lipomas, and 14.3% of scars could be classified correctly, whereas inflammatory lesions were misclassified.
CONCLUSION: FDG PET should be used preferentially for monitoring patients with G III sarcomas. Visual analysis provides a low specificity. In contrast, the evaluation of the full FDG kinetics provides superior information, particularly for the discrimination of G I and G III tumors (positive predictive value, >80%).

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Year:  2001        PMID: 11337565

Source DB:  PubMed          Journal:  J Nucl Med        ISSN: 0161-5505            Impact factor:   10.057


  42 in total

1.  FDG-PET for preoperative differential diagnosis between benign and malignant soft tissue masses.

Authors:  J Aoki; H Watanabe; T Shinozaki; K Takagishi; M Tokunaga; Y Koyama; N Sato; K Endo
Journal:  Skeletal Radiol       Date:  2003-01-24       Impact factor: 2.199

2.  Comparison of the pharmacokinetics of 68Ga-DOTATOC and [18F]FDG in patients with metastatic neuroendocrine tumours scheduled for 90Y-DOTATOC therapy.

Authors:  Sophia Koukouraki; Ludwig G Strauss; Vassilios Georgoulias; Michael Eisenhut; Uwe Haberkorn; Antonia Dimitrakopoulou-Strauss
Journal:  Eur J Nucl Med Mol Imaging       Date:  2006-06-09       Impact factor: 9.236

3.  Evaluation of the pharmacokinetics of 68Ga-DOTATOC in patients with metastatic neuroendocrine tumours scheduled for 90Y-DOTATOC therapy.

Authors:  Sophia Koukouraki; Ludwig G Strauss; Vassilios Georgoulias; Jochen Schuhmacher; Uwe Haberkorn; Nikolaos Karkavitsas; Antonia Dimitrakopoulou-Strauss
Journal:  Eur J Nucl Med Mol Imaging       Date:  2006-01-17       Impact factor: 9.236

Review 4.  Importance of quantification for the analysis of PET data in oncology: review of current methods and trends for the future.

Authors:  Giampaolo Tomasi; Federico Turkheimer; Eric Aboagye
Journal:  Mol Imaging Biol       Date:  2012-04       Impact factor: 3.488

5.  Determination of the unmetabolised (18)F-FDG fraction by using an extension of simplified kinetic analysis method: clinical evaluation in paragangliomas.

Authors:  Dominique Barbolosi; Sebastien Hapdey; Stephanie Battini; Christian Faivre; Julien Mancini; Karel Pacak; Bardia Farman-Ara; David Taïeb
Journal:  Med Biol Eng Comput       Date:  2015-06-05       Impact factor: 2.602

Review 6.  The Complexity and Fractal Geometry of Nuclear Medicine Images.

Authors:  Fabio Grizzi; Angelo Castello; Dorina Qehajaj; Carlo Russo; Egesta Lopci
Journal:  Mol Imaging Biol       Date:  2019-06       Impact factor: 3.488

7.  Sparsity Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET.

Authors:  Yanguang Lin; Justin P Haldar; Quanzheng Li; Peter S Conti; Richard M Leahy
Journal:  IEEE Trans Med Imaging       Date:  2013-11-07       Impact factor: 10.048

8.  Volume-normalized uptake rates with robust transportability from PET dual-time and Patlak analyses.

Authors:  Joseph A Thie
Journal:  Mol Imaging Biol       Date:  2009-12-01       Impact factor: 3.488

9.  Repeatability of regional myocardial blood flow calculation in 82Rb PET imaging.

Authors:  Karin Knešaurek; Josef Machac; Zhuangyu Zhang
Journal:  BMC Med Phys       Date:  2009-01-29

10.  The use of positron emission tomography in soft tissue sarcoma patients under therapy with trabectedin.

Authors:  Bernd Kasper; Thomas Schmitt; Patrick Wuchter; Antonia Dimitrakopoulou-Strauss; Anthony D Ho; Gerlinde Egerer
Journal:  Mar Drugs       Date:  2009-07-17       Impact factor: 5.118

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