Quantitative PET-based biomarkers in lymphoma: getting ready for primetime.

Autor: Alderuccio JP; Department of Medicine, Division of Hematology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA. jalderuccio@med.miami.edu., Kuker RA; Department of Radiology, Division of Nuclear Medicine, University of Miami Miller School of Medicine, Miami, FL, USA., Yang F; Department of Radiation Oncology, Division of Medical Physics, University of Miami Miller School of Medicine, Miami, FL, USA., Moskowitz CH; Department of Medicine, Division of Hematology, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA.
Jazyk: angličtina
Zdroj: Nature reviews. Clinical oncology [Nat Rev Clin Oncol] 2023 Sep; Vol. 20 (9), pp. 640-657. Date of Electronic Publication: 2023 Jul 17.
DOI: 10.1038/s41571-023-00799-2
Abstrakt: The use of functional quantitative biomarkers extracted from routine PET-CT scans to characterize clinical responses in patients with lymphoma is gaining increased attention, and these biomarkers can outperform established clinical risk factors. Total metabolic tumour volume enables individualized estimation of survival outcomes in patients with lymphoma and has shown the potential to predict response to therapy suitable for  risk-adapted treatment approaches in clinical trials. The deployment of machine learning tools in molecular imaging research can assist in recognizing complex patterns and, with image classification, in tumour identification and segmentation of data from PET-CT scans. Initial studies using fully automated approaches to calculate metabolic tumour volume and other PET-based biomarkers have demonstrated appropriate correlation with calculations from experts, warranting further testing in large-scale studies. The extraction of computer-based quantitative tumour characterization through radiomics can provide a comprehensive view of phenotypic heterogeneity that better captures the molecular and functional features of the disease. Additionally, radiomics can be integrated with genomic data to provide more accurate prognostic information. Further improvements in PET-based biomarkers are imminent, although their incorporation into clinical decision-making currently has methodological shortcomings that need to be addressed with confirmatory prospective validation in selected patient populations. In this Review, we discuss the current knowledge, challenges and opportunities in the integration of quantitative PET-based biomarkers in clinical trials and the routine management of patients with lymphoma.
(© 2023. Springer Nature Limited.)
Databáze: MEDLINE
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