Evaluation of a convolution neural network for baseline total tumor metabolic volume on [18F]FDG PET in diffuse large B cell lymphoma
Author:
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s00330-022-09375-1.pdf
Reference30 articles.
1. Flodr P, Latalova P, Tichy M, et al (2014) Diffuse large B-cell lymphoma: the history, current view and new perspectives. Neoplasma 62:491–504. https://doi.org/10.4149/neo_2014_062
2. Cottereau A-S, Lanic H, Mareschal S et al (2016) Molecular profile and FDG-PET/CT total metabolic tumor volume improve risk classification at diagnosis for patients with diffuse large B-cell lymphoma. Clin Cancer Res 22:3801–3809. https://doi.org/10.1158/1078-0432.CCR-15-2825
3. Shagera QA, Cheon GJ, Koh Y et al (2019) Prognostic value of metabolic tumour volume on baseline 18F-FDG PET/CT in addition to NCCN-IPI in patients with diffuse large B-cell lymphoma: further stratification of the group with a high-risk NCCN-IPI. Eur J Nucl Med Mol Imaging 46:1417–1427. https://doi.org/10.1007/s00259-019-04309-4
4. Wight JC, Chong G, Grigg AP, Hawkes EA (2018) Prognostication of diffuse large B-cell lymphoma in the molecular era: moving beyond the IPI. Blood Rev 32:400–415. https://doi.org/10.1016/j.blre.2018.03.005
5. Nowakowski GS, Feldman T, Rimsza LM et al (2019) Integrating precision medicine through evaluation of cell of origin in treatment planning for diffuse large B-cell lymphoma. Blood Cancer J 9:48. https://doi.org/10.1038/s41408-019-0208-6
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