Jurgita Usinskiene1, Agne Ulyte2, Atle Bjørnerud3,4, Jonas Venius5, Vasileios K Katsaros6, Ryte Rynkeviciene5, Simona Letautiene5,2, Darius Norkus5, Kestutis Suziedelis5, Saulius Rocka2,7, Andrius Usinskas8, Eduardas Aleknavicius5,2. 1. National Cancer Institute, Radiology Center, Santariskiu 1, LT-08660, Vilnius, Lithuania. jurgita.usinskiene@gmail.com. 2. Faculty of Medicine, Vilnius University, Vilnius, Lithuania. 3. Department of Physics, Oslo University Hospital, Oslo, Norway. 4. The Intervention Centre, Oslo University Hospital, Oslo, Norway. 5. National Cancer Institute, Radiology Center, Santariskiu 1, LT-08660, Vilnius, Lithuania. 6. General Anti-Cancer and Oncological Hospital "St. Savvas", Athens, Greece. 7. Neuroangiosurgery Center, Faculty of Medicine Vilnius University, Vilnius, Lithuania. 8. Department of Electronic Systems, Vilnius Gedimino Technical University, Vilnius, Lithuania.
Abstract
INTRODUCTION: To perform a meta-analysis of advanced magnetic resonance imaging (MRI) metrics, including relative cerebral blood volume (rCBV), normalized apparent diffusion coefficient (nADC), and spectroscopy ratios choline/creatine (Cho/Cr) and choline/N-acetyl aspartate (Cho/NAA), for the differentiation of high- and low-grade gliomas (HGG, LGG) and metastases (MTS). METHODS: For systematic review, 83 articles (dated 2000-2013) were selected from the NCBI database. Twenty-four, twenty-two, and eight articles were included respectively for spectroscopy, rCBV, and nADC meta-analysis. In the meta-analysis, we calculated overall means for rCBV, nADC, Cho/Cr (short TE-from 20 to 35 ms, medium-from 135 to 144 ms), and Cho/NAA for the HGG, LGG, and MTS groups. We used random effects model to obtain weighted averages and select thresholds. RESULTS: Overall means (with 95% CI) for rCBV, nADC, Cho/Cr (short and medium echo time, TE), and Cho/NAA were: for HGG 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). LGG had significantly lower rCBV, Cho/Cr, and Cho/NAA values than HGG or MTS. No significant differences were found for nADC. CONCLUSIONS: Best differentiation between HGG and LGG is obtained from rCBV, Cho/Cr, and Cho/NAA metrics. MTS could not be reliably distinguished from HGG by the methods investigated.
INTRODUCTION: To perform a meta-analysis of advanced magnetic resonance imaging (MRI) metrics, including relative cerebral blood volume (rCBV), normalized apparent diffusion coefficient (nADC), and spectroscopy ratios choline/creatine (Cho/Cr) and choline/N-acetyl aspartate (Cho/NAA), for the differentiation of high- and low-grade gliomas (HGG, LGG) and metastases (MTS). METHODS: For systematic review, 83 articles (dated 2000-2013) were selected from the NCBI database. Twenty-four, twenty-two, and eight articles were included respectively for spectroscopy, rCBV, and nADC meta-analysis. In the meta-analysis, we calculated overall means for rCBV, nADC, Cho/Cr (short TE-from 20 to 35 ms, medium-from 135 to 144 ms), and Cho/NAA for the HGG, LGG, and MTS groups. We used random effects model to obtain weighted averages and select thresholds. RESULTS: Overall means (with 95% CI) for rCBV, nADC, Cho/Cr (short and medium echo time, TE), and Cho/NAA were: for HGG 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). LGG had significantly lower rCBV, Cho/Cr, and Cho/NAA values than HGG or MTS. No significant differences were found for nADC. CONCLUSIONS: Best differentiation between HGG and LGG is obtained from rCBV, Cho/Cr, and Cho/NAA metrics. MTS could not be reliably distinguished from HGG by the methods investigated.
Entities:
Keywords:
Brain tumor; Diffusion magnetic resonance imaging; Magnetic resonance spectroscopy; Meta-analysis; Perfusion magnetic resonance imaging
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