R F Barajas1, J J Phillips2, S R Vandenberg3, M W McDermott4, M S Berger4, W P Dillon5, S Cha6. 1. Department of Radiology, Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, CR 135, Portland, OR 97239, USA. 2. Department of Neurological Surgery, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA; Department of Pathology, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA. 3. Department of Pathology, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA. 4. Department of Neurological Surgery, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA. 5. Department of Radiology and Biomedical Imaging, Neuroradiology Section, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA. 6. Department of Radiology and Biomedical Imaging, Neuroradiology Section, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA; Department of Neurological Surgery, University of California, San Francisco, 500 Parnassus Ave, San Francisco, CA 94143, USA. Electronic address: soonmee.cha@ucsf.edu.
Abstract
AIM: To investigate whether quantitative dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) metrics are influenced by cellular and genomic expression patterns of glioblastoma angiogenesis. MATERIALS AND METHODS: Twenty-five stereotactic neurosurgical tissue samples were prospectively obtained from enhancing and non-enhancing tumour regions from 10 patients with treatment-naïve glioblastoma. Using monoclonal antibodies, histopathological features of angiogenesis were examined: total microvascular density, vascular morphology, and hypoxia. Angiogenic expression patterns of tissue samples were investigated using RNA microarrays. DSC perfusion MRI metrics were measured from the tissue sampling sites. MRI and histopathological variables were compared using Pearson's correlations. Microarray analysis was performed using false discovery rate (FDR) statistics. RESULTS: Thirteen enhancing and 12 non-enhancing MR image-guided tissue specimens were prospectively obtained. Enhancing tumour regions demonstrated a significant difference in DSC perfusion and histopathological metrics of angiogenesis when compared to non-enhancing regions. Four angiogenic pathways (vascular endothelial growth factor [VEGF], hypoxia inducible factor [HIF], platelet-derived growth factor [PDGF], fibroblast growth factor [FGF]; 25 individual genes) were significantly up-regulated within enhancing regions when compared to non-enhancing regions (adjusted p<0.05, FDR <0.05). A statistically significant correlation was observed between VEGF-A expression, microvascular density, microvascular morphology, and DSC perfusion MRI metrics (p<0.05). CONCLUSION: Pro-angiogenic genomic and cellular expression patterns of treatment-naïve primary glioblastoma significantly influences morphological and physiological DSC perfusion metrics suggesting that expression levels of therapeutically relevant genetic signatures can be quantified using MRI.
AIM: To investigate whether quantitative dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion magnetic resonance imaging (MRI) metrics are influenced by cellular and genomic expression patterns of glioblastoma angiogenesis. MATERIALS AND METHODS: Twenty-five stereotactic neurosurgical tissue samples were prospectively obtained from enhancing and non-enhancing tumour regions from 10 patients with treatment-naïve glioblastoma. Using monoclonal antibodies, histopathological features of angiogenesis were examined: total microvascular density, vascular morphology, and hypoxia. Angiogenic expression patterns of tissue samples were investigated using RNA microarrays. DSC perfusion MRI metrics were measured from the tissue sampling sites. MRI and histopathological variables were compared using Pearson's correlations. Microarray analysis was performed using false discovery rate (FDR) statistics. RESULTS: Thirteen enhancing and 12 non-enhancing MR image-guided tissue specimens were prospectively obtained. Enhancing tumour regions demonstrated a significant difference in DSC perfusion and histopathological metrics of angiogenesis when compared to non-enhancing regions. Four angiogenic pathways (vascular endothelial growth factor [VEGF], hypoxia inducible factor [HIF], platelet-derived growth factor [PDGF], fibroblast growth factor [FGF]; 25 individual genes) were significantly up-regulated within enhancing regions when compared to non-enhancing regions (adjusted p<0.05, FDR <0.05). A statistically significant correlation was observed between VEGF-A expression, microvascular density, microvascular morphology, and DSC perfusion MRI metrics (p<0.05). CONCLUSION: Pro-angiogenic genomic and cellular expression patterns of treatment-naïve primary glioblastoma significantly influences morphological and physiological DSC perfusion metrics suggesting that expression levels of therapeutically relevant genetic signatures can be quantified using MRI.
Authors: Bob L Hou; Sijin Wen; Gennadiy A Katsevman; Hui Liu; Ogaga Urhie; Ryan C Turner; Jeffrey Carpenter; Sanjay Bhatia Journal: World Neurosurg Date: 2018-12-27 Impact factor: 2.104
Authors: Ramon F Barajas; Kenneth A Krohn; Jeanne M Link; Randall A Hawkins; Jennifer L Clarke; Miguel H Pampaloni; Soonmee Cha Journal: Biomedicines Date: 2016-10-31
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