Predictive Value of Metabolic Parameters Derived From 18F-FDG PET/CT for Microsatellite Instability in Patients With Colorectal Carcinoma

被引:12
作者
Liu, Hao [1 ,2 ]
Ye, Zheng [1 ]
Yang, Ting [1 ]
Xie, Hongjun [2 ]
Duan, Ting [1 ]
Li, Mou [1 ]
Wu, Min [1 ]
Song, Bin [1 ]
机构
[1] Sichuan Univ, West China Hosp, Dept Radiol, Chengdu, Peoples R China
[2] Sichuan Acad Med Sci, Sichuan Prov Peoples Hosp, Dept Nucl Med, Chengdu, Peoples R China
来源
FRONTIERS IN IMMUNOLOGY | 2021年 / 12卷
关键词
PET; CT; metabolism; colorectal carcinoma; microsatellite instability; immunotherapy; TOTAL LESION GLYCOLYSIS; CANCER PATIENTS; TUMOR VOLUME; PROGNOSTIC VALUE; MISMATCH REPAIR; HETEROGENEITY; SURVIVAL; UTILITY;
D O I
10.3389/fimmu.2021.724464
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background Microsatellite instability (MSI) is one of the important factors that determine the effectiveness of immunotherapy in colorectal cancer (CRC) and serves as a prognostic biomarker for its clinical outcomes. Purpose To investigate whether the metabolic parameters derived from(18)F-fluorodeoxyglucose (F-18-FDG) positron emission tomography/computed tomography (PET/CT) can predict MSI status in patients with CRC. Materials and Methods A retrospective analysis was performed on CRC patients who underwent F-18-FDG PET/CT examination before surgery between January 2015 and April 2021. The metabolic F-18-FDG PET/CT parameters of the primary CRC lesion were calculated and recorded with different thresholds, including the maximum, peak, and mean standardized uptake value (SUVmax, SUVpeak, and SUVmean), as well as the metabolic tumor volume (MTV) and the total lesion glycolysis (TLG). The status of MSI was determined by immunohistochemical assessment. The difference of quantitative parameters between MSI and microsatellite stability (MSS) groups was assessed, and the receiver operating characteristic (ROC) analyses with area under ROC curves (AUC) was used to evaluate the predictive performance of metabolic parameters. Results A total of 44 patients (24 men and 20 women; mean +/- standard deviation age: 71.1 +/- 14.2 years) were included. There were 14 patients in the MSI group while there were 30 in the MSS group. MTV30%, MTV40%, MTV50%, and MTV60%, as well as TLG(50%) and TLG(60%) showed significant difference between two groups (all p-values <0.05), among which MTV50% demonstrated the highest performance in the prediction of MSI, with an AUC of 0.805 [95% confidence interval (CI): 0.657-0.909], a sensitivity of 92.9% (95% CI: 0.661-0.998), and a specificity of 66.7% (95% CI: 0.472-0.827). Patients' age and MTV50% were significant predictive indicators of MSI in multivariate logistic regression. Conclusion The metabolic parameters derived from(18)F-FDG PET/CT were able to preoperatively predict the MSI status in CRC, with MTV50% demonstrating the highest predictive performance. PET/CT imaging could serve as a noninvasive tool in the guidance of immunotherapy and individualized treatment in CRC patients.
引用
收藏
页数:8
相关论文
共 50 条
  • [31] Contribution of Metabolic Parameters and Pericolic Fat Stranding on Preoperative 18F-FDG PET/CT in Predicting Post-operative Histopathology and Outcome in Colorectal Cancer
    Soyluoglu, Selin
    Gunay, Busra Ozdemir
    NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2023, 57 (05) : 223 - 234
  • [32] The Volume-metabolic Combined Parameters from 18F-FDG PET/CT May Help Predict the Outcomes of Cervical Carcinoma
    Sun, Yanqin
    Lu, Peiou
    Yu, Lijuan
    ACADEMIC RADIOLOGY, 2016, 23 (05) : 605 - 610
  • [33] Predictive value of clinical and 18F-FDG-PET/CT derived imaging parameters in patients undergoing neoadjuvant chemoradiation for esophageal squamous cell carcinoma
    Marr, Lisa
    Haller, Bernhard
    Pyka, Thomas
    Peeken, Jan C.
    Jesinghaus, Moritz
    Scheidhauer, Klemens
    Friess, Helmut
    Combs, Stephanie E.
    Muench, Stefan
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [34] Prognostic value of 18F-FDG PET-CT metabolic index for nasopharyngeal carcinoma
    Xie, Peng
    Yue, Jin-Bo
    Zhao, Han-xi
    Sun, Xin-Dong
    Kong, Li
    Fu, Zheng
    Yu, Jin-Ming
    JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2010, 136 (06) : 883 - 889
  • [35] Prognostic Value of 18F-FDG PET/CT in Patients with Malignant Pleural Mesothelioma
    Lee, S. T.
    Ghanem, M.
    Herbertson, R. A.
    Berlangieri, S. U.
    Byrne, A. J.
    Tabone, K.
    Mitchell, P.
    Knight, S. R.
    Feigen, M.
    Scott, A. M.
    MOLECULAR IMAGING AND BIOLOGY, 2009, 11 (06) : 473 - 479
  • [36] Predictive value of 18F-FDG PET/CT in restaging patients affected by ovarian carcinoma: a multicentre study
    Federico Caobelli
    Pierpaolo Alongi
    Laura Evangelista
    Maria Picchio
    Giorgio Saladini
    Marco Rensi
    Onelio Geatti
    Angelo Castello
    Iashar Laghai
    Cristina E. Popescu
    Carlotta Dolci
    Cinzia Crivellaro
    Silvia Seghezzi
    Margarita Kirienko
    Vincenzo De Biasi
    Fabrizio Cocciolillo
    Natale Quartuccio
    European Journal of Nuclear Medicine and Molecular Imaging, 2016, 43 : 404 - 413
  • [37] Prognostic Value of Metabolic Parameters of 18F-FDG PET/CT and Apparent Diffusion Coefficient of MRI in Hepatocellular Carcinoma
    Hong, Chae Moon
    Ahn, Byeong-Cheol
    Jang, Yun-Jin
    Jeong, Shin Young
    Lee, Sang-Woo
    Lee, Jaetae
    CLINICAL NUCLEAR MEDICINE, 2017, 42 (02) : 95 - 99
  • [38] Predictive value of 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity in the prognosis of gastric cancer
    Wang, Jianlin
    Yu, Xiaopeng
    Shi, Aiqi
    Xie, Long
    Huang, Liqun
    Su, Yingrui
    Zha, Jinshun
    Liu, Jiangyan
    JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY, 2023, 149 (16) : 14535 - 14547
  • [39] The Role of the Metabolic Parameters of 18F-FDG PET/CT in Patients With Locally Advanced Cervical Cancer
    Wang, Dunhuang
    Liu, Xiaoliang
    Wang, Weiping
    Huo, Li
    Pan, Qingqing
    Ren, Xue
    Zhang, Fuquan
    Hu, Ke
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [40] Prognostic value of metabolic parameters on baseline 18F-FDG PET/CT in small cell lung cancer
    Araz, Mine
    Soydal, Cigdem
    Ozkan, Elgin
    Sen, Elif
    Nak, Demet
    Kucuk, Ozlem N.
    Gonullu, Ugur
    Kir, K. Metin
    QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2022, 66 (01) : 61 - 66