Skip to main content
SpringerLink
Log in

Évolution des critères d’évaluation de la réponse tumorale: apport de l’imagerie fonctionnelle

Changes in the assessment criteria for tumour response: the contribution of functional imaging

  • Original
  • Published:
Oncologie

Résumé

L’évaluation de réponse tumorale est fondée sur les modifications du nombre et de la taille de « cibles » mesurables. Les règles de l’Organisation Mondiale de la Santé (OMS), qui définissaient les méthodes de mesure et les critères de réponse ne sont plus adaptées à l’évolution technique de l’imagerie. Les nouveaux critères édités par le Response Evaluation Criteria in Solid Tumors (RECIST) Group restent fondés sur la mesure de la taille des cibles. Ce seul critère de taille doit être discuté à la lumière des nouvelles possibilités de l’imagerie dite fonctionnelle (échographie-Doppler avec produit de contraste, scanner ou IRM dynamiques, imagerie de diffusion, spectroscopie par résonance magnétique, imagerie ciblée, TEP scanner) susceptible de fournir des informations sur la vascularisation, le métabolisme ou la viabilité des tumeurs, paramètres dont les modifications traduisent la réponse au traitement avant la diminution de volume.

Abstract

Tumour response is based on changes in the number and size of measurable tumour “targets”. The World Health Organization (WHO) guidelines defining the method of measurement of solid tumours and response criteria are no longer adapted to technical progress in imaging. New guidelines, updated by the Response Evaluation Criteria in Solid Tumors (RECIST) Group, remain based on measurement of the size of the target lesion. The use of this single criterion of size needs to be discussed in the light of new functional imaging technologies (contrast-enhanced ultrasonography, dynamic CT or MRI, diffusion-weighted MR imaging, magnetic resonance spectroscopy, targeted imaging, PET scanner) able to provide information on tumour vascularization, composition, or viability, modifications of which reflect response to treatment before a reduction in tumour volume can be detected.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Références

  1. Al Saffar NM, Troy H, Ramirez DM, et al. (2006) Noninvasive magnetic resonance spectroscopic pharmacodynamic markers of the choline kinase inhibitor MN58b in human carcinoma models. Cancer Res 66: 427–34

    Article  Google Scholar 

  2. Barrett T, Kobayashi H, Brechbiel M, et al. (2006) Macromolecular MRI contrast agents for imaging tumor angiogenesis. Eur J Radiol 60: 353–66

    Article  PubMed  Google Scholar 

  3. Bourguet P, Blanc-Vincent MP, Boneu A, et al. (2003) Standards, Options et Recommandations 2002 pour l’utilisation de la tomographie par émission de positons au 18F-FDG [TEP-FDG] en cancérologie (rapport intégral). Bull Cancer 90: S1–S109

    PubMed  Google Scholar 

  4. Carde P, Koscielny S, Franklin J, et al. (2002) Early response to chemotherapy: a surrogate for final outcome of Hodgkin’s disease patients that should influence initial treatment length and intensity? Ann Oncol 13(Suppl 1): 86–91

    PubMed  Google Scholar 

  5. Choi H (2005) Critical issues in response evaluation on computed tomography: lessons from the gastrointestinal stromal tumor model. Curr Oncol Rep 7: 307–11

    Article  PubMed  Google Scholar 

  6. Collingridge DR, Carroll VA, Glaser M, et al. (2002) The development of [(124)I] iodinated-VG76e: a novel tracer for imaging vascular endothelial growth factor in vivo using positron emission tomography. Cancer Res 62: 5912–19

    PubMed  CAS  Google Scholar 

  7. Collins VP, Loeffler RK, Tivey H (1956) Observations on growth rates of human tumors. Am J Roentgenol Radium Ther Nucl Med 76: 988–1000

    PubMed  CAS  Google Scholar 

  8. Curran SD, Muellner AU, Schwartz LH (2006) Imaging response assessment in oncology. Cancer Imaging 6: S126–S130

    PubMed  CAS  Google Scholar 

  9. Dawson P (2006) Functional imaging in CT. Eur J Radiol 60: 331–40

    Article  PubMed  Google Scholar 

  10. Duffaud F, Therasse P (2000) New guidelines to evaluate the response to treatment in solid tumors. Bull Cancer 87: 881–86

    PubMed  CAS  Google Scholar 

  11. El Khoury C, Servois V, Thibault F, et al. (2005) MR quantification of the washout changes in breast tumors under preoperative chemotherapy: feasibility and preliminary results. Am J Roentgenol 184: 1499–1504

    Google Scholar 

  12. Harvey C, Dooher A, Morgan J, et al. (1999) Imaging of tumor therapy responses by dynamic CT. Eur J Radiol 30: 221–26

    Article  PubMed  CAS  Google Scholar 

  13. Hori K, Saito S, Sato Y, et al. (2003) Differential relationship between changes in tumor size and microcirculatory functions induced by therapy with an antivascular drug and with cytotoxic drugs. Implications for the evaluation of therapeutic efficacy of AC7700 (AVE-8062). Eur J Cancer 39: 1957–1966

    Article  PubMed  CAS  Google Scholar 

  14. Kostakoglu L, Coleman M, Leonard JP, et al. (2002) PET predicts prognosis after 1 cycle of chemotherapy in aggressive lymphoma and Hodgkin’s disease. J Nucl Med 43: 1018–27

    PubMed  Google Scholar 

  15. Larson SM, Schwartz LH (2006) 18F-FDG PET as a candidate for “qualified biomarker”: functional assessment of treatment response in oncology. J Nucl Med 47: 901–03

    PubMed  CAS  Google Scholar 

  16. Leach MO, Brindle KM, Evelhoch JL, et al. (2005) The assessment of antiangiogenic and antivascular therapies in early-stage clinical trials using magnetic resonance imaging: issues and recommendations. Br J Cancer 92: 1599–1610

    Article  PubMed  CAS  Google Scholar 

  17. Magnon C, Galaup A, Rouffiac V, et al. (2007) Dynamic assessment of antiangiogenic therapy by monitoring both tumoral vascularization and tissue degeneration. Gene Ther 14: 190: 108–17

    Google Scholar 

  18. Michaelis LC, Ratain MJ (2006) Measuring response in a post-RECIST world: from black and white to shades of grey. Nat Rev Cancer 6: 409–14

    Article  PubMed  CAS  Google Scholar 

  19. Negrier S (2000) New guidelines for evaluating the therapeutic response of solid tumors: try them! Bull Cancer 87: 869–70

    PubMed  CAS  Google Scholar 

  20. Ollivier L (2000) International Criteria for Tumor Assessment. Cancer Imaging 1: 32–4

    Google Scholar 

  21. Ott K, Fink U, Becker K, et al. (2003) Prediction of response to preoperative chemotherapy in gastric carcinoma by metabolic imaging: results of a prospective trial. J Clin Oncol 24: 4604–10

    Article  Google Scholar 

  22. Provenzale JM (2007) Imaging of angiogenesis: clinical techniques and novel imaging methods. Am J Roentgenol 188: 11–23

    Article  Google Scholar 

  23. Reddick WE, Wang S, Xiong X, et al. (2001) Dynamic magnetic resonance imaging of regional contrast access as an additional prognostic factor in pediatric osteosarcoma. Cancer 9: 2230–37

    Article  Google Scholar 

  24. Schelling M, Avril N, Nahrig J, et al. (2000) Positron emission tomography using [18 F] fluorodeoxyglucose for monitoring primary chemotherapy in breast cancer. J Clin Oncol 18: 1689–95

    PubMed  CAS  Google Scholar 

  25. Spaepen K, Stroobants S, Dupont P, et al. (2002) Early restaging positron emission tomography with [18]F-fluorodesoxyglucose predicts outcome in patients with aggressive non-Hodgkin’s lymphoma. Ann Oncol 13: 1356–63

    Article  PubMed  CAS  Google Scholar 

  26. Therasse P, Arbuck SG, Eisenhauer EA, et al. (2000) New guidelines to evaluate 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 2000 92: 205–16

    Article  PubMed  CAS  Google Scholar 

  27. Thoeny HC, De Keyzer F, Vandecaveye V, et al. (2005) Effect of vascular targeting agent in rat tumor model: dynamic contrast-enhanced versus diffusion-weighted MR imaging. Radiology 237: 492–99

    Article  PubMed  Google Scholar 

  28. Vanel D, Bonvalot S, Guinebretiere JM, et al. (2004) MR imaging in the evaluation of isolated limb perfusion: a prospective study of 18 cases. Skeletal Radiol 33: 150–56

    Article  PubMed  Google Scholar 

  29. Verstraete KL, Van der Woude HJ, Hogendoorn PC, et al. (1996) Dynamic contrast-enhanced MR imaging of musculoskeletal tumors: basic principles and clinical applications. J Magn Reson Imaging 6: 311–21

    Article  PubMed  CAS  Google Scholar 

  30. Weber WA, Ott K, Becker K, et al. (2001) Prediction of response to preoperative chemotherapy in adenocarcinomas of the oesophagogastric junction by metabolic imaging. J Clin Oncol 19: 3058–65

    PubMed  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Département d’Imagerie, Institut Curie, 26, rue d’Ulm, F-75005, Paris, France

    L. Ollivier

  2. Département d’Imagerie, Institut Gustave-Roussy, rue Camille-Desmoulins, F-94805, Villejuif, France

    J. Leclère

Authors
  1. L. Ollivier
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Leclère
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to L. Ollivier.

About this article

Cite this article

Ollivier, L., Leclère, J. Évolution des critères d’évaluation de la réponse tumorale: apport de l’imagerie fonctionnelle. Oncologie 9, 294–298 (2007). https://doi.org/10.1007/s10269-007-0618-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10269-007-0618-0

Mots clés

Keywords

Search

Navigation