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Repeatability of metabolic tumor burden and lesion glycolysis between clinical readers.
Choi, Jung W; Dean, Erin A; Lu, Hong; Thompson, Zachary; Qi, Jin; Krivenko, Gabe; Jain, Michael D; Locke, Frederick L; Balagurunathan, Yoganand.
Afiliación
  • Choi JW; Department of Diagnostic Imaging and Interventional Radiology, H Lee Moffitt Cancer Center, Tampa, FL, United States.
  • Dean EA; Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
  • Lu H; Division of Hematology and Oncology, University of Florida, Gainesville, FL, , United States.
  • Thompson Z; Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
  • Qi J; Tianjin Medical University Cancer Institute and Hospital, Tianjin,  China.
  • Krivenko G; Biostatistics & Bioinformatics, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
  • Jain MD; Cancer Physiology, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
  • Locke FL; Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
  • Balagurunathan Y; Blood and Marrow Transplant and Cellular Immunotherapy, H. Lee. Moffitt Cancer Center, Tampa, FL, United States.
Front Immunol ; 14: 994520, 2023.
Article en En | MEDLINE | ID: mdl-36875072
The Metabolic Tumor Volume (MTV) and Tumor Lesion Glycolysis (TLG) has been shown to be independent prognostic predictors for clinical outcome in Diffuse Large B-cell Lymphoma (DLBCL). However, definitions of these measurements have not been standardized, leading to many sources of variation, operator evaluation continues to be one major source. In this study, we propose a reader reproducibility study to evaluate computation of TMV (& TLG) metrics based on differences in lesion delineation. In the first approach, reader manually corrected regional boundaries after automated detection performed across the lesions in a body scan (Reader M using a manual process, or manual). The other reader used a semi-automated method of lesion identification, without any boundary modification (Reader A using a semi- automated process, or auto). Parameters for active lesion were kept the same, derived from standard uptake values (SUVs) over a 41% threshold. We systematically contrasted MTV & TLG differences between expert readers (Reader M & A). We find that MTVs computed by Readers M and A were both concordant between them (concordant correlation coefficient of 0.96) and independently prognostic with a P-value of 0.0001 and 0.0002 respectively for overall survival after treatment. Additionally, we find TLG for these reader approaches showed concordance (CCC of 0.96) and was prognostic for over -all survival (p ≤ 0.0001 for both). In conclusion, the semi-automated approach (Reader A) provides acceptable quantification & prognosis of tumor burden (MTV) and TLG in comparison to expert reader assisted measurement (Reader M) on PET/CT scans.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Tomografía de Emisión de Positrones / Glucólisis Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Front Immunol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Tomografía Computarizada por Tomografía de Emisión de Positrones / Glucólisis Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Front Immunol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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