Skip to main content

Advertisement

Log in

The impact of reliable prebolus T 1 measurements or a fixed T 1 value in the assessment of glioma patients with dynamic contrast enhancing MRI

  • Diagnostic Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Introduction

Accurate quantification of hemodynamic parameters using dynamic contrast enhanced (DCE) MRI requires a measurement of tissue T 1 prior to contrast injection (T 1). We evaluate (i) T 1 estimation using the variable flip angle (VFA) and the saturation recovery (SR) techniques and (ii) investigate if accurate estimation of DCE parameters outperform a time-saving approach with a predefined T 1 value when differentiating high- from low-grade gliomas.

Methods

The accuracy and precision of T 1 measurements, acquired by VFA and SR, were investigated by computer simulations and in glioma patients using an equivalence test (p > 0.05 showing significant difference). The permeability measure, K trans, cerebral blood flow (CBF), and - volume, V p, were calculated in 42 glioma patients, using fixed T 1 of 1500 ms or an individual T 1 measurement, using SR. The areas under the receiver operating characteristic curves (AUCs) were used as measures for accuracy to differentiate tumor grade.

Results

The T 1 values obtained by VFA showed larger variation compared to those obtained using SR both in the digital phantom and the human data (p > 0.05). Although a fixed T 1 introduced a bias into the DCE calculation, this had only minor impact on the accuracy differentiating high-grade from low-grade gliomas, (AUCfix = 0.906 and AUCind = 0.884 for K trans; AUCfix = 0.863 and AUCind = 0.856 for V p; p for AUC comparison > 0.05).

Conclusion

T 1 measurements by VFA were less precise, and the SR method is preferable, when accurate parameter estimation is required. Semiquantitative DCE values, based on predefined T 1 values, were sufficient to perform tumor grading in our study.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Jain RK, di Tomaso E, Duda DG, Loeffler JS, Sorensen AG, Batchelor TT (2007) Angiogenesis in brain tumours. Nat Rev Neurosci 8:610–622

    Article  CAS  PubMed  Google Scholar 

  2. Horsman MR, Siemann DW (2006) Pathophysiologic effects of vascular-targeting agents and the implications for combination with conventional therapies. Cancer Res 66:11520–11539

    Article  CAS  PubMed  Google Scholar 

  3. Dale BM, Jesberger JA, Lewin JS, Hillenbrand CM, Duerk JL (2003) Determining and optimizing the precision of quantitative measurements of perfusion from dynamic contrast enhanced MRI. J Magn Reson Imaging 18:575–584

    Article  PubMed  Google Scholar 

  4. Heye T, Davenport MS, Horvath JJ, Feuerlein S, Breault SR, Bashir MR, Merkle EM, Boll DT (2013) Reproducibility of dynamic contrast-enhanced MR imaging. Part I. Perfusion characteristics in the female pelvis by using multiple computer-aided diagnosis perfusion analysis solutions. Radiology 266:801–811

    Article  PubMed  Google Scholar 

  5. Huang W, Li X, Chen Y, Li X, Chang MC, Oborski MJ, Malyarenko DI, Muzi M, Jajamovich GH, Fedorov A, Tudorica A, Gupta SN, Laymon CM, Marro KI, Dyvorne HA, Miller JV, Barbodiak DP, Chenevert TL, Yankeelov TE, Mountz JM, Kinahan PE, Kikinis R, Taouli B, Fennessy F, Kalpathy-Cramer J (2014) Variations of dynamic contrast-enhanced magnetic resonance imaging in evaluation of breast cancer therapy response: a multicenter data analysis challenge. Transl Oncol 7:153–166

    Article  PubMed Central  PubMed  Google Scholar 

  6. Walker-Samuel S, Parker CC, Leach MO, Collins DJ (2007) Reproducibility of reference tissue quantification of dynamic contrast-enhanced data: comparison with a fixed vascular input function. Phys Med Biol 52:75–89

    Article  CAS  PubMed  Google Scholar 

  7. Haacke EM, Filleti CL, Gattu R, Ciulla C, Al-Bashir A, Suryanarayanan K, Li M, Latif Z, DelProposto Z, Sehgal V, Li T, Torquato V, Kanaparti R, Jiang J, Neelavalli J (2007) New algorithm for quantifying vascular changes in dynamic contrast-enhanced MRI independent of absolute T1 values. Magn Reson Med 58:463–472

    Article  PubMed  Google Scholar 

  8. Yuan J, Chow SK, Yeung DK, Ahuja AT, King AD (2012) Quantitative evaluation of dual-flip-angle T1 mapping on DCE-MRI kinetic parameter estimation in head and neck. Quant Imaging Med Surg 2:245–253

    PubMed Central  PubMed  Google Scholar 

  9. Larsson C, Kleppesto M, Grothe I, Vardal J, Bjornerud A (2015) T1 in high-grade glioma and the influence of different measurement strategies on parameter estimations in DCE-MRI. J Magn Reson Imaging. doi:10.1002/jmri.24772

  10. Guo JY, Reddick WE, Rosen MA, Song HK (2009) Dynamic contrast-enhanced magnetic resonance imaging parameters independent of baseline T-10 values. Magn Reson Imaging 27:1208–1215

    Article  PubMed Central  PubMed  Google Scholar 

  11. Li J, Yu YM, Zhang YB, Bao SL, Wu CX, Wang XY, Li J, Zhang XP, Hu JN (2009) A clinically feasible method to estimate pharmacokinetic parameters in breast cancer. Med Phys 36:3786–3794

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Kaldoudi E, Williams SCR (1993) Relaxation time measurements in NMR imaging. Part I: longitudinal relaxation time. Concepts Magn Reson 5:217–242

    Article  CAS  Google Scholar 

  13. Mikkelsen IK, Peters DA, Tietze A (2012) DCE-PWI 3D T1-measurement as function of time or flip angle. ISMRM, Melbourne, Australien

    Google Scholar 

  14. Studler U, White LM, Andreisek G, Luu S, Cheng HL, Sussman MS (2010) Impact of motion on T1 mapping acquired with inversion recovery fast spin echo and rapid spoiled gradient recalled-echo pulse sequences for delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) in volunteers. J Magn Reson Imaging 32:394–398

    Article  PubMed  Google Scholar 

  15. Larsson HB, Courivaud F, Rostrup E, Hansen AE (2009) Measurement of brain perfusion, blood volume, and blood–brain barrier permeability, using dynamic contrast-enhanced T(1)-weighted MRI at 3 tesla. Magn Reson Med 62:1270–1281

    Article  PubMed  Google Scholar 

  16. Sourbron S, Ingrisch M, Siefert A, Reiser M, Herrmann K (2009) Quantification of cerebral blood flow, cerebral blood volume, and blood–brain-barrier leakage with DCE-MRI. Magn Reson Med 62:205–217

    Article  PubMed  Google Scholar 

  17. Wansapura JP, Holland SK, Dunn RS, Ball WS Jr (1999) NMR relaxation times in the human brain at 3.0 tesla. J Magn Reson Imaging 9:531–538

    Article  CAS  PubMed  Google Scholar 

  18. DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845

    Article  CAS  PubMed  Google Scholar 

  19. Draganski B, Ashburner J, Hutton C, Kherif F, Frackowiak RS, Helms G, Weiskopf N (2011) Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ). Neuroimage 55:1423–1434

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Treier R, Steingoetter A, Fried M, Schwizer W, Boesiger P (2007) Optimized and combined T1 and B1 mapping technique for fast and accurate T1 quantification in contrast-enhanced abdominal MRI. Magn Reson Med 57:568–576

    Article  PubMed  Google Scholar 

  21. Di Giovanni P, Azlan CA, Ahearn TS, Semple SI, Gilbert FJ, Redpath TW (2010) The accuracy of pharmacokinetic parameter measurement in DCE-MRI of the breast at 3 T. Phys Med Biol 55(1):121–132. doi:10.1088/0031-9155/55/1/008

    Article  PubMed  Google Scholar 

  22. Sung K, Daniel BL, Hargreaves BA (2013) Transmit B1+ field inhomogeneity and T1 estimation errors in breast DCE-MRI at 3 tesla. J Magn Reson Imaging 38:454–459

    Article  PubMed Central  PubMed  Google Scholar 

  23. Wang J, Qiu M, Kim H, Constable RT (2006) T1 measurements incorporating flip angle calibration and correction in vivo. J Magn Reson 182:283–292

    Article  CAS  PubMed  Google Scholar 

  24. Yun TJ, Park CK, Kim TM, Lee SH, Kim JH, Sohn CH, Park SH, Kim IH, Choi SH (2014) Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging. Radiology. doi:10.1148/radiol.14132632

  25. Ashton E (2010) Quantitative MR in multi-center clinical trials. J Magn Reson Imaging 31:279–288

    Article  PubMed  Google Scholar 

  26. Sorensen AG, Batchelor TT, Zhang WT, Chen PJ, Yeo P, Wang M, Jennings D, Wen PY, Lahdenranta J, Ancukiewicz M, di Tomaso E, Duda DG, Jain RK (2009) A “vascular normalization index” as potential mechanistic biomarker to predict survival after a single dose of cediranib in recurrent glioblastoma patients. Cancer Res 69:5296–5300

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  27. Batchelor TT, Sorensen AG, di Tomaso E, Zhang WT, Duda DG, Cohen KS, Kozak KR, Cahill DP, Chen PJ, Zhu M, Ancukiewicz M, Mrugala MM, Plotkin S, Drappatz J, Louis DN, Ivy P, Scadden DT, Benner T, Loeffler JS, Wen PY, Jain RK (2007) AZD2171, a pan-VEGF receptor tyrosine kinase inhibitor, normalizes tumor vasculature and alleviates edema in glioblastoma patients. Cancer Cell 11:83–95

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Schabel MC, Parker DL (2008) Uncertainty and bias in contrast concentration measurements using spoiled gradient echo pulse sequences. Phys Med Biol 53:2345–2373

    Article  PubMed Central  PubMed  Google Scholar 

  29. Mouridsen K, Friston K, Hjort N, Gyldensted L, Østergaard L, Kiebel S (2006) Bayesian estimation of cerebral perfusion using a physiological model of microvasculature. Neuroimage 33:570–579

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by the Danish Ministry of Science, Technology and Innovation’s University Investment Grant (MINDLab).

Ethical Standards and Patient Consent

We declare that all human studies have been approved by the Danish National Committee on Health Research Ethics (Journal Number M-20100027) and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. We declare that all patients gave informed consent prior to inclusion in this study.

Conflict of interest

We declare that we have no conflict of interest.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anna Tietze.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 67 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tietze, A., Mouridsen, K. & Mikkelsen, I.K. The impact of reliable prebolus T 1 measurements or a fixed T 1 value in the assessment of glioma patients with dynamic contrast enhancing MRI. Neuroradiology 57, 561–572 (2015). https://doi.org/10.1007/s00234-015-1502-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00234-015-1502-z

Keywords

Navigation