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Chapter 6
REFERENCES
1. Oldham RK, Dillman RO. Monoclonal antibodies in cancer therapy: 25 years of progress. J Clin Oncol. 2008; 26: 1774-1777.
2. Tout M, Casasnovas O, Meignan M, et al. Rituximab exposure is influenced by baseline metabolic tumor volume and predicts outcome of DLBCL patients: a Lymphoma Study Association report. Blood. 2017; 129 (19): 2616-2623.
3. Lamberts LE, Williams SP, Terwisscha van Scheltinga AG, et al. Antibody positron emission tomography imaging in anticancer drug development. J Clin Oncol. 2015; 33: 1491-504.
4. Jauw, YWS, Menke-van der Houven van Oordt CW, Hoekstra OS, et al. Immuno-positron emission tomography with zirconium-89-labeled monoclonal antibodies in oncology: what can we learn from initial clinical trials? Front. Pharmacol. 2016; 7: 131.
5. Menke-van der Houven van Oordt, CW, Gootjes EC, Huisman MC, et al. 89Zr-cetuximab PET imaging in patients with advanced colorectal cancer. Oncotarget. 2015; 30: 30384-93.
6. Jauw, YWS, Zijlstra JM, de Jong D, et al. Performance of 89Zr-labeled-rituximab-PET as an imaging biomarker to assess CD20 targeting: a pilot study in patients with relapsed/refractory diffuse large B cell lymphoma. PLoS One. 2017; 12: e0169828.
7. Bensch F, Brouwers AH, Lub-de Hooge MN, et al. 89Zr-trastuzumab PET supports clinical decision making in breast cancer patients, when HER2 status cannot be determined by standard work up. Eur J Nucl Med Mol Imaging. 2018; 45(13): 2300-2306. doi: 10.1007/s00259-018-4099-8. Epub 2018 Jul 30.
8. Makris NE, Boellaard R, Visser EP, et al. Multicenter harmonization of 89Zr PET/CT performance. J Nucl Med. 2014; 55: 264-7.
9. Boellaard R. QuAntitative onCology moleCUlaR Analysis suiTE: ACCURATE. J Nucl Med. 2018; 59: 1753.
10. Frings V, de Langen AJ, Yaqub M, et al. Methodological considerations in quantification of 3’-deoxy- 3’-[18F]fluorothymidine uptake measured with positron emission tomography in patients with non- small cell lung cancer. Mol Imaging Biol. 2014; 16:136-145.
11. de Vet HC, Terwee CB, Knol DL, et al. When to use agreement versus reliability measures. J Clin Epidemiol. 2006; 59: 1033-1039.
12. Huang YE, Chen CF, Huang YJ, et al. Interobserver variability among measurements of the maximum and mean standardized uptake values on (18)F-FDG PET/CT and measurements of tumor size on diagnostic CT in patients with pulmonary tumors. Acta Radiol. 2010; 51: 782-788.
13. Lee JR, Madsen MT, Bushnel D, et al. A threshold method to improve standardized uptake reproducibility. Nucl Med Commun. 2000; 21: 685-690.
14. Kanoun S, Tal I, Berriolo-Riedinger A, et al. Influence of software tool and methodological aspects of total metabolic tumor volume calculation on baseline [18F]FDG PET to predict survival in Hodgkin lymphoma. PLoS One. 2015; 10: e0140830.
15. Boellaard R, Delgado-Bolton R, Oyen WJ, et el. FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0. Eur J Nucl Med Mol Imaging. 2015; 42: 328-354.
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