Magnetic Resonance Relaxometry is a quantitative MRI-based technique able to estimate tissue relaxation times T1 and T2. This approach allows increasing the MRI diagnostic accuracy mostly in case of brain neoplasia or neurodegenerative disorders in human medicine. However, few reports are available on the application of this technique in the clinical field of veterinary medicine. For this reason, in this work, we developed a relaxometry based approach on experimentally induced brain hemorrhages on rabbits. Specifically, the methodology is based on a hierarchical clustering procedure driven by the T1 relaxometry signals from a set of regions of interest selected on the T2 map. The approach is multivariate since it combines both T1 and T2 information and allows the diagnosis at the subject level by comparing “suspected” pathological regions with healthy homologous ones within the same brain.To validate the proposed technique, the scanned brains underwent histopathological analyses to estimate the performance of the proposed classifier in terms of Receiver Operator Curve analyses. The results showed that, in terms of identification of the lesion and its contours, the proposed approach resulted accurate and outperformed the standard techniques based on T1w and T2w images. Finally, since the proposed protocol in terms of the adopted scanner, sequences, and analysis tools, is suitable for the clinical practice, it can be potentially validated through large-scale multi-center clinical studies.
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