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- W4385336306 abstract "Most hematological malignancies display heightened glycolytic activity, leading to their detectability through 18F-FDG-PET imaging. PET quantification enables the extraction of metabolic information from tumors. Among various PET measurements, maximum standardized uptake value (SUVmax), which indicates the highest value of 18F-FDG uptake within the tumor, has emerged as the commonly used parameter in clinical oncology. This is because of SUVmax ease of calculation using most available commercial workstations, as well as its simplicity and independence from observer interpretation. Nonetheless, SUVmax represents the increase in activity within a specific small area, which may not fully capture the overall tumor uptake. Volumetric PET parameters have been identified as a potential solution to overcome certain limitations associated with SUVmax. However, these parameters are influenced by the low septal resolution of PET when assessing small lesions. Another challenge is the high number of lesions observed in some patients, leading to a time-consuming process for evaluating all focal lesions. Some institutions recently have started advocating for CT-based segmentation as a method for measuring radiotracer uptake in the bone marrow and overall bone of the patients. This review article aims to provide insights into clinical application of PET quantification specifically focusing on three major hematologic malignancies: multiple myeloma, lymphoma, and chronic lymphocytic leukemia." @default.
- W4385336306 created "2023-07-29" @default.
- W4385336306 creator A5087410376 @default.
- W4385336306 date "2023-07-01" @default.
- W4385336306 modified "2023-09-23" @default.
- W4385336306 title "Clinical Application of 18F-FDG-PET Quantification in Hematological Malignancies: Emphasizing Multiple Myeloma, Lymphoma and Chronic Lymphocytic Leukemia" @default.
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- W4385336306 doi "https://doi.org/10.1016/j.clml.2023.07.008" @default.
- W4385336306 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37558532" @default.
- W4385336306 hasPublicationYear "2023" @default.
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