Skip to main content

Onkologische Bildgebung zur Beurteilung des Therapieansprechens

  • Chapter
Weiterbildung Radiologie
  • 1591 Accesses

Zusammenfassung

Der vorliegende Beitrag erläutert auf der Basis der aktuellen Literatur verschiedene radiologische Methoden zur Beurteilung des Therapieansprechens. Eindimensionale Messungen der Tumorgröße entsprechend der Response Evaluation Criteria in Solid Tumors (RECIST) sind am weitesten verbreitet. Die dort definierten Größenänderungen entscheiden über die Kategorien Complete Response (CR), Partial Response (PR), Stable Disease (SD) und Progressive Disease (PD), die als prägnante Bewertung des Therapieerfolgs eine hohe Akzeptanz besitzen. Probleme der größenbasierten Therapiebewertung ergeben sich verstärkt bei der zielgerichteten Therapie („targeted therapy“) sowie durch Phänomene wie die Pseudoprogression. Verschiedene Formen der funktionellen Bildgebung sowie der gegenwärtige Stellenwert dieser Methoden unter Berücksichtigung onkologischer Anforderungen werden vorgestellt.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 17.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

Literatur

  1. Padhani AR, Miles KA (2010) Multipa- rametric imaging of tumor response to therapy. Radiology 256:348–364

    Article  PubMed  Google Scholar 

  2. Yaghmai V, Miller FH, Rezai P et al (2011) Response to treatment series: part 2, tumor response assessment - using new and conventional criteria. AJRAm J Roentgenol 197:18–27

    Article  Google Scholar 

  3. World Health Organization (1979) WHO Handbookfor Reporting Results of CancerTreatment. Genf

    Google Scholar 

  4. Therasse P, Arbuck SG, Eisenhauer EA et al (2000) New guidelines to eva- luate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 92:205–216

    Article  CAS  PubMed  Google Scholar 

  5. Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228–247

    Article  CAS  PubMed  Google Scholar 

  6. Stattaus J, Hahn S, GaulerTet al (2009) Osteoblastic response as a healing reaction to chemotherapy mimicking progressive disease in pa- tients with small cell lung cancer. Eur Radiol 19:193–200

    Article  PubMed  Google Scholar 

  7. Hopper KD, Kasales CJ, Van SlykeMA et al (1996) Analysis of interobserver and intraobserver variability in CT tumor measurements. AJR Am J Roentgenol 167:851–854

    Article  CAS  PubMed  Google Scholar 

  8. Oxnard GR, Zhao B, Sima CS et al (2011) Variability of lung tumor measurements on repeat computed to- mographyscanstaken within 15 mi- nutes. J Clin Oncol 29:3114–3119

    Article  PubMed Central  PubMed  Google Scholar 

  9. Kalkmann J, Ladd SC, de Greift A et al (2009) Suitability of semi-automated tumor response assessment of liver metastases using a dedicated Software package. Rofo 182:581–588

    Article  Google Scholar 

  10. Cademartiri F, Luccichenti G, Maffei E et al (2008) Imaging for oncologic staging andfollow-up: reviewof current methods and novel approaches. Acta Biomed 79:85–91

    PubMed  Google Scholar 

  11. Fabel M, Bolte H (2008) Automatisierte Verfahren zur Volumetrie von Metastasen: Ermittlung der Tumorlast. Radiologe 48:857–862

    Article  CAS  PubMed  Google Scholar 

  12. LlovetJM, Di Bisceglie AM, BruixJ et al (2008) Design and endpoints of clinical trials in hepatocellular Carcinoma. J Natl Cancer Inst 100:698–711

    Google Scholar 

  13. Choi H, Charnsangavej C, Faria SC et al (2007) Correlation of computed tomography and positron emission tomography in patients with meta- static gastrointestinal stromal tumor treated at a single Institution with imatinib mesylate: proposal of new computed tomography response criteria. J Clin Oncol 25:1753–1759

    Article  PubMed  Google Scholar 

  14. BauerS, Hartmann JT, de WitM et al (2005) Resection of residual disease in patients with metastatic gastrointestinal stromal tumors responding to treatment with imatinib. Int J Cancer 117:316–325

    Google Scholar 

  15. Nathan PD, Vinayan A, Stott D et al (2010) CT response assessment com- bining reduction in both size and ar- terial phase density correlates with time to progression in metastatic renal cancer patients treated with tar- geted therapies. Cancer Biol Ther 9:15–19

    Article  PubMed  Google Scholar 

  16. Smith AD, Shah SN, Rini Bl et al (2010) Morphology, Attenuation, Size, and Structure (MASS) criteria: as- sessing response and predicting clinical outcome in metastatic renal cell carcinoma on antiangiogenic targeted therapy. AJR Am J Roentgenol 194:1470–1478

    Article  PubMed  Google Scholar 

  17. Van Persijn van Meerten EL, Gelder- blom H, Bloem JL (2010) RECIST revised: implicationsforthe radiologist. A review article on the modified RECIST guideline. Eur Radiol 20:1456–1467

    Article  Google Scholar 

  18. Willett CG, BoucherY, DiTomaso E et al (2004) Direct evidence that the VEGF-specific antibody bevacizumab has antivascular effects in human rectal cancer. Nat Med 10:145–147

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Kambadakone AR, Sahani DV (2009) Body perfusion CT: technique, clinical applications, and advances. Radiol Clin North Am 47:161–178

    Article  PubMed  Google Scholar 

  20. Hutchings M, Barrington SF (2009) PET/CT for therapy response assessment in lymphoma. J Nud Med 50(Suppl 1 ):21 S–30S

    Google Scholar 

  21. Cheson BD, Pfistner B, Juweid ME et al (2007) Revised response criteria for malignant lymphoma. J Clin Oncol 25:579–586

    Article  PubMed  Google Scholar 

  22. Wahl RL, Jacene H, Kasamon Y et al (2009) From RECIST to PERCIST: evol- ving considerations for PET response criteria in solid tumors. J Nucl Med 50(Suppl 1 ):122S–150S

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. O'connor JP, Jackson A, Parker GJ et al (2012) Dynamic contrast-enhan- ced MRI in clinical trials of antivascular therapies. Nat RevClin Oncol 9:167–177

    Article  Google Scholar 

  24. Marinovich ML, Sardanelli F, Ciatto S et al (2012) Early prediction of pa- thologic response to neoadjuvant therapy in breast cancer: systematic review of the accuracy of MRI. Breast 21:669–677

    Article  CAS  PubMed  Google Scholar 

  25. Gossmann A, Helbich TH, Kuriyama N et al (2002) Dynamic contrast-en- hanced magnetic resonance imaging as a Surrogate markerof tumor response to anti-angiogenic therapy in a xenograft model of glioblastoma multiforme. J Magn Reson Imaging 15:233–240

    Article  PubMed  Google Scholar 

  26. Hamstra DA, Rehemtulla A, Ross BD (2007) Diffusion magnetic resonance imaging: a biomarker for treatment response in oncology. J Clin Oncol 25:4104–4109

    Article  PubMed  Google Scholar 

  27. Kamel IR, Bluemke DA, Ramsey D et al (2003) Roleofdiffusion-weighted imaging in estimating tumor necro- sis after chemoembolization of hepatocellular carcinoma. AJR Am J Roentgenol 181:708–710

    Article  PubMed  Google Scholar 

  28. Kamel IR, Bluemke DA, Eng J et al (2006) The roleoffunctional MR imaging in the assessment of tumor response after chemoembolization in patients with hepatocellular carcinoma. J Vase Interv Radiol 17:505–512

    Article  Google Scholar 

  29. Theilmann RJ, Borders RJrouardTP et al (2004) Changes in water mobili- ty measured by diffusion MRI predict response of metastatic breast cancer to chemotherapy. Neoplasia 6:831–837

    Article  PubMed Central  PubMed  Google Scholar 

  30. Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Stattaus, J. (2015). Onkologische Bildgebung zur Beurteilung des Therapieansprechens. In: Delorme, S., Reimer, P., Reith, W., Schäfer-Prokop, C., Schüller-Weidekamm, C., Uhl, M. (eds) Weiterbildung Radiologie. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46785-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-46785-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46784-8

  • Online ISBN: 978-3-662-46785-5

  • eBook Packages: Medicine (German Language)

Publish with us

Policies and ethics