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Published in: Journal of Neuro-Oncology 2/2013

01-01-2013 | Clinical Study

Measurements of heterogeneity in gliomas on computed tomography relationship to tumour grade

Authors: Karoline Skogen, Balaji Ganeshan, Catriona Good, Giles Critchley, Ken Miles

Published in: Journal of Neuro-Oncology | Issue 2/2013

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Abstract

To undertake a preliminary study that uses CT texture analysis (CTTA) to quantify heterogeneity in gliomas on contrast-enhanced CT and to assess the relationship between tumour heterogeneity and grade. Retrospective analysis of contrast enhanced CT images was performed in 44 patients with histologically proven cerebral glioma between 2007 and 2010. 11 tumours were low grade (Grade I = 3; Grade II, = 8) and 33 high grade (Grade III = 10, Grade IV = 23). CTTA assessment of tumour heterogeneity was performed using a proprietary software algorithm (TexRAD) that selectively filters and extracts textures at different anatomical scales between filter values 1.0 (fine detail) and 2.5 (coarse features). Heterogeneity was quantified as standard deviation (SD) with or without filtration. Tumour heterogeneity, size and attenuation were correlated with tumour grade. For each parameter, receiver operating characteristics characterised the diagnostic performance for discrimination of high grade from low grade glioma and of grade III tumours from grade IV. Further the CTTA was compared to the radiological diagnosis. Tumour heterogeneity correlated significantly with grade (SD without filtration rs = 0.664, p < 0.001, SD with coarse filtration (rs = 0.714, p < 0.001). Tumour size and attenuation showed only moderate correlations with tumour grade (rs = 0.426, p = 0.004 and rs = 0.447, p = 0.002 respectively). Coarse texture was the best discriminator between high and low grade tumours (AUC 0.832, p < 0.0001) and between grade III and grade IV gliomas (AUC = 0.878 p = 0.0001). Compared to the radiological diagnosis, CTTA further characterised the indetermined cases. By quantifying tumour heterogeneity, CTTA has the potential to provide a marker of tumour grade for patients with cerebral glioma. By differentiating between high and low grade tumours, CTTA could possibly assist clinical management.
Literature
1.
go back to reference Louis DN, Ohgaki H, Wiestler OD et al (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropahtol 114(2):97–109CrossRef Louis DN, Ohgaki H, Wiestler OD et al (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropahtol 114(2):97–109CrossRef
3.
go back to reference Siker ML, Chakravarti A, Mehta MP (2006) Should concomitant and adjuvant treatment with temozolomide be used as standard therapy in patients with anaplastic glioma? Critical reviews in Oncology-Haematology 60(2):99–111CrossRef Siker ML, Chakravarti A, Mehta MP (2006) Should concomitant and adjuvant treatment with temozolomide be used as standard therapy in patients with anaplastic glioma? Critical reviews in Oncology-Haematology 60(2):99–111CrossRef
4.
5.
go back to reference Server A, Kulle B, Gadmar OB et al (2010) 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. doi: 10.1016/j.ejrad.2010.07.017 Server A, Kulle B, Gadmar OB et al (2010) 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. doi: 10.​1016/​j.​ejrad.​2010.​07.​017
6.
go back to reference Nelson DA, Tan TT, Rabson AB, Anderson D, Degenhardt K, White E (2004) Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev 18:2095–2107PubMedCrossRef Nelson DA, Tan TT, Rabson AB, Anderson D, Degenhardt K, White E (2004) Hypoxia and defective apoptosis drive genomic instability and tumorigenesis. Genes Dev 18:2095–2107PubMedCrossRef
7.
go back to reference Arogundade RA, Awosanya GO, Ariqbabu SO (2006) Role of computer tomography in the management of adult brain tumours. Niger Postgrad Med J. 13(2):123–127PubMed Arogundade RA, Awosanya GO, Ariqbabu SO (2006) Role of computer tomography in the management of adult brain tumours. Niger Postgrad Med J. 13(2):123–127PubMed
8.
go back to reference Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles KA (2012) Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 22(4):796–802PubMedCrossRef Ganeshan B, Panayiotou E, Burnand K, Dizdarevic S, Miles KA (2012) Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival. Eur Radiol 22(4):796–802PubMedCrossRef
9.
go back to reference Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles KA (2012) Tumour heterogeneity in oesophageal cancer assessed by CT Texture Analysis: preliminary evidence of an association with tumour metabolism, stage and survival. Clin Radiol 67(2):157–164PubMedCrossRef Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles KA (2012) Tumour heterogeneity in oesophageal cancer assessed by CT Texture Analysis: preliminary evidence of an association with tumour metabolism, stage and survival. Clin Radiol 67(2):157–164PubMedCrossRef
10.
go back to reference Goh V, Ganeshan B, Nathan P, Juttla J, Vinayan A, Miles KA (2011) Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology 261(1):165–171PubMedCrossRef Goh V, Ganeshan B, Nathan P, Juttla J, Vinayan A, Miles KA (2011) Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology 261(1):165–171PubMedCrossRef
11.
go back to reference Ganeshan B, Abaleke SC, Young RCD, Chatwin CR, Miles KA (2010) Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 6(10):137–143CrossRef Ganeshan B, Abaleke SC, Young RCD, Chatwin CR, Miles KA (2010) Texture analysis of non-small cell lung cancer on unenhanced computed tomography: initial evidence for a relationship with tumour glucose metabolism and stage. Cancer Imaging 6(10):137–143CrossRef
12.
go back to reference Miles KA, Ganeshan B, Griffiths MR, Young RC, Chatwin CR (2009) Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology 250(2):444–452PubMedCrossRef Miles KA, Ganeshan B, Griffiths MR, Young RC, Chatwin CR (2009) Colorectal cancer: texture analysis of portal phase hepatic CT images as a potential marker of survival. Radiology 250(2):444–452PubMedCrossRef
13.
go back to reference Ganeshan B, Miles KA, Young RC, Chatwin CR (2007) In search of biologic correlates for liver texture on portal-phase CT. Acad Radiol. 14(9):1058–1068PubMedCrossRef Ganeshan B, Miles KA, Young RC, Chatwin CR (2007) In search of biologic correlates for liver texture on portal-phase CT. Acad Radiol. 14(9):1058–1068PubMedCrossRef
14.
go back to reference Kojima S, YoshitomiY Yano M et al (2000) Heterogeneity of renal cortical circulation in hypertension assessed by dynamic computed tomography. Am J Hypertens 13(4 PT 1):346–352PubMedCrossRef Kojima S, YoshitomiY Yano M et al (2000) Heterogeneity of renal cortical circulation in hypertension assessed by dynamic computed tomography. Am J Hypertens 13(4 PT 1):346–352PubMedCrossRef
15.
go back to reference Ganeshan B, Ziauddin Z, Goh VJ, Rodriguez-Just0 M, Engledow A, Taylor S, Halligan S, Miles KA 2012 Quantitative imaging biomarkers from PET–CT as potential correlates for angiogenesis and hypoxia in colorectal cancer. In: European Society of Radiology Conference 2012, Vienna, Austria Ganeshan B, Ziauddin Z, Goh VJ, Rodriguez-Just0 M, Engledow A, Taylor S, Halligan S, Miles KA 2012 Quantitative imaging biomarkers from PET–CT as potential correlates for angiogenesis and hypoxia in colorectal cancer. In: European Society of Radiology Conference 2012, Vienna, Austria
16.
go back to reference Zagzag D, Goldenberg M, Brem S (1989) Angiogenesis and blood-brain barrier breakdown modulate CT contrast enhancement: an experimental study in a rabbit brain-tumor model. Am J Roentgenol 153:141–146 Zagzag D, Goldenberg M, Brem S (1989) Angiogenesis and blood-brain barrier breakdown modulate CT contrast enhancement: an experimental study in a rabbit brain-tumor model. Am J Roentgenol 153:141–146
17.
go back to reference Tervonen O, Forbes G, Scheithauer BW et al (1992) Diffuse “fibrillary” astrocytomas: correlation of MRI features with histopathologic parameters and tumour grade. Neuroradiology 34:173–178PubMedCrossRef Tervonen O, Forbes G, Scheithauer BW et al (1992) Diffuse “fibrillary” astrocytomas: correlation of MRI features with histopathologic parameters and tumour grade. Neuroradiology 34:173–178PubMedCrossRef
18.
go back to reference Moller-Hartmann W, Herminghaus S, Krings T et al (2002) Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology 44:371–381PubMedCrossRef Moller-Hartmann W, Herminghaus S, Krings T et al (2002) Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology 44:371–381PubMedCrossRef
19.
go back to reference Dean BL, Drayer BP, Bird CR et al (1990) Glioma classification with MR imaging. Radiology 174:411–415PubMed Dean BL, Drayer BP, Bird CR et al (1990) Glioma classification with MR imaging. Radiology 174:411–415PubMed
20.
go back to reference Watanabe M, Tanaka R, Takeda N (1992) Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology 34:463–469PubMedCrossRef Watanabe M, Tanaka R, Takeda N (1992) Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology 34:463–469PubMedCrossRef
21.
go back to reference Kondziolka D, Lunsford LD, Martinez AJ (1993) Unreliability of contemporary neurodiagnostic imaging in evaluating suspected adult supratentorial (low Grade) astrocytoma. J Neurosurg 79(4):533–536PubMedCrossRef Kondziolka D, Lunsford LD, Martinez AJ (1993) Unreliability of contemporary neurodiagnostic imaging in evaluating suspected adult supratentorial (low Grade) astrocytoma. J Neurosurg 79(4):533–536PubMedCrossRef
22.
go back to reference Christofordis GA, Grecula JC, Newton HB et al (2002) Visualization of microvascularity in glioblastoma multiforme with 8-T high-spatial-resolution MR imaging. AM J Neuroradiol 23:1553–1556 Christofordis GA, Grecula JC, Newton HB et al (2002) Visualization of microvascularity in glioblastoma multiforme with 8-T high-spatial-resolution MR imaging. AM J Neuroradiol 23:1553–1556
23.
go back to reference Assefa D, Keller H, Ménard C, Laperriere N, Ferrari RJ, Yeung I (2010) Robust texture features for response monitoring of glioblastoma multiforme onT1-weighted and T2-FLAIR MR images: a preliminary investigation in terms of identification and segmentation. Med Phys 37(4):1722–1736PubMedCrossRef Assefa D, Keller H, Ménard C, Laperriere N, Ferrari RJ, Yeung I (2010) Robust texture features for response monitoring of glioblastoma multiforme onT1-weighted and T2-FLAIR MR images: a preliminary investigation in terms of identification and segmentation. Med Phys 37(4):1722–1736PubMedCrossRef
24.
go back to reference Drabycz S, Roldán G, de Robles P, Adler D, McIntyre JB, Magliocco AM, Cairncross JG, Mitchell JR (2010) An analysis of image texture, tumor location, and MGMT promoter methylation in glioblastoma using magnetic resonance imaging. Neuroimage 49(2):1398–1405PubMedCrossRef Drabycz S, Roldán G, de Robles P, Adler D, McIntyre JB, Magliocco AM, Cairncross JG, Mitchell JR (2010) An analysis of image texture, tumor location, and MGMT promoter methylation in glioblastoma using magnetic resonance imaging. Neuroimage 49(2):1398–1405PubMedCrossRef
25.
go back to reference Levner I, Drabycz S, Roldan G, De Robles P, Cairncross JG, Mitchell R (2009) Predicting MGMT methylation status of glioblastomas from MRI texture. Med Image Comput Comput Assist Interv. 12(Pt 2):522–530PubMed Levner I, Drabycz S, Roldan G, De Robles P, Cairncross JG, Mitchell R (2009) Predicting MGMT methylation status of glioblastomas from MRI texture. Med Image Comput Comput Assist Interv. 12(Pt 2):522–530PubMed
26.
go back to reference Mahmoud-Ghoneim D, Alkaabi MK, de Certaines JD, Goettsche FM (2008) The impact of image dynamic range on texture classification of brain white matter. BMC Med Imaging 23(8):18CrossRef Mahmoud-Ghoneim D, Alkaabi MK, de Certaines JD, Goettsche FM (2008) The impact of image dynamic range on texture classification of brain white matter. BMC Med Imaging 23(8):18CrossRef
27.
go back to reference Georgiadis P, Cavouras D, Kalatzis I, Glotsos D, Athanasiadis E, Kostopoulos S, Sifaki K, Malamas M, Nikiforidis G, Solomou E (2009) Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods. Magn Reson Imaging 27(1):120–130PubMedCrossRef Georgiadis P, Cavouras D, Kalatzis I, Glotsos D, Athanasiadis E, Kostopoulos S, Sifaki K, Malamas M, Nikiforidis G, Solomou E (2009) Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods. Magn Reson Imaging 27(1):120–130PubMedCrossRef
28.
go back to reference Mahmoud-Ghoneim D, Toussaint G, Constans JM, de Certaines JD (2003) Three dimensional texture analysis in MRI: a preliminary evaluation in gliomas. Magn Reson Imaging 21(9):983–987PubMedCrossRef Mahmoud-Ghoneim D, Toussaint G, Constans JM, de Certaines JD (2003) Three dimensional texture analysis in MRI: a preliminary evaluation in gliomas. Magn Reson Imaging 21(9):983–987PubMedCrossRef
29.
go back to reference Schad LR, Blüml S, Zuna I (1993) MR tissue characterization of intracranial tumors by means of texture analysis. Magn Reson Imaging 11(6):889–896PubMedCrossRef Schad LR, Blüml S, Zuna I (1993) MR tissue characterization of intracranial tumors by means of texture analysis. Magn Reson Imaging 11(6):889–896PubMedCrossRef
30.
go back to reference Ganeshan B, Miles KA, Young RC, Chatwin CR (2008) Three-dimensional selective-scale texture analysis of computed tomography pulmonary angiograms. Invest Radiol 43(6):382–394PubMedCrossRef Ganeshan B, Miles KA, Young RC, Chatwin CR (2008) Three-dimensional selective-scale texture analysis of computed tomography pulmonary angiograms. Invest Radiol 43(6):382–394PubMedCrossRef
31.
go back to reference Ng F, Ganeshan B, Miles KA, Goh V 2012 Assessment of tumor heterogeneity by CT texture analysis: Comparison of the largest cross-sectional area versus whole tumor analysis. In: The European Society of Radiology Conference 2012, Vienna, Austria Ng F, Ganeshan B, Miles KA, Goh V 2012 Assessment of tumor heterogeneity by CT texture analysis: Comparison of the largest cross-sectional area versus whole tumor analysis. In: The European Society of Radiology Conference 2012, Vienna, Austria
Metadata
Title
Measurements of heterogeneity in gliomas on computed tomography relationship to tumour grade
Authors
Karoline Skogen
Balaji Ganeshan
Catriona Good
Giles Critchley
Ken Miles
Publication date
01-01-2013
Publisher
Springer US
Published in
Journal of Neuro-Oncology / Issue 2/2013
Print ISSN: 0167-594X
Electronic ISSN: 1573-7373
DOI
https://doi.org/10.1007/s11060-012-1010-5

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