Maria Duvaldt1 and Tomas Jonsson1
1Dept. of Medical Physics, Karolinska University Hospital, Stockholm, Sweden
Synopsis
In order to make an adequate decision on the further treatment of a glioma cancer patient a tissue sample from the tumour is microscopically analysed and classified on a malignancy scale set by the WHO. In this project a software program with a graphical user interface is developed, where the malignancy grade of a tumour could be found by image analysis of susceptibility-weighted MR images. The parameters examined are the local image variance and intratumoural susceptibility signal and the results show the possibility of distinguishing high grade from low grade astrocytoma by image analysis only.Introduction
Gliomas are a common type of brain tumour and for the treatment of a patient it is important to determine the tumour's grade of malignancy. This is done today by a biopsy, a histopathological analysis of the tumourous tissue, that is classified on a malignancy scale set by the World Health Organization (WHO). Recent studies have shown that the local image variance (LIV) (1) and the intratumoural susceptibility signal (ITSS) (2) in susceptibility-weighted MR images of the tumour correlate to the WHO-grade. In this thesis project a software program with these analyses implemented is built and tested. The goal was to separate the gliomas into groups of low grade (I-II) and high grade (III-IV). The purpose of the project is to aid the radiologists when grading a glioma and in the long run reduce the need of a biopsy.
Methods
16 patients with glioma grades confirmed by biopsy were included in the study to verify the image analyses. he software was written in Python 3.4.3. A graphical user interface (GUI) with a drawing tool was constructed. A radiologist drew a region of interest in a susceptibility-weighted MR DICOM image that was loaded into the GUI. The region of interest was analysed with respect to LIV and ITSS, and the outcome of the image analyses was tested versus the known grade of the patients. MannWhitney U tests, Spearman Correlation Coefficients and binary logistics were performed for the statistical analysis.
Results
No statistically significant difference could be seen between the high and the low grade group, in the case of LIV. Concerning ITSS a statistically significant difference could be seen between the high and the low grade group (p < 0.02). The sensitivity and specificity was 80% and 100% respectively. Among these 16 gliomas, 11 were astrocytic tumours and between low and high grade astrocytomas a statistically significant difference was shown. The degree of LIV was significantly different between the two groups (p < 0.03) and the sensitivity and specificity were 86% and 100% respectively. The degree of ITSS was significantly different between the two groups (p < 0.04) and the sensitivity and specificity were 86% and 100% respectively. Spearman correlation showed a correlation between LIV and tumour grade (for all gliomas r = 0.53 and p < 0.04, for astrocytomas r = 0.84 and p < 0.01). A correlation was also found between ITSS and tumour grade (for all gliomas r = 0.69 and p < 0.01, for astrocytomas r = 0.63 and p < 0.04).
Conclusion
The results indicate that analysing LIV and ITSS in susceptibility-weighted 1.5T images is useful for distinguishing between high and low grade astrocytoma within this cohort. It also seems possible to distinguish between high and low grade glioma with ITSS. Hemorrhage and calcification within the regions of interest are important to exclude, otherwise they might be interpreted as blood vessels and contribute to an error in the results.
Acknowledgements
No acknowledgement found.References
1. Trattnig S, Grabner G, Goed S, et al. Quantification of 7 Tesla Hypointensities in gliomas using the local image variance. Study presented at ESMRMB Conference in Vienna 2014.
2. Chuang T-C, Shui W-P, Chung H-W, Lai P-H. Quantitative intra-tumoural susceptibility signal in grading brain astrocytomas with susceptibility-weighted imaging. Study presented at Annual Meeting of International Society of Magnetic Resonance in Medicine, Milan, Italy, 2014.