List of communications

Threshold values and means of rCBV, ADC, Cho/Cr and Cho/NAA as imaging biomarkers for glioma grade and metastasis diagnosis: calculation based on systematic review and meta-analysis of clinical trials

A. Ulyte1, J. Usinskiene1, A. Bjornerud2, J. Venius1, V.K. Katsaros3, R. Rynkeviciene1, S.
Letautiene1, D. Norkus1, K. Suziedelis1, S. Rocka1, A. Usinskas1, E. Aleknavicius1; 1Vilnius/LT,
2Oslo/NO, 3Athens/GR

To perform meta-analysis of relative cerebral blood volume (rCBV), normalized apparent diffusion coefficient
(nADC), and the spectroscopy metrics choline/creatine (Cho/Cr) and choline/N-acetyl aspartate (Cho/NAA)
for high and low grade gliomas (HGG, LGG) and metastases (MTS) differentiation.
Subjects and Methods
Using PRISMA method, 24, 22 and 8 articles (dated 2000-2013) were selected respectively for spectroscopy,
rCBV and nADC meta-analysis from the NCBI database. We used random effects model to obtain weighted
averages and area under receiver operating characteristic (ROC) curve for parameter thresholds.
Overall means (with 95% CI) for rCBV, nADC, Cho/Cr (short and medium echo time, TE) and Cho/NAA were:
for HGG g 5.47 (4.78-6.15), 1.38 (1.16-1.60), 2.40 (1.67-3.13), 3.27 (2.78-3.77) and 4.71 (3.24-6.19); for LGG
2.00 (1.71-2.28), 1.61 (1.36-1.87), 1.46 (1.20-1.72), 1.71 (1.49-1.93) and 2.36 (1.50-3.23); for MTS – 5.06
(3.85-6.27), 1.35 (1.06-1.64), 1.89 (1.72-2.06), 3.14 (1.57-4.72) (Cho/NAA was not available).
Optimal differentiation between HGG and LGG was obtained using thresholds rCBV 2.28, Cho/Cr 1.56 and
1.93 (short and medium TE) and Cho/NAA (medium TE) 2.0.
The inter-study heterogeneity of metrics derived from pMRI, MRS and DWI is large thereby limiting the ability
to establish cut-off values to differentiate between brain tumor subtypes. Best differentiation between HGG
and LGG is obtained from rCBV or Cho/Cr and Cho/NAA metrics.
1. Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Preferred reporting items for systematic reviews and
meta-analyses: the PRISMA statement. BMJ 339:b2535.
2. Gaudino S, Di Lella GM, Russo R, Lo Russo VS, Piludu F, Quaglio FR, Gualano MR, De Waure C,
Colosimo C (2012) Magnetic resonance imaging of solitary brain metastases: main findings of
nonmorphological sequences. Radiol Medica 117:1225–1241.
3. Server A, Kulle B, Gadmar ØB, Josefsen R, Kumar T, Nakstad PH (2011) Measurements of diagnostic
examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic
imaging in the preoperative evaluation of tumor grade in cerebral gliomas. Eur J Radiol 80:462–470.
4. Emblem KE, Nedregaard B, Nome T, Due-Tonnessen P, Hald JK, Scheie D, Borota OC, Cvancarova M,
Bjornerud A (2008) Glioma Grading by Using Histogram Analysis of Blood Volume Heterogeneity from
MR-derived Cerebral Blood Volume Maps1. Radiology 247:808–817.
5.Bendini M, Marton E, Feletti A, Rossi S, Curtolo S, Inches I, Ronzon M, Longatti P, Di Paola F (2011)
Primary and metastatic intraaxial brain tumors: Prospective comparison of multivoxel 2D chemical-shift
imaging (CSI) proton MR spectroscopy, perfusion MRI, and histopathological findings in a group of 159
patients. Acta Neurochir (Wien) 153:403–412.

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