Scaling laws and fractal measures on high-resolution tumor images (SCALFRACT).
Many growth processes in nature depend on the geometrical properties of the interface between the growing object and the external medium. We intend to study the interface tumor – healthy tissue of a broad variety of cancer types as observed in MRI images (lung, breast, brain metastasis, brain tumors, etc.) to identify universal features that can be used for prognosis or predictive metrics.
Where is it being implemented?
The protocol has been approved at Instituto Valenciano de Oncología (Valencia). Data from GLIOMAT, TOG and METMATH studies will also be used for some common goals (but limited to brain tumors).
What data do we collect?
Retrospective high-resolution imaging data obtained in the clinical routine allowing the tumor – host interface to be studied at a macroscopic level will be used, i.e. thin slice CT or volumetric or 3D magnetic resonance images depending on the tumor type.
What are the expected benefits for patients?
The idea is to develop prognostic and response biomarkers based on the concepts that could help clinicians in finding the best treatment options for patients.
When will the results be available?
Data collection has started and the algorithms are under development. We expect to have results sometime in 2019.