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A deep learning-derived, shear wave elastography biomarker for cancer therapy prediction

CORDIS · observation · Publication date unknown

A deep learning-derived, shear wave elastography biomarker for cancer therapy prediction The efficacy of standard cancer therapies varies, and while some patients respond to a particular treatment, other patients do not gain any benefit. In response, an era of individualized cancer treatments is emerging which are based on the identification of biomarkers that characterize the state of a tumor. Many solid tumors (e.g., breast cancers and sarcomas) stiffen as they grow within a normal tissue. Tumor stiffening is a known factor leading to compromised efficacy of therapeutics. Repurposing drugs in order to alleviate tumor stiffness before the initiation of therapy has been tested in preclinical studies and has recently made it to the clinic. Despite recent success of these strategies, optimization of their application is understudied. Here, we aim to harness the power of deep learning (DL) me

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recordType

award

status

TERMINATED

region

EU

value

148488

unit

EUR