A new application of Compressive Sensing (CS) in Magnetic Resonance Imaging (MRI) field is presented. In particular, first results of the Intra Voxel Analysis (IVA) technique are reported. The idea is to exploit CS peculiarities in order to distinguish different contributions inside the same resolution cell, instead of reconstructing images from not fully sampled k-space acquisition. Applied to MRI field, this means the possibility of estimating the presence of different tissues inside the same voxel, i.e. in one pixel of the obtained image. In other words, the method is the first attempt, as far as we know, of achieving Spectroscopy-like results starting from each pixel of MR images. In particular, tissues are distinguished each others by evaluating their spin-spin relaxation times. Within this manuscript, first results on clinical dataset, in particular a phantom made by aqueous solution and oil and an occipital brain lesion corresponding to a metastatic breast cancer nodule, are reported. Considering the phantom dataset, in particular focusing on the slice where the separation between water and oil occurs, the methodology is able to distinguish the two components with different spin-spin relaxation times. With respect to clinical dataset,focusing on a voxel of the lesion area, the approach is able to detect the presence of two tissues, namely the healthy and the cancer related ones, while in other location outside the lesion only the healthy tissue is detected. Of course, these are the first results of the proposed methodology, further studies on different types of clinical datasets are required in order to widely validate the approach. Although few datasets have been considered, results seem both interesting and promising.