Generation of patient-specific surrogate metrics based on multi-parametric tissue signatures

See video


Multiparametric Tissue Signature (MTS) is a new procedure for solid tumours, where using the imaging data collected during the standard protocol, we are able to generate sub-compartments within the morphologic regions of the tumour with distinctive physiological features.

MTS has been tested on highly aggressive and diffuse tumours where the rapid evolution of the disease difficults the assessment of therapies, the prognosis, and avoid the early use of second line therapies. The first results obtained suggest a correlation of the MTS with patient survival.

With an extended clinical validation of this finding, MTS could constitute a useful tool to improve the efficacy of solid tumour clinical trials speeding up the identification of new therapeutic compounds. by supporting the precision recruitment of patients, the early treatment assessment, and the definition of surrogate outcomes to overall survival. 


  • To support the precision recruitment of patients during clinical trials
  • To generate novel evidences on the tumour extent to support the early treatment assessment
  • To generate patient-specific surrogate metrics for late outcomes (e.g. patient overal survival)

Problem to Solve

The proportion of compounds that finally reach the market is estimated to be less than 10%, with highly expensive and lenghtly clinical trials. In the case of highly aggressive and diffusive tumours, the nature and severity of the disease greatly complicates the development of novel therapeutic compounds. 


Surrogate outcomes, such as MTS imagining, could be used in the development of patient-specific metrics, substantially contributing to the reduction in the duration of clinical trials for novel therapeutic approaches. MTS could constitute a reference surrogated metric for early therapy assessment of aggressive brain tumours such as glioblastoma.

Level of Innovation

Currently, there are very few technologies able to perform novel imaging biomarker analytics based on advanced unsupervised segmentation algorithms such as the  proposed in MTS imaging. In addition, MTS computed at early stages of disease has been found to correlate with key outcomes such as patient survival. Therefore, MTS is a promising technology to be used as surrogate outcomes in the development of novel therapeutic strategies for solid tumours.


Ph.D., Project leader and research fellow at the ITACA institute

Elies Fuster Garcia

UPV - Universitat Politècnica de València

Project leader

MSc, MTS technology developer and researcher at the ITACA institute

Javier Juan

UPV - Universitat Politècnica de València

Ph.D., Reader at UPV and head of BDSLab at the ITACA institute

Juan M. Garcia-Gomez

UPV - Universitat Politècnica de València

PhD., Assistant Researcher and Lecturer at INGENIO Institute

Francisco Javier Ortega Colomer

UPV - Universitat Politècnica de València


Research Director

Clara Campàs

Kern Pharma SL


Obra Social
Caixa Capital Risc

Scientific Area

Clinical sciences

Business area


Research center

Universitat Politècnica de València