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To Explore a Representative Hypoxic Parameter to Predict the Treatment Response and Prognosis Obtained by [18F]FMISO-PET in Patients with Non-small Cell Lung Cancer

  • Li Li
  • Yuchun Wei
  • Yong Huang
  • Qingxi Yu
  • Wenju Liu
  • Shuqiang Zhao
  • Jinsong Zheng
  • Hong Lu
  • Jinming Yu
  • Shuanghu Yuan
Research Article
  • 62 Downloads

Abstract

Purpose

To explore a representative hypoxic parameter to predict the treatment response and prognosis for [18F]fluoromisonidazole ([18F]FMISO) positron emission tomography (PET)/X-ray computed tomography (CT) in patients with non-small cell lung cancer (NSCLC).

Procedures

Twenty-nine patients with NSCLC underwent FMISO-PET scans before chemoradiotherapy (CRT). The maximum standard uptake values (SUVmax) in the tumor, normal lung, aortic arch, and vertical ridge muscle were measured, and the tumor-to-lung (T/L) ratios, tumor-to-blood (T/B) ratios, ands tumor-to-muscle (T/M) ratios were calculated and analyzed. Fractional hypoxic volume (FHV) was expressed as percentage of hypoxic volume.

Results

SUVmax, T/L ratio, T/B ratio, and FHV were all significantly different between the responders and the non-responders (SUVmax, 2.07 ± 0.53 vs. 2.61 ± 0.69, P = 0.026; T/L ratio, 3.16 ± 0.85 vs. 4.09 ± 1.46, P = 0.047; T/B ratio, 1.27 ± 0.20 vs. 1.48 ± 0.32, P = 0.042; 38.92 ± 18.47 vs. 52.91 ± 11.29 %, P = 0.020). However, the T/M ratio was not significantly different between the two populations (1.46 ± 0.31 vs. 1.67 ± 0.33, P = 0.098). The correlation ratio between hypoxic parameters and treatment responses ranged from high to low as FHV (r = 0.412); SUVmax (r = 0.400); T/L ratio (r = 0.379), P < 0.05; and T/B ratio (r = 0.355), P = 0.059. According to the area under curve (AUC) to predict response, the hypoxic parameters were arranged as FHV (AUC = 0.748), SUVmax (AUC = 0.731), T/L ratio (AUC = 0.719), and T/B ratio (AUC = 0.705). Binary logistic regression analyses showed that FHV was the only independent predictor for treatment response with the P value of 0.038. In the progression-free survival (PFS) prediction, both FHV and SUVmax reached statistical significance by Kaplan–Meier plots (FHV, 46.99 %, P = 0.010; SUVmax, 1.99, P = 0.046) while only FHV was the independent prognostic factor in multivariate analysis by Cox proportional hazard model (P = 0.037).

Conclusion

FHV may be a representative hypoxic parameter to predict the CRT response and PFS in patients with NSCLC.

Key words

[18F]FMISO PET/CT Hypoxia Representative Hypoxic parameter Predict FHV Response Prognosis CRT Non-small cell lung cancer 

Notes

Funding Information

This study was partially funded by the Special Fund for Scientific Research in the Public Interest (201402011), the National Key Research and Development Plan(2016YFC0904700), the Natural Science Foundation of China (NSFC81172133, NSFC81372413), the Shandong Key Research and Development Plan(2017CXGC1209, 2017GSF18164), and the Outstanding Youth Natural Science Foundation of Shandong Province (JQ201423).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Our investigation of 29 patients was approved by the Shandong Cancer Hospital affiliated to Shandong University Ethical Committee and has, therefore, been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. All persons gave their informed consent prior to their inclusion in the study.

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Copyright information

© World Molecular Imaging Society 2018

Authors and Affiliations

  • Li Li
    • 1
    • 2
  • Yuchun Wei
    • 2
  • Yong Huang
    • 2
  • Qingxi Yu
    • 2
  • Wenju Liu
    • 3
  • Shuqiang Zhao
    • 2
  • Jinsong Zheng
    • 2
  • Hong Lu
    • 2
  • Jinming Yu
    • 2
  • Shuanghu Yuan
    • 2
    • 4
    • 5
  1. 1.School of Medicine and Life SciencesUniversity of Jinan-Shandong Academy of Medical SciencesJinanChina
  2. 2.Shandong Cancer Hospital and Institute-Shandong Cancer Hospital Affiliated to Shandong UniversityJinanChina
  3. 3.Department of Radiation OncologyLiaocheng People’s HospitalLiaochengChina
  4. 4.Shandong Academy of Medical SciencesJinanChina
  5. 5.Department of Radiation OncologyShandong Cancer Hospital and Institute-Shandong Cancer Hospital Affiliated to Shandong UniversityJinanChina

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