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European Radiology

, Volume 29, Issue 5, pp 2669–2676 | Cite as

Wavelet-based reconstruction of dynamic susceptibility MR-perfusion: a new method to visualize hypervascular brain tumors

  • Thomas HuberEmail author
  • Lukas Rotkopf
  • Benedikt Wiestler
  • Wolfgang G. Kunz
  • Stefanie Bette
  • Jens Gempt
  • Christine Preibisch
  • Jens Ricke
  • Claus Zimmer
  • Jan S. Kirschke
  • Wieland H. Sommer
  • Kolja M. Thierfelder
Neuro
  • 81 Downloads

Abstract

Objectives

Parameter maps based on wavelet-transform post-processing of dynamic perfusion data offer an innovative way of visualizing blood vessels in a fully automated, user-independent way. The aims of this study were (i) a proof of concept regarding wavelet-based analysis of dynamic susceptibility contrast (DSC) MRI data and (ii) to demonstrate advantages of wavelet-based measures compared to standard cerebral blood volume (CBV) maps in patients with the initial diagnosis of glioblastoma (GBM).

Methods

Consecutive 3-T DSC MRI datasets of 46 subjects with GBM (mean age 63.0 ± 13.1 years, 28 m) were retrospectively included in this feasibility study. Vessel-specific wavelet magnetic resonance perfusion (wavelet-MRP) maps were calculated using the wavelet transform (Paul wavelet, order 1) of each voxel time course. Five different aspects of image quality and tumor delineation were each qualitatively rated on a 5-point Likert scale. Quantitative analysis included image contrast and contrast-to-noise ratio.

Results

Vessel-specific wavelet-MRP maps could be calculated within a mean time of 2:27 min. Wavelet-MRP achieved higher scores compared to CBV in all qualitative ratings: tumor depiction (4.02 vs. 2.33), contrast enhancement (3.93 vs. 2.23), central necrosis (3.86 vs. 2.40), morphologic correlation (3.87 vs. 2.24), and overall impression (4.00 vs. 2.41); all p < .001. Quantitative image analysis showed a better image contrast and higher contrast-to-noise ratios for wavelet-MRP compared to conventional perfusion maps (all p < .001).

Conclusions

wavelet-MRP is a fast and fully automated post-processing technique that yields reproducible perfusion maps with a clearer vascular depiction of GBM compared to standard CBV maps.

Key Points

Wavelet-MRP offers high-contrast perfusion maps with a clear delineation of focal perfusion alterations.

• Both image contrast and visual image quality were beneficial for wavelet-MRP compared to standard perfusion maps like CBV.

• Wavelet-MRP can be automatically calculated from existing dynamic susceptibility contrast (DSC) perfusion data.

Keywords

Brain neoplasms Cerebral blood volume Glioblastoma Perfusion imaging Wavelet analysis 

Abbreviations

AIF

Arterial input function

CBF

Cerebral blood flow

CBV

Cerebral blood volume

CNR

Contrast-to-noise ratio

DCE

Dynamic contrast enhanced

DSC

Dynamic susceptibility contrast

FLAIR

Fluid-attenuated inversion recovery

GBM

Glioblastoma

ICC

Intra-class correlation

MPRAGE

Magnetization prepared rapid gradient echo

MTT

Mean transit time

PRESTO

Principles of echo-shifting with a train of observations sequence

PWI

Perfusion-weighted imaging

TTP

Time to peak

wavelet-MRP

Wavelet magnetic resonance perfusion

Notes

Funding

The authors state that this work has not received any specific funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dr. Thomas Huber.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: TH and LR consultancy for Smart Reporting GmbH (Munich, Germany); BW speaker honoraria from Bayer; TH, JG and SB consultancy for Brainlab AG (Feldkirchen, Germany); JSK research support by DFG, ERC, Acandis—travel support by Kaneka Europe—speaker honoraria by Philips; WHS founder and CEO of Smart Reporting GmbH (Munich, Germany) and founder of Planerio GmbH (Munich, Germany); JR research grant Sirtex Medical Ltd. and research grant Bayer AG; CZ has served on scientific advisory boards for Philips and Bayer Schering; serves as co-editor on the Advisory Board of Clinical Neuroradiology; has received speaker honoraria from Bayer-Schering and Philips and has received research support and investigator fees for clinical studies from Biogen Idec, Quintiles, M.S.D. Sharp & Dome, Boehringer Ingelheim, Inventive Health Clinical U.K. Ltd., Advance Cor, Brainsgate, Pfizer, BayerSchering, Novartis, Roche, Servier, Penumbra, W.C.T. GmbH, Syngis, S.S.S. International Clinical Research, P.P.D. Germany GmbH, Worldwide Clinical Trials Ltd., Phenox, Covidien, Actelion, Medivation, Medtronic, Harrison Clinical Research, Concentric, Penumbra, Pharmtrace, Reverse Medical Corp., Premier Research Germany Ltd., Surpass Medical Ltd., and GlaxoSmithKline. All listed conflicts of interest are unrelated to the present study.

Statistics and biometry

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Experimental

• Performed at one institution

Supplementary material

330_2018_5892_MOESM1_ESM.docx (23 kb)
Table S1 (DOCX 23 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Thomas Huber
    • 1
    Email author
  • Lukas Rotkopf
    • 1
    • 2
  • Benedikt Wiestler
    • 2
  • Wolfgang G. Kunz
    • 1
  • Stefanie Bette
    • 2
  • Jens Gempt
    • 3
  • Christine Preibisch
    • 2
  • Jens Ricke
    • 1
  • Claus Zimmer
    • 2
  • Jan S. Kirschke
    • 2
  • Wieland H. Sommer
    • 1
  • Kolja M. Thierfelder
    • 1
    • 4
  1. 1.Department of RadiologyUniversity Hospital, LMU MunichMunichGermany
  2. 2.Department of Neuroradiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  3. 3.Department of Neurosurgery, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  4. 4.Institute of Diagnostic and Interventional RadiologyUniversity Medicine RostockRostockGermany

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