title: Measurements of heterogeneity in gliomas on computed tomography relationship to tumour grade.
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.
authors.affiliation: Brighton and Sussex Medical School, Brighton, UK. karolineskogen@hotmail.com
authors.forename: Karoline
authors.initials: K
authors.lastname: Skogen
authors.forename: Balaji
authors.initials: B
authors.lastname: Ganeshan
authors.forename: Catriona
authors.initials: C
authors.lastname: Good
authors.forename: Giles
authors.initials: G
authors.lastname: Critchley
authors.forename: Ken
authors.initials: K
authors.lastname: Miles
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D005910:Glioma / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D008297:Male; D010865:Pilot Projects; D012372:ROC Curve; D012189:Retrospective Studies; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed / Q000379:methods*