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Der Radiologe

, Volume 56, Issue 2, pp 113–123 | Cite as

Quantitative Perfusionsbildgebung in der Magnetresonanztomographie

  • F. G. Zöllner
  • T. Gaa
  • F. Zimmer
  • M. M. Ong
  • P. Riffel
  • D. Hausmann
  • S. O. Schoenberg
  • M. Weis
Leitthema

Zusammenfassung

Klinisches/methodisches Problem

Die Magnetresonanztomographie (MRT) zeichnet sich durch einen überlegenen Gewebekontrast aus, während sie nichtinvasiv und frei von ionisierender Strahlung ist. Sie bietet Zugang zu Gewebe- und Organfunktion. Eine dieser funktionellen bildgebenden Verfahren ist die Perfusionsbildgebung. Mit dieser Technik können u. a. Gewebeperfusion und Kapillarpermeabilität aus dynamischen Bilddaten bestimmt werden.

Radiologische Standardverfahren

Perfusionsbildgebung mithilfe der MRT kann durch 2 Ansätze, nämlich „arterial spin labeling“ (ASL) und dynamische kontrastverstärkte (DCE-)MRT durchgeführt werden. Während die erste Methode magnetisch markierte Wasserprotonen im arteriellen Blut als endogenen Tracer verwendet, erfolgt bei der DCE-MRT eine Injektion eines Kontrastmittels, üblicherweise Gadolinium (Gd) als Tracer für die Berechnung hämodynamischer Parameter.

Leistungsfähigkeit

Aus Studien werden das Potenzial und die Möglichkeiten der MRT-Perfusionsbildgebung deutlich, sei es in Bezug auf die Diagnostik oder aber auch zunehmend im Bereich des Therapiemonitorings.

Bewertung

Nutzung und Anwendung der MRT-Perfusionsbildgebung beschränken sich jedoch auf spezialisierte Zentren wie Universitätskliniken. Eine breite Anwendung der Technik ist bisher leider nicht erfolgt.

Empfehlung für die Praxis

Die MRT-Perfusionsbildgebung ist ein wertvolles Tool, das im Rahmen europäischer und internationaler Standardisierungsbemühungen für die Praxis zukünftig einsetzbar werden sollte.

Schlüsselwörter

Quantitative Perfusionsbildgebung Gewebeperfusion Kapillarpermeabilität DCE-MRT „Arterial spin labeling“ 

Quantitative perfusion imaging in magnetic resonance imaging

Abstract

Clinical/methodical issue

Magnetic resonance imaging (MRI) is recognized for its superior tissue contrast while being non-invasive and free of ionizing radiation. Due to the development of new scanner hardware and fast imaging techniques during the last decades, access to tissue and organ functions became possible. One of these functional imaging techniques is perfusion imaging with which tissue perfusion and capillary permeability can be determined from dynamic imaging data.

Standard radiological methods

Perfusion imaging by MRI can be performed by two approaches, arterial spin labeling (ASL) and dynamic contrast-enhanced (DCE) MRI. While the first method uses magnetically labelled water protons in arterial blood as an endogenous tracer, the latter involves the injection of a contrast agent, usually gadolinium (Gd), as a tracer for calculating hemodynamic parameters.

Performance

Studies have demonstrated the potential of perfusion MRI for diagnostics and also for therapy monitoring.

Achievements

The utilization and application of perfusion MRI are still restricted to specialized centers, such as university hospitals. A broad application of the technique has not yet been implemented.

Practical recommendations

The MRI perfusion technique is a valuable tool that might come broadly available after implementation of standards on European and international levels. Such efforts are being promoted by the respective professional bodies.

Keywords

Tissue perfusion Quantitative perfusion imaging Capillary permeability Dynamic contrast enhanced magnetic resonance imaging Arterial spin labeling 

Notes

Danksagung

Diese Arbeit wurde in Teilen unterstützt durch den Forschungscampus M2OLIE der mit Mitteln des Bundesministeriums für Bildung und Forschung (BMBF) innerhalb der Förderinitiative „Forschungscampus: öffentlich-private Partnerschaft für Innovationen“ unter dem Förderkennzeichen 13GW0092D gefördert.

Einhaltung ethischer Richtlinien

Interessenkonflikt

F.G. Zöllner, T. Gaa, F. Zimmer, M.M. Ong, P. Riffel, D. Hausmann, S.O. Schoenberg und M. Weis geben an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine Studien an Menschen oder Tieren.

Literatur

  1. 1.
    Ai T, Morelli JN, Hu X et al (2012) A historical overview of magnetic resonance imaging, focusing on technological innovations. Invest Radiol 47:725–741CrossRefPubMedGoogle Scholar
  2. 2.
    Alsop DC, Detre JA, Golay X et al (2015) Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the european consortium for aSL in dementia. Magn Reson Med 73:102–116PubMedCentralCrossRefPubMedGoogle Scholar
  3. 3.
    Bjornerud A, Sorensen AG, Mouridsen K et al (2011) T1- and T2*-dominant extravasation correction in DSC-MRI: part I – theoretical considerations and implications for assessment of tumor hemodynamic properties. J Cereb Blood Flow Metab 31:2041–2053PubMedCentralCrossRefPubMedGoogle Scholar
  4. 4.
    Bolar DS, Levin DL, Hopkins SR et al (2006) Quantification of regional pulmonary blood flow using ASL-FAIRER. Magn Reson Med 55:1308–1317CrossRefPubMedGoogle Scholar
  5. 5.
    Buxton RB, Frank LR, Wong EC et al (1998) A general kinetic model for quantitative perfusion imaging with arterial spin labeling. Magn Reson Med 40:383–396CrossRefPubMedGoogle Scholar
  6. 6.
    Calamante F (2013) Arterial input function in perfusion MRI: a comprehensive review. Prog Nucl Magn Reson Spectrosc 74:1–32CrossRefPubMedGoogle Scholar
  7. 7.
    Cutajar M, Thomas DL, Hales PW et al (2014) Comparison of ASL and DCE MRI for the non-invasive measurement of renal blood flow: quantification and reproducibility. Eur Radiol 24:1300–1308CrossRefPubMedGoogle Scholar
  8. 8.
    Dai W, Garcia D, Bazelaire CD et al (2008) Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magn Reson Med 60:1488–1497PubMedCentralCrossRefPubMedGoogle Scholar
  9. 9.
    Davenport MS, Heye T, Dale BM et al (2013) Inter-and intra-rater reproducibility of quantitative dynamic contrast enhanced MRI using TWIST perfusion data in a uterine fibroid model. J Magn Reson Imaging 38:329–335CrossRefPubMedGoogle Scholar
  10. 10.
    Davids M, Zollner FG, Ruttorf M et al (2014) Fully-automated quality assurance in multi-center studies using MRI phantom measurements. Magn Reson Imaging 32:771–780CrossRefPubMedGoogle Scholar
  11. 11.
    Detre JA, Leigh JS, Williams DS et al (1992) Perfusion imaging. Magn Reson Med 23:37–45CrossRefPubMedGoogle Scholar
  12. 12.
    Detre JA, Rao H, Wang DJJ et al (2012) Applications of arterial spin labeled MRI in the brain. J Magn Reson Imaging 35:1026–1037PubMedCentralCrossRefPubMedGoogle Scholar
  13. 13.
    Dujardin M, Sourbron S, Luypaert R et al (2005) Quantification of renal perfusion and function on a voxel-by-voxel basis: a feasibility study. Magn Reson Med 54:841–849CrossRefPubMedGoogle Scholar
  14. 14.
    Emblem KE, Due-Tonnessen P, Hald JK et al (2014) Machine learning in preoperative glioma MRI: survival associations by perfusion-based support vector machine outperforms traditional MRI. J Magn Reson Imaging 40:47–54CrossRefPubMedGoogle Scholar
  15. 15.
    European Society Of R (2015) ESR position paper on imaging Biobanks. Insights Imaging 6:403–410CrossRefGoogle Scholar
  16. 16.
    Futterer JJ, Heijmink SW, Scheenen TW et al (2006) Prostate cancer localization with dynamic contrast-enhanced MR imaging and proton MR spectroscopic imaging. Radiology 241:449–458CrossRefPubMedGoogle Scholar
  17. 17.
    Günther M, Bock M, Schad LR (2001) Arterial spin labeling in combination with a look-locker sampling strategy: Inflow turbo-sampling EPI-FAIR (ITS-FAIR). Magn Reson Med 46:974–984CrossRefPubMedGoogle Scholar
  18. 18.
    Gunther M, Oshio K, Feinberg DA (2005) Single-shot 3D imaging techniques improve arterial spin labeling perfusion measurements. Magn Reson Med 54:491–498CrossRefPubMedGoogle Scholar
  19. 19.
    Hahn OM, Yang C, Medved M et al (2008) Dynamic contrast-enhanced magnetic resonance imaging pharmacodynamic biomarker study of sorafenib in metastatic renal carcinoma. J Clin Oncol 26:4572–4578PubMedCentralCrossRefPubMedGoogle Scholar
  20. 20.
    Heusch P, Wittsack HJ, Blondin D, Ljimani A, Nguyen-Quang M, Martirosian P, Zenginli H, Bilk P, Kröpil P, Heusner TA, Antoch G, Lanzman RS (2014) Functional evaluation of transplanted kidneys using arterial spin labeling MRI. J Magn Reson Imaging 40(1):84–89Google Scholar
  21. 21.
    Heye T, Davenport MS, Horvath JJ et al (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 266:801–811CrossRefPubMedGoogle Scholar
  22. 22.
    Ishimori Y, Kimura H, Matsuda T et al (2003) Dynamic contrast-enhanced T(1) measuring MRI using variable flip angle SPGR. Nihon Hoshasen Gijutsu Gakkai Zasshi 59:1535–1541PubMedGoogle Scholar
  23. 23.
    Kim SG (1995) Quantification of relative cerebral blood flow change by flow-sensitive alternating inversion recovery (FAIR) technique: application to functional mapping. Magn Reson Med 34:293–301CrossRefPubMedGoogle Scholar
  24. 24.
    Kneeshaw PJ, Lowry M, Manton D et al (2006) Differentiation of benign from malignant breast disease associated with screening detected microcalcifications using dynamic contrast enhanced magnetic resonance imaging. Breast 15:29–38CrossRefPubMedGoogle Scholar
  25. 25.
    Kwong KK, Belliveau JW, Chesler DA et al (1992) Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. Proc Natl Acad Sci U S A 89:5675–5679PubMedCentralCrossRefPubMedGoogle Scholar
  26. 26.
    Lanzman RS, Robson PM, Sun MR et al (2012) Arterial spin-labeling MR imaging of renal masses: correlation with histopathologic findings. Radiology 265:799–808PubMedCentralCrossRefPubMedGoogle Scholar
  27. 27.
    Lietzmann F, Zöllner FG, Attenberger UI et al (2012) DCE-MRI of the human kidney using BLADE: a feasibility study in healthy volunteers. J Magn Reson Imaging 35:868–874CrossRefPubMedGoogle Scholar
  28. 28.
    Luh WM, Wong EC, Bandettini PA et al (1999) QUIPSS II with thin-slice TI1 periodic saturation: a method for improving accuracy of quantitative perfusion imaging using pulsed arterial spin labeling. Magn Reson Med 41:1246–1254CrossRefPubMedGoogle Scholar
  29. 29.
    Macintosh BJ, Filippini N, Chappell MA et al (2010) Assessment of arterial arrival times derived from multiple inversion time pulsed arterial spin labeling MRI. Magn Reson Med 63:641–647CrossRefPubMedGoogle Scholar
  30. 30.
    Martirosian P, Boss A, Schraml C et al (2010) Magnetic resonance perfusion imaging without contrast media. Eur J Nucl Med Mol Imaging 37(Suppl 1):52–64CrossRefGoogle Scholar
  31. 31.
    Martirosian P, Klose U, Mader I et al (2004) FAIR true-FISP perfusion imaging of the kidneys. Magn Reson Med 51:353–361CrossRefPubMedGoogle Scholar
  32. 32.
    Mcdonald JS, Mcdonald RJ, Comin J et al (2013) Frequency of acute kidney injury following intravenous contrast medium administration: a systematic review and meta-analysis. Radiology 267:119–128CrossRefPubMedGoogle Scholar
  33. 33.
    Meier P, Zierler KL (1954) On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol 6:731–744PubMedGoogle Scholar
  34. 34.
    Mendichovszky IA, Cutajar M, Gordon I (2009) Reproducibility of the aortic input function (AIF) derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the kidneys in a volunteer study. Eur J Radiol 71:576–581CrossRefPubMedGoogle Scholar
  35. 35.
    Merrem AD, Zollner FG, Reich M et al (2013) A variational approach to image registration in dynamic contrast-enhanced MRI of the human kidney. Magn Reson Imaging 31:771–777CrossRefPubMedGoogle Scholar
  36. 36.
    Michaely HJ, Thomsen HS, Reiser MF et al (2007) Nephrogenic systemic fibrosis (NSF) – implications for radiology. Radiologe 47:785–793CrossRefPubMedGoogle Scholar
  37. 37.
    Norman JT, Stidwill R, Singer M et al (2003) Angiotensin II blockade augments renal cortical microvascular pO2 indicating a novel, potentially renoprotective action. Nephron Physiol 94:p39–46CrossRefPubMedGoogle Scholar
  38. 38.
    Notohamiprodjo M, Sourbron S, Staehler M et al (2010) Measuring perfusion and permeability in renal cell carcinoma with dynamic contrast-enhanced MRI: a pilot study. J Magn Reson Imaging 31:490–501CrossRefPubMedGoogle Scholar
  39. 39.
    O’Connor JP, Jackson A, Asselin MC et al (2008) Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives. Lancet Oncol 9:766–776CrossRefPubMedGoogle Scholar
  40. 40.
    O’Connor JP, Tofts PS, Miles KA et al (2011) Dynamic contrast-enhanced imaging techniques: CT and MRI. Br J Radiol 84(Spec No 2):112–120CrossRefGoogle Scholar
  41. 41.
    Ohno Y, Koyama H, Nogami M et al (2008) Dynamic perfusion MRI: capability for evaluation of disease severity and progression of pulmonary arterial hypertension in patients with connective tissue disease. J Magn Reson Imaging 28:887–899CrossRefPubMedGoogle Scholar
  42. 42.
    Ostergaard L (2005) Principles of cerebral perfusion imaging by bolus tracking. J Magn Reson Imaging 22:710–717CrossRefPubMedGoogle Scholar
  43. 43.
    Pallwein-Prettner L, Flory D, Rotter CR et al (2011) Assessment and characterisation of common renal masses with CT and MRI. Insights Imaging 2:543–556PubMedCentralCrossRefPubMedGoogle Scholar
  44. 44.
    Park S-H, Wang DJJ, Duong TQ (2013) Balanced steady state free precession for arterial spin labeling MRI: Initial experience for blood flow mapping in human brain, retina, and kidney. Magn Reson Imaging 31:1044–1050PubMedCentralCrossRefPubMedGoogle Scholar
  45. 45.
    Petersen ET, Mouridsen K, Golay X (2010) The QUaSaR reproducibility study, part II: results from a multi-center arterial spin labeling test – retest study. Neuroimage 49:104–113PubMedCentralCrossRefPubMedGoogle Scholar
  46. 46.
    Quantitative Imaging Biomarkers Alliance (2015) Quantitative Imaging Biomarkers Alliance. (In:RSNA) http://www.rsna.org/QIBA.aspx. Zugegriffen: 01. Juli 2015Google Scholar
  47. 47.
    Rischke HC, Schafer AO, Nestle U et al (2012) Detection of local recurrent prostate cancer after radical prostatectomy in terms of salvage radiotherapy using dynamic contrast enhanced-MRI without endorectal coil. Radiat Oncol 7:185PubMedCentralCrossRefPubMedGoogle Scholar
  48. 48.
    Roberts DA, Rizi R, Lenkinski RE et al (1996) Magnetic resonance imaging of the brain: Blood partition coefficient for water: Application to spin-tagging measurement of perfusion. J Magn Reson Imaging 6:363–366CrossRefPubMedGoogle Scholar
  49. 49.
    Rosen MA, Schnall MD (2007) Dynamic contrast-enhanced magnetic resonance imaging for assessing tumor vascularity and vascular effects of targeted therapies in renal cell carcinoma. Clin Cancer Res 13:770s–776sCrossRefPubMedGoogle Scholar
  50. 50.
    Rossi C, Boss A, Artunc F et al (2009) Comprehensive assessment of renal function and vessel morphology in potential living kidney donors: an MRI-based approach. Invest Radiol 44:705–711CrossRefPubMedGoogle Scholar
  51. 51.
    Runge VM, Aoki S, Bradley WG Jr et al (2015) Magnetic resonance imaging and computed Tomography of the brain-50 years of innovation, with a focus on the future. Invest Radiol 50:551–556CrossRefPubMedGoogle Scholar
  52. 52.
    Sertdemir M, Schoenberg SO, Sourbron S et al (2013) Interscanner comparison of dynamic contrast-enhanced MRI in prostate cancer: 1.5 versus 3 T MRI. Invest Radiol 48:92–97CrossRefPubMedGoogle Scholar
  53. 53.
    Sorensen AG (2008) Perfusion MR imaging: moving forward. Radiology 249:416–417CrossRefPubMedGoogle Scholar
  54. 54.
    Sourbron S (2010) Technical aspects of MR perfusion. Eur J Radiol 76:304–313CrossRefPubMedGoogle Scholar
  55. 55.
    Sourbron SP, Buckley DL (2013) Classic models for dynamic contrast-enhanced MRI. NMR Biomed 26:1004–1027CrossRefPubMedGoogle Scholar
  56. 56.
    Sourbron SP, Buckley DL (2012) Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability. Phys Med Biol 57:R1–33CrossRefPubMedGoogle Scholar
  57. 57.
    Van Meurs KP, Newman KD, Anderson KD et al (1990) Effect of extracorporeal membrane oxygenation on survival of infants with congenital diaphragmatic hernia. J Pediatr 117:954–960CrossRefPubMedGoogle Scholar
  58. 58.
    Weidner M, Zöllner FG, Hagelstein C et al (2014) High temporal versus high spatial resolution in MR quantitative pulmonary perfusion imaging of two-year old children after congenital diaphragmatic hernia repair. Eur Radiol 24:2427–2434CrossRefPubMedGoogle Scholar
  59. 59.
    Wentland AL, Sadowski EA, Djamali A et al (2009) Quantitative MR measures of intrarenal perfusion in the assessment of transplanted kidneys: initial experience. Acad Radiol 16:1077–1085PubMedCentralCrossRefPubMedGoogle Scholar
  60. 60.
    Williams DS, Detre JA, Leigh JS et al (1992) Magnetic resonance imaging of perfusion using spin inversion of arterial water. Proc Natl Acad Sci USA 89:212–216PubMedCentralCrossRefPubMedGoogle Scholar
  61. 61.
    Wong EC, Buxton RB, Frank LR (1997) Implementation of quantitative perfusion imaging techniques for functional brain mapping using pulsed arterial spin labeling. NMR Biomed 10:237–249CrossRefPubMedGoogle Scholar
  62. 62.
    Wong EC, Buxton RB, Frank LR (1998) Quantitative imaging of perfusion using a single subtraction (QUIPSS and QUIPSS II). Magn Reson Med 39:702–708CrossRefPubMedGoogle Scholar
  63. 63.
    Zimmer F, Zöllner FG, Hoeger S et al (2013) Quantitative renal perfusion measurements in a rat model of acute kidney injury at 3 T: testing inter- and intramethodical significance of ASL and DCE-MRI. PLoS One 8:e53849PubMedCentralCrossRefPubMedGoogle Scholar
  64. 64.
    Zöllner FG, Weisser G, Reich M et al (2013) UMMPerfusion: an open source software tool towards quantitative MRI perfusion analysis in clinical routine. J Digit Imaging 26:344–352PubMedCentralCrossRefPubMedGoogle Scholar
  65. 65.
    Zöllner FG, Zahn K, Schaible T et al (2012) Quantitative pulmonary perfusion imaging at 3.0 T of 2-year-old children after congenital diaphragmatic hernia repair: initial results. Eur Radiol 22:2743–2749CrossRefPubMedGoogle Scholar
  66. 66.
    Zun Z, Wong EC, Nayak KS (2009) Assessment of myocardial blood flow (MBF) in humans using arterial spin labeling (ASL): Feasibility and noise analysis. Mag Reson Med 62:975–983CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • F. G. Zöllner
    • 1
  • T. Gaa
    • 1
  • F. Zimmer
    • 1
  • M. M. Ong
    • 2
  • P. Riffel
    • 2
  • D. Hausmann
    • 2
  • S. O. Schoenberg
    • 2
  • M. Weis
    • 2
  1. 1.Computerunterstützte Klinische Medizin, Medizinische Fakultät MannheimUniversität HeidelbergMannheimDeutschland
  2. 2.Institut für Klinische Radiologie und Nuklearmedizin, Universitätsmedizin Mannheim, Medizinische Fakultät MannheimUniversität HeidelbergMannheimDeutschland

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