Drug homogeneity index in mass spectrometry imaging (MSI)

Enhancing drug penetration in solid tumors is an interesting clinical issue, of considerable importance. In pre-clinical research mass spectrometry imaging is a promising technique to visualize drug distribution in tumors in different treatment conditions and its application in this field is rapidly increasing. However, in view of the huge variability among MSI datasets, drug homogeneity is usually manually assessed by an expert and this approach is biased by inter-observer variability and lacks reproducibility. We propose a new texture-based feature, the ‘Drug Homogeneity Index (DHI)’ which provides an objective, automated measure of drug homogeneity in MSI data. A simulation study on synthetic datasets showed that previously known texture features do not give an accurate picture of intra-tumor drug distribution patterns and are easily influenced by the tumor tissue morphology. The DHI has been used to study the distribution profile of the anti-cancer drug paclitaxel in various xenograft models, either not pretreated or pretreated with anti-angiogenesis compounds. The conclusion is that drug homogeneity is better in the pretreated condition, which is in agreement with previous experimental findings published by our group. This study shows that DHI could be useful in preclinical studies as a new parameter for the evaluation of protocols for better drug penetration