Skip to main content
SpringerLink
Log in

Impact of Temporal Heterogeneity of Acute Hypoxia on the Radiation Response of Experimental Tumors

  • Chapter
  • First Online:
Oxygen Transport to Tissue XL

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1072))

  • 2320 Accesses

Abstract

Tumor hypoxia is a major factor inducing resistance to radiotherapy. Spatial limitation in oxygen (O2) diffusion usually leads to chronic hypoxia, whereas temporary shut-down of perfusion or fluctuations in red blood cell flux can cause acute hypoxia. Since the role of temporal heterogeneity of pO2 in acute hypoxia during radiotherapy remains unclear, this study focuses on analyzing the influence of temporal heterogeneity of tumor hypoxia upon radiotherapy by modeling the temporal variance of acute hypoxia. The computational simulation was conducted on digital 2D tumor phantoms. The O2 diffusion and consumption within the tumor tissues were calculated using the reaction-diffusion equation. A total of nine experimental tumor lines (FaDu, GL, C3H, RIF, SCCVII, KHT, MEF, MTG, HT29) were modeled according to known pO2 distributions. Each tumor line was first simulated 36 times with various temporal heterogeneities (dynamic hypoxia) and once again without temporal heterogeneity (static hypoxia). Temporal pO2 fluctuations were modeled according to known red blood cell (RBC) fluxes. All tumor phantoms were irradiated with 30 fractions of 2 Gy. Cell survival was calculated as a function of pO2 and radiation dose via linear quadratic model. The simulation results indicate that the temporal heterogeneity varies with different tumor types, and tumor line HT29 shows the most significant impact of temporal heterogeneity upon the treatment effect. The ratio between the surviving fractions without and with temporal variance ranges from 1.44 to 6.28. Given the same mean pO2, the fraction of killed tumor cells in dynamic hypoxia is higher than in static hypoxia. A temporal heterogeneity index (THI) denoting normalized average pO2 temporal variance is proposed. The results show that for similar mean tumor pO2, a strong inverse correlation between THI and the surviving fraction is observed for each tumor line. THI is highly proportional to the fraction of acute hypoxia and to the RBC flux. The proposed THI corresponds well to the fraction of acute hypoxia.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Vaupel P, Kallinowski F, Okunieff P (1989) Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res 49:6449–6465

    CAS  Google Scholar 

  2. Vaupel P, Harrison L (2004) Tumor hypoxia: causative factors, compensatory mechanisms, and cellular response. Oncologist 9:4–9

    Article  Google Scholar 

  3. Moeller BJ, Richardson RA, Dewhirst MW (2007) Hypoxia and radiotherapy: opportunities for improved outcomes in cancer treatment. Cancer Metastasis Rev 26:241–248

    Article  CAS  Google Scholar 

  4. Vaupel P (2004) The role of hypoxia-induced factors in tumor progression. Oncologist 9:10–17

    Article  CAS  Google Scholar 

  5. Bayer C, Shi K, Astner ST et al (2011) Acute versus chronic hypoxia: why a simplified classification is simply not enough. Int J Radiat Oncol Biol Phys 80:965–968

    Article  Google Scholar 

  6. Toma-Daşu I, Daşu A, Karlsson M (2004) The relationship between temporal variation of hypoxia, polarographic measurements and predictions of tumour response to radiation. Phys Med Biol 49:4463

    Article  Google Scholar 

  7. Bruley DF (1993) Modeling oxygen transport: development of methods and current state. Adv Exp Med Biol 345:33–42

    Article  Google Scholar 

  8. Toma-Daşu I, Uhrdin J, Antonovic L et al (2012) Dose prescription and treatment planning based on FMISO-PET hypoxia. Acta Oncol 51:222–230

    Article  Google Scholar 

  9. Toma-Daşu I, Daşu A (2013) Modelling tumour oxygenation, reoxygenation and implications on treatment outcome. Comput Math Methods Med 2013:1–9

    Article  Google Scholar 

  10. Yang Y, Xing L (2005) Towards biologically conformal radiation therapy (BCRT): selective IMRT dose escalation under the guidance of spatial biology distribution. Med Phys 32:1473–1484

    Article  Google Scholar 

  11. Thorwarth D, Eschmann S-M, Paulsen F et al (2007) Hypoxia dose painting by numbers: a planning study. Int J Radiat Oncol Biol Phys 68:291–300

    Article  Google Scholar 

  12. Petit SF, Dekker AL, Seigneuric R et al (2009) Intra-voxel heterogeneity influences the dose prescription for dose-painting with radiotherapy: a modelling study. Phys Med Biol 54:2179–2196

    Article  Google Scholar 

  13. Adam MF, Dorie MJ, Brown JM (1999) Oxygen tension measurements of tumors growing in mice. Int J Radiat Oncol Biol Phys 45:171–180

    Article  CAS  Google Scholar 

  14. Wang Q, Vaupel P, Ziegler SI et al (2015) Exploring the quantitative relationship between metabolism and enzymatic phenotype by physiological modeling of glucose metabolism and lactate oxidation in solid tumors. Phys Med Biol 60:2547–2571

    Article  CAS  Google Scholar 

  15. Mönnich D, Troost EG, Kaanders JH et al (2011) Modelling and simulation of [18F] fluoromisonidazole dynamics based on histology-derived microvessel maps. Phys Med Biol 56:2045–2057

    Article  Google Scholar 

  16. Daşu A, Toma-Daşu I, Karlsson M (2003) Theoretical simulation of tumour oxygenation and results from acute and chronic hypoxia. Phys Med Biol 48:2829

    Article  Google Scholar 

  17. Tannock IF (1972) Oxygen diffusion and the distribution of cellular radiosensitivity in tumours. Br J Radiol 45:515–524

    Article  CAS  Google Scholar 

  18. Goldman D (2008) Theoretical models of microvascular oxygen transport to tissue. Microcirculation 15:795–811

    Article  Google Scholar 

  19. Wouters BG, Brown JM (1997) Cells at intermediate oxygen levels can be more important than the “hypoxic fraction” in determining tumor response to fractionated radiotherapy. Radiat Res 147:541–550

    Article  CAS  Google Scholar 

  20. Maftei C, Bayer C, Shi K et al (2011) Quantitative assessment of hypoxia subtypes in microcirculatory supply units of malignant tumors using (immuno-) fluorescence techniques. Strahlenther Onkol 187:260–266

    Article  Google Scholar 

  21. Maftei C, Bayer C, Shi K, et al. (2012) Intra- and intertumor heterogeneities in total, chronic, and acute hypoxia in xenografted squamous cell carcinomas. Strahlenther Onkol 188:606–615

    Article  Google Scholar 

  22. Michiels C, Tellier C, Feron O (2016) Cycling hypoxia: a key feature of the tumor microenvironment. Biochim Biophys Acta 1866:76–86

    CAS  PubMed  Google Scholar 

  23. Kato Y, Yashiro M, Fuyuhiro Y et al (2011) Effects of acute and chronic hypoxia on the radiosensitivity of gastric and esophageal cancer cells. Anticancer Res 31:3369–3375

    CAS  PubMed  Google Scholar 

  24. Bayer C, Vaupel P (2012) Acute versus chronic hypoxia in tumors. Strahlenther Onkol 188:616–627

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Informatics, TU München, Munich, Germany

    Lina Xu & Bjoern H. Menze

  2. Institute of Medical Engineering, TU München, Munich, Germany

    Lina Xu & Bjoern H. Menze

  3. Department of Radiation Oncology and Radiotherapy, TU München, Munich, Germany

    Peter Vaupel

  4. Department of Nuclear Medicine, Klinikum rechts der Isar, TU München, Munich, Germany

    Kuangyu Shi

Authors
  1. Lina Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter Vaupel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bjoern H. Menze
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kuangyu Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lina Xu .

Editor information

Editors and Affiliations

  1. Julius Bernstein Institute of Physiology, Martin Luther University, Halle-Wittenberg, Halle/Saale, Germany

    Oliver Thews

  2. Department of Physiology & Biophysics, Case Western Reserve University, School of Medicine, Cleveland, OH, USA

    Joseph C. LaManna

  3. Microvascular Measurements, St. Lorenzen, Italy

    David K. Harrison

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Xu, L., Vaupel, P., Menze, B.H., Shi, K. (2018). Impact of Temporal Heterogeneity of Acute Hypoxia on the Radiation Response of Experimental Tumors. In: Thews, O., LaManna, J., Harrison, D. (eds) Oxygen Transport to Tissue XL. Advances in Experimental Medicine and Biology, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-319-91287-5_30

Download citation

Publish with us

Policies and ethics

Search

Navigation