Glycolytic activity in breast cancer using 18F-FDG PET/CT as prognostic predictor: A molecular phenotype approach

被引:6
|
作者
Garcia Vicente, A. M. [1 ]
Soriano Castrejon, A. [1 ]
Amo-Salas, M. [2 ]
Lopez Fidalgo, J. F. [2 ]
Munoz Sanchez, M. M. [3 ]
Alvarez Cabellos, R. [4 ]
Espinosa Aunion, R. [5 ]
Munoz Madero, V. [6 ]
机构
[1] Univ Gen Hosp, Dept Nucl Med, Ciudad Real, Spain
[2] Univ Castilla La Mancha, Dept Math, E-13071 Ciudad Real, Spain
[3] Virgen de la Luz Hosp, Dept Oncol, Cuenca, Spain
[4] Virgen de la Salud Hosp, Dept Oncol, Toledo, Spain
[5] La Mancha Ctr Hosp, Dept Oncol, Ciudad Real, Spain
[6] Gomez Ulla Hosp, Dept Surg, Madrid, Spain
来源
REVISTA ESPANOLA DE MEDICINA NUCLEAR E IMAGEN MOLECULAR | 2016年 / 35卷 / 03期
关键词
Breast cancer; F-18-FDG PET/CT; Molecular phenotypes; Prognosis; Disease free status; Disease free survival; Overall survival; POSITRON-EMISSION-TOMOGRAPHY; NEOADJUVANT CHEMOTHERAPY; HER-2/NEU ONCOGENE; TUMOR METABOLISM; SUBTYPES; RECURRENCE; PARAMETERS; RELEVANCE; CONSENSUS; SURVIVAL;
D O I
10.1016/j.remn.2015.08.001
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Aim: To explore the relationship between basal F-18-FDG uptake in breast tumors and survival in patients with breast cancer (BC) using a molecular phenotype approach. Material and Methods: This prospective and multicentre study included 193 women diagnosed with BC. All patients underwent an F-18-FDG PET/CT prior to treatment. Maximum standardized uptake value (SUVmax) in tumor (T), lymph nodes (N), and the N/T index was obtained in all the cases. Metabolic stage was established. As regards biological prognostic parameters, tumors were classified into molecular sub-types and risk categories. Overall survival (OS) and disease free survival (DFS) were obtained. An analysis was performed on the relationship between semi-quantitative metabolic parameters with molecular phenotypes and risk categories. The effect of molecular sub-type and risk categories in prognosis was analyzed using Kaplan-Meier and univariate and multivariate tests. Results: Statistical differences were found in both SUVT and SUVN, according to the molecular sub-types and risk classifications, with higher semi-quantitative values in more biologically aggressive tumors. No statistical differences were observed with respect to the N/T index. Kaplan-Meier analysis revealed that risk categories were significantly related to DFS and OS. In the multivariate analysis, metabolic stage and risk phenotype showed a significant association with DFS. Conclusion: High-risk phenotype category showed a worst prognosis with respect to the other categories with higher SUVmax in primary tumor and lymph nodes. (C) 2015 Elsevier Espana, S.L.U. and SEMNIM. All rights reserved.
引用
收藏
页码:152 / 158
页数:7
相关论文
共 50 条
  • [1] Intratumoral heterogeneity in 18F-FDG PET/CT by textural analysis in breast cancer as a predictive and prognostic subrogate
    Molina-Garcia, David
    Maria Garcia-Vicente, Ana
    Perez-Beteta, Julian
    Amo-Salas, Mariano
    Martinez-Gonzalez, Alicia
    Jesus Tello-Galan, Maria
    Soriano-Castrejon, Angel
    Perez-Garcia, Victor M.
    ANNALS OF NUCLEAR MEDICINE, 2018, 32 (06) : 379 - 388
  • [2] Prognostic Role of Early and End-of-Neoadjuvant Treatment 18F-FDG PET/CT in Patients With Breast Cancer
    Garcia Vicente, Ana Maria
    Amo-Salas, Mariano
    Relea Calatayud, Fernanda
    Munoz Sanchez, Maria del Mar
    Pena Pardo, Francisco Jose
    Jimenez Londono, German Andres
    Alvarez Cabellos, Ruth
    Espinosa Aunion, Ruth
    Soriano Castrejon, Angel
    CLINICAL NUCLEAR MEDICINE, 2016, 41 (07) : E313 - E322
  • [3] 18F-FDG PET/CT for Staging and Restaging of Breast Cancer
    Groheux, David
    Cochet, Alexandre
    Humbert, Olivier
    Alberini, Jean-Louis
    Hindie, Elif
    Mankoff, David
    JOURNAL OF NUCLEAR MEDICINE, 2016, 57 : 17S - 26S
  • [4] Prognostic significance of preoperative 18F-FDG PET/CT for breast cancer subtypes
    Higuchi, Tomoko
    Nishimukai, Arisa
    Ozawa, Hiromi
    Fujimoto, Yukie
    Yanai, Ayako
    Miyagawa, Yoshimasa
    Murase, Keiko
    Imamura, Michiko
    Takatsuka, Yuichi
    Kitajima, Kazuhiro
    Fukushima, Kazuhito
    Miyoshi, Yasuo
    BREAST, 2016, 30 : 5 - 12
  • [5] Glycolytic activity with 18F-FDG PET/CT predicts final neoadjuvant chemotherapy response in breast cancer
    Garcia Vicente, Ana Maria
    Cruz Mora, Miguel Angel
    Leon Martin, Antonio Alberto
    Munoz Sanchez, Maria del Mar
    Relea Calatayud, Fernanda
    Van Gomez Lopez, Ober
    Espinosa Aunion, Ruth
    Gonzalez Ageitos, Ana
    Soriano Castrejon, Angel
    TUMOR BIOLOGY, 2014, 35 (11) : 11613 - 11620
  • [6] Molecular subtypes of breast cancer: metabolic correlation with 18F-FDG PET/CT
    Garcia Vicente, Ana Maria
    Soriano Castrejon, Angel
    Leon Martin, Alberto
    Chacon Lopez-Muniz, Ignacio
    Munoz Madero, Vicente
    Munoz Sanchez, Maria del Mar
    Palomar Munoz, Azahara
    Espinosa Aunion, Ruth
    Gonzalez Ageitos, Ana
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2013, 40 (09) : 1304 - 1311
  • [7] 18F-FDG PET/CT as a prognostic factor in penile cancer
    Salazar, Andre
    Paulino Junior, Eduardo
    Salles, Paulo Guilherme O.
    Silva-Filho, Raul
    Reis, Edna A.
    Mamede, Marcelo
    EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2019, 46 (04) : 855 - 863
  • [8] 18F-FDG PET/CT for Monitoring of Treatment Response in Breast Cancer
    Avril, Stefanie
    Muzic, Raymond F., Jr.
    Plecha, Donna
    Traughber, Bryan J.
    Vinayak, Shaveta
    Avril, Norbert
    JOURNAL OF NUCLEAR MEDICINE, 2016, 57 : 34S - 39S
  • [9] Prognostic Value of Metabolic Information in Advanced Gastric Cancer Using Preoperative 18F-FDG PET/CT
    Kwon, Hye Ryeong
    Pahk, Kisoo
    Park, Sungsoo
    Kwon, Hyun Woo
    Kim, Sungeun
    NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2019, 53 (06) : 386 - 395
  • [10] Prognostic Prediction of BRCA Mutations by 18F-FDG PET/CT SUVmax in Breast Cancer
    Ozdemir, Semra
    Silan, Fatma
    Akgun, Mehmet Yilmaz
    Araci, Nilgun
    Cirpan, Ismail
    Ozturk, Fulya Koc
    Ozdemir, Ozturk
    MOLECULAR IMAGING AND RADIONUCLIDE THERAPY, 2021, 30 (03) : 158 - 168