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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Computed tomography-based skeletal segmentation for quantitative PET metrics of bone involvement in multiple myeloma

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Autor(es):
Takahashi, Maria E. S. [1, 2] ; Mosci, Camila [3] ; Souza, Edna M. [3, 4] ; Brunetto, Sergio Q. [3, 4] ; de Souza, Carmino [5, 1] ; Pericole, Fernando V. [5] ; Lorand-Metze, Irene [6] ; Ramos, Celso D. [1, 3]
Número total de Autores: 8
Afiliação do(s) autor(es):
[1] Univ Estadual Campinas, Sch Med Sci, Fac Med Sci, Campinas - Brazil
[2] Univ Estadual Campinas, Phys Inst, Fac Med Sci, Campinas - Brazil
[3] Univ Estadual Campinas, Div Nucl Med, Fac Med Sci, Campinas - Brazil
[4] Univ Estadual Campinas, Ctr Biomed Engn, Fac Med Sci, Campinas - Brazil
[5] Univ Estadual Campinas, Ctr Hematol & Hemotherapy, Fac Med Sci, Campinas - Brazil
[6] Univ Estadual Campinas, Dept Internal Med, Fac Med Sci, Campinas - Brazil
Número total de Afiliações: 6
Tipo de documento: Artigo Científico
Fonte: NUCLEAR MEDICINE COMMUNICATIONS; v. 41, n. 4, p. 377-382, APR 2020.
Citações Web of Science: 0
Resumo

Purpose Quantifications in nuclear medicine are occasionally limited by the lack of standardization for defining volumes of interest (VOIs) on functional images. In the present article, we propose the use of computed tomography (CT)-based skeletal segmentation to determine anatomically the VOI in order to calculate quantitative parameters of fluorine 18 fluorodeoxyglucose (F-18-FDG) PET/CT images from patients with multiple myeloma. Methods We evaluated 101 whole-body F-18-FDG PET/CTs of 58 patients with multiple myeloma. An initial subjective visual analysis of the PET images was used to classify the bone involvement as negative/mild, moderate, or marked. Then, a fully automated CT-based segmentation of the skeleton was performed on PET images. The maximum, mean, and SD of the standardized uptake values (SUVmax, SUVmean, and SDSUV) were calculated for bone tissue and compared with the visual analysis. Results Forty-five (44.5%), 32 (31.7%), and 24 (23.8%) PET images were, respectively, classified as negative/mild, moderate, or marked bone involvement. All quantitative parameters were significantly related to the visual assessment of bone involvement. This association was stronger for the SUVmean {[}odds ratio (OR): 10.52 (95% confidence interval (CI), 5.68-19.48); P < 0.0001] and for the SDSUV {[}OR: 5.58 (95% CI, 3.31-9.42); P < 0.001) than for the SUVmax {[}OR: 1.01 (95% CI, 1.003-1.022); P = 0.003]. Conclusion CT-based skeletal segmentation allows for automated and therefore reproducible calculation of PET quantitative parameters of bone involvement in patients with multiple myeloma. Using this method, the SUVmean and its respective SD correlated better with the visual analysis of F-18-FDG PET images than SUVmax. Its value in staging and evaluating therapy response needs to be evaluated. (AU)

Processo FAPESP: 18/00654-4 - ESTUDO PILOTO DE COMPARAÇÃO ENTRE NEOVASCULARIZAÇÃO E HIPERMETABOLISMO CELULAR NO MIELOMA MÚLTIPLO UTILIZANDO IMAGENS DE PET/CT PSMA-68Ga E PET/CT FDG-18F
Beneficiário:Celso Darío Ramos
Linha de fomento: Auxílio à Pesquisa - Regular
Processo FAPESP: 09/54065-0 - EMU: aquisição de PET/CT para quantificação da atividade metabólica de tecidos vivos
Beneficiário:Carmino Antonio de Souza
Linha de fomento: Auxílio à Pesquisa - Programa Equipamentos Multiusuários