Literature DB >> 29943313

18F-FDG PET/CT can predict chemosensitivity and proliferation of epithelial ovarian cancer via SUVmax value.

Shuai Liu1,2,3,4, Zheng Feng4,5, Hao Wen4,5, Zhaoxia Jiang4,6, Herong Pan1,2,3,4, Yu Deng5,7, Lei Zhang5,7, Xingzhu Ju4,5, Xiaojun Chen4,5, Xiaohua Wu8,9.   

Abstract

PURPOSE: This study aimed to explore the clinical and prognostic significance of 18F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in epithelial ovarian cancer (EOC).
METHODS: We retrospectively investigated 48 EOC patients who underwent preoperative 18F-FDG PET/CT and primary cytoreductive surgery at our hospital between January 2010 and June 2015. None of these patients received neoadjuvant chemotherapy. PET/CT parameters including the maximum and average standardized uptake value (SUVmax, SUVavg), the metabolic tumor volume (MTV) were measured. Tumor proliferation marker Ki67 was evaluated using immunohistochemistry. The relationships between the PET/CT parameters and chemosensitivity, tumor proliferation, and overall survival (OS) were analyzed, respectively.
RESULTS: The median (range) SUVmax, SUVavg, and MTV values were 11.42 (3.14-20.20), 4.8 (2.55-9.47), and 150.11 (0.19-792.46), respectively. Overall, 93.8% (45/48) of patients had high-grade serous ovarian cancer. The SUVmax value had a positive correlation with the Ki67 index (P = 0.030, r = 0.314), and a higher SUVmax level was associated with chemosensitivity (P = 0.026). However, neither SUVavg nor MTV had associations with the patients' clinicopathological parameters. None of these three PET/CT parameters were found to be potential predictors of OS.
CONCLUSIONS: Preoperative 18F-FDG PET/CT had a predictive value on chemosensitivity and proliferation after primary debulking surgery in EOC patients noninvasively.

Entities:  

Keywords:  18F-FDG PET/CT; Chemosensitivity; Epithelial ovarian cancer; Maximum standardized uptake value; Proliferation

Mesh:

Substances:

Year:  2018        PMID: 29943313     DOI: 10.1007/s11604-018-0755-y

Source DB:  PubMed          Journal:  Jpn J Radiol        ISSN: 1867-1071            Impact factor:   2.374


  30 in total

1.  Preoperative risk stratification using metabolic parameters of (18)F-FDG PET/CT in patients with endometrial cancer.

Authors:  Kazuhiro Kitajima; Yuko Suenaga; Yoshiko Ueno; Tetsuo Maeda; Yasuhiko Ebina; Hideto Yamada; Takashi Okunaga; Kazuhiro Kubo; Keitarou Sofue; Tomonori Kanda; Yukihisa Tamaki; Kazuro Sugimura
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-04-02       Impact factor: 9.236

2.  Positron emission tomography-laparoscopy based method in the prediction of complete cytoreduction in platinum-sensitive recurrent ovarian cancer.

Authors:  Francesco Fanfani; Giorgia Monterossi; Anna Fagotti; Valerio Gallotta; Barbara Costantini; Giuseppe Vizzielli; Marco Petrillo; Maria Vittoria Carbone; Giovanni Scambia
Journal:  Ann Surg Oncol       Date:  2014-08-26       Impact factor: 5.344

3.  The role of metabolic tumor volume and total lesion glycolysis on ¹⁸F-FDG PET/CT in the prognosis of epithelial ovarian cancer.

Authors:  Jeong Won Lee; Arthur Cho; Jae-Hoon Lee; Mijin Yun; Jong Doo Lee; Young Tae Kim; Won Jun Kang
Journal:  Eur J Nucl Med Mol Imaging       Date:  2014-05-23       Impact factor: 9.236

4.  (18)F-FDG PET/CT mean SUV and metabolic tumor volume for mean survival time in non-small cell lung cancer.

Authors:  Ercan Kurtipek; Mustafa Çayci; Nuri Düzgün; Hidir Esme; Yüksel Terzi; Süleyman Bakdik; Murat Serhat Aygün; Yaşar Unlü; Cengiz Burnik; Taha Tahir Bekci
Journal:  Clin Nucl Med       Date:  2015-06       Impact factor: 7.794

5.  Assessment of cell proliferation in renal cell carcinoma using dual-phase 18F-fluorodeoxyglucose PET/CT.

Authors:  Rei Onishi; Masanori Noguchi; Hayato Kaida; Fukuko Moriya; Katsuaki Chikui; Seiji Kurata; Akihiko Kawahara; Masayoshi Kage; Masatoshi Ishibashi; Kei Matsuoka
Journal:  Oncol Lett       Date:  2015-06-11       Impact factor: 2.967

6.  Quantitative metabolic parameters measured on F-18 FDG PET/CT predict survival after relapse in patients with relapsed epithelial ovarian cancer.

Authors:  Choon-Young Kim; Shin Young Jeong; Gun Oh Chong; Seung Hyun Son; Ji-hoon Jung; Do-Hoon Kim; Sang-Woo Lee; Byeong-Cheol Ahn; Jaetae Lee
Journal:  Gynecol Oncol       Date:  2014-12-31       Impact factor: 5.482

Review 7.  Molecular imaging: what can be used today.

Authors:  P L Jager; M A de Korte; M N Lub-de Hooge; A van Waarde; K P Koopmans; P J Perik; E G E de Vries
Journal:  Cancer Imaging       Date:  2005-11-23       Impact factor: 3.909

8.  Pretreatment (18)F-FDG uptake heterogeneity can predict survival in patients with locally advanced nasopharyngeal carcinoma--a retrospective study.

Authors:  Zhongyi Yang; Qi Shi; Yongping Zhang; Herong Pan; Zhifeng Yao; Silong Hu; Wei Shi; Beiling Zhu; Yingjian Zhang; Chaosu Hu
Journal:  Radiat Oncol       Date:  2015-01-08       Impact factor: 3.481

9.  Prognostic value of metabolic parameters determined by preoperative ¹⁸F-FDG PET/CT in patients with uterine carcinosarcoma.

Authors:  Hyun Ju Lee; Jong Jin Lee; Jeong Yeol Park; Jong Hyeok Kim; Yong Man Kim; Young Tak Kim; Joo Hyun Nam
Journal:  J Gynecol Oncol       Date:  2017-07       Impact factor: 4.401

10.  Thrombocytosis and hyperfibrinogenemia are predictive factors of clinical outcomes in high-grade serous ovarian cancer patients.

Authors:  Zheng Feng; Hao Wen; Rui Bi; Yachen Duan; Wentao Yang; Xiaohua Wu
Journal:  BMC Cancer       Date:  2016-01-27       Impact factor: 4.430

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Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-07-03       Impact factor: 9.236

2.  Correlation analysis between the SUVmax of FDG-PET/CT and clinicopathological characteristics in oral squamous cell carcinoma.

Authors:  Dong Zheng; Lixuan Niu; Wenpeng Liu; Changgang Zheng; Ruyi Yan; Liyan Gong; Zhongxing Dong; Ke Li; Jun Fei
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Authors:  Sherif B Elsherif; Priya R Bhosale; Chandana Lall; Christine O Menias; Malak Itani; Kristina A Butler; Dhakshinamoorthy Ganeshan
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Review 4.  Combining Diagnostic Imaging and Pathology for Improving Diagnosis and Prognosis of Cancer.

Authors:  Orazio Schillaci; Manuel Scimeca; Nicola Toschi; Rita Bonfiglio; Nicoletta Urbano; Elena Bonanno
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