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

Author(s)

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]}

Affiliation

^[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

• Document type: Journal article
• Source: NUCLEAR MEDICINE COMMUNICATIONS; v. 41, n. 4, p. 377-382, APR 2020.
• Web of Science Citations: 0

Abstract

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)

• FAPESP's process: 18/00654-4 - Comparison between Neovascularization and Cellular Hypermetabolism in Multiple Myeloma Using 68Ga-PSMA and 18F-FDG PET/CT Imaging - A Pilot Study
• Grantee: Celso Darío Ramos
• Support type: Regular Research Grants
• FAPESP's process: 09/54065-0 - Acquisition of a PET/CT for the quantification of metabolic activity in living tissue
• Grantee: Carmino Antonio de Souza
• Support type: Multi-user Equipment Program