Histogram Analysis of MR Imaging–Derived Cerebral Blood Volume Maps: Combined Glioma Grading and Identification of Low-Grade Oligodendroglial Subtypes

Emblem, Kyrre E.; Scheie, David; Due‐Tønnessen, Paulina; Nedregaard, Bård; Nome, Terje; Hald, John; Beiske, Klaus; Meling, Torstein R.; Bjørnerud, Atle

doi:10.3174/ajnr.a1182

Cited by 66 publications

(48 citation statements)

References 26 publications

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“…In this study rCBV was determined by placing regions of interest over areas of highest blood volume to derive rCBV max . Subsequently elevated rCBV in association with 1p/19q loss has been supported in other small series of oligodendroglial tumours measuring rCBV [161][162][163] or using histogram analysis [164]. These data warrant further study in larger series to determine the potential of rCBV measurements for the non-invasive prediction of genotype.…”

Section: P/19q Genotypementioning

confidence: 63%

Biology, genetics and imaging of glial cell tumours

Walker¹,

Baborie²,

Crooks³

et al. 2011

BJR

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ABSTRACT. Despite advances in therapy, gliomas remain associated with poor prognosis. Clinical advances will be achieved through molecularly targeted biological therapies, for which knowledge of molecular genetic and gene expression characteristics in relation to histopathology and in vivo imaging are essential. Recent research supports the molecular classification of gliomas based on genetic alterations or gene expression profiles, and imaging data supports the concept that molecular subtypes of glioma may be distinguished through non-invasive anatomical, physiological and metabolic imaging techniques, suggesting differences in the baseline biology of genetic subtypes of infiltrating glioma. Furthermore, MRI signatures are now being associated with complex gene expression profiles and cellular signalling pathways through genome-wide microarray studies using samples obtained by image guidance which may be co-registered with clinical imaging. In this review we describe the pathobiology, molecular pathogenesis, stem cells and imaging characteristics of gliomas with emphasis on astrocytomas and oligodendroglial neoplasms.

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Section: P/19q Genotypementioning

confidence: 63%

Biology, genetics and imaging of glial cell tumours

Walker¹,

Baborie²,

Crooks³

et al. 2011

BJR

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“…There have been many reports of glioma grading using perfusion-weighted imaging, although only a few studies have dealt with the histogram method to [14,26,28,29]. Emblem et al [26] reported that the maximum peak height of the nCBV histogram was lower and exhibited a wider distribution of pixel values in HGGs, which represented the tumor heterogeneity in HGGs.…”

Section: Discussionmentioning

confidence: 98%

Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging

et al. 2014

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The purpose of our study was to explore the difference between isocitrate dehydrogenase (IDH)-1/2 gene mutation-positive and -negative high-grade gliomas (HGGs) using histogram analysis of apparent diffusion coefficient (ADC) and normalized cerebral blood volume (nCBV) maps. We enrolled 52 patients with histopathologically confirmed HGGs with IDH1/2 (P) (n = 16) or IDH1/2 (N) (n = 36). Histogram parameters of ADC and nCBV maps were correlated with gene mutations by using the unpaired student's t test and multivariable stepwise logistic regression analysis. The mean ADC value was higher in the IDH1 (P) group than IDH1 (N) (1,282.8 vs. 1,159.6 mm(2)/s, P = .0113). In terms of the cumulative ADC histograms, the 10th and 50th percentile values were also higher in the IDH1 (P) than IDH1 (N) (P = .0104 and .0183, respectively). We observed a higher 90th percentile value (3.121 vs. 2.397, P = .0208) and a steeper slope between the 10th (C10) and 90th (C90) of cumulative nCBV histograms (0.03386 vs. 0.02425/%, P = .0067) in the IDH1 (N) group. Multivariate analysis showed that the mean ADC mean value (P = .0048), the C90 value (P = .0113), and the slope between C10 and C90 (P = .0049) were the significant variables in the differentiation of IDH1 (P) from IDH1 (N). In conclusion, histogram analysis of ADC and nCBV maps based on entire tumor volume can be a useful tool for distinguishing IDH1 (P) and IDH1 (N), and it predicts that IDH (P) tumors have a more heterogeneous microenvironment than IDH (N) ones.

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“…3). Several studies have investigated individual histograms in rCBV maps (25)(26)(27), but to the best of our knowledge this was the first study to compare mean histograms of 18 F-FET PET and rCBV maps in gliomas.…”

Section: Discussionmentioning

confidence: 99%

Comparison of ¹⁸F-FET PET and Perfusion-Weighted MR Imaging: A PET/MR Imaging Hybrid Study in Patients with Brain Tumors

et al. 2014

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PET using O-(2-18 F-fluoroethyl)-L-tyrosine ( 18 F-FET) provides important diagnostic information in addition to that from conventional MR imaging on tumor extent and activity of cerebral gliomas. Recent studies suggest that perfusion-weighted MR imaging (PWI), especially maps of regional cerebral blood volume (rCBV), may provide similar diagnostic information. In this study, we directly compared 18 F-FET PET and PWI in patients with brain tumors. Methods: Fifty-six patients with gliomas were investigated using static 18 F-FET PET and PWI. For comparison, 8 patients with meningiomas were included. We generated a set of tumor and reference volumes of interest (VOIs) based on morphologic MR imaging and transferred these VOIs to the corresponding 18 F-FET PET scans and PWI maps. From these VOIs, tumor-to-brain ratios (TBR) were calculated, and normalized histograms were generated for 18 F-FET PET and rCBV maps. Furthermore, in rCBV maps and in 18 F-FET PET scans, tumor volumes, their spatial congruence, and the distance between the local hot spots were assessed. Results: For patients with glioma, TBR was significantly higher in 18 F-FET PET than in rCBV maps (TBR, 2.28 ± 0.99 vs. 1.62 ± 1.13; P , 0.001). Histogram analysis of the VOIs revealed that 18 F-FET scans could clearly separate tumor from background. In contrast, deriving this information from rCBV maps was difficult. Tumor volumes were significantly larger in 18 F-FET PET than in rCBV maps (tumor volume, 24.3 ± 26.5 cm 3 vs. 8.9 ± 13.9 cm 3 ; P , 0.001). Accordingly, spatial overlap of both imaging parameters was poor (congruence, 11.0%), and mean distance between the local hot spots was 25.4 ± 16.1 mm. In meningioma patients, TBR was higher in rCBV maps than in 18 F-FET PET (TBR , 5.33 ± 2.63 vs. 2.37 ± 0.32; P , 0.001) whereas tumor volumes were comparable. Conclusion: In patients with cerebral glioma, tumor imaging with 18 F-FET PET and rCBV yields different information. 18 F-FET PET shows considerably higher TBRs and larger tumor volumes than rCBV maps. The spatial congruence of both parameters is poor. The locations of the local hot spots differ considerably. Taken together, our data show that metabolically active tumor tissue of gliomas as depicted by amino acid PET is not reflected by rCBV as measured with PWI.

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Histogram Analysis of MR Imaging–Derived Cerebral Blood Volume Maps: Combined Glioma Grading and Identification of Low-Grade Oligodendroglial Subtypes

Cited by 66 publications

References 26 publications

Biology, genetics and imaging of glial cell tumours

Biology, genetics and imaging of glial cell tumours

Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging

Comparison of ¹⁸F-FET PET and Perfusion-Weighted MR Imaging: A PET/MR Imaging Hybrid Study in Patients with Brain Tumors

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Histogram Analysis of MR Imaging–Derived Cerebral Blood Volume Maps: Combined Glioma Grading and Identification of Low-Grade Oligodendroglial Subtypes

Cited by 66 publications

References 26 publications

Biology, genetics and imaging of glial cell tumours

Biology, genetics and imaging of glial cell tumours

Evaluation of the microenvironmental heterogeneity in high-grade gliomas with IDH1/2 gene mutation using histogram analysis of diffusion-weighted imaging and dynamic-susceptibility contrast perfusion imaging

Comparison of 18F-FET PET and Perfusion-Weighted MR Imaging: A PET/MR Imaging Hybrid Study in Patients with Brain Tumors

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Comparison of ¹⁸F-FET PET and Perfusion-Weighted MR Imaging: A PET/MR Imaging Hybrid Study in Patients with Brain Tumors