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18F-Fluorocholine PET/CT in the Prediction of Molecular Subtypes and Prognosis for Gliomas

García Vicente, Ana María MD, PhD*; Pérez-Beteta, Julian PhD; Amo-Salas, Mariano PhD; Pena Pardo, Francisco José MD, PhD*; Villena Martín, Maikal MD§; Sandoval Valencia, Hernán MD; Mollejo Villanueva, Manuela MD, PhD; Barbella, Rosa MD**; Klein Zampaña, Christoph José MD; Borrás Moreno, José María MD§; Soriano Castrejón, Ángel María MD*; Pérez-García, Víctor Manuel PhD

doi: 10.1097/RLU.0000000000002715
Original Articles

Aim To study the association of metabolic features of 18F-fluorocholine in gliomas with histopathological and molecular parameters, progression-free survival (PFS) and overall survival (OS).

Methods Prospective multicenter and nonrandomized study (Functional and Metabolic Glioma Analysis). Patients underwent a basal 18F-fluorocholine PET/CT and were included after histological confirmation of glioma. Histological and molecular profile was assessed: grade, Ki-67, isocitrate dehydrogenase status and 1p/19q codeletion. Patients underwent standard treatment after surgery or biopsy, depending on their clinical situation. Overall survival and PFS were obtained after follow-up. After tumor segmentation of PET images, SUV and volume-based variables, sphericity, surface, coefficient of variation, and multilesionality were obtained. Relations of metabolic variables with histological, molecular profile and prognosis were evaluated using Pearson χ2 and t test. Receiver operator caracteristic curves were used to obtain the cutoff of PET variables. Survival analysis was performed using Kaplan-Meier and Cox regression analysis.

Results Forty-five patients were assessed; 38 were diagnosed as having high-grade gliomas. Significant differences of SUV-based variables with isocitrate dehydrogenase status, tumor grade, and Ki-67 were found. Tumor grade, Ki-67, SUVmax, and SUVmean were related to progression. Kaplan-Meier analysis revealed significant associations of SUVmax, SUVmean, and multilesionaly with OS and PFS. SUVmean, sphericity, and multilesionality were independent predictors of OS and PFS in Cox regression analysis.

Conclusions Metabolic information obtained from 18F-fluorocholine PET of patients with glioma may be useful in the prediction of tumor biology and patient prognosis.

From the *Nuclear Medicine Department, University General Hospital, Ciudad Real

Mathematical Oncology Laboratory (MôLAB), Castilla La Mancha University, Ciudad Real

Department of Mathematics, Castilla La Mancha University, Ciudad Real

§Neurosurgery Department. University General Hospital, Ciudad Real

Neurosurgery Department, University General Hospital, Albacete

Pathology Department, Complejo Hospitalario de Toledo, Toledo

**Pathology Department, University General Hospital, Albacete, Spain.

Received for publication March 21, 2019; revision accepted June 2, 2019.

All the authors confirm that the article is not under consideration for publication elsewhere.

All ethical standards were complied with.

Conflicts of interest and sources of funding: JPB and VMP-G were partially funded by the Ministerio de Economía y Competitividad/FEDER, Spain (grant number MTM2015-71200-R), Junta de Comunidades de Castilla-La Mancha (grant number SBPLY/17/180501/000154) and James S. Mc. Donnell Foundation 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer (Collaborative awards 220020560 and 220020450). All other authors declare no conflicts of interest.

Research involving human participants and/or animals: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent: Informed consent was obtained from all individual participants included in the study.

Correspondence to: Ana María García Vicente, MD, PhD, Nuclear Medicine Department, University General Hospital, C/ Obispo Rafael Torija, s/n 13005 Ciudad Real, Spain. E-mail:

Online date: July 15, 2019

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