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Perfusion imaging of brain gliomas using arterial spin labeling: correlation with histopathological vascular density in MRI-guided biopsies

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An Erratum to this article was published on 24 February 2017

Abstract

Introduction

This study was designed to determine if cerebral blood flow (CBF) derived from arterial spin labeling (ASL) perfusion imaging could be used to quantitatively evaluate the microvascular density (MVD) of brain gliomas on a “point-to-point” basis by matching CBF areas and surgical biopsy sites as accurate as possible.

Methods

The study enrolled 47 patients with treatment-naive brain gliomas who underwent preoperative ASL, 3D T1-weighted imaging with gadolinium contrast enhancement (3D T1C+), and T2 fluid acquisition of inversion recovery (T2FLAIR) sequences before stereotactic surgery. We histologically quantified MVD from CD34-stained sections of stereotactic biopsies and co-registered biopsy locations with localized CBF measurements. The correlation between CBF and MVD was determined using Spearman’s correlation coefficient. P ≤ .05 was considered statistically significant.

Results

Of the 47 patients enrolled in the study, 6 were excluded from the analysis because of brain shift or poor co-registration and localization of the biopsy site during surgery. Finally, 84 biopsies from 41 subjects were included in the analysis. CBF showed a statistically significant positive correlation with MVD (ρ = 0.567; P = .029).

Conclusion

ASL can be a useful noninvasive perfusion MR method for quantitative evaluation of the MVD of brain gliomas.

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References

  1. Provenzale JM, Mukundan S, Barboriak DP (2006) Diffusion weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response. Radiology 239:632–649

    Article  PubMed  Google Scholar 

  2. Detre JA, Rao H, Wang DJ, Chen YF, Wang Z (2012) Applications of arterial spin labeled MRI in the brain. J Magn Reson Imaging 35:1026–1037

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kuo PH, Kanal E, Abu-Alfa AK, Cowper SE (2007) Gadolinium-based MR contrast agents and nephrogenic systemic fibrosis. Radiology 242:647–649

    Article  PubMed  Google Scholar 

  4. Warmuth C, Gunther M, Zimmer C (2003) Quantification of blood flow in brain tumors: comparison of arterial spin labeling and dynamic susceptibility-weighted contrast-enhanced MR imaging. Radiology 228:523–532

    Article  PubMed  Google Scholar 

  5. Hirai T, Kitajima M, Nakamura H et al (2011) Quantitative blood flow measurements in gliomas using arterial spin-labeling at 3T: intermodality agreement and inter- and intraobserver reproducibility study. AJNR Am J Neuroradiol 32:2073–2079

    Article  CAS  PubMed  Google Scholar 

  6. Nael K, Meshksar A, Liebeskind DS, Coull BM, Krupinski EA, Villablanca JP (2013) Quantitative analysis of hypoperfusion in acute stroke: arterial spin labeling versus dynamic susceptibility contrast. Stroke 44:3090–3096

    Article  PubMed  PubMed Central  Google Scholar 

  7. Chen J, Zhao B, Bu C, Xie G (2014) Relationship between the hemodynamic changes on multi-Td pulsed arterial spin labeling images and the degrees of cerebral artery stenosis. Magn Reson Imaging 32:1277–1283

    Article  PubMed  Google Scholar 

  8. Mak HK, Qian W, Ng KS et al (2014) Combination of MRI hippocampal volumetry and arterial spin labeling MR perfusion at 3-Tesla improves the efficacy in discriminating Alzheimer’s disease from cognitively normal elderly adults. J Alzheimers Dis 41:749–758

    PubMed  Google Scholar 

  9. Dangouloff-Ros V, Deroulers C, Foissac F et al (2016) Arterial spin labeling to predict brain tumor grading in children: correlations between histopathologic vascular density and perfusion MR imaging. Radiology 281:1–14

    Article  Google Scholar 

  10. Noguchi T, Yoshiura T, Hiwatashi A et al (2008) Perfusion imaging of brain tumors using arterial spin-labeling: correlation with histopathologic vascular density. AJNR Am J Neuroradiol 29:688–693

    Article  CAS  PubMed  Google Scholar 

  11. Kimura H, Takeuchi H, Koshimoto Y et al (2006) Perfusion imaging of meningioma by using continuous arterial spin-labeling: comparison with dynamic susceptibility-weighted contrast-enhanced MR images and histopathologic features. AJNR Am J Neuroradiol 27:85–93

    CAS  PubMed  Google Scholar 

  12. Yamamoto T, Takeuchi H, Kinoshita K, Kosaka N, Kimura H (2014) Assessment of tumor blood flow and its correlation with histopathologic features in skull base meningiomas and schwannomas by using pseudo-continuous arterial spin labeling images. Eur J Radiol 83:817–823

    Article  PubMed  Google Scholar 

  13. Gerlinger M, Rowan AJ, Horswell S et al (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883–892

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Goh V, Halligan S, Daley F, Wellsted DM, Guenther T, Bartram CI (2008) Colorectal tumor vascularity: quantitative assessment with multidetector CT—do tumor perfusion measurements reflect angiogenesis? Radiology 249:510–517

    Article  PubMed  Google Scholar 

  15. Dighe S, Blake H, Jeyadevan N et al (2013) Perfusion CT vascular parameters do not correlate with immunohistochemically derived microvessel density count in colorectal tumors. Radiology 268:400–410

    Article  PubMed  Google Scholar 

  16. Weidner N (1995) Current pathologic methods for measuring intratumoral microvessel density within breast carcinoma and other solid tumors. Breast Cancer Res Treat 36:169–180

    Article  CAS  PubMed  Google Scholar 

  17. Louis DN, Perry A, Reifenberger G et al (2016) The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol 6:803–820

    Article  Google Scholar 

  18. Ostrom QT, Bauchet L, Davis FG et al (2014) The epidemiology of glioma in adults: a “state of the science” review. Neuro-Oncology 16:896–913

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Folkman J (1989) What is evidence that tumors are angiogenesis dependent? J Natl Cancer Inst 82:4–6

    Article  Google Scholar 

  20. Sorensen AG, Emblem KE, Polaskova P et al (2012) Increased survival of glioblastoma patients who respond to antiangiogenic therapy with elevated blood perfusion. Cancer Res 72:402–407

    Article  CAS  PubMed  Google Scholar 

  21. Tolaney SM, Boucher Y, Duda DG et al (2015) Role of vascular density and normalization in response to neoadjuvant bevacizumab and chemotherapy in breast cancer patients. Proc Natl Acad Sci U S A 112:14325–14330

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Knopp EA, Cha S, Johnson G et al (1999) Glial neoplasms: dynamic contrast-enhanced T2*-weighted MR imaging. Radiology 211:791–798

    Article  CAS  PubMed  Google Scholar 

  23. Hu LS, Eschbacher JM, Dueck AC et al (2012) Correlations between perfusion MR imaging cerebral blood volume, microvessel quantification, and clinical outcome using stereotactic analysis in recurrent high-grade glioma. AJNR Am J Neuroradiol 33:69–76

    Article  CAS  PubMed  Google Scholar 

  24. Ellingson B, Zaw T, Cloughesy TF et al (2012) Comparison between intensity normalization techniques for dynamic susceptibility contrast (DSC)-MRI estimates of cerebral blood volume (CBV) in human gliomas. J Magn Reson Imaging 25:1472–1477

    Article  Google Scholar 

  25. Boxerman JL, Schmainda KM, Weisskoff RM (2006) Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not. AJNR Am J Neuroradiol 27:859–867

    CAS  PubMed  Google Scholar 

  26. Boxerman JL, Prah DE, Paulson ES, Machan JT, Bedekar D, Schmainda KM (2012) The role of preload and leakage correction in gadolinium-based cerebral blood volume estimation determined by comparison with MION as a criterion standard. AJNR Am J Neuroradiol 33:1081–1087

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Chen Y, Wang DJ, Detre JA (2011) Test-retest reliability of arterial spin labeling with common labeling strategies. J Magn Reson Imaging 33:940–949

    Article  PubMed  PubMed Central  Google Scholar 

  28. Golay X, Hendrikse J, Lim TC (2004) Perfusions imaging using arterial spin labeling. Top Magn Reson Imaging 15:10–27

    Article  PubMed  Google Scholar 

  29. Teeuwisse WM, Schmid S, Ghariq E, Veer IM, van Osch MJ (2014) Time-encoded pseudocontinuous arterial spin labeling: basic properties and timing strategies for human applications. Magn Reson Med 72:1712–1722

    Article  PubMed  Google Scholar 

  30. Weber MA, Zoubaa S, Schlieter M et al (2006) Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 66:1899–1906

    Article  CAS  PubMed  Google Scholar 

  31. Guo P, Imanishi Y, Cackowski FC et al (2005) Up-regulation of angiopoietin-2, matrix metalloprotease-2, membrane type 1 metalloprotease, and laminin 5 gamma 2 correlates with the invasiveness of human glioma. Am J Pathol 166:877–890

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sadeghi N, Salmon I, Decaestecker C et al (2015) Stereotactic comparison among cerebral blood volume, methionine uptake, and histopathology in brain glioma. AJNR Am J Neuroradiol 28:455–461

    Google Scholar 

  33. Jain R, Gutierrez J, Narang J et al (2011) In vivo correlation of tumor blood volume and permeability with histologic and molecular angiogenic markers in gliomas. AJNR Am J Neuroradiol 32:388–394

    Article  CAS  PubMed  Google Scholar 

  34. Price SJ, Green HA, Dean AF et al (2011) Correlation of MR relative cerebral blood volume measurements with cellular density and proliferation in high-grade gliomas: an image-guided biopsy study. AJNR Am J Neuroradiol 32:501–506

    Article  CAS  PubMed  Google Scholar 

  35. Christoforidis GA, Yang M, Abduljalil A et al (2012) “Tumoral pseudoblush” identified within gliomas at high-spatial-resolution ultrahigh-field-strength gradient-echo MR imaging corresponds to microvascularity at stereotactic biopsy. Radiology 264:210–217

    Article  PubMed  PubMed Central  Google Scholar 

  36. Zhang Y, Kapur P, Yuan Q et al (2016) Tumor vascularity in renal masses: correlation of arterial spin-labeled and dynamic contrast-enhanced magnetic resonance imaging assessments. Clin Genitourin Cancer 14:e25–e36

    Article  PubMed  Google Scholar 

  37. Schor-Bardach R, Alsop DC, Pedrosa I et al (2009) Does arterial spin-labeling MR imaging-measured tumor perfusion correlate with renal cell cancer response to antiangiogenic therapy in a mouse model? Radiology 251:731–742

    Article  PubMed  PubMed Central  Google Scholar 

  38. Alexiou GA, Zikou A, Tsiouris S et al (2014) Correlation of diffusion tensor dynamic susceptibility contrast MRI and (99m)Tc-tetrofosmin brain SPECT with tumour grade and Ki-67 immunohistochemistry in glioma. Clin Neurol Neurosurg 116:41–45

    Article  PubMed  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Radiology, Huashan Hospital Fudan University, Mid Urumqi Road, Shanghai, 200040, People’s Republic of China

    Di Ningning, Pang Haopeng, Ren Yan, Yao Zhenwei & Feng Xiaoyuan

  2. Shang Hai Gamma Knife Hospital, Shanghai, People’s Republic of China

    Dang Xuefei

  3. Department of Pharmacy, Binzhou Medical University Affiliated Hospital, Binzhou, People’s Republic of China

    Cheng Wenna

  4. Department of Neurosurgery, Huashan Hospital Fudan University, Shanghai, People’s Republic of China

    Wu Jingsong & Yao Chengjun

Authors
  1. Di Ningning
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  2. Pang Haopeng
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  3. Dang Xuefei
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  4. Cheng Wenna
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  5. Ren Yan
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  6. Wu Jingsong
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  7. Yao Chengjun
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  8. Yao Zhenwei
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  9. Feng Xiaoyuan
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Corresponding author

Correspondence to Feng Xiaoyuan.

Ethics declarations

We declare that all human studies have been approved by the Huashan Hospital Ethics Committee 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.

Additional information

DN and PH contributed equally to this study and are joint first authors.

An erratum to this article is available at http://dx.doi.org/10.1007/s00234-017-1785-3.

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Ningning, D., Haopeng, P., Xuefei, D. et al. Perfusion imaging of brain gliomas using arterial spin labeling: correlation with histopathological vascular density in MRI-guided biopsies. Neuroradiology 59, 51–59 (2017). https://doi.org/10.1007/s00234-016-1756-0

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  • DOI: https://doi.org/10.1007/s00234-016-1756-0

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