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1- Forthcoming TexRAD presentations at European Congress of Radiology (ECR) – Feedback (FDBK)

Presentation at forthcoming European Congress of Radiology (March 1-5 2017)

Provided by Oslo University Hospital.

Presentation Title: Texture analysis on diffusion-tensor imaging: discriminating glioblastomas from single brain metastasis
Author Block: K. Skogen1, A. Schulz1, E. Helseth1, J.B. Dormagen1, B. Ganeshan2, A. Server1;  1Oslo/NO, 2London/GB
(The presenting author is underlined.)
Disclosure Block:   K. Skogen: Shareholder; Yes. Speaker; Yes. A. Schulz: None. E. Helseth: None. J.B. Dormagen: None. B. Ganeshan: Shareholder; Yes. A. Server: None.
Session Number: SS 711
Session Title: Brain tumours: lesion characterisation and treatment evaluation
Session Date/Time: Thursday Mar 2 2017, 14:00 – 15:30
Room: 11/E2

Below is a view of your accepted abstract:
Purpose: Texture analysis has been used to stage, differentiate and predict prognosis in many oncologic tumours. It has been used on CT, MRI and PET. The purpose of this study was to determine the diagnostic accuracy of discriminating glioblastoma (GBM) from single brain metastasis (MET) by assessing the heterogeneity of both the solid tumour and the peritumoural oedema with MRI texture analysis (MRTA).
Methods and Materials: Preoperative MRI examinations done on a 3T scanner of 44 patients were included, 23 GBM and 21 MET. MRTA was performed on the DTI in a representative ROI. The MRTA was assessed using a commercially available research software program (TexRAD)
which applies a filtration histogram technique for characterising tumour and peritumoural heterogeneity. The filtration step selectively filters and extracts texture features at different anatomical scales varying from 2mm (fine) to 6mm (coarse). Heterogeneity quantification was obtained by the statistical parameter entropy. A threshold value to differentiate GBM from MET with sensitivity and specificity was calculated by receiver operating characteristics (ROC) analysis.
Results: Quantifying the heterogeneity of the solid part of the tumour showed no significant difference between GBM and MET. However the heterogeneity of the GBMs peritumoural oedema was significantly higher than the oedema surrounding MET, differentiating them with a sensitivity of 90% and specificity of 80%.
Conclusion: Assessing the peritumoural heterogeneity can increase the radiological diagnostic accuracy when discriminating GBM and MET. This will facilitate the medical staging and optimise the planning for surgical resection of the tumour and postoperative management.

Link to ECR presentation page here


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