Finding discriminative subtypes of aggressive brain tumours using magnetic resonance spectroscopy

Aggressive tumour types such as glioblastomas (gl) and metastases (me) are known to be difficult to discriminate on the basis of single-voxel proton magnetic resonance spectroscopy (SV 1H-MRS) information. Each of them is also heterogeneous in nature and a statistically robust subtyping analysis is likely to shed light on their structure and, possibly, on their differences. In this brief paper we carry out such analysis. From the original MRS frequencies and their first derivative approximation, the most discriminant variables are first selected by χ(2)-testing. Subtypes are then discovered in the distribution of gl and me by repeated model based cluster analysis. Then, the mean of each subtype is contrasted with the original distribution of MRS spectra by t-testing with tail probabilities for the proportion of false positive (TPPFP) control. Finally, the distribution of gl and me in each subtype is compared with random expectation by χ(2)-testing. The experimental results confirm the existence of consistent subtypes. They exhibit relative proportions of gl and me very unlikely to occur at random.